Slicer Wiki - User contributions [en]

Documentation/Nightly/Modules/AirwaySegmentation

2018-01-03T09:29:01Z

Pietro.nardelli: Updating contributor's emails

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>pnardelli@bwh.harvard.edu</email>, <email>pie.nardelli@gmail.com</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is an extension for airway segmentation starting from chest CT images. Two modules come with this extension. A simple CLI module, called Airway Segmentation CLI, that uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. To use this module for the segmentation, the user is required to place only one
fiducial point within the trachea. This fiducial is used as starting point for the region growing segmentation. Also, using this module, the user needs to specify the convolution kernel used for reconstructing the DICOM image. A scripted module, called AirwaySegmentation, is also available. This is a python module that automatically invokes the CLI module described above. It automatically extracts the convolution kernel of the image, and for this reason it only works for DICOM images. The output volume is also automatically created. This way, the user needs to only specify the input volume, and the fiducial placed in the trachea. A label color can also be optionally selected.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:Screenshot from 2015-01-08 11-32-48.jpg|thumb|500px|Airway Segmentation Scripted Module: example of usage]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''IO Parameters''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Seed''': Seed point for the algorithm. Only one seed point must be placed within the trachea. If using an pig CT chest image, the fiducial has to be placed between the carina and the further branch coming out of the trachea.

* '''''Segmentation Parameters''''': Input parameters for segmentation (optional).
** '''Airway Label Color''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
The user interface panel for the scripted module:

{|
|[[Image:AirwaySegmentation_Scripted_Interface.jpg|thumb|300px|{{documentation/modulename}} Scripted Module Interface ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
Nardelli, P., Khan, K. A., Corvò, A., Moore, N., Murphy, M. J., Twomey, M., O’Connor, O. J., Kennedy, M. P., Estépar, R. S. J., Maher, M. M. & Cantillon-Murphy, P. (2015). Optimizing parameters of an open-source airway segmentation algorithm using different CT images. Biomedical engineering online, 14(1), 62.


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/Slicer-AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

Documentation/Nightly/Modules/AirwaySegmentation

2015-07-28T15:46:53Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>p.nardelli@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is an extension for airway segmentation starting from chest CT images. Two modules come with this extension. A simple CLI module, called Airway Segmentation CLI, that uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. To use this module for the segmentation, the user is required to place only one
fiducial point within the trachea. This fiducial is used as starting point for the region growing segmentation. Also, using this module, the user needs to specify the convolution kernel used for reconstructing the DICOM image. A scripted module, called AirwaySegmentation, is also available. This is a python module that automatically invokes the CLI module described above. It automatically extracts the convolution kernel of the image, and for this reason it only works for DICOM images. The output volume is also automatically created. This way, the user needs to only specify the input volume, and the fiducial placed in the trachea. A label color can also be optionally selected.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:Screenshot from 2015-01-08 11-32-48.jpg|thumb|500px|Airway Segmentation Scripted Module: example of usage]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''IO Parameters''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Seed''': Seed point for the algorithm. Only one seed point must be placed within the trachea. If using an pig CT chest image, the fiducial has to be placed between the carina and the further branch coming out of the trachea.

* '''''Segmentation Parameters''''': Input parameters for segmentation (optional).
** '''Airway Label Color''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
The user interface panel for the scripted module:

{|
|[[Image:AirwaySegmentation_Scripted_Interface.jpg|thumb|300px|{{documentation/modulename}} Scripted Module Interface ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
Nardelli, P., Khan, K. A., Corvò, A., Moore, N., Murphy, M. J., Twomey, M., O’Connor, O. J., Kennedy, M. P., Estépar, R. S. J., Maher, M. M. & Cantillon-Murphy, P. (2015). Optimizing parameters of an open-source airway segmentation algorithm using different CT images. Biomedical engineering online, 14(1), 62.


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/Slicer-AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

Documentation/Nightly/Modules/AirwaySegmentation

2015-01-08T12:19:51Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>p.nardelli@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is an extension for airway segmentation starting from chest CT images. Two modules come with this extension. A simple CLI module, called Airway Segmentation CLI, that uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. To use this module for the segmentation, the user is required to place only one
fiducial point within the trachea. This fiducial is used as starting point for the region growing segmentation. Also, using this module, the user needs to specify the convolution kernel used for reconstructing the DICOM image. A scripted module, called AirwaySegmentation, is also available. This is a python module that automatically invokes the CLI module described above. It automatically extracts the convolution kernel of the image, and for this reason it only works for DICOM images. The output volume is also automatically created. This way, the user needs to only specify the input volume, and the fiducial placed in the trachea. A label color can also be optionally selected.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:Screenshot from 2015-01-08 11-32-48.jpg|thumb|500px|Airway Segmentation Scripted Module: example of usage]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''IO Parameters''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Seed''': Seed point for the algorithm. Only one seed point must be placed within the trachea. If using an pig CT chest image, the fiducial has to be placed between the carina and the further branch coming out of the trachea.

* '''''Segmentation Parameters''''': Input parameters for segmentation (optional).
** '''Airway Label Color''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
The user interface panel for the scripted module:

{|
|[[Image:AirwaySegmentation_Scripted_Interface.jpg|thumb|300px|{{documentation/modulename}} Scripted Module Interface ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
N/A


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/Slicer-AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

File:AirwaySegmentation Scripted Interface.jpg

2015-01-08T12:19:21Z

Pietro.nardelli: Interface of airway segmentation scripted module.

Interface of airway segmentation scripted module.

Documentation/Nightly/Modules/AirwaySegmentation

2015-01-08T12:16:26Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>p.nardelli@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is an extension for airway segmentation starting from chest CT images. Two modules come with this extension. A simple CLI module, called Airway Segmentation CLI, that uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. To use this module for the segmentation, the user is required to place only one
fiducial point within the trachea. This fiducial is used as starting point for the region growing segmentation. Also, using this module, the user needs to specify the convolution kernel used for reconstructing the DICOM image. A scripted module, called AirwaySegmentation, is also available. This is a python module that automatically invokes the CLI module described above. It automatically extracts the convolution kernel of the image, and for this reason it only works for DICOM images. The output volume is also automatically created. This way, the user needs to only specify the input volume, and the fiducial placed in the trachea. A label color can also be optionally selected.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:Screenshot from 2015-01-08 11-32-48.jpg|thumb|500px|Airway Segmentation Scripted Module: example of usage]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''IO Parameters''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Seed''': Seed point for the algorithm. Only one seed point must be placed within the trachea. If using an pig CT chest image, the fiducial has to be placed between the carina and the further branch coming out of the trachea.

* '''''Segmentation Parameters''''': Input parameters for segmentation (optional).
** '''Airway Label Color''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
The user interface panel for the scripted module:

{|
|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Scripted Module Interface ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
N/A


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/Slicer-AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

File:Slicer4-AirwaySegmentation-PANEL.png

2015-01-08T12:15:32Z

Pietro.nardelli: uploaded a new version of "File:Slicer4-AirwaySegmentation-PANEL.png": Interface of airway segmentation scripted module

Documentation/Nightly/Modules/AirwaySegmentation

2015-01-08T12:12:23Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>p.nardelli@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is an extension for airway segmentation starting from chest CT images. Two modules come with this extension. A simple CLI module, called Airway Segmentation CLI, that uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. To use this module for the segmentation, the user is required to place only one
fiducial point within the trachea. This fiducial is used as starting point for the region growing segmentation. Also, using this module, the user needs to specify the convolution kernel used for reconstructing the DICOM image. A scripted module, called AirwaySegmentation, is also available. This is a python module that automatically invokes the CLI module described above. It automatically extracts the convolution kernel of the image, and for this reason it only works for DICOM images. The output volume is also automatically created. This way, the user needs to only specify the input volume, and the fiducial placed in the trachea. A label color can also be optionally selected.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:Screenshot from 2015-01-08 11-32-48.jpg|thumb|500px|Airway Segmentation Scripted Module: example of usage]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''IO Parameters''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Seed''': Seed point for the algorithm. Only one seed point must be placed within the trachea. If using an pig CT chest image, the fiducial has to be placed between the carina and the further branch coming out of the trachea.

* '''''Segmentation Parameters''''': Input parameters for segmentation (optional).
** '''Airway Label Color''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
The user interface panel for the scripted module:

{|
|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Module GUI ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
N/A


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/Slicer-AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

Documentation/Nightly/Modules/AirwaySegmentation

2015-01-08T12:06:48Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>p.nardelli@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is an extension for airway segmentation starting from chest CT images. Two modules come with this extension. A simple CLI module, called Airway Segmentation CLI, that uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. To use this module for the segmentation, the user is required to place only one
fiducial point within the trachea. This fiducial is used as starting point for the region growing segmentation. Also, using this module, the user needs to specify the convolution kernel used for reconstructing the DICOM image. A scripted module, called AirwaySegmentation, is also available. This is a python module that automatically invokes the CLI module described above. It automatically extracts the convolution kernel of the image, and for this reason it only works for DICOM images. The output volume is also automatically created. This way, the user needs to only specify the input volume, and the fiducial placed in the trachea. A label color can also be optionally selected.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:Screenshot from 2015-01-08 11-32-48.jpg|thumb|500px|Airway Segmentation Scripted Module: example of usage]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''IO Parameters''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Seed''': Seed point for the algorithm. Only one seed point must be placed within the trachea. If using an pig CT chest image, the fiducial has to be placed between the carina and the further branch coming out of the trachea.

* '''''Segmentation Parameters''''': Input parameters for segmentation (optional).
** '''Airway Label Color''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
The user interface panel:

{|
|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Module GUI ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
N/A


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/Slicer-AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

Documentation/Nightly/Modules/AirwaySegmentation

2015-01-08T12:01:53Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>p.nardelli@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is an extension for airway segmentation starting from chest CT images. Two modules come with this extension. A simple CLI module, called Airway Segmentation CLI, that uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. To use this module for the segmentation, the user is required to place only one
fiducial point within the trachea. This fiducial is used as starting point for the region growing segmentation. Also, using this module, the user needs to specify the convolution kernel used for reconstructing the DICOM image. A scripted module, called AirwaySegmentation, is also available. This is a python module that automatically invokes the CLI module described above. It automatically extracts the convolution kernel of the image, and for this reason it only works for DICOM images. The output volume is also automatically created. This way, the user needs to only specify the input volume, and the fiducial placed in the trachea. A label color can also be optionally selected.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:Screenshot from 2015-01-08 11-32-48.jpg|thumb|500px|Airway Segmentation Scripted Module: example of usage]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''Segmentation Parameters''''': Input parameters for segmentation.
** '''Airway Label Value''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
** '''Seeds''': Seed points for the algorithm. Three seeds points must be placed. The first one in the trachea, the others in the main bronchi of the left and right lungs.

* '''''IO''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Output Parameters''': Output label.

The user interface panel:

{|
|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Module GUI ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
N/A


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/Slicer-AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

Documentation/Nightly/Modules/AirwaySegmentation

2015-01-08T12:00:43Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>p.nardelli@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is an extension for airway segmentation starting from chest CT images. Two modules come with this extension. A simple CLI module, called Airway Segmentation CLI, that uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. To use this module for the segmentation, the user is required to place only one
fiducial point within the trachea. This fiducial is used as starting point for the region growing segmentation. Also, using this module, the user needs to specify the convolution kernel used for reconstructing the DICOM image. A scripted module, called AirwaySegmentation, is also available. This is a python module that automatically invokes the CLI module described above. It automatically extracts the convolution kernel of the image, and for this reason it only works for DICOM images. The output volume is also automatically created. This way, the user needs to only specify the input volume, and the fiducial placed in the trachea. A label color can also be optionally selected.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:Screenshot from 2015-01-08 11-32-48.jpg|thumb|500px|Airway Segmentation Module ]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''Segmentation Parameters''''': Input parameters for segmentation.
** '''Airway Label Value''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
** '''Seeds''': Seed points for the algorithm. Three seeds points must be placed. The first one in the trachea, the others in the main bronchi of the left and right lungs.

* '''''IO''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Output Parameters''': Output label.

The user interface panel:

{|
|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Module GUI ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
N/A


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/Slicer-AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

File:Screenshot from 2015-01-08 11-32-48.jpg

2015-01-08T11:58:28Z

Pietro.nardelli: Screenshot of airway segmentation scripted module usage.

Screenshot of airway segmentation scripted module usage.

Documentation/Nightly/Modules/AirwaySegmentation

2015-01-08T11:48:05Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>p.nardelli@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is an extension for airway segmentation starting from chest CT images. Two modules come with this extension. A simple CLI module, called Airway Segmentation CLI, that uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. To use this module for the segmentation, the user is required to place only one
fiducial point within the trachea. This fiducial is used as starting point for the region growing segmentation. Also, using this module, the user needs to specify the convolution kernel used for reconstructing the DICOM image. A scripted module, called AirwaySegmentation, is also available. This is a python module that automatically invokes the CLI module described above. It automatically extracts the convolution kernel of the image, and for this reason it only works for DICOM images. The output volume is also automatically created. This way, the user needs to only specify the input volume, and the fiducial placed in the trachea. A label color can also be optionally selected.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:AirwaySegmentation_Module.png|thumb|500px|Airway Segmentation Module ]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''Segmentation Parameters''''': Input parameters for segmentation.
** '''Airway Label Value''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
** '''Seeds''': Seed points for the algorithm. Three seeds points must be placed. The first one in the trachea, the others in the main bronchi of the left and right lungs.

* '''''IO''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Output Parameters''': Output label.

The user interface panel:

{|
|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Module GUI ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
N/A


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/Slicer-AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

Documentation/Nightly/Modules/AirwaySegmentation

2015-01-08T11:46:32Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>p.nardelli@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is an extension for airway segmentation starting from chest CT images. Two modules come with this extension. A simple CLI module, called Airway Segmentation CLI, that uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. To use this module for the segmentation, the user is required to place only one
fiducial point within the trachea. This fiducial is used as starting point for the region growing segmentation. Also, using this module, the user needs to specify the convolution kernel used for reconstructing the DICOM image. A scripted module, called AirwaySegmentation, is also available. This is a python module that automatically invokes the CLI module described above. It automatically extracts the convolution kernel of the image, and for this reason it only works for DICOM images. The output volume is also automatically created. This way, the user needs to only specify the input volume, and the fiducial placed in the trachea. a label color can also be optionally selected.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:AirwaySegmentation_Module.png|thumb|500px|Airway Segmentation Module ]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''Segmentation Parameters''''': Input parameters for segmentation.
** '''Airway Label Value''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
** '''Seeds''': Seed points for the algorithm. Three seeds points must be placed. The first one in the trachea, the others in the main bronchi of the left and right lungs.

* '''''IO''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Output Parameters''': Output label.

The user interface panel:

{|
|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Module GUI ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
N/A


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/Slicer-AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

Documentation/Nightly/Modules/AirwaySegmentation

2014-07-01T15:21:14Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>p.nardelli@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is a simple CLI module for airway segmentation starting from chest CT images. This CLI uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. The user has to specify three fiducial points: one in the trachea, and two in the main bronchi of the left and right lungs. These fiducials are the starting points for the region growing segmentation. No more than 3 seed points are allowed.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:AirwaySegmentation_Module.png|thumb|500px|Airway Segmentation Module ]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''Segmentation Parameters''''': Input parameters for segmentation.
** '''Airway Label Value''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
** '''Seeds''': Seed points for the algorithm. Three seeds points must be placed. The first one in the trachea, the others in the main bronchi of the left and right lungs.

* '''''IO''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Output Parameters''': Output label.

The user interface panel:

{|
|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Module GUI ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
N/A


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/Slicer-AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

Documentation/Nightly/Modules/AirwaySegmentation

2013-07-27T08:54:43Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>111126418@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is a simple CLI module for airway segmentation starting from chest CT images. This CLI uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. The user has to specify three fiducial points: one in the trachea, and two in the main bronchi of the left and right lungs. These fiducials are the starting points for the region growing segmentation. No more than 3 seed points are allowed.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:AirwaySegmentation_Module.png|thumb|500px|Airway Segmentation Module ]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''Segmentation Parameters''''': Input parameters for segmentation.
** '''Airway Label Value''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
** '''Seeds''': Seed points for the algorithm. Three seeds points must be placed. The first one in the trachea, the others in the main bronchi of the left and right lungs.

* '''''IO''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Output Parameters''': Output label.

The user interface panel:

{|
|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Module GUI ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
N/A


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/Slicer-AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

Documentation/Nightly/Modules/AirwaySegmentation

2013-07-24T13:44:38Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>111126418@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is a simple CLI module for the segmentation of the airway starting from chest CT images. This CLI uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. The user has to specify three fiducial points: one in the trachea, and two in the main bronchi of the left and right lungs. The fiducials are the starting points for the region growing segmentation. No more than 3 seed points are allowed.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:AirwaySegmentation_Module.png|thumb|500px|Airway Segmentation Module ]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''Segmentation Parameters''''': Input parameters for segmentation.
** '''Airway Label Value''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
** '''Seeds''': Seed points for the algorithm. Three seeds points must be placed. The first one in the trachea, the others in the main bronchi of the left and right lungs.

* '''''IO''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Output Parameters''': Output label.

The user interface panel:

{|
|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Module GUI ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
N/A


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/Slicer-AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

Documentation/Nightly/Modules/AirwaySegmentation

2013-07-18T08:44:34Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>111126418@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is a simple CLI module for the segmentation of the airway starting from chest CT images. This CLI uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. The user has to specify three fiducial points: one in the trachea, and two in the main bronchi of the left and right lungs. The fiducials are the starting points for the region growing segmentation. No more than 3 seed points are allowed.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:AirwaySegmentation_Module.png|thumb|500px|Airway Segmentation Module ]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''Segmentation Parameters''''': Input parameters for segmentation.
** '''Airway Label Value''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
** '''Seeds''': Seed points for the algorithm. Three seeds points must be placed. The first one in the trachea, the others in the main bronchi of the left and right lungs.

* '''''IO''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Output Parameters''': Output label.

The user interface panel:

{|
|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Module GUI ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
N/A


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

File:AirwaySegmentation-ICON.png

2013-07-17T15:57:08Z

Pietro.nardelli: uploaded a new version of "File:AirwaySegmentation-ICON.png"

File:AirwaySegmentation-ICON.png

2013-07-17T15:39:50Z

Pietro.nardelli: uploaded a new version of "File:AirwaySegmentation-ICON.png"

File:AirwaySegmentation-ICON.png

2013-07-17T15:39:19Z

Pietro.nardelli: uploaded a new version of "File:AirwaySegmentation-ICON.png"

File:AirwaySegmentation-ICON.png

2013-07-17T15:37:38Z

Pietro.nardelli:

Documentation/Nightly/Modules/AirwaySegmentation

2013-07-15T14:09:59Z

Pietro.nardelli:

<noinclude>{{documentation/versioncheck}}</noinclude>

{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
Extension: [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] 
Acknowledgments:
This work is supported by NA-MIC, the Slicer Community and University College of Cork. 
Author: Pietro Nardelli (University College Cork) 
Contributor1: 
Contact: Pietro Nardelli, <email>111126418@umail.ucc.ie</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|{{collaborator|logo|namic}}|{{collaborator|longname|namic}}
|Image:UCC-logoNEW.png|University College Cork (UCC)
|Image:Biolectromagnetics_group_UCC.jpg|Bioelectromagnetics group UCC
|{{collaborator|logo|spl}}|{{collaborator|longname|spl}}
}}

{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
AirwaySegmentation is a simple CLI module for the segmentation of the airway starting from chest CT images. This CLI uses a modified version of ITK's itkConnectedThresholdImageFilter to segment all the pixels with an intensity below a threshold. The threshold is automatically identified by the module. The user has to specify three fiducial points: one in the trachea, and two in the main bronchi of the left and right lungs. The fiducials are the starting points for the region growing segmentation. No more than 3 seed points are allowed.


{{documentation/{{documentation/version}}/module-section|Use Cases}}
*Airway Segmentation starting from chest CT datasets

{|
|[[Image:AirwaySegmentation_Module.png|thumb|500px|Airway Segmentation Module ]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}

N/A


{{documentation/{{documentation/version}}/module-section|Panels and their use}}

* '''''Segmentation Parameters''''': Input parameters for segmentation.
** '''Airway Label Value''': The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the algorithm.
** '''Seeds''': Seed points for the algorithm. Three seeds points must be placed. One in the trachea, the others in the main bronchi of the left and right lungs.

* '''''IO''''': Input and Output parameters.
** '''Input Volume''': Input chest CT dataset to be segmented.
** '''Output Parameters''': Output label.

The user interface panel:

{|
|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Module GUI ]]
|}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
N/A


{{documentation/{{documentation/version}}/module-section|References}}
N/A


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
The code is available at [https://github.com/PietroNardelli/AirwaySegmentation Github].


{{documentation/{{documentation/version}}/module-footer}}
[[Category:Documentation/{{documentation/version}}/Modules/Segmentation]]

Documentation/Nightly/Modules/AirwaySegmentation

2013-06-24T14:41:31Z

Pietro.nardelli:

File:Biolectromagnetics group UCC.jpg

2013-06-24T14:40:37Z

Pietro.nardelli:

Documentation/Nightly/Modules/AirwaySegmentation

2013-06-21T14:23:21Z

Pietro.nardelli:

Documentation/Nightly/Modules/AirwaySegmentation

2013-06-21T14:23:05Z

Pietro.nardelli:

Documentation/Nightly/Modules/AirwaySegmentation

2013-06-21T14:22:47Z

Pietro.nardelli:

Documentation/Nightly/Modules/AirwaySegmentation

2013-06-21T14:22:38Z

Pietro.nardelli:

Documentation/Nightly/Modules/AirwaySegmentation

2013-06-21T14:22:04Z

Pietro.nardelli:

Documentation/Nightly/Modules/AirwaySegmentation

2013-06-21T14:21:38Z

Pietro.nardelli:

Documentation/Nightly/Modules/AirwaySegmentation

2013-06-21T14:14:03Z

Pietro.nardelli:

Documentation/Nightly/Modules/AirwaySegmentation

2013-06-21T14:11:32Z

Pietro.nardelli:

Documentation/Nightly/Modules/AirwaySegmentation

2013-06-21T14:04:33Z

Pietro.nardelli:

Documentation/Nightly/Modules/AirwaySegmentation

2013-06-21T14:04:10Z

Pietro.nardelli:

File:UCC-logoNEW.png

2013-06-21T13:58:29Z

Pietro.nardelli:

Documentation/Nightly/Modules/AirwaySegmentation

2013-06-21T13:53:46Z

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Documentation/Nightly/Modules/AirwaySegmentation

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Documentation/Nightly/Modules/AirwaySegmentation

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Documentation/Nightly/Modules/AirwaySegmentation

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File:Slicer4-AirwaySegmentation-PANEL.png

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Documentation/Nightly/Modules/AirwaySegmentation

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Documentation/Nightly/Modules/AirwaySegmentation

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Documentation/Nightly/Modules/AirwaySegmentation

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File:AirwaySegmentation Module.png

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Documentation/Nightly/Modules/AirwaySegmentation

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Documentation/Nightly/Modules/AirwaySegmentation

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File:Slicer4 AirwaySegmentation-LOGO.png

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File:Slicer4-AirwaySegmentation-GUI.png

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Pietro.nardelli:

Documentation/Nightly/Extensions/AirwaySegmentation

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Pietro.nardelli: Created page with '<noinclude>{{documentation/versioncheck}}</noinclude> #REDIRECT Documentation/Nightly/Modules/AirwaySegmentation'

<noinclude>{{documentation/versioncheck}}</noinclude>
#REDIRECT [[Documentation/Nightly/Modules/AirwaySegmentation]]

Documentation/Nightly/Extensions

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Pietro.nardelli: /* Cat 2 */

<noinclude>{{documentation/versioncheck}}</noinclude>
<noinclude>
__TOC__
</noinclude>= Extensions by Category =

==Cat 1==

==Cat 2==
* [[Documentation/{{documentation/version}}/Extensions/SkullStripper|SkullStripper]] (Xiaodong Tao)
* [[Documentation/{{documentation/version}}/Extensions/CARMA|Cardiac MRI Toolkit]] (Alan Morris, Salma Bengali)[[image:UnderConstruction.png|tumb|10px]]
* [[Documentation/{{documentation/version}}/Extensions/PkModeling|PkModeling]] (Emma Zhu, Jim Miller)
* [[Documentation/{{documentation/version}}/Extensions/FacetedVisualizer|FacetedVisualizer]] (Harini Veeraraghavan, Jim Miller)
* [[Documentation/{{documentation/version}}/Extensions/Reporting|Reporting]] (Andrey Fedorov, Nicole Aucoin, Steve Pieper) (work in progress)
* [[Documentation/{{documentation/version}}/Extensions/SlicerRT|SlicerRT]] (Csaba Pinter, Andras Lasso, Kevin Wang, Steve Pieper)
** [[Documentation/{{documentation/version}}/Modules/DicomRtImport|DICOM-RT import]]
** [[Documentation/{{documentation/version}}/Modules/Contours|Contours]]
** [[Documentation/{{documentation/version}}/Modules/DoseVolumeHistogram|Dose volume histogram]]
** [[Documentation/{{documentation/version}}/Modules/DoseAccumulation|Dose accumulation]]
** [[Documentation/{{documentation/version}}/Modules/DoseComparison|Dose comparison]]
** [[Documentation/{{documentation/version}}/Modules/Isodose|Isodose line and surface display]]
** [[Documentation/{{documentation/version}}/Modules/ContourComparison|Contour comparison]]
** [[Documentation/{{documentation/version}}/Modules/ContourMorphology|Contour morphology]]
** [[Documentation/{{documentation/version}}/Modules/PatientHierarchy|Patient hierarchy]]
** [[Documentation/{{documentation/version}}/Modules/DeformationFieldVisualizer|Deformation field visualizer]]
** Modules from [[Documentation/{{documentation/version}}/Extensions/Plastimatch|Plastimatch]] (Greg Sharp)
*** [[Documentation/{{documentation/version}}/Modules/PlmBSplineDeformableRegistration|Plastimatch Automatic deformable image registration]]
*** [[Documentation/{{documentation/version}}/Modules/PlmDICOMRTImport|Plastimatch DICOM-RT import]]
*** [[Documentation/{{documentation/version}}/Modules/PlmDICOMRTExport|Plastimatch DICOM-RT export]] [[image:UnderConstruction.png|tumb|10px]]
*** [[Documentation/{{documentation/version}}/Modules/PlmLANDWARP|Plastimatch LANDWARP Landmark]]
*** [[Documentation/{{documentation/version}}/Modules/PlmXFORMWARP|Plastimatch XFORMWARP]] [[image:UnderConstruction.png|tumb|10px]]
* [[Documentation/{{documentation/version}}/Extensions/SlicerIGT|SlicerIGT]] (Tamas Ungi, Adam Rankin, Andras Lasso, Junichi Tokuda, Laurent Chauvin)
** [[Documentation/{{documentation/version}}/Modules/CollectFiducials|CollectFiducials]] (Tamas Ungi)
** [[Documentation/{{documentation/version}}/Modules/CreateModels|CreateModels]] (Tamas Ungi, Matthew Holden)
** [[Documentation/{{documentation/version}}/Modules/OpenIGTLinkRemote|OpenIGTLinkRemote]] (Tamas Ungi, Andras Lasso)
** [[Documentation/{{documentation/version}}/Modules/UltrasoundSnapshots|UltrasoundSnapshots]] (Tamas Ungi, Franklin King)
** [[Documentation/{{documentation/version}}/Extensions/VolumeResliceDriver|VolumeResliceDriver]] (Junichi Tokuda, Tamas Ungi, Laurent Chauvin)
* [[Documentation/{{documentation/version}}/Extensions/iGyne|iGyne]] (Xiaojun Chen and iGyne Team)
* [[Documentation/{{documentation/version}}/Extensions/LongitudinalPETCT|LongitudinalPETCT]] (Paul Mercea, Andrey Fedorov)
* [[Documentation/{{documentation/version}}/Extensions/DTIProcess|DTIProcess]] (Francois Budin)
* [[Documentation/{{documentation/version}}/Extensions/DTIAtlasFiberAnalyzer|DTIAtlasFiberAnalyzer]] (Francois Budin)
* [[Documentation/{{documentation/version}}/Extensions/FiberViewerLight|FiberViewerLight]] (Francois Budin)
* [[Documentation/{{documentation/version}}/Extensions/DTIPrep|DTIPrep]] (Francois Budin)
* [[Documentation/{{documentation/version}}/Extensions/DTIAtlasBuilder|DTIAtlasBuilder]] (Adrien Kaiser)
* [[Documentation/{{documentation/version}}/Extensions/TubeTK|TubeTK]] (Stephen Aylward, Jean-Christophe Fillion-Robin, Christopher Mullins, Michael Jeulin-L, Matthew McCormick)
* [[Documentation/{{documentation/version}}/Extensions/UKFTractography|UKFTractography]] (Ryan Eckbo, Yogesh Rathi)
* [[Documentation/{{documentation/version}}/Extensions/TrackerStabilizer|TrackerStabilizer]] (Laurent Chauvin, Jayender Jagadeesan)
* [[Documentation/{{documentation/version}}/Extensions/ChangeTracker|ChangeTracker]] (Andrey Fedorov)
* [[Documentation/{{documentation/version}}/Extensions/SobolevSegmenter|SobolevSegmenter]] (Arie Nakhmani)
* [[Documentation/{{documentation/version}}/Extensions/QuickTools|QuickTools]] (Julien Finet)
** [[Documentation/{{documentation/version}}/Modules/ImageMaker|Image Maker]]
* [[Documentation/{{documentation/version}}/Extensions/XNATSlicer|XNATSlicer]]
* [[Documentation/{{documentation/version}}/Extensions/ErodeDilateLabel|ErodeDilateLabel]] (Junichi)
* [[Documentation/{{documentation/version}}/Extensions/ThingiverseBrowser|ThingiverseBrowser]] (Nigel Goh)
* [[Documentation/{{documentation/version}}/Extensions/PathPlanner|PathPlanner]] (Laurent Chauvin)
* [[Documentation/{{documentation/version}}/Extensions/VisuaLine|VisuaLine]] (Laurent Chauvin)
* [[Documentation/{{documentation/version}}/Extensions/VirtualFractureReconstruction|Virtual Fracture Reconstruction]] (Karl Fritscher, Peter Karasev)
* [[Documentation/{{documentation/version}}/Extensions/AirwaySegmentation|AirwaySegmentation]] (Pietro Nardelli)

==Cat 3==
* [[Documentation/{{documentation/version}}/Extensions/LesionSegmentation|LesionSegmentation]] (Mark Scully)
**[[Documentation/{{documentation/version}}/Modules/TrainModel|LesionSegmentation->TrainModel]] (Mark Scully)
**[[Documentation/{{documentation/version}}/Modules/PredictLesions|LesionSegmentation->PredictLesions]] (Mark Scully)

<noinclude>
{{:Documentation/{{documentation/version}}/FAQ/Extensions|Extensions}}
</noinclude>