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

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This project is supported by...
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This project is supported by P41 RR019703/RR/NCRR NIH HHS/United States, P01 CA067165/CA/NCI NIH HHS/United States and P41 EB015898/EB/NIBIB NIH HHS/United States
  
 
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{{documentation/modulename}} module allows to output a filtered transform node based on an tracker input (transform node). Tracking sensors are particularly usefull to track surgical tools, robots, patient motion, etc... . However, data imported in 3D Slicer from these devices are often noisy. To reduce the noise and smoothly control objects, such as 3D Slicer camera, the {{documentation/modulename}} module will apply a low-pass filter on input data. The cut-off frequency (i.e. the smoothing parameter) is adjustable by the user.
 
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{{documentation/{{documentation/version}}/extension-section|Modules}}
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*[[Documentation/{{documentation/version}}/Modules/SegmentCAD|SegmentCAD: Tumor Segmentation from DCE-MRI]]
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*[[Documentation/{{documentation/version}}/Modules/HeterogeneityCAD|HeterogeneityCAD: Feature Extraction toolbox for image heterogeneity analysis]]
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*The SegmentCAD module is designed to segment tumors from DCE-MRI datasets which include a pre-contrast image and post-contrast images at different time points.
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**SegmentCAD uses blackbox methods to calculate the wash-in and wash-out slopes from the time-intensity curves.
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**The segmentation output is a Label Map with red, yellow, and blue colors respectively identifying washout (Type III), plateau (Type II), and persistent (Type I) voxels.
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*The HeterogeneityCAD module is an extensible, image feature extraction toolbox primarily to quantify the heterogeneity of tumor images and their label maps.
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**Metrics have been implemented from a variety of feature classes including:
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***First-Order/Histogram statistics
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***Morphology/Shape measures and Geometrical (4D Extrusion) measures
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***Renyi/Fractal dimensions
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***Texture features computed from Gray-Level Co-occurrence Matrices (GLCM) and from Gray-Level Run Length matrices (GLRL)
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The {{documentation/modulename}} module could be used in any situation requiring stable tracking data and not requiring a "real-time" information. Indeed, applying a filter on raw data will induce a delay (depending on choosen parameters) on the filtered position/orientation.
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An example could be to drive Slicer's virtual camera. Having some noise on the transformation driving the camera will cause the camera to "shake" which could be really distracting and uncomfortable to look at. By filtering this raw data, camera motion is smoothed. -->
 
  
 
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[[Media:OpenCADTutorial.pptx|OpenCAD Tutorial (pptx)]]‎  
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*SegmentCAD
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**[[Media:SegmentCADTutorial.pptx|SegmentCAD Tutorial (pptx)]]‎
  
 
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[[Media:Breast-data1.zip|Breast DCE-MRI Data Set 1 (zip file containing the nrrd volumes for the OpenCAD tutorial)]]‎  
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*SegmentCAD
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**[[Media:Breast-data1.zip|Breast DCE-MRI Data Set 1 (zip file containing the nrrd volumes for the tutorial)]]‎  
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[[Media:Breast-data2.zip|Breast DCE-MRI Data Set 2 (zip file containing additional test set of nrrd volumes)]]‎
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**[[Media:Breast-data2.zip|Breast DCE-MRI Data Set 2 (zip file containing additional test set of nrrd volumes)]]‎
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*HeterogeneityCAD
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**[[Media:BreastHeteroCADData.zip|Breast DCE-MRI Data Set (zip file containing the nrrd volumes for the  tutorial)]]‎  
  
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[[Media:Liver-data1.zip|Liver DCE-MRI Data Set 1 (zip file containing additional test set of nrrd volumes)]]‎
 
  
 
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{{documentation/{{documentation/version}}/module-section|Quick Instructions for Use}}
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{|
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*[[Documentation/{{documentation/version}}/Modules/SegmentCAD|SegmentCAD (Click link for detailed description)]]
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The GUI of the {{documentation/modulename}} module contains 4 sections:
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**Select the pre-contrast volume
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* '''Select DCE-MRI Volumes for Segmentation'''
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**Select the first post-contrast volume
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* '''Select or Create Output OpenCAD Label Map'''
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**Select the second post-contrast volume
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* '''Set Advanced Segmentation Parameters'''
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**Select the third post-contrast volume
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* '''OpenCAD Label Statistics'''
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**Select the fourth post-contrast volume
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* '''Interactive Charting Settings'''
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**Create or select a label map volume node to represent the output of the segmentation
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**Click "Apply OpenCAD Segmentation"
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{|
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*[[Documentation/{{documentation/version}}/Modules/HeterogeneityCAD|HeterogeneityCAD (Click link for detailed description)]]
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|[[Image:Slicer-OpenCAD-GUI.png|thumb|400px|{{documentation/modulename}} GUI ]]
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**Add an image or parameter map (.nrrd file) to the Nodes List
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**Select a corresponding segmentation label map to use as ROI
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**Click "Apply HeterogeneityCAD"
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{{documentation/{{documentation/version}}/module-section|Similar Modules}}
 
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N/A
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*SegmentCAD:
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*HeterogeneityCAD:
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**LabelStatistics
  
 
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{{documentation/{{documentation/version}}/module-section|References}}
 
{{documentation/{{documentation/version}}/module-section|References}}
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N/A
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* J. Jayender, E. Gombos, S. Chikarmane, D. Dabydeen, F. A. Jolesz, and K. G. Vosburgh, “Statistical Learning Algorithm for In-situ and Invasive Breast Carcinoma Segmentation”, Journal of Computerized Medical Imaging and Graphics, vol. 37, no. 4, pp. 281-292, 2013
 +
* J. Jayender, S. A. Chikarmane, F. A. Jolesz and E. Gombos, “Automatic Segmentation of Invasive Breast Carcinomas from DCE-MRI using Time Series Analysis”, Journal of MRI, Article first published online 23 September 2013, doi: 10.1002/jmri.24394
 +
* J. Jayender, K.G. Vosburgh, E. Gombos, A. Ashraf, D. Kontos, S.C. Gavenonis, F. A. Jolesz and K. Pohl , “Automatic Segmentation of Breast Carcinomas from DCE-MRI using a Statistical Learning Algorithm”, IEEE International Symposium on Biomedical Imaging, pp. 122-125, 2012.
 +
* J. Jayender, D.T. Ruan, V. Narayan, N. Agrawal, F. A. Jolesz and H. Mamata, “Segmentation of Parathyroid Tumors from DCE-MRI using Linear Dynamic System Analysis”, IEEE International Symposium on Biomedical Imaging, 2013.
 +
* J. Jayender, J. Jagannathan, S.Chikarmane, C.P.Raut and F.A. Jolesz, “Computer-Aided Diagnosis of Breast Angiosarcoma: Results in 14 cases”, Quantitative Medical Imaging Symposium, 2013 (invited paper).
 +
* HJWL Aerts, ER Velazquez, RTH Leijenaar, et al., "Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach", vol. 5, Nat Communication, 2014.
 +
 
  
 
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Source code: https://github.com/vnarayan13/Slicer-OpenCAD
 
Source code: https://github.com/vnarayan13/Slicer-OpenCAD
 
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Latest revision as of 03:46, 2 August 2014

Home < Documentation < Nightly < Extensions < OpenCAD


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


OpenCAD.PNG

Introduction and Acknowledgements

This work is supported by NA-MIC, NCIGT, and the Slicer Community.
Author: Vivek Narayan, Jayender Jagadeesan
Contact: Jayender Jagadeesan <email> jayender@bwh.harvard.edu</email>

NA-MIC  
NCIGT  
SPL  

This project is supported by P41 RR019703/RR/NCRR NIH HHS/United States, P01 CA067165/CA/NCI NIH HHS/United States and P41 EB015898/EB/NIBIB NIH HHS/United States


Modules


Extension Description

  • The SegmentCAD module is designed to segment tumors from DCE-MRI datasets which include a pre-contrast image and post-contrast images at different time points.
    • SegmentCAD uses blackbox methods to calculate the wash-in and wash-out slopes from the time-intensity curves.
    • The segmentation output is a Label Map with red, yellow, and blue colors respectively identifying washout (Type III), plateau (Type II), and persistent (Type I) voxels.
  • The HeterogeneityCAD module is an extensible, image feature extraction toolbox primarily to quantify the heterogeneity of tumor images and their label maps.
    • Metrics have been implemented from a variety of feature classes including:
      • First-Order/Histogram statistics
      • Morphology/Shape measures and Geometrical (4D Extrusion) measures
      • Renyi/Fractal dimensions
      • Texture features computed from Gray-Level Co-occurrence Matrices (GLCM) and from Gray-Level Run Length matrices (GLRL)


Tutorials

Data sets


Quick Instructions for Use

  • SegmentCAD (Click link for detailed description)
    • Select the pre-contrast volume
    • Select the first post-contrast volume
    • Select the second post-contrast volume
    • Select the third post-contrast volume
    • Select the fourth post-contrast volume
    • Create or select a label map volume node to represent the output of the segmentation
    • Click "Apply OpenCAD Segmentation"
  • HeterogeneityCAD (Click link for detailed description)
    • Add an image or parameter map (.nrrd file) to the Nodes List
    • Select a corresponding segmentation label map to use as ROI
    • Click "Apply HeterogeneityCAD"

Similar Modules

  • SegmentCAD:
  • HeterogeneityCAD:
    • LabelStatistics

References

  • J. Jayender, E. Gombos, S. Chikarmane, D. Dabydeen, F. A. Jolesz, and K. G. Vosburgh, “Statistical Learning Algorithm for In-situ and Invasive Breast Carcinoma Segmentation”, Journal of Computerized Medical Imaging and Graphics, vol. 37, no. 4, pp. 281-292, 2013
  • J. Jayender, S. A. Chikarmane, F. A. Jolesz and E. Gombos, “Automatic Segmentation of Invasive Breast Carcinomas from DCE-MRI using Time Series Analysis”, Journal of MRI, Article first published online 23 September 2013, doi: 10.1002/jmri.24394
  • J. Jayender, K.G. Vosburgh, E. Gombos, A. Ashraf, D. Kontos, S.C. Gavenonis, F. A. Jolesz and K. Pohl , “Automatic Segmentation of Breast Carcinomas from DCE-MRI using a Statistical Learning Algorithm”, IEEE International Symposium on Biomedical Imaging, pp. 122-125, 2012.
  • J. Jayender, D.T. Ruan, V. Narayan, N. Agrawal, F. A. Jolesz and H. Mamata, “Segmentation of Parathyroid Tumors from DCE-MRI using Linear Dynamic System Analysis”, IEEE International Symposium on Biomedical Imaging, 2013.
  • J. Jayender, J. Jagannathan, S.Chikarmane, C.P.Raut and F.A. Jolesz, “Computer-Aided Diagnosis of Breast Angiosarcoma: Results in 14 cases”, Quantitative Medical Imaging Symposium, 2013 (invited paper).
  • HJWL Aerts, ER Velazquez, RTH Leijenaar, et al., "Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach", vol. 5, Nat Communication, 2014.


Information for Developers

Source code: https://github.com/vnarayan13/Slicer-OpenCAD

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