Difference between revisions of "Documentation/Nightly/Extensions/LesionSpotlight"

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[[Image:LesionSpotlight-logo.png|left]]
 
[[Image:LesionSpotlight-logo.png|left]]
  
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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>.  
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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>.
  
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'''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.  
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'''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.  
  
 
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*[[Documentation/{{documentation/version}}/Modules/LSSegmenter|LS Segmenter]]
 
*[[Documentation/{{documentation/version}}/Modules/LSSegmenter|LS Segmenter]]
 
*[[Documentation/{{documentation/version}}/Modules/LSContrastEnhancer|LS Contrast Enhancer]]
 
*[[Documentation/{{documentation/version}}/Modules/LSContrastEnhancer|LS Contrast Enhancer]]
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*[[Documentation/{{documentation/version}}/Modules/AFTSegmenter|AFT Segmenter]]
  
 
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{{documentation/{{documentation/version}}/module-section|Use Cases}}
 
{{documentation/{{documentation/version}}/module-section|Use Cases}}
 
Most frequently used for these scenarios:
 
Most frequently used for these scenarios:
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* Use Case 1: Multiple Sclerosis (MS) hyperintense lesions segmentation
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* Use Case 1: Hyperintense Multiple Sclerosis (MS) lesions segmentation
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**Hyperintense Multiple Sclerosis lesions, mainly in T2-FLAIR images, have a easy application of this segmentations procedure.
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**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.
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* Use Case 2: Increase contrast in abnormal voxels in white matter
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* Use Case 2: Increase contrast in abnormal voxels in white matter tissue
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**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).
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**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">
 
<gallery widths="300px" heights="300px" perrow="3">
 
Image:T2FLAIR_patient.png|T2-FLAIR image from a MS patient
 
Image:T2FLAIR_patient.png|T2-FLAIR image from a MS patient
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Image:T2FLAIR_patient_lesionLabel.png|T2-FLAIR hyperintense lesion segmentation provided by the LS Segmenter module
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Image:T2FLAIR_patient_lesionLabel.png|T2-FLAIR hyperintense lesion segmentation provided by the '''LS Segmenter''' module
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Image:Lesion3DRender.png|Lesion and White Matter 3D representation
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Image:Lesion3DRender.png|MS lesions and White Matter 3D representation
 
Image:T2FLAIR_beforeContrast.png|T2-FLAIR image with original lesion contrast
 
Image:T2FLAIR_beforeContrast.png|T2-FLAIR image with original lesion contrast
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Image:T2FLAIR_afterContrast.png|T2-FLAIR image with hyperintense lesion contrast enhanced provided by the LS Contrast Enhancer module
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Image:T2FLAIR_afterContrast.png|T2-FLAIR image with hyperintense MS lesion contrast enhanced by the '''LS Contrast Enhancer''' module
 
</gallery>
 
</gallery>
  
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{{documentation/{{documentation/version}}/extension-section|References}}
 
{{documentation/{{documentation/version}}/extension-section|References}}
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* paper
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* 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.
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* 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.
  
  

Latest revision as of 11:14, 6 December 2017

Home < Documentation < Nightly < Extensions < LesionSpotlight


For the latest Slicer documentation, visit the read-the-docs.


Introduction and Acknowledgements

This work was partially funded by CAPES and CNPq, a Brazillian Agencies. Information on CAPES can be obtained on the CAPES website and CNPq website.
Author: Antonio Carlos da S. Senra Filho, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics)
Contact: Antonio Carlos da S. Senra Filho <email>acsenrafilho@usp.br</email>

CSIM Laboratory  
University of Sao Paulo  
CNPq Brazil  
CAPES Brazil  


Extension Description

LesionSpotlight-logo.png

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[1] approaches. The LS Segmenter module implements a T2-FLAIR hyperintense lesion segmentation based on the algorithm published in the paper[2].

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.

Modules

Use Cases

Most frequently used for these scenarios:

  • Use Case 1: Hyperintense Multiple Sclerosis (MS) lesions segmentation
    • 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 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).

  • T2-FLAIR image from a MS patient

  • T2-FLAIR hyperintense lesion segmentation provided by the LS Segmenter module

  • MS lesions and White Matter 3D representation

  • T2-FLAIR image with original lesion contrast

  • T2-FLAIR image with hyperintense MS lesion contrast enhanced by the LS Contrast Enhancer module

Similar Extensions

N/A

References

  • 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.


Information for Developers

Work in progress
 Section under construction.


Repositories:

  1. ↑ DOI: 10.1016/j.cmpb.2014.04.006.
  2. ↑ DOI: 10.1007/s11517-017-1747-2
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