Marianna at 19:12, 19 January 2016

2016-01-19T19:12:58Z

UpdateBot: Nightly -> 4.5

2015-11-12T20:17:31Z

Nightly -> 4.5

New page

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{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
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This work is supported by NA-MIC, NCIGT, and the Slicer Community.<br>
Author: Vivek Narayan, Jayender Jagadeesan<br>
Contact: Jayender Jagadeesan <email> jayender@bwh.harvard.edu</email> <br>
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|{{collaborator|logo|namic}}|NA-MIC
|{{collaborator|logo|ncigt}}|NCIGT
|{{collaborator|logo|spl}}|SPL
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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/{{documentation/version}}/extension-section|Modules}}
*[[Documentation/{{documentation/version}}/Modules/SegmentCAD|SegmentCAD: Tumor Segmentation from DCE-MRI]]
*[[Documentation/{{documentation/version}}/Modules/HeterogeneityCAD|HeterogeneityCAD: Feature Extraction toolbox for image heterogeneity analysis]]


{{documentation/{{documentation/version}}/extension-section|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)




{{documentation/{{documentation/version}}/module-section|Tutorials}}
*SegmentCAD
**[[Media:SegmentCADTutorial.pptx|SegmentCAD Tutorial (pptx)]]‎


{{documentation/{{documentation/version}}/module-section|Data sets}}
*SegmentCAD
**[[Media:Breast-data1.zip|Breast DCE-MRI Data Set 1 (zip file containing the nrrd volumes for the tutorial)]]‎
**[[Media:Breast-data2.zip|Breast DCE-MRI Data Set 2 (zip file containing additional test set of nrrd volumes)]]‎
*HeterogeneityCAD
**[[Media:BreastHeteroCADData.zip|Breast DCE-MRI Data Set (zip file containing the nrrd volumes for the tutorial)]]‎


{{documentation/{{documentation/version}}/module-section|Quick Instructions for Use}}
*[[Documentation/{{documentation/version}}/Modules/SegmentCAD|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"
*[[Documentation/{{documentation/version}}/Modules/HeterogeneityCAD|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"


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
*SegmentCAD:
*HeterogeneityCAD:
**LabelStatistics


{{documentation/{{documentation/version}}/module-section|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.


{{documentation/{{documentation/version}}/module-section|Information for Developers}}

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

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 {{documentation/{{documentation/version}}/module-section|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
+* Jayender J., Gombos E., Chikarmane S., Dabydeen D., Jolesz F.A., Vosburgh K.G. Statistical Learning Algorithm for in situ and Invasive Breast Carcinoma Segmentation. Comput Med Imaging Graph. 2013 Jun;37(4):281-92. PMID: 23693000. PMCID: PMC3725215.
-* 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
+* Jayender J., Chikarmane S., Jolesz F.A., Gombos E. Automatic Segmentation of Invasive Breast Carcinomas from Dynamic Contrast-Enhanced MRi using Time Series Analysis. J Magn Reson Imaging. 2014 Aug;40(2):467-75. PMID: 24115175. PMCID: PMC3962815.
 * 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.

Documentation/4.5/Extensions/OpenCAD - Revision history

Marianna at 19:12, 19 January 2016

UpdateBot: Nightly -> 4.5