2010 Winter Project Week RobustStatisticsDrivenActiveContourSegmentation
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Key Investigators
- Yi Gao, Allen Tannenbaum, Georgia Tech
- Andriy Fedorov, Katie Hayes, Ron Kikinis
Objective
Develop a general purpose active contour segmentor in Slicer3.
More detail and testing are at here.
Approach, Plan
Driven by the robust statistics, we provide an active contour segmentor module for general purpose in Sclier3. The algorithm will simultaneously extract multiple objects in the scene given some user provided labels.
Plan for project week: Integrated into Slicer3 using interactive module.
Progress
The CLI is already on Extension server and ready to be used through extension manager in Slicer.
The next step is to change the user input manner from fiducial points to label maps.
Furthermore, we plan to use multiple labels to simultaneously extract multiple objects.
Work done in this week
- Use label map, instead of fiducial points, as input. This brings two benefits:
- User friendly: easier to set more seeds ===> better knowledge.
- Assign different labels.
- Simultaneous multi-object segmentation. The surfaces of different object compete when they touch each other, and stop at balanced position.
- Keep the history. Though this level set evolution function can not go backward. Use can pull scroll bar back if contour leakages, don't have to start from beginning again.
References
- NA-MIC Publications Database
- Yang, Y. and Tannenbaum, A. and Giddens, D. and Coulter, WH, "Knowledge-based 3D segmentation and reconstruction of coronary arteries using CT images", in IEEE EMBS 2004, pp1664--1666