Documentation/Nightly/Modules/DiceComputation - Revision history

UpdateBot: Prepend documentation/versioncheck template. See http://na-mic.org/Mantis/view.php?id=2887

2013-06-14T07:58:37Z

Prepend documentation/versioncheck template. See http://na-mic.org/Mantis/view.php?id=2887

Lchauvin at 16:24, 13 June 2013

2013-06-13T16:24:35Z

Tokuda at 18:24, 3 June 2013

2013-06-03T18:24:24Z

Tokuda at 18:21, 3 June 2013

2013-06-03T18:21:45Z

Lchauvin at 14:46, 3 June 2013

2013-06-03T14:46:31Z

Lchauvin at 14:46, 3 June 2013

2013-06-03T14:46:02Z

Lchauvin at 14:43, 3 June 2013

2013-06-03T14:43:56Z

Lchauvin at 14:36, 3 June 2013

2013-06-03T14:36:50Z

Lchauvin at 18:54, 31 May 2013

2013-05-31T18:54:55Z

Lchauvin at 18:51, 31 May 2013

2013-05-31T18:51:15Z

← Older revision		Revision as of 07:58, 14 June 2013
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	{{documentation/{{documentation/version}}/module-header}}		{{documentation/{{documentation/version}}/module-header}}

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 This work is supported by NA-MIC, NCIGT, and the Slicer Community.<br>
 Author: Laurent Chauvin, Nobuhiko Hata<br>
 Contact: Laurent Chauvin <email> lchauvin@bwh.harvard.edu</email> <br>
 {{documentation/{{documentation/version}}/module-introduction-row}}

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 {{documentation/{{documentation/version}}/module-section|Module Description}}
-This module is capable of calculating the Dice Similarity Coefficient (DSC) between multiple label map images. If the label map images represent '''registered''' segmented structures, the DSC will provide a volumetric alignment between the images. The DSC gives measures of the volumetric overlap between two of the segmented structures, and indicates twice the number of voxels which are shared by or are common to both structures divided by the total number of non-zero voxels in both structures. The DSC can range from zero to one, where zero is no alignment between images and one is perfect alignment.
+{{documentation/modulename}}  is capable of calculating the Dice Similarity Coefficient (DSC) between multiple label map images. If the label map images represent '''registered''' segmented structures, the DSC will provide a volumetric alignment between the images. The DSC gives measures of the volumetric overlap between two of the segmented structures, and indicates twice the number of voxels which are shared by or are common to both structures divided by the total number of non-zero voxels in both structures. The DSC can range from zero to one, where zero is no alignment between images and one is perfect alignment.
-{{documentation/modulename}} is a Slicer4 module computing DSC for several label map images, and presenting results in a NxN matrix (where N is number of label map images) with color coding for convenient reading.
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@@ Line 23: / Line 23: @@
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 {{documentation/{{documentation/version}}/module-section|Module Description}}
-This module is capable of calculating the Dice Similarity Coefficient (DSC) between several label map images. If the label map images represent '''registered''' segmented structures then the DSC will provide a volumetric alignment between the images. The DSC gives measures of the volumetric overlap between two of the segmented structures, and indicates twice the number of voxels which are shared by or are common to both structures divided by the total number of non-zero voxels in both structures. The DSC can range from zero to one, where zero is no alignment between images and one is perfect alignment.
+This module is capable of calculating the Dice Similarity Coefficient (DSC) between multiple label map images. If the label map images represent '''registered''' segmented structures, the DSC will provide a volumetric alignment between the images. The DSC gives measures of the volumetric overlap between two of the segmented structures, and indicates twice the number of voxels which are shared by or are common to both structures divided by the total number of non-zero voxels in both structures. The DSC can range from zero to one, where zero is no alignment between images and one is perfect alignment.
 {{documentation/modulename}} is a Slicer4 module computing DSC for several label map images, and presenting results in a NxN matrix (where N is number of label map images) with color coding for convenient reading.

@@ Line 28: / Line 28: @@
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 {{documentation/{{documentation/version}}/module-section|Use Cases}}
-{{documentation/modulename}} compute DSC to quantitatively compare several registered segmented volumes. It could be used to compare:
+{{documentation/modulename}} compute DSC to quantitatively compare several '''registered''' segmented volumes. It could be used to compare:
 * Several algorithms with ground truth
 * Automated segmentation vs manual

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 {{documentation/{{documentation/version}}/module-section|References}}
+* A. Bharatha, M. Hirose, N. Hata, S. K. Warfield, M. Ferrant, K. H. Zou, E. Suarez-Santana, J. Ruiz-Alzola, A. D'Amico, R. A. Cormack, R. Kikinis, F. A. Jolesz, and C. M. Tempany, "Evaluation of three-dimensional finite element-based deformable registration of pre- and intraoperative prostate imaging," Med Phys, vol. 28(12), pp. 2551-60, 2001.
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 {{documentation/{{documentation/version}}/module-section|Information for Developers}}

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 {{documentation/{{documentation/version}}/module-section|Module Description}}
-Dice's coefficient is used to measure the similarity of two datasets together. If Dice's coefficient is 1, datasets are identical, is coefficient is 0, datasets are not overlapping at all.
+This module is capable of calculating the Dice Similarity Coefficient (DSC) between several label map images. If the label map images represent '''registered''' segmented structures then the DSC will provide a volumetric alignment between the images. The DSC gives measures of the volumetric overlap between two of the segmented structures, and indicates twice the number of voxels which are shared by or are common to both structures divided by the total number of non-zero voxels in both structures. The DSC can range from zero to one, where zero is no alignment between images and one is perfect alignment.
-{{documentation/modulename}} is a Slicer4 module designed to compute several Dice's coefficients and display them to immediately visualize results.
+{{documentation/modulename}} is a Slicer4 module computing DSC for several label map images, and presenting results in a NxN matrix (where N is number of label map images) with color coding for convenient reading.
 <!-- ---------------------------- -->
 {{documentation/{{documentation/version}}/module-section|Use Cases}}
-{{documentation/modulename}} could be useful to quantitatively compare several label maps. It could be used to compare several algorithms with ground truth, or automated segmentation vs manual.
+{{documentation/modulename}} could be useful to quantitatively compare several registered segmented volumes. It could be used to compare several algorithms with ground truth, or automated segmentation vs manual, etc...
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 |}
 # Parameters
-#* Number of label maps to use for computation
+#* Number of label map images to use for computation
 # Label Maps
-#* Select labels maps (only label maps could be selected) to use for computation or None
+#* Select labels map images (only label maps could be selected) to use for computation or None
 #* Compute Dice coefficient: Press button to start computation
 # Results
-#* Once computation is over, results will appear in an array
+#* Once computation is over, results will appear in an NxN matrix with color coding
-#* Red stripes indicate no label map have been selected (None)
+#** Red stripes indicate no label map have been selected (None)
-#* Green stripes indicate this is Dice's coefficient of a label map with itself (always 1.0, so not displayed)
+#** Green stripes indicate this is Dice's coefficient of a label map with itself (always 1.0, so not displayed)
-#* Values represent Dice's similarity coefficient. The bigger the value is, the greener the background is, in order to quickly find higher matches.
+#** Values represent Dice's similarity coefficient. The bigger the value is, the greener the background is, in order to quickly find higher matches.
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