2012 Summer Project Week:QuantitativePETImageAnalysisModule
- University of Iowa: Christian Bauer, Reinhard Beichel, Markus Van Tol, ...?
We are developing a loadable module for Slicer to allow for threshold-based segmentation of tumors (or other regions of uptake) in PET scans within user-specified bounds and the tracking of such tumors. This would be used so that multiple physicians could segment the tumor and all consistently create one segmentation. With this, further work would go into checking values such as size and intensity values of tumors, which could be compared over time.
This project may become a part of another: http://www.na-mic.org/Wiki/index.php/2012_Summer_Project_Week:LongitudinalPETCTModule
Tasks, in order of importance/doability at this project week:
1. Set up module testing so it can expand as the rest of the module expands.
2. Start on the section for comparing segmentations in different images over time. (Would need information on relating data sets over time)
3. Debug issues with saving the scene and interacting with the Annotations module.
Before project week: Created a loadable module that currently allows threshold-based segmentation in user-defined regions of interest. Currently designed for PET scan images. Has functionality to suggest a threshold in a space and exclude other regions by uptake values or by user-defined excluded regions and points. Fully functional without the need to change to another module.
After project week: Didn't end up working on things in approach. Instead, worked on creating a spherical region of interest (SROI) for annotations. This is currently partially done and reasonably functional, if not as apparent as desired.
This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)
- ITK Module
- Slicer Module
- Extension -- commandline
- Extension -- loadable YES
- Other (Please specify)
- Reinhard Beichel's UIowa staff page: http://www.engineering.uiowa.edu/~rbeichel/index.html
- Quantitative Imaging Network (QIN) page: http://imaging.cancer.gov/programsandresources/specializedinitiatives/qin