Difference between revisions of "Projects:StatisticalSegmentationSlicer2"
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* A statistically based flow for image segmentation, using Fast Marching | * A statistically based flow for image segmentation, using Fast Marching | ||
| − | + | [[Image:Gatech_SlicerModel2.jpg|thumb|right|180px|Figure 1:Screenshot from the Slicer Fast Marching module]] | |
* The code has been integrated into the Slicer | * The code has been integrated into the Slicer | ||
Revision as of 15:56, 20 December 2006
Home < Projects:StatisticalSegmentationSlicer2Back to NA-MIC_Collaborations
Objective:
We want to add various statistical measures into our PDE flows for medical imaging. This will allow the incorporation of global image information into the locally defined PDE frameowrk.
Progress:
We developped flows which can separate the distributions inside and outside the evolving contour, and we have also been including shape information in the flows.
Completed:
- A statistically based flow for image segmentation, using Fast Marching
- The code has been integrated into the Slicer
- A user-oriented tutorial for the Fast Marching algorithm is available at:Slicer Module Tutorial
Key Investigators:
Delphine Nain, Eric Pichon, Oleg Michailovich, Yogesh Rathi, James Malcolm, Allen Tannenbaum
References:
- Eric Pichon, Allen Tannenbaum, and Ron Kikinis. A statistically based surface evolution method for medical image segmentation: presentation and validation. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), volume 2, pages 711-720, 2003. Note: Best student presentation in image segmentation award[1]
Links:
