Difference between revisions of "Projects:StatisticalSegmentationSlicer2"
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Back to [[NA-MIC_Collaborations|NA-MIC_Collaborations]], [[Algorithm:GATech|Georgia Tech Algorithms]] | Back to [[NA-MIC_Collaborations|NA-MIC_Collaborations]], [[Algorithm:GATech|Georgia Tech Algorithms]] | ||
| − | + | = Statistical Segmentation Slicer 2 = | |
| − | + | Our objective is 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. | |
| − | + | = Description = | |
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. | 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. | ||
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* A user-oriented tutorial for the Fast Marching algorithm is available at:[http://www.bme.gatech.edu/groups/minerva/publications/papers/pichon.slicer.fastMarching/index.html Slicer Module Tutorial] | * A user-oriented tutorial for the Fast Marching algorithm is available at:[http://www.bme.gatech.edu/groups/minerva/publications/papers/pichon.slicer.fastMarching/index.html Slicer Module Tutorial] | ||
| − | + | = Publications = | |
* 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[http://www.bme.gatech.edu/groups/minerva/publications/papers/pichon-media2004-segmentation.pdf [1]] | * 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[http://www.bme.gatech.edu/groups/minerva/publications/papers/pichon-media2004-segmentation.pdf [1]] | ||
| − | + | = Key Investigators = | |
* Georgia Tech: Delphine Nain, Eric Pichon, Oleg Michailovich, Yogesh Rathi, James Malcolm, Allen Tannenbaum | * Georgia Tech: Delphine Nain, Eric Pichon, Oleg Michailovich, Yogesh Rathi, James Malcolm, Allen Tannenbaum | ||
| − | + | = Links = | |
Revision as of 22:34, 21 September 2007
Home < Projects:StatisticalSegmentationSlicer2Back to NA-MIC_Collaborations, Georgia Tech Algorithms
Contents
Statistical Segmentation Slicer 2
Our objective is 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.
Description
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
Publications
- 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]
Key Investigators
- Georgia Tech: Delphine Nain, Eric Pichon, Oleg Michailovich, Yogesh Rathi, James Malcolm, Allen Tannenbaum
