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

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{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
 
{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
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Author: Jean-Baptise Vimort, Kitware Inc.<br>
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'''''Author:''''' Jean-Baptise Vimort, Kitware Inc.<br>
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Contributors: Beatriz Paniagua (Kitware Inc), Lucia Cevidanes (University of Michigan - School of Dentistry), Erika Benavides (University of Michigan - School of Dentistry), Antônio Carlos de Oliveira Ruellas (University of Michigan - School of Dentistry)<br>
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'''''Contributors:''''' Beatriz Paniagua (Kitware Inc), Lucia Cevidanes (University of Michigan - School of Dentistry), Erika Benavides (University of Michigan - School of Dentistry), Antônio Carlos de Oliveira Ruellas (University of Michigan - School of Dentistry)<br>
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Contact: Jean-Baptiste Vimort, <email>jb.vimort@kitware.com</email><br>
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'''''Contact:''''' Jean-Baptiste Vimort, <email>jb.vimort@kitware.com</email><br>
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License: [http://www.apache.org/licenses/LICENSE-2.0.html Apache License, Version 2.0]
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'''''Acknowledgments:''''' This work was supported by the National Institute of Health (NIH) National Institute for Dental and Craniofacial Research (NIDCR) grant R21DE025306 (Textural Biomarkers of Arthritis for the Subchondral Bone in the Temporomandibular Joint), NIDCR grant R01DE024450 (Quantification of 3D bony Changes in
 +
Temporomandibular Joint Osteoarthritis) and National Institute of Biomedical Imaging and Bioengineering NIBIB) grant R01EB021391 (Shape Analysis Toolbox for Medical Image Computing Projects).<br>
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'''''License:''''' [http://www.apache.org/licenses/LICENSE-2.0.html Apache License, Version 2.0]
 
<gallery>
 
<gallery>
 
Image:Kitware-logo.png|Kitware Inc.
 
Image:Kitware-logo.png|Kitware Inc.
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{|
 
{|
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|[[Image:Logo-BoneTextureExtension.png|thumb|400px|Logo BoneTextureExtension]]
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|[[Image:Logo-BoneTextureExtension.png|250px]]
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|}
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|
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This extensions contain several modules that can be used to compute feature maps of N-Dimensional images using two well-known texture analysis methods: the study of Grey Level Co-occurrence Matrix (GLCM) and the study of Grey Level Run Length Matrix (GLRLM). The main algorithms used in this extension are part of a remote module of insight toolkit (ITK) called [http://www.insight-journal.org/browse/publication/985 itkTextureFeatures]
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This extensions contain several modules that can be used to compute feature maps of N-Dimensional images using two well-known texture analysis methods: the study of Grey Level Co-occurrence Matrix (GLCM) and the study of Grey Level Run Length Matrix (GLRLM). The main algorithms used in this extension are part of a remote module of ITK called [http://www.insight-journal.org/browse/publication/985 itkTextureFeatures]
 
  
 
Key Features:
 
Key Features:
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** 8 co-occurrence textural features: energy, entropy, correlation, inverse difference moment, inertia, cluster shade, cluster prominence and Haralick correlation
 
** 8 co-occurrence textural features: energy, entropy, correlation, inverse difference moment, inertia, cluster shade, cluster prominence and Haralick correlation
 
** 10 run length textural features: short run emphasis, long run emphasis, grey level non uniformity, run length non uniformity, low grey level run emphasis, high grey level run emphasis, short run low grey level emphasis, short run high grey level emphasis, long run low grey level emphasis and long run high grey level emphasis.
 
** 10 run length textural features: short run emphasis, long run emphasis, grey level non uniformity, run length non uniformity, low grey level run emphasis, high grey level run emphasis, short run low grey level emphasis, short run high grey level emphasis, long run low grey level emphasis and long run high grey level emphasis.
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* Input configurable parameters: locality of the texture, offset directions for co-occurrence and run length computation, the number of bins for the intensity histograms, and the intensity range or the range of run lengths.")
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* Input configurable parameters: locality of the texture, offset directions for co-occurrence and run length computation, the number of bins for the intensity histograms, and the intensity range or the range of run lengths.
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|}
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{{documentation/{{documentation/version}}/module-section|Usage}}
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==Main modules interface==
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{|
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|[[Image:BoneTexture-Interface.png|thumb|400px|BoneTexture User Interface]]
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|[[Image:BoneTextureSerializer-Interface.png|thumb|400px|BoneTextureSerializer User Interface]]
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|}
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==Input example==
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{|
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|[[Image:Scan.eps|thumb|400px|Input scan]]
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|[[Image:CondileMask.eps|thumb|345px|Input mask]]
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|}
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==Texture features==
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{|
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|[[Image:TextureFeaturesTab.png|thumb|600px|Texture feature result table]]
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|}
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==Texture feature maps==
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 +
===Co-occurrence texture feature maps===
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{|
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|[[Image:Energy.eps|thumb|200px|Energy]]
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|[[Image:Entropy.eps|thumb|200px|Entropy]]
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|[[Image:Correlation.eps|thumb|200px|Correlation]]
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|[[Image:InverseDifferenceMoment.eps|thumb|200px|Inverse difference moment]]
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|}
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{|
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|[[Image:Inertia.eps|thumb|200px|Inertia]]
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|[[Image:ClusterShade.eps|thumb|200px|Cluster shade]]
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|[[Image:ClusterProminence.eps|thumb|200px|Cluster prominence]]
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|[[Image:HaralickCorrelation.eps|thumb|200px|Haralick correlation]]
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|}
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===Run Length texture feature maps===
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{|
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|[[Image:ShortRunEmphasis.eps|thumb|200px|Short run emphasis]]
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|[[Image:LongRunEmphasis.eps|thumb|200px|Long run emphasis]]
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|[[Image:GreyLevelnonUniformity.eps|thumb|200px|Grey level non uniformity]]
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|[[Image:RunLengthnonUniformity.eps|thumb|200px|Run length non uniformity]]
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|[[Image:LowGreyLevelRunEmphasis.eps|thumb|200px|Low grey level run emphasis]]
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|}
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{|
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|[[Image:HighGreyLevelRunEmphasis.eps|thumb|200px|High grey level run emphasis]]
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|[[Image:ShortRunLowGreyLevelEmphasis.eps|thumb|200px|Short run low grey level emphasis]]
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|[[Image:ShortRunHighGreyLevelEmphasis.eps|thumb|200px|Short run high grey level emphasis]]
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|[[Image:LongRunLowGreyLevelEmphasis.eps|thumb|200px|Long run low grey level emphasis]]
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|[[Image:LongRunHighGreyLevelEmphasis.eps|thumb|200px|Long run high grey level emphasis]]
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|}
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 +
 
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*[[Documentation/{{documentation/version}}/Modules/ComputeGLRLMFeatures|ComputeGLRLMFeatures]]
 
*[[Documentation/{{documentation/version}}/Modules/ComputeGLRLMFeatures|ComputeGLRLMFeatures]]
 
*[[Documentation/{{documentation/version}}/Modules/SeparateVectorImage|SeparateVectorImage]]
 
*[[Documentation/{{documentation/version}}/Modules/SeparateVectorImage|SeparateVectorImage]]
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{{documentation/{{documentation/version}}/module-section|Additional Information}}
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* [http://www.insight-journal.org/browse/publication/985 InsightJournal article]
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* [https://github.com/InsightSoftwareC BoneTextureExtension Tutorial]
  
 
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Latest revision as of 15:12, 7 July 2017

Home < Documentation < Nightly < Extensions < BoneTextureExtesion


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


Introduction and Acknowledgements

Author: Jean-Baptise Vimort, Kitware Inc.
Contributors: Beatriz Paniagua (Kitware Inc), Lucia Cevidanes (University of Michigan - School of Dentistry), Erika Benavides (University of Michigan - School of Dentistry), Antônio Carlos de Oliveira Ruellas (University of Michigan - School of Dentistry)
Contact: Jean-Baptiste Vimort, <email>jb.vimort@kitware.com</email>
Acknowledgments: This work was supported by the National Institute of Health (NIH) National Institute for Dental and Craniofacial Research (NIDCR) grant R21DE025306 (Textural Biomarkers of Arthritis for the Subchondral Bone in the Temporomandibular Joint), NIDCR grant R01DE024450 (Quantification of 3D bony Changes in Temporomandibular Joint Osteoarthritis) and National Institute of Biomedical Imaging and Bioengineering NIBIB) grant R01EB021391 (Shape Analysis Toolbox for Medical Image Computing Projects).
License: Apache License, Version 2.0

  • Kitware Inc.

  • University of Michigan

Extension Description

Logo-BoneTextureExtension.png

This extensions contain several modules that can be used to compute feature maps of N-Dimensional images using two well-known texture analysis methods: the study of Grey Level Co-occurrence Matrix (GLCM) and the study of Grey Level Run Length Matrix (GLRLM). The main algorithms used in this extension are part of a remote module of insight toolkit (ITK) called itkTextureFeatures

Key Features:

  • Estimated texture features:
    • 8 co-occurrence textural features: energy, entropy, correlation, inverse difference moment, inertia, cluster shade, cluster prominence and Haralick correlation
    • 10 run length textural features: short run emphasis, long run emphasis, grey level non uniformity, run length non uniformity, low grey level run emphasis, high grey level run emphasis, short run low grey level emphasis, short run high grey level emphasis, long run low grey level emphasis and long run high grey level emphasis.
  • Input configurable parameters: locality of the texture, offset directions for co-occurrence and run length computation, the number of bins for the intensity histograms, and the intensity range or the range of run lengths.

Usage

Main modules interface

BoneTexture User Interface
BoneTextureSerializer User Interface

Input example

Input scan
Input mask

Texture features

Texture feature result table

Texture feature maps

Co-occurrence texture feature maps

Energy
Entropy
Correlation
Inverse difference moment
Inertia
Cluster shade
Cluster prominence
Haralick correlation

Run Length texture feature maps

Short run emphasis
Long run emphasis
Grey level non uniformity
Run length non uniformity
Low grey level run emphasis
High grey level run emphasis
Short run low grey level emphasis
Short run high grey level emphasis
Long run low grey level emphasis
Long run high grey level emphasis



Modules

Additional Information

Similar Extensions

N/A

Information for Developers

The source code is available on github

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