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

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This extension provides tools for automatic and semi-automatic pathology image segmentation.
  
 
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|[[File:SlicerPathologyScreenShot2.png|thumb|800px|Step 1 - Go to the SlicerPathology Extension.]]
 
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* [http://qiicr.org Quantitative Image Informatics for Cancer Research (QIICR)]
 
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* [http://cancergenome.nih.gov/ The Cancer Genome Atlas]
  
 
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The source code for SlicerPathology is available at https://github.com/SBU-BMI/SlicerPathology
  
 
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Latest revision as of 20:54, 7 December 2016

Home < Documentation < Nightly < Extensions < SlicerPathology


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


Introduction and Acknowledgements

Extension: SlicerPathology
Acknowledgments: This work was supported by via the NIH-National Cancer Institute Grant U24 CA180918, as well as, U24 CA180918 Quantitative Image Informatics for Cancer Research (QIICR), http://qiicr.org, PIs Ron Kikinis and Andrey Fedorov, Brigham and Women's Hospital.
Author: Erich Bremer

Contributor 1: Yi Gao
Contributor 2: Nicole Aucoin (SPL)
Contributor 3: Andrey Fedorov (SPL)
Contributor 4: Jean-Christophe Fillion-Robin (Kitware)
Contact: Erich Bremer, <email>erich.bremer@stonybrook.edu</email>

Module Description

This extension provides tools for automatic and semi-automatic pathology image segmentation.

Use Cases

Work in progress
 Section under construction.


Tutorials

Step 1 - Go to the SlicerPathology Extension.
Step 2 - Click the user information tab. Enter your email address. This is used for identification of you in the file data files.
Step 3 - Click "Load data" to select an image.
Step 4 - Click the button Quick TCGA Effect button to activate the effect.
Step 5 - Click "Start TCGA Segmenter and adjust the five segmentation algorithm parameters as needed.
Step 6 - you can select a subregion to speed up the parameter tuning process. Press "Y" to execute the segmenter on the subregion (if it was selected) or the whole image
Step 7 - you can click "Clear Selection" to clear the selected sub-region so that the segmenter operates on the whole image.
Step 8 - "Click the "Submission" tab so that you can save your label masks and related meta data. (meta data will be stored as JSON)
Step 9 - "This is a sample of the stored meta data. Notice the addition of your username for identification.

References

Information for Developers

The source code for SlicerPathology is available at https://github.com/SBU-BMI/SlicerPathology

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