Documentation/Nightly/Extensions/BrainTissuesExtension - Revision history

Acsenrafilho at 16:30, 30 October 2017

2017-10-30T16:30:04Z

Acsenrafilho at 19:19, 30 September 2017

2017-09-30T19:19:19Z

Acsenrafilho at 15:55, 9 December 2016

2016-12-09T15:55:22Z

Acsenrafilho at 17:43, 27 November 2016

2016-11-27T17:43:40Z

Acsenrafilho at 17:35, 26 November 2016

2016-11-26T17:35:02Z

Acsenrafilho at 16:55, 26 November 2016

2016-11-26T16:55:15Z

Acsenrafilho at 16:33, 26 November 2016

2016-11-26T16:33:44Z

Acsenrafilho at 16:25, 26 November 2016

2016-11-26T16:25:06Z

Acsenrafilho at 00:54, 26 November 2016

2016-11-26T00:54:21Z

Acsenrafilho at 00:33, 26 November 2016

2016-11-26T00:33:51Z

@@ Line 35: / Line 35: @@
 * '''General purpose segmentation method''': [[Documentation/{{documentation/version}}/Modules/BrainStructuresSegmenter|Brain Structures Segmenter]]
 * '''Clustering classification based on k-Means algorithm''': [[Documentation/{{documentation/version}}/Modules/BasicBrainTissues|Basic Brain Tissues (k-Means)]]
-* '''Multiple logistic classification algorithm''': [[Documentation/{{documentation/version}}/Modules/BrainLogisticSegmentation|Brain Logistic Classification (BLS)]]
+* '''Multiple logistic classification algorithm''': [[Documentation/{{documentation/version}}/Modules/BrainLogisticSegmentation|Brain Logistic Segmentation (BLS)]]
 '''NOTE''': The [[Documentation/{{documentation/version}}/Modules/BrainStructuresSegmenter|Brain Structures Segmenter]] is the main module for a general brain segmentation approach, which uses a predefined image processing pipeline in order to result in a smoothed tissue mask. See the module's documentation for more details.

@@ Line 27: / Line 27: @@
 [[Image:BrainTissuesExtension-logo.png|left]]
-Brain tissue segmentation plays an important role in many different image processing steps, which offers a possibility to study different neurodegenerative diseases or also in more specific tasks such as in brain structural quantitative parameters (brain atrophy, for instance). For this reason, brain tissue segmentation procedures have been intensively studied in recent years. This extension aims to offer a fast, robust and simple solutions for brain tissue segmentation, in which specific segmentation tasks are separated in different modules. See the modules list below to find the most appropriate tool for your study.
+Brain tissue segmentation plays an important role in many different image processing steps, which offers a possibility to study different neurodegenerative diseases or also in more specific tasks such as in brain structural quantitative morphological parameters such as brain atrophy. For this reason, brain tissue segmentation procedures have been intensively studied in recent years. This extension aims to offer a fast, robust and simple solutions for brain tissue segmentation, in which specific segmentation tasks are separated into different modules. See the modules list below to find the most appropriate tool for your study.
 <!-- ---------------------------- -->
 {{documentation/{{documentation/version}}/extension-section|Modules}}
 *General purpose segmentation method: [[Documentation/{{documentation/version}}/Modules/BrainStructuresSegmenter|Brain Structures Segmenter]]
-*Global brain tissues segmentation: [[Documentation/{{documentation/version}}/Modules/BasicBrainTissues|Basic Brain Tissues]]
+* '''General purpose segmentation method''': [[Documentation/{{documentation/version}}/Modules/BrainStructuresSegmenter|Brain Structures Segmenter]]
 '''NOTE''': The [[Documentation/{{documentation/version}}/Modules/BrainStructuresSegmenter|Brain Structures Segmenter]] is the main module for a general brain segmentation approach, which uses a predefined image processing pipeline in order to result in a smoothed tissue mask. See the module's documentation for more details.
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@@ Line 59: / Line 64: @@
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 {{documentation/{{documentation/version}}/extension-section|References}}
-N/A
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@@ Line 45: / Line 45: @@
 ** A white matter mask could be used for specific measurements in some brain diseases, for example, in Multiple Sclerosis it could be useful to help lesion detection algorithms.
-<gallery>
+<gallery widths="300px" heights="300px" perrow="3">
 Image:T1_fullBrain.png|A T1 weighted MRI image illustrating a usual brain
 Image:T1_tissues.png|White matter, gray matter and CSF tissues segmented from the previous MRI image

@@ Line 45: / Line 45: @@
 ** A white matter mask could be used for specific measurements in some brain diseases, for example, in Multiple Sclerosis it could be useful to help lesion detection algorithms.
-<gallery widths="200px">
+<gallery>
 Image:T1_fullBrain.png|A T1 weighted MRI image illustrating a usual brain
 Image:T1_tissues.png|White matter, gray matter and CSF tissues segmented from the previous MRI image

@@ Line 45: / Line 45: @@
 ** A white matter mask could be used for specific measurements in some brain diseases, for example, in Multiple Sclerosis it could be useful to help lesion detection algorithms.
-<gallery widths="200px" perrow="3">
+<gallery widths="200px">
 Image:T1_fullBrain.png|A T1 weighted MRI image illustrating a usual brain
 Image:T1_tissues.png|White matter, gray matter and CSF tissues segmented from the previous MRI image
 Image:WM_3DReconstruction.png|A white matter mask 3D reconstruction
 Image:GM_3DReconstruction.png|A gray matter mask 3D reconstruction
-Image:WM_GM_3DReconstruction.png|A merge white and gray matter masks 3D reconstruction
+Image:WM_GM_3DReconstruction.png|A merged white and gray matter masks 3D reconstruction
 </gallery>

@@ Line 27: / Line 27: @@
 [[Image:BrainTissuesExtension-logo.png|left]]
-Brain tissue segmentation plays an important role in many different image processing steps, which offers a possibility to study different neurodegenerative disease progression and global brain structural quantitative parameters (brain atrophy, for instance). For this reason, tissue segmentation procedures have been intensively studied in the recent years. This extension aims to offer a fast, robust and simple solutions for brain tissue segmentation, in which are separated in different modules. See the modules list below to find the most appropriate tool for your study.
+Brain tissue segmentation plays an important role in many different image processing steps, which offers a possibility to study different neurodegenerative diseases or also in more specific tasks such as in brain structural quantitative parameters (brain atrophy, for instance). For this reason, brain tissue segmentation procedures have been intensively studied in recent years. This extension aims to offer a fast, robust and simple solutions for brain tissue segmentation, in which specific segmentation tasks are separated in different modules. See the modules list below to find the most appropriate tool for your study.
 <!-- ---------------------------- -->
 {{documentation/{{documentation/version}}/extension-section|Modules}}
-*[[Documentation/{{documentation/version}}/Modules/BrainStructuresSegmenter|Brain Structures Segmenter]]
+*General purpose segmentation method: [[Documentation/{{documentation/version}}/Modules/BrainStructuresSegmenter|Brain Structures Segmenter]]
-*[[Documentation/{{documentation/version}}/Modules/BasicBrainTissues|Basic Brain Tissues]]
+*Global brain tissues segmentation: [[Documentation/{{documentation/version}}/Modules/BasicBrainTissues|Basic Brain Tissues]]
 '''NOTE''': The [[Documentation/{{documentation/version}}/Modules/BrainStructuresSegmenter|Brain Structures Segmenter]] is the main module for a general brain segmentation approach, which uses a predefined image processing pipeline in order to result in a smoothed tissue mask. See the module's documentation for more details.
@@ Line 39: / Line 40: @@
 {{documentation/{{documentation/version}}/module-section|Use Cases}}
 Most frequently used for these scenarios:
-* Use Case 1: Specific tissue classification
+* Use Case 1: Tissue classification
 ** There are several image quantitative approaches that are applied only in a certain tissue type (for instance, cortical thickness) in which a previous brain segmentation could be needed.
-* Use Case 2: Restrict areas for image quantitative analysis
+* Use Case 2: Restrict brain regions for image quantitative analysis
 ** A white matter mask could be used for specific measurements in some brain diseases, for example, in Multiple Sclerosis it could be useful to help lesion detection algorithms.

@@ Line 37: / Line 37: @@
 {{documentation/{{documentation/version}}/module-section|Use Cases}}
 Most frequently used for these scenarios:
-* Use Case 1: a
+* Use Case 1: Specific tissue classification and study
-**b
+** There are several quantitative approaches that are applied only in a certain tissue type (for instance, cortical thickness) in which a previous brain segmentation could be needed.
 <gallery widths="200px" perrow="3">
-Image:MRI_raw.png|Raw T1 weighted MRI Image
+Image:T1_fullBrain.png|A T1 weighted MRI image illustrating a usual brain
-Image:MRI_AAD.png|T1 weighted MRI Image with AAD filter (q=1.2)
+Image:T1_tissues.png|White matter, gray matter and CSF tissues segmented from the previous MRI image
-Image:MRI_IAD.png|T1 weighted MRI Image with IAD filter (q=1.2)
+Image:WM_3DReconstruction.png|A 3D reconstruction using only the white matter mask
 </gallery>
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 {{documentation/{{documentation/version}}/extension-section|Similar Extensions}}
-N/A
+[https://www.slicer.org/wiki/Modules:EMSegmenter-3.6 EM Segmenter]
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@@ Line 60: / Line 60: @@
 Repositories:
-* Source code: [https://github.com/CSIM-Toolkits/ GitHub repository]
+* Source code: [https://github.com/CSIM-Toolkits/BrainTissuesExtension GitHub repository]
-* Issue tracker:  [https://github.com/CSIM-Toolkits/ open issues and enhancement requests]
+* Issue tracker:  [https://github.com/CSIM-Toolkits/BrainTissuesExtension/issues open issues and enhancement requests]
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 {{documentation/{{documentation/version}}/extension-footer}}
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