Documentation/Nightly/Extensions/LesionSpotlight - Revision history

Acsenrafilho at 11:14, 6 December 2017

2017-12-06T11:14:31Z

Acsenrafilho at 12:41, 25 July 2017

2017-07-25T12:41:39Z

Acsenrafilho: NEW: Added AFT Segmenter method

2017-07-24T17:10:07Z

NEW: Added AFT Segmenter method

Acsenrafilho at 17:39, 7 March 2017

2017-03-07T17:39:20Z

Acsenrafilho at 18:46, 16 February 2017

2017-02-16T18:46:04Z

Acsenrafilho at 15:19, 9 December 2016

2016-12-09T15:19:26Z

Acsenrafilho: First edition in the LesionSpotlight Extension.

2016-11-17T23:27:26Z

First edition in the LesionSpotlight Extension.

New page

<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}}
This work was partially funded by CAPES and CNPq, a Brazillian Agencies. Information on CAPES can be obtained on the [http://www.capes.gov.br/ CAPES website] and [http://www.cnpq.br/ CNPq website].<br>
Author: Antonio Carlos da S. Senra Filho, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics)<br>
Contact: Antonio Carlos da S. Senra Filho <email>acsenrafilho@usp.br</email><br>
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|Image:CSIM-logo.png|CSIM Laboratory
|Image:USP-logo.png|University of Sao Paulo
|Image:CNPq-logo.png|CNPq Brazil
|Image:CAPES-logo.png|CAPES Brazil
}}
{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Extension Description}}
{{documentation/{{documentation/version}}/module-description}}
{|
[[Image:LesionSpotlight-logo.png|left]]

... <ref>Tsallis, C. (2009). Introduction to Nonextensive Statistical Mechanics: Approaching a Complex World. Springer.</ref>

This extension offer...


{{documentation/{{documentation/version}}/extension-section|Modules}}
*[[Documentation/{{documentation/version}}/Modules/LSSegmenter|LS Segmenter]]
*[[Documentation/{{documentation/version}}/Modules/LSContrastEnhancer|LS Contrast Enhancer]]


{{documentation/{{documentation/version}}/module-section|Use Cases}}
Most frequently used for these scenarios:
* Use Case 1: Multiple Sclerosis (MS) hyperintense lesions segmentation
**Hyperintense Multiple Sclerosis lesions, mainly in T2-FLAIR images, have a easy application of this segmentations procedure.
* Use Case 2: Increase contrast in abnormal voxels in white matter
**...

<gallery widths="200px" perrow="3">
Image:T2FLAIR_raw.png|T2-FLAIR image with MS lesions
Image:T2FLAIR_Enhanced.png|T2-FLAIR image with enhanced MS lesions
Image:T2FLAIR_LesionMap.png|Lesion map obtained from the enhanced T2-FLAIR image
</gallery>


{{documentation/{{documentation/version}}/extension-section|Similar Extensions}}
N/A


{{documentation/{{documentation/version}}/extension-section|References}}
* paper


{{documentation/{{documentation/version}}/extension-section|Information for Developers}}
{{documentation/{{documentation/version}}/extension-developerinfo}}

Repositories:
* Source code: [https://github.com/CSIM-Toolkits/LesionSpotlightExtension GitHub repository]
* Issue tracker: [https://github.com/CSIM-Toolkits/LesionSpotlightExtension/issues open issues and enhancement requests]


{{documentation/{{documentation/version}}/extension-footer}}

@@ Line 27: / Line 27: @@
 [[Image:LesionSpotlight-logo.png|left]]
-This extension provides image segmentation and local image contrast enhancement approaches in order to detect abnormal white matter voxels signals in magnetic resonance images. At moment, there are available the '''LS Segmenter''' (specific for hyperintense Multiple Sclerosis lesion segmentation on T2-FLAIR images), '''LS Contrast Enhancement''' (specific to increase the contrast of abnormal voxels of T2-FLAIR images) and '''AFT Segmenter''' as a simple implementation of a recent automatic Multiple Sclerosis (MS) lesion segmentation<ref>Cabezas M. et al.(2014) "Automatic multiple sclerosis lesion detection in brain MRI by FLAIR thresholding", Computer Methods and Programs in Biomedicine, DOI: 10.1016/j.cmpb.2014.04.006.</ref> approaches. The '''LS Segmenter''' module implements a T2-FLAIR hyperintense lesion segmentation based on the algorithm published in the paper<ref>DOI:</ref>.
+This extension provides image segmentation and local image contrast enhancement approaches in order to detect abnormal white matter voxels signals in magnetic resonance images. At moment, there are available the '''LS Segmenter''' (specific for hyperintense Multiple Sclerosis lesion segmentation on T2-FLAIR images), '''LS Contrast Enhancement''' (specific to increase the contrast of abnormal voxels of T2-FLAIR images) and '''AFT Segmenter''' as a simple implementation of a recent automatic Multiple Sclerosis (MS) lesion segmentation<ref>DOI: 10.1016/j.cmpb.2014.04.006.</ref> approaches. The '''LS Segmenter''' module implements a T2-FLAIR hyperintense lesion segmentation based on the algorithm published in the paper<ref>DOI: 10.1007/s11517-017-1747-2</ref>.
 '''NOTE''': The Logistic Contrast Enhancement, Weighted Enhancement Image Filter and Automatic FLAIR Threshold modules are '''only supporting CLI methods''' added in the extension in order to calculate specific parts of the segmentation procedure. For this reason, these modules are '''not''' supposed to be used alone. Please, use the '''LS Contrast Enhancer''' or '''LS Segmenter''' modules only.
@@ Line 43: / Line 43: @@
 **T2-FLAIR images are usually applied to MS diagnosis in order to detect hyperintense MS lesions. In this case, the '''LS Segmenter''' module can be useful.
 * Use Case 2: Increase contrast in abnormal voxels in white matter tissue
-**There are some lesion segmentation approaches that relies on the voxel intensity level presented in the white matter tissue, where the '''LS Contrast Enhancer''' module can be helpful to increase the contrast between lesions and surrounding brain tissues (mainly normal-appearing white matter - NAWM).
+**There are some lesion segmentation approaches that rely on the voxel intensity level presented in the white matter tissue, where the '''LS Contrast Enhancer''' module can be helpful to increase the contrast between lesions and surrounding brain tissues (mainly normal-appearing white matter - NAWM).
 <gallery widths="300px" heights="300px" perrow="3">
@@ Line 59: / Line 59: @@
 <!-- ---------------------------- -->
 {{documentation/{{documentation/version}}/extension-section|References}}
-* PAPER
+* da Silva Senra Filho, A. C. (2017) ‘A hybrid approach based on logistic classification and iterative contrast enhancement algorithm for hyperintense multiple sclerosis lesion segmentation’, Medical & Biological Engineering & Computing. doi: 10.1007/s11517-017-1747-2.
 * Cabezas, M., Oliver, A., Roura, E., Freixenet, J., Vilanova, J. C., Ramió-Torrentà, L., Rovira, À. and Lladó, X. (2014) ‘Automatic multiple sclerosis lesion detection in brain MRI by FLAIR thresholding’, Computer Methods and Programs in Biomedicine. Elsevier Ireland Ltd, 115(3), pp. 147–161. DOI: 10.1016/j.cmpb.2014.04.006.

@@ Line 27: / Line 27: @@
 [[Image:LesionSpotlight-logo.png|left]]
-This extension provides a image segmentation and local image contrast enhancement approaches in order to detect abnormal white matter voxels signals in magnetic resonance images. At moment, there are available the '''LS Segmenter''' (specific for hyperintense Multiple Sclerosis lesion segmentation on T2-FLAIR images) and '''LS Contrast Enhancement''' (specific to increase the contrast of abnormal voxels of T2-FLAIR images) modules. The '''LS Contrast Enhancement''' module can be used as an image contrast enhancement pre-processing step before a future lesion segmentation algorithm (which could be used any other approach, such as LesionTOADS, OASIS or LST). The '''LS Segmenter''' module implements a hyperintense T2-FLAIR lesion segmentation based on the algorithm published in the paper<ref>DOI:</ref>.  In addition, a simple implementation of another lesion segmentation algorithm is provided, being the method described in Cabezas M. et al. paper <ref>Cabezas M. et al.(2014) "Automatic multiple sclerosis lesion detection in brain MRI by FLAIR thresholding", Computer Methods and Programs in Biomedicine, DOI: 10.1016/j.cmpb.2014.04.006.</ref>
+This extension provides image segmentation and local image contrast enhancement approaches in order to detect abnormal white matter voxels signals in magnetic resonance images. At moment, there are available the '''LS Segmenter''' (specific for hyperintense Multiple Sclerosis lesion segmentation on T2-FLAIR images), '''LS Contrast Enhancement''' (specific to increase the contrast of abnormal voxels of T2-FLAIR images) and '''AFT Segmenter''' as a simple implementation of a recent automatic Multiple Sclerosis (MS) lesion segmentation<ref>Cabezas M. et al.(2014) "Automatic multiple sclerosis lesion detection in brain MRI by FLAIR thresholding", Computer Methods and Programs in Biomedicine, DOI: 10.1016/j.cmpb.2014.04.006.</ref> approaches. The '''LS Segmenter''' module implements a T2-FLAIR hyperintense lesion segmentation based on the algorithm published in the paper<ref>DOI:</ref>.
-'''NOTE''': The Logistic Contrast Enhancement, Weighted Enhancement Image Filter and Automatic FLAIR Threshold modules are '''only supporting CLI methods''' added in the extension to calculate specific parts of the segmentation procedure. For this reason, these modules are '''not''' supposed to be used alone. Please, use the '''LS Contrast Enhancer''' or '''LS Segmenter''' modules only.
+'''NOTE''': The Logistic Contrast Enhancement, Weighted Enhancement Image Filter and Automatic FLAIR Threshold modules are '''only supporting CLI methods''' added in the extension in order to calculate specific parts of the segmentation procedure. For this reason, these modules are '''not''' supposed to be used alone. Please, use the '''LS Contrast Enhancer''' or '''LS Segmenter''' modules only.
 <!-- ---------------------------- -->
@@ Line 43: / Line 43: @@
 **T2-FLAIR images are usually applied to MS diagnosis in order to detect hyperintense MS lesions. In this case, the '''LS Segmenter''' module can be useful.
 * Use Case 2: Increase contrast in abnormal voxels in white matter tissue
-**There are some lesion segmentation approaches that relies on the voxel intensity level presented in the white matter tissue, where the '''LS Contrast Enhancer''' module can be helpful to increase the contrast between lesions and surrounding brain tissues (mainly normal appearing white matter - NAWM).
+**There are some lesion segmentation approaches that relies on the voxel intensity level presented in the white matter tissue, where the '''LS Contrast Enhancer''' module can be helpful to increase the contrast between lesions and surrounding brain tissues (mainly normal-appearing white matter - NAWM).
 <gallery widths="300px" heights="300px" perrow="3">
 Image:T2FLAIR_patient.png|T2-FLAIR image from a MS patient
 Image:T2FLAIR_patient_lesionLabel.png|T2-FLAIR hyperintense lesion segmentation provided by the '''LS Segmenter''' module
-Image:Lesion3DRender.png|Lesions and White Matter 3D representation
+Image:Lesion3DRender.png|MS lesions and White Matter 3D representation
 Image:T2FLAIR_beforeContrast.png|T2-FLAIR image with original lesion contrast
 Image:T2FLAIR_afterContrast.png|T2-FLAIR image with hyperintense MS lesion contrast enhanced by the '''LS Contrast Enhancer''' module
@@ Line 59: / Line 59: @@
 <!-- ---------------------------- -->
 {{documentation/{{documentation/version}}/extension-section|References}}
-* paper
+* PAPER

@@ Line 27: / Line 27: @@
 [[Image:LesionSpotlight-logo.png|left]]
-This extension provides a image segmentation and local image contrast enhancement approaches in order to detect abnormal white matter voxels signals in magnetic resonance images. At moment, there are available the '''LS Segmenter''' (specific for hyperintense Multiple Sclerosis lesion segmentation on T2-FLAIR images) and '''LS Contrast Enhancement''' (specific to increase the contrast of abnormal voxels of T2-FLAIR images) modules. The '''LS Contrast Enhancement''' module can be used as an image contrast enhancement pre-processing step before a future lesion segmentation algorithm (which could be used any other approach, such as LesionTOADS, OASIS or LST). The '''LS Segmenter''' module implements a hyperintense T2-FLAIR lesion segmentation based on the algorithm published in the paper<ref>DOI:</ref>.
+This extension provides a image segmentation and local image contrast enhancement approaches in order to detect abnormal white matter voxels signals in magnetic resonance images. At moment, there are available the '''LS Segmenter''' (specific for hyperintense Multiple Sclerosis lesion segmentation on T2-FLAIR images) and '''LS Contrast Enhancement''' (specific to increase the contrast of abnormal voxels of T2-FLAIR images) modules. The '''LS Contrast Enhancement''' module can be used as an image contrast enhancement pre-processing step before a future lesion segmentation algorithm (which could be used any other approach, such as LesionTOADS, OASIS or LST). The '''LS Segmenter''' module implements a hyperintense T2-FLAIR lesion segmentation based on the algorithm published in the paper<ref>DOI:</ref>.  In addition, a simple implementation of another lesion segmentation algorithm is provided, being the method described in Cabezas M. et al. paper <ref>Cabezas M. et al.(2014) "Automatic multiple sclerosis lesion detection in brain MRI by FLAIR thresholding", Computer Methods and Programs in Biomedicine, DOI: 10.1016/j.cmpb.2014.04.006.</ref>
 '''NOTE''': The Logistic Contrast Enhancement, Weighted Enhancement Image Filter and Automatic FLAIR Threshold modules are '''only supporting CLI methods''' added in the extension to calculate specific parts of the segmentation procedure. For this reason, these modules are '''not''' supposed to be used alone. Please, use the '''LS Contrast Enhancer''' or '''LS Segmenter''' modules only.
@@ Line 35: / Line 35: @@
 *[[Documentation/{{documentation/version}}/Modules/LSSegmenter|LS Segmenter]]
 *[[Documentation/{{documentation/version}}/Modules/LSContrastEnhancer|LS Contrast Enhancer]]
 <!-- ---------------------------- -->

@@ Line 27: / Line 27: @@
 [[Image:LesionSpotlight-logo.png|left]]
-This extension provides a image segmentation and enhancement approaches in order to increase the abnormal white matter voxels in magnetic resonance images. At moment, there are available the '''LS Segmenter''' (specific for hyperintense Multiple Sclerosis lesion segmentation on T2-FLAIR images) and '''LS Contrast Enhancement''' (specific to increase the contrast of abnormal voxels of T2-FLAIR images) modules. The '''LS Contrast Enhancement''' module can be used as an image enhancement pre-processing step before a future lesion segmentation algorithm (which could be used any other approach, such as LesionTOADS, OASIS or LST). The '''LS Segmenter''' module implements a hyperintense T2-FLAIR lesion segmentation based on the algorithm published in the paper<ref>DOI:</ref>.
+This extension provides a image segmentation and local image contrast enhancement approaches in order to detect abnormal white matter voxels signals in magnetic resonance images. At moment, there are available the '''LS Segmenter''' (specific for hyperintense Multiple Sclerosis lesion segmentation on T2-FLAIR images) and '''LS Contrast Enhancement''' (specific to increase the contrast of abnormal voxels of T2-FLAIR images) modules. The '''LS Contrast Enhancement''' module can be used as an image contrast enhancement pre-processing step before a future lesion segmentation algorithm (which could be used any other approach, such as LesionTOADS, OASIS or LST). The '''LS Segmenter''' module implements a hyperintense T2-FLAIR lesion segmentation based on the algorithm published in the paper<ref>DOI:</ref>.
-'''NOTE''': The Logistic Contrast Enhancement, Weighted Enhancement Image Filter and Automatic FLAIR Threshold modules are only supporting CLI methods added in the extension to calculate specific parts of the segmentation procedure. For this reason, these modules are '''not''' supposed to be used alone. Please, use the '''LS Contrast Enhancer''' or '''LS Segmenter''' modules only.
+'''NOTE''': The Logistic Contrast Enhancement, Weighted Enhancement Image Filter and Automatic FLAIR Threshold modules are '''only supporting CLI methods''' added in the extension to calculate specific parts of the segmentation procedure. For this reason, these modules are '''not''' supposed to be used alone. Please, use the '''LS Contrast Enhancer''' or '''LS Segmenter''' modules only.
 <!-- ---------------------------- -->
@@ Line 39: / Line 39: @@
 {{documentation/{{documentation/version}}/module-section|Use Cases}}
 Most frequently used for these scenarios:
-* Use Case 1: Multiple Sclerosis (MS) hyperintense lesions segmentation
+* Use Case 1: Hyperintense Multiple Sclerosis (MS) lesions segmentation
-**Hyperintense Multiple Sclerosis lesions, mainly in T2-FLAIR images, have an easy application of this segmentations procedure.
+**T2-FLAIR images are usually applied to MS diagnosis in order to detect hyperintense MS lesions. In this case, the '''LS Segmenter''' module can be useful.
-* Use Case 2: Increase contrast in abnormal voxels in white matter
+* Use Case 2: Increase contrast in abnormal voxels in white matter tissue
-**There are some lesion segmentation approaches that relies on the voxel intensity level presented in the lesion signal, where the '''LS Contrast Enhancer''' module can be helpful to increase the contrast between lesions and surrounding brain tissues (mainly normal appearing white matter - NAWM).
+**There are some lesion segmentation approaches that relies on the voxel intensity level presented in the white matter tissue, where the '''LS Contrast Enhancer''' module can be helpful to increase the contrast between lesions and surrounding brain tissues (mainly normal appearing white matter - NAWM).
 <gallery widths="300px" heights="300px" perrow="3">
 Image:T2FLAIR_patient.png|T2-FLAIR image from a MS patient
-Image:T2FLAIR_patient_lesionLabel.png|T2-FLAIR hyperintense lesion segmentation provided by the LS Segmenter module
+Image:T2FLAIR_patient_lesionLabel.png|T2-FLAIR hyperintense lesion segmentation provided by the '''LS Segmenter''' module
-Image:Lesion3DRender.png|Lesion and White Matter 3D representation
+Image:Lesion3DRender.png|Lesions and White Matter 3D representation
 Image:T2FLAIR_beforeContrast.png|T2-FLAIR image with original lesion contrast
-Image:T2FLAIR_afterContrast.png|T2-FLAIR image with hyperintense lesion contrast enhanced provided by the LS Contrast Enhancer module
+Image:T2FLAIR_afterContrast.png|T2-FLAIR image with hyperintense MS lesion contrast enhanced by the '''LS Contrast Enhancer''' module
 </gallery>

@@ Line 27: / Line 27: @@
 [[Image:LesionSpotlight-logo.png|left]]
-This extension provides image segmentation and enhancement approaches in order to increase the abnormal white matter voxels in magnetic resonance images. At moment, there are available the LS Segmenter module (specific for hyperintense Multiple Sclerosis lesion segmentation on T2-FLAIR images) and LS Contrast Enhancement Module (specific to increase the contrast of abnormal voxels of the same T2-FLAIR images). The LS Contrast Enhancement module can be used as an image enhancement pre-processing step before a future lesion segmentation algorithm (which could be used any other approach, such as LesionTOADS, OASIS or LST). The LS Segmenter module implements a hyperintense T2-FLAIR lesion segmentation based on the algorithm published in the paper Cabezas, M. et al<ref>Cabezas, M. et al (2014) "Automatic multiple sclerosis lesion detection in brain MRI by FLAIR thresholding", Computer Methods and Programs in Biomedicine, DOI: 10.1016/j.cmpb.2014.04.006.</ref>.
+This extension provides a image segmentation and enhancement approaches in order to increase the abnormal white matter voxels in magnetic resonance images. At moment, there are available the '''LS Segmenter''' (specific for hyperintense Multiple Sclerosis lesion segmentation on T2-FLAIR images) and '''LS Contrast Enhancement''' (specific to increase the contrast of abnormal voxels of T2-FLAIR images) modules. The '''LS Contrast Enhancement''' module can be used as an image enhancement pre-processing step before a future lesion segmentation algorithm (which could be used any other approach, such as LesionTOADS, OASIS or LST). The '''LS Segmenter''' module implements a hyperintense T2-FLAIR lesion segmentation based on the algorithm published in the paper<ref>DOI:</ref>.
-'''NOTE''': The Logistic Contrast Enhancement, Weighted Enhancement Image Filter and Automatic FLAIR Threshold modules are only supporting CLI methods added here to apply part of the other modules. For this reason these modules are not supposed to be used alone. Please, use the LS Contrast Enhancer or LS Segmenter modules only.
+'''NOTE''': The Logistic Contrast Enhancement, Weighted Enhancement Image Filter and Automatic FLAIR Threshold modules are only supporting CLI methods added in the extension to calculate specific parts of the segmentation procedure. For this reason, these modules are '''not''' supposed to be used alone. Please, use the '''LS Contrast Enhancer''' or '''LS Segmenter''' modules only.
 <!-- ---------------------------- -->
@@ Line 40: / Line 40: @@
 Most frequently used for these scenarios:
 * Use Case 1: Multiple Sclerosis (MS) hyperintense lesions segmentation
-**Hyperintense Multiple Sclerosis lesions, mainly in T2-FLAIR images, have a easy application of this segmentations procedure.
+**Hyperintense Multiple Sclerosis lesions, mainly in T2-FLAIR images, have an easy application of this segmentations procedure.
 * Use Case 2: Increase contrast in abnormal voxels in white matter
-**There are some lesion segmentation approaches that relies on the voxel intensity level presented in the lesion signal, where the LS Contrast Enhancer module can be helpful to increase the contrast between lesions and surrounding brain tissues (mainly White Matter).
+**There are some lesion segmentation approaches that relies on the voxel intensity level presented in the lesion signal, where the '''LS Contrast Enhancer''' module can be helpful to increase the contrast between lesions and surrounding brain tissues (mainly normal appearing white matter - NAWM).
 <gallery widths="300px" heights="300px" perrow="3">