Slicer Wiki - User contributions [en]

Documentation/4.1/Modules/BRAINSMush

2010-05-04T06:00:51Z

StevenDunn: /* More Information */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|-
|* '''Output panel:'''
Specify(optionally) the weights file, which stores the final values for the MUSH equation. Specify also the filename of the MUSH image as well as the brain volume mask.
|[[Image:MushOutputPanel.png|thumb|280px|Output Panel]]

|-
|* '''Seed point panel:'''
Specify the seed point for mask generation. This defaults to the center of the brain in a standard MRI image. Normally this shouldn't need to be changed.
|[[Image:MushSeedPointPanel.png|thumb|280px|Seed Point Panel]]

|-
|* '''Target statistic parameters panel:'''
Specify a variety of advanced parameters. In most cases these will not change. Desired mean and desired variance allow the user to modify the values used in the MUSH image generation equation as listed above. The lower and upper threshold factors are used to threshold the brain mask from the MUSH image. This is done in two passes; the pre-factors specify the initial thresholding, while the remaining two factors specify the second (and primary) thresholding. While the non-pre factors could likely change, the pre-factors most likely will not. However, they have been parameterized in case it is ever needed. The bounding box size specifies an initial cubic brain mask to be used in the event an ROI mask is not provided. The bounding box start is the XYZ point-coordinate of its start.
|[[Image:MushTargetStatisticParametersPanel.png|thumb|280px|Target Statistic Parameters Panel]]
|}

== Development ==

===Dependencies===

[http://www.itk.org ITK]

===Known bugs===

Follow this [http://www.nitrc.org/tracker/?group_id=183 link] to the bug tracker at NITRC.

===Source code & documentation===

Available at [http://www.nitrc.org/projects/brainsmush NITRC]

== More Information ==

===Acknowledgment===
This work was developed by the University of Iowa Departments of Radiology and Psychiatry. This software was supported in part of NIH/NINDS award NS050568.

===References===

Documentation/4.1/Modules/BRAINSMush

2010-05-04T06:00:10Z

StevenDunn: /* Development */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|-
|* '''Output panel:'''
Specify(optionally) the weights file, which stores the final values for the MUSH equation. Specify also the filename of the MUSH image as well as the brain volume mask.
|[[Image:MushOutputPanel.png|thumb|280px|Output Panel]]

|-
|* '''Seed point panel:'''
Specify the seed point for mask generation. This defaults to the center of the brain in a standard MRI image. Normally this shouldn't need to be changed.
|[[Image:MushSeedPointPanel.png|thumb|280px|Seed Point Panel]]

|-
|* '''Target statistic parameters panel:'''
Specify a variety of advanced parameters. In most cases these will not change. Desired mean and desired variance allow the user to modify the values used in the MUSH image generation equation as listed above. The lower and upper threshold factors are used to threshold the brain mask from the MUSH image. This is done in two passes; the pre-factors specify the initial thresholding, while the remaining two factors specify the second (and primary) thresholding. While the non-pre factors could likely change, the pre-factors most likely will not. However, they have been parameterized in case it is ever needed. The bounding box size specifies an initial cubic brain mask to be used in the event an ROI mask is not provided. The bounding box start is the XYZ point-coordinate of its start.
|[[Image:MushTargetStatisticParametersPanel.png|thumb|280px|Target Statistic Parameters Panel]]
|}

== Development ==

===Dependencies===

[http://www.itk.org ITK]

===Known bugs===

Follow this [http://www.nitrc.org/tracker/?group_id=183 link] to the bug tracker at NITRC.

===Source code & documentation===

Available at [http://www.nitrc.org/projects/brainsmush NITRC]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T05:51:46Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|-
|* '''Output panel:'''
Specify(optionally) the weights file, which stores the final values for the MUSH equation. Specify also the filename of the MUSH image as well as the brain volume mask.
|[[Image:MushOutputPanel.png|thumb|280px|Output Panel]]

|-
|* '''Seed point panel:'''
Specify the seed point for mask generation. This defaults to the center of the brain in a standard MRI image. Normally this shouldn't need to be changed.
|[[Image:MushSeedPointPanel.png|thumb|280px|Seed Point Panel]]

|-
|* '''Target statistic parameters panel:'''
Specify a variety of advanced parameters. In most cases these will not change. Desired mean and desired variance allow the user to modify the values used in the MUSH image generation equation as listed above. The lower and upper threshold factors are used to threshold the brain mask from the MUSH image. This is done in two passes; the pre-factors specify the initial thresholding, while the remaining two factors specify the second (and primary) thresholding. While the non-pre factors could likely change, the pre-factors most likely will not. However, they have been parameterized in case it is ever needed. The bounding box size specifies an initial cubic brain mask to be used in the event an ROI mask is not provided. The bounding box start is the XYZ point-coordinate of its start.
|[[Image:MushTargetStatisticParametersPanel.png|thumb|280px|Target Statistic Parameters Panel]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

File:MushTargetStatisticParametersPanel.png

2010-05-04T05:40:58Z

StevenDunn:

Documentation/4.1/Modules/BRAINSMush

2010-05-04T05:40:49Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|-
|* '''Output panel:'''
Specify(optionally) the weights file, which stores the final values for the MUSH equation. Specify also the filename of the MUSH image as well as the brain volume mask.
|[[Image:MushOutputPanel.png|thumb|280px|Output Panel]]

|-
|* '''Seed point panel:'''
Specify the seed point for mask generation. This defaults to the center of the brain in a standard MRI image. Normally this shouldn't need to be changed.
|[[Image:MushSeedPointPanel.png|thumb|280px|Seed Point Panel]]

|-
|* '''Target statistic parameters panel:'''

|[[Image:MushTargetStatisticParametersPanel.png|thumb|280px|Target Statistic Parameters Panel]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T05:40:26Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|-
|* '''Output panel:'''
Specify(optionally) the weights file, which stores the final values for the MUSH equation. Specify also the filename of the MUSH image as well as the brain volume mask.
|[[Image:MushOutputPanel.png|thumb|280px|Output Panel]]

|-
|* '''Seed point panel:'''
Specify the seed point for mask generation. This defaults to the center of the brain in a standard MRI image. Normally this shouldn't need to be changed.
|[[Image:MushSeedPointPanel.png|thumb|280px|Seed Point Panel]]

|-
|* '''Target statistic parameters panel:'''

|[[Image::MushTargetStatisticParametersPanel.png|thumb|280px|Target Statistic Parameters Panel]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T05:29:44Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|-
|* '''Output panel:'''
Specify(optionally) the weights file, which stores the final values for the MUSH equation. Specify also the filename of the MUSH image as well as the brain volume mask.
|[[Image:MushOutputPanel.png|thumb|280px|Output Panel]]

|-
|* '''Seed point panel:'''
Specify the seed point for mask generation. This defaults to the center of the brain in a standard MRI image. Normally this shouldn't need to be changed.
|[[Image:MushSeedPointPanel.png|thumb|280px|Seed Point Panel]]

|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

File:MushSeedPointPanel.png

2010-05-04T05:28:10Z

StevenDunn:

Documentation/4.1/Modules/BRAINSMush

2010-05-04T05:28:02Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|-
|* '''Output panel:'''
Specify(optionally) the weights file, which stores the final values for the MUSH equation. Specify also the filename of the MUSH image as well as the brain volume mask.
|[[Image:MushOutputPanel.png|thumb|280px|Output Panel]]

|-
|* '''Seed point panel:'''

|[[Image:MushSeedPointPanel.png|thumb|280px|Seed Point Panel]]

|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T05:12:06Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|-
|* '''Output panel:'''
Specify(optionally) the weights file, which stores the final values for the MUSH equation. Specify also the filename of the MUSH image as well as the brain volume mask.
|[[Image:MushOutputPanel.png|thumb|280px|Output Panel]]

|-
|* '''Viewing panel:'''

|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T05:11:49Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|-
|* '''Parameters panel:'''

|-
|* '''Output panel:'''
Specify(optionally) the weights file, which stores the final values for the MUSH equation. Specify also the filename of the MUSH image as well as the brain volume mask.
|[[Image:MushOutputPanel.png|thumb|280px|Output Panel]]

|-
|* '''Viewing panel:'''

|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T05:11:21Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|-
|* '''Parameters panel:'''

|-
|* '''Output panel:'''
|[[Image:MushOutputPanel.png|thumb|280px|Output Panel]]
Specify(optionally) the weights file, which stores the final values for the MUSH equation. Specify also the filename of the MUSH image as well as the brain volume mask.

|-
|* '''Viewing panel:'''

|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

File:MushOutputPanel.png

2010-05-04T05:04:09Z

StevenDunn:

Documentation/4.1/Modules/BRAINSMush

2010-05-04T05:03:41Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|-
|* '''Parameters panel:'''

|-
|* '''Output panel:'''
|[[Image:MushOutputPanel.png|thumb|280px|Output Panel]]

|-
|* '''Viewing panel:'''

|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:56:57Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|-
|* '''Parameters panel:'''

|-
|* '''Output panel:'''

|-
|* '''Viewing panel:'''

|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:56:35Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|-
|* '''Parameters panel:'''
|** '''First parameter'''
|** '''Second parameter'''
|* '''Output panel:'''
|** '''First output'''
|** '''Second output'''
|* '''Viewing panel:'''

|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:56:21Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|-
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|* '''Parameters panel:'''
|** '''First parameter'''
|** '''Second parameter'''
|* '''Output panel:'''
|** '''First output'''
|** '''Second output'''
|* '''Viewing panel:'''

|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:55:46Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
|* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

|* '''Parameters panel:'''
|** '''First parameter'''
|** '''Second parameter'''
|* '''Output panel:'''
|** '''First output'''
|** '''Second output'''
|* '''Viewing panel:'''

|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:54:56Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''

|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:54:36Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who want it.

* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

File:MushInputPanel.png

2010-05-04T04:54:05Z

StevenDunn:

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:52:51Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who may need it.

* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:52:33Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
Specify the two input images(typically T1 and T2) as well as an optional ROI mask. This mask can be specified to aid the creation of the MUSH image, but is not necessary. Providing an ROI mask occasionally produces greater contrast in the output MUSH image(by constraining the pixels over which the mean and variance are calculated), so it is provided as an option for those who may need it.
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:42:21Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:41:55Z

StevenDunn: /* Quick Tour of Features and Use */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
|[[Image:MushInputPanel.png|thumb|280px|Input Panel]]

** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:40:35Z

StevenDunn: /* Tutorials */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:40:15Z

StevenDunn: /* Use Cases, Examples */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Case===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:02:01Z

StevenDunn:

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Coronal)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

File:MushMask2.png

2010-05-04T04:01:27Z

StevenDunn:

File:MushMask.png

2010-05-04T04:00:24Z

StevenDunn:

Documentation/4.1/Modules/BRAINSMush

2010-05-04T04:00:05Z

StevenDunn:

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:MushMask.png|thumb|280px|Mush Brain Extraction Mask(Axial)]]
|[[Image:MushMask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T03:59:34Z

StevenDunn:

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:Mask.png|thumb|280px|Mush Brain Extraction Mask(Axial)]]
|[[Image:Mask2.png|thumb|280px|Mush Brain Extraction Mask(Sagittal)]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

File:Mask.png

2010-05-04T03:58:02Z

StevenDunn:

Documentation/4.1/Modules/BRAINSMush

2010-05-04T03:57:46Z

StevenDunn:

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|[[Image:Mask.png|thumb|280px|Mush Brain Extraction Mask]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

File:Mush.png

2010-05-04T03:57:04Z

StevenDunn:

Documentation/4.1/Modules/BRAINSMush

2010-05-04T03:56:47Z

StevenDunn:

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}
{|
|[[Image:Mush.png|thumb|280px|Mush Image]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T03:56:18Z

StevenDunn:

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|[[Image:Mush.png|thumb|280px|Mush Image]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

File:T2.png

2010-05-04T03:55:39Z

StevenDunn:

Documentation/4.1/Modules/BRAINSMush

2010-05-04T03:55:10Z

StevenDunn:

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|[[Image:T2.png|thumb|280px|T2 Image]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

File:T1.png

2010-05-04T03:54:30Z

StevenDunn:

Documentation/4.1/Modules/BRAINSMush

2010-05-04T03:54:12Z

StevenDunn:

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:T1.png|thumb|280px|T1 Image]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T03:52:40Z

StevenDunn: Removed unused image stubs

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-05-04T03:52:13Z

StevenDunn:

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:screenshotBlank.png|thumb|280px|Caption]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

File:ScreenshotBlankNotOptional.png

2010-05-04T03:41:39Z

StevenDunn: uploaded a new version of "File:ScreenshotBlankNotOptional.png": Changed image to one showing all the interface options.

File:ScreenshotBlankNotOptional.png

2010-05-04T03:39:13Z

StevenDunn: uploaded a new version of "File:ScreenshotBlankNotOptional.png": Added user interface image

Documentation/4.1/Modules/BRAINSMush

2010-04-27T20:55:32Z

StevenDunn: /* Use Cases, Examples */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:screenshotBlank.png|thumb|280px|Output]]
|[[Image:screenshotBlank.png|thumb|280px|Caption]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===
The processing involved in the module is not designed for interactive use. It may take up to 15 minutes( or longer, depending on processor speed) to process a dataset.

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-04-27T20:46:15Z

StevenDunn: /* Module Description */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:screenshotBlank.png|thumb|280px|Output]]
|[[Image:screenshotBlank.png|thumb|280px|Caption]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>Mush = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-04-27T20:44:45Z

StevenDunn: /* Module Description */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:screenshotBlank.png|thumb|280px|Output]]
|[[Image:screenshotBlank.png|thumb|280px|Caption]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>MUSH = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-04-27T20:44:25Z

StevenDunn: /* Module Description */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:screenshotBlank.png|thumb|280px|Output]]
|[[Image:screenshotBlank.png|thumb|280px|Caption]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>MUSH = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.

Documentation/4.1/Modules/BRAINSMush

2010-04-27T20:39:43Z

StevenDunn: /* Module Description */

[[Documentation-3.6|Return to Slicer 3.6 Documentation]]

[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]

__NOTOC__
===BRAINSMush===
BRAINSMush

{|
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|[[Image:screenshotBlank.png|thumb|280px|Output]]
|[[Image:screenshotBlank.png|thumb|280px|Caption]]
|}

== General Information ==
===Module Type & Category===

Type: CLI

Category: Segmentation

===Authors, Collaborators & Contact===
* Ronald Pierson, University of Iowa
* Gregory Harris, University of Iowa
* Hans Johnson, PhD: University of Iowa
* Steven A. Dunn: University of Iowa
* Vincent Magnotta, PhD: University of Iowa
* Contacts: Vincent Magnotta, [mailto:vincent-magnotta@uiowa.edu vincent-magnotta@uiowa.edu]; Steven Dunn, [mailto:steven-dunn@uiowa.edu steven-dunn@uiowa.edu]

===Module Description===
BRAINSMush uses the Maximize Uniformity Summation Heuristic(MUSH) optimizer, as developed at the [http://www.uiowa.edu University of Iowa], to extract the
brain and surface CSF from a multi-modal imaging study. It forms a linear combination of multi-modal MR imaging data to make the
signal intensity within the brain as uniform as possible. This resulting image is then thresholded to obtain the brain and surface CSF region.

MUSH uses a T1-weighted and T2-weighted image as its inputs, and their mean and variance are calculated. A linear combination is then found that approaches the desired mean and variance( by default 1000.0 and 0.0, respectively) by only varying the coefficients a and b in the following equation:

<center><math>MUSH = {\color{red}a}T1 + {\color{blue}b}T2</math></center>

Within the region of interest, the MUSH optimizer finds the number of voxels, the sum voxels and the sum of squares for
both images separately. Then a 2 by 2 Levenberg-Marquardt optimizer repeatedly reconstructs the mean and variance of
the mixture model corresponding to the weighted sum image of coefficients a and b. This is very fast because each step
only involves the calculation of two jointly weighted statistics. The result of optimization is the pair of linear coefficients
that minimizes the sum of squares error:

<center><math>Error = (mean - 1000.0)^2 + (variance - 0.0)^2</math></center>

The image is thresholded by the mean signal intensity plus-or-minus five standard deviations.

This method was applied to a sample of 20 MR brain scans and its results were compared to those obtained by 3dSkullStrip, 3dIntracranial, BET and BET2. The average Jaccard metrics for the twenty subjects was 0.66(BET), 0.61(BET2), 0.88(3dIntracranial), 0.91(3dSkullStrip) and 0.94(MUSH).

== Usage ==

===Use Cases, Examples===

This module is especially appropriate for these use cases:

* Use Case 1:
* Use Case 2:

Examples of the module in use:

* Example 1
* Example 2

===Tutorials===

Links to tutorials explaining how to use this module:

* Tutorial 1
** Data Set 1

===Quick Tour of Features and Use===

A list panels in the interface, their features, what they mean, and how to use them. For instance:

{|
|
* '''Input panel:'''
** '''First input'''
** '''Second input'''
* '''Parameters panel:'''
** '''First parameter'''
** '''Second parameter'''
* '''Output panel:'''
** '''First output'''
** '''Second output'''
* '''Viewing panel:'''
|[[Image:screenshotBlankNotOptional.png|thumb|280px|User Interface]]
|}

== Development ==

===Notes from the Developer(s)===

Algorithms used, library classes depended upon, use cases, etc.

===Dependencies===

Other modules or packages that are required for this module's use.

===Tests===

On the [http://www.cdash.org/CDash/index.php?project=Slicer3 Dashboard], these tests verify that the module is working on various platforms:

* MyModuleTest1 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest1.cxx]
* MyModuleTest2 [http://viewvc.slicer.org/viewcvs.cgi/trunk MyModuleTest2.cxx]

===Known bugs===

Links to known bugs in the Slicer3 bug tracker

* [http://www.na-mic.org/Bug/view.php?id=000 Bug 000: description]

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

Links to the module's source code:

Source code:
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.cxx ]
*[http://viewvc.slicer.org/viewcvs.cgi/trunk file.h ]

Doxygen documentation:
*[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classes.html class1]

== More Information ==

===Acknowledgment===
Include funding and other support here.

===References===
Publications related to this module go here. Links to pdfs would be useful.