Modules:DiffusionTensorEstimation-Documentation-3.6 - Revision history

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

2010-07-15T19:31:16Z

Quick Tour of Features and Use

Kikinis: /* Module Name */

2010-05-20T03:08:05Z

Module Name

Raul: /* Module Type & Category */

2010-05-19T19:43:48Z

Module Type & Category

Raul: /* Acknowledgement */

2010-05-19T19:19:57Z

Acknowledgement

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

2010-05-19T18:47:49Z

Quick Tour of Features and Use

Raul: /* Module Description */

2010-05-19T18:44:55Z

Module Description

Westin at 19:09, 8 April 2010

2010-04-08T19:09:57Z

Westin: Created page with 'Return to Slicer 3.6 Documentation Gallery of New Features NOTOC ===Module Name=== Diffusion Tensor Estimation {…'

2010-04-08T19:01:40Z

Created page with 'Return to Slicer 3.6 Documentation Gallery of New Features __NOTOC__ ===Module Name=== Diffusion Tensor Estimation {…'

New page

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

[[Announcements:Slicer3.4#Highlights|Gallery of New Features]]
__NOTOC__
===Module Name===
Diffusion Tensor Estimation
{|
|[[Image:DiffusionTensorEstimationGUI.png|thumb|280px|Caption 1]]
|}
== General Information ==
===Module Type & Category===

Type: CLI

Category: Base or (Filtering, Registration, ''etc.'')

===Authors, Collaborators & Contact===
* Author: Raúl San José Estépar, BWH
* Contributor: Gordon Kindlmann, University of Chicago
* [http://lmi.bwh.harvard.edu/~rjosest/address.html Contact Information]

===Module Description===
This module estimates the diffusion tensor model from a Diffusion Weighted Image (DWI) Volume. The results is a tensor volume that can be used to compute different anisotropy measurements, for example Fractional Anisotropy, and perform tractography.

== Usage ==

===Examples, Use Cases & Tutorials===

* Compute DTI volume from DWI. It is the first step of any pipeline that employs DTI to assess white matter structure.

===Quick Tour of Features and Use===
The module takes one DWI volume and computes a DTI volume. The parameters are the following:
* '''Input/Output:''' Defines input and output files.
** ''Input DWI Volume'' is the input DWI volume,
** ''Output DTI Volume'' is the DTI volume that will be estimated.
** ''Output Baseline Volume'' is the average of the B0 images (non-diffusion weighted images) of the DWI sequence. This volume is useful to have a structural representation of the DTI volume .
** ''Otsu Threshold Mask'' is a approximated mask of the white matter that can be used to filter out the background.
* '''Estimation Parameters:'''
** ''Least Squares'': Least Squares estimation method. This is the method by default and stable [Basser, 2002].
** ''Weighted Least Squares'': WLS estimation method based on Salvador. This method implementation is still experimental [Salvador, 2005].
** ''Non-linear'': direct non-least squares fitting of the tensor model to the data without log-transformation. This method is experimental.
** ''Otsu Omega Threshold Parameter'': weight that controls the otsu threshold.
** ''Remove Island in Tensor Mask'': if active, holes in the produced mask will be removed.
** ''Apply Mask to Tensor Image'': Mask output DTI volume with the computed mask. Tensor outside the mask will be set to zero.

== Development ==

===Dependencies===

None

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===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===

[http://www.na-mic.org/ViewVC/index.cgi/ Source code].

[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/ Links] to documentation generated by doxygen.

== More Information ==

===Acknowledgement===

===References===
*P. J. Basser and D. K. Jones. Diffusion-tensor MRI: theory, experimental design and data analysis - a technical review. NMR Biomed, 15(7-8):456–67, 2002.
*R. Salvador, A. Pena, D. K. Menon, T. A. Carpenter, J. D. Pickard, and E. T. Bullmore. Formal characterization and extension of the linearized diffusion tensor model. Hum Brain Mapp, 24(2):144–55, 2005.

@@ Line 41: / Line 41: @@
 ** ''Weighted Least Squares'': WLS estimation method based on Salvador's method that takes into account the Rician noise model in the MRI signal to weight the least square fitting by the magnitude of the DWI signal. This method implementation is still experimental [Salvador, 2005].
 ** ''Non-linear'': direct non-least squares fitting of the tensor model to the data without log-transformation. This method is experimental.
-** ''Otsu Omega Threshold Parameter'': weight that controls the otsu threshold.
+** ''Otsu Omega Threshold Parameter'': weight that controls the otsu threshold.  Smaller numbers create larger masks.
 ** ''Remove Island in Tensor Mask'': if active,  holes in the produced mask will be removed.
 ** ''Apply Mask to Tensor Image'': Mask output DTI volume with the computed mask. Tensor outside the mask will be set to zero.

@@ Line 6: / Line 6: @@
 Diffusion Tensor Estimation
 {|
-|[[Image:DiffusionTensorEstimationGUI.png|thumb|280px|Caption 1]]
+|[[Image:DiffusionTensorEstimationGUI.png|thumb|380px|Caption 1]]
 |}
 == General Information ==
 ===Module Type & Category===

@@ Line 13: / Line 13: @@
 Type: CLI
-Category: Base or (Filtering, Registration, ''etc.'')
+Category: Diffusion MRI Applications
 ===Authors, Collaborators & Contact===

@@ Line 67: / Line 67: @@
 ===Acknowledgement===
 ===References===
 *P. J. Basser and D. K. Jones. Diffusion-tensor MRI: theory, experimental design and data analysis - a technical review. NMR Biomed, 15(7-8):456–67, 2002.
 *R. Salvador, A. Pena, D. K. Menon, T. A. Carpenter, J. D. Pickard, and E. T. Bullmore. Formal characterization and extension of the linearized diffusion tensor model. Hum Brain Mapp, 24(2):144–55, 2005.

@@ Line 35: / Line 35: @@
 ** ''Output DTI Volume'' is the DTI volume that will be estimated.
 ** ''Output Baseline Volume'' is the average of the B0 images (non-diffusion weighted images) of the DWI sequence. This volume is useful to have a structural representation of the DTI volume .
-** ''Otsu Threshold Mask'' is a approximated mask of the white matter that can be used to filter out the background.
+** ''Otsu Threshold Mask'' is an approximated mask of the white matter that can be used to filter out the background.
 * '''Estimation Parameters:'''
-** ''Least Squares'': Least Squares estimation method. This is the method by default and stable [Basser, 2002].
+** ''Least Squares'': Least Squares estimation method. This is the method by default and the most stable [Basser, 2002].
-** ''Weighted Least Squares'': WLS estimation method based on Salvador. This method implementation is still experimental [Salvador, 2005].
+** ''Weighted Least Squares'': WLS estimation method based on Salvador's method that takes into account the Rician noise model in the MRI signal to weight the least square fitting by the magnitude of the DWI signal. This method implementation is still experimental [Salvador, 2005].
 ** ''Non-linear'': direct non-least squares fitting of the tensor model to the data without log-transformation. This method is experimental.
 ** ''Otsu Omega Threshold Parameter'': weight that controls the otsu threshold.

@@ Line 21: / Line 21: @@
 ===Module Description===
-This module estimates the diffusion tensor model from a Diffusion Weighted Image (DWI) Volume. The results is a tensor volume that can be used to compute different anisotropy measurements, for example Fractional Anisotropy, and perform tractography.
+This module estimates the diffusion tensor model from a Diffusion Weighted Image (DWI) Volume. The result is a tensor volume that can be used to compute different anisotropy measurements, for example Fractional Anisotropy, and perform tractography.
 == Usage ==

@@ Line 1: / Line 1: @@
 [[Documentation-3.6|Return to Slicer 3.6 Documentation]]
-[[Announcements:Slicer3.4#Highlights|Gallery of New Features]]
+[[Announcements:Slicer3.6#Highlights|Gallery of New Features]]
 __NOTOC__
 ===Module Name===