Documentation/Nightly/Modules/AirwaySegmentation - Revision history

Lasso: Moved to github

2022-03-21T20:53:45Z

Moved to github

Pietro.nardelli: Updating contributor's emails

2018-01-03T09:29:01Z

Updating contributor's emails

Pietro.nardelli at 15:46, 28 July 2015

2015-07-28T15:46:53Z

Pietro.nardelli at 12:19, 8 January 2015

2015-01-08T12:19:51Z

Pietro.nardelli at 12:16, 8 January 2015

2015-01-08T12:16:26Z

Pietro.nardelli at 12:12, 8 January 2015

2015-01-08T12:12:23Z

Pietro.nardelli at 12:06, 8 January 2015

2015-01-08T12:06:48Z

Pietro.nardelli at 12:01, 8 January 2015

2015-01-08T12:01:53Z

Pietro.nardelli at 12:00, 8 January 2015

2015-01-08T12:00:43Z

Pietro.nardelli at 11:48, 8 January 2015

2015-01-08T11:48:05Z

@@ Line 1: / Line 1: @@
-<noinclude>{{documentation/versioncheck}}</noinclude>
+{{documentation/banner
-<!-- ---------------------------- -->
+| text  = [https://github.com/Slicer/SlicerAirwaySegmentation This page has been moved to github.]
-{{documentation/{{documentation/version}}/module-header}}
+| background-color = 8FBC8F }}

@@ Line 13: / Line 13: @@
 Author: Pietro Nardelli (University College Cork)<br>
 Contributor1:<br>
-Contact: Pietro Nardelli, <email>p.nardelli@umail.ucc.ie</email><br>
+Contact: Pietro Nardelli, <email>pnardelli@bwh.harvard.edu</email>, <email>pie.nardelli@gmail.com</email><br>
 {{documentation/{{documentation/version}}/module-introduction-row}}
 {{documentation/{{documentation/version}}/module-introduction-logo-gallery

@@ Line 63: / Line 63: @@
 <!-- ---------------------------- -->
 {{documentation/{{documentation/version}}/module-section|References}}
-N/A
+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.
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@@ Line 54: / Line 54: @@
 {|
-|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Scripted Module Interface ]]
+|[[Image:AirwaySegmentation_Scripted_Interface.jpg|thumb|300px|{{documentation/modulename}} Scripted Module Interface ]]
 |}

@@ Line 54: / Line 54: @@
 {|
-|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Module GUI ]]
+|[[Image:Slicer4-AirwaySegmentation-PANEL.png|thumb|300px|{{documentation/modulename}} Scripted Module Interface ]]
 |}

@@ Line 51: / Line 51: @@
 * <span>'''''Segmentation Parameters'''''</span>: Input parameters for segmentation (optional).
 ** <span>'''Airway Label Color'''</span>: 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:
+The user interface panel for the scripted module:
 {|

@@ Line 45: / Line 45: @@
 {{documentation/{{documentation/version}}/module-section|Panels and their use}}
-* <span>'''''Segmentation Parameters'''''</span>: Input parameters for segmentation.
+* <span>'''''IO Parameters'''''</span>: Input and Output parameters.
 ** <span>'''Input Volume'''</span>: Input chest CT dataset to be segmented.
-** <span >'''Output Parameters'''</span>: Output label.
+** <span>'''Seed'''</span>: 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.
 The user interface panel:

@@ Line 34: / Line 34: @@
 {|
-|[[Image:Screenshot from 2015-01-08 11-32-48.jpg|thumb|500px|Airway Segmentation Module ]]
+|[[Image:Screenshot from 2015-01-08 11-32-48.jpg|thumb|500px|Airway Segmentation Scripted Module: example of usage]]
 |}

@@ Line 27: / Line 27: @@
 {{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.
+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.
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