Documentation/4.10/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.

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

• Quantitative Image Informatics for Cancer Research (QIICR)
• Open Source Computer Vision
• The Cancer Genome Atlas

Information for Developers

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