Difference between revisions of "NeedleFinder"
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Revision as of 17:00, 19 December 2014
Home < NeedleFinderKey Investigators
Andre Mastmeyer, Guillaume Pernelle, Yang Gao, Tina Kapur, Steve Pieper, Ron Kikinis
Project Description
Objective
- Improve performance and usability of NeedleFinder [ADD A SHORT MOVIE TO SHOW WHAT IT DOES TODAY]
- Code profiling, refactoring
- GUI simplification
- Provide Bounding Box/Region of Interest
- Semi-Automatic needle tip (and body) detection
- Parameter optimization
Approach, Plan
- Improvements of the source code quality, algorithms and GUI (usability):
- Ad-hoc python profiling concept (method tagging, logging and message boxes as code probes)
- Improved standardized and guided workflow more usable by MDs (state machine)
- Interaction protocol using existing tools for MD to provide bounding-box quickly
- Incorporate SimpleITK filtering/preprocessing and a little user interaction (try e.g. derivatives: gradient magnitude, vesselness)
- Look into machine learning (implement simple genetic algorithm & compare to brute-force grid search)
Progress
- N/Y
- N/Y
- N/Y
- N/Y
- N/Y
References
- Validation of catheter segmentation for MR-guided gynecologic cancer brachytherapy. Med Image Comput Comput Assist Interv. 2013;16(Pt 3):380-7.
- ADD LINK FOR EXISTING DOCUMENTATION FOR NEEDLE FINDER IN SLICER