Difference between revisions of "NeedleFinder"
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<div style="width: 27%; float: left; padding-right: 3%;"> | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
<h3>Objective</h3> | <h3>Objective</h3> | ||
− | * Automatic needle tip detection | + | * Automatic needle tip (and body) detection |
* Modelfit of oburator base and tube using CAD models | * Modelfit of oburator base and tube using CAD models | ||
* NF detection parameter optimization | * NF detection parameter optimization | ||
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</div> | </div> | ||
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==References== | ==References== |
Revision as of 15:12, 17 December 2014
Home < NeedleFinderHere we will fill in tomorrow...
Key Investigators
Andre Mastmeyer, Guillaume Pernelle, Tina Kapur
Project Description
Objective
- Automatic needle tip (and body) detection
- Modelfit of oburator base and tube using CAD models
- NF detection parameter optimization
- Code profiling (is the code used?), refactoring
- GUI improvements
Approach, Plan
- SimpleITK filtering (e.g. derivatives: gradient magnitude, vesselness etc.)
- Rigid registration of CAD models to (preprocessed) scene (ICP, Besl)
- Machine learning (genetic algorithm etc.)
- New ad-hoc python profiling concept (logging and message boxes as code probes)
- Improved standardized and guided workflow more usable by MDs (disabling unsuitable buttons)
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