SHAPE PRIOR BASED ON STATISTICAL MAP FOR ACTIVE CONTOUR SEGMENTATION

We propose a new method for performing active contour segmentation based on the statistical prior knowledge of the object to detect. From a binary training set of objects, a statistical map describes the possible shapes of the object by computing the probability for each point to belong to the object. This statistical map is treated as a prior distribution and an energy functional is defined such that the object reaches the most probable shape knowing the model. The optimization is done in the level-set framework. Results on both synthetic and medical images are shown.


Published in:
International Conference on Image Processing
Presented at:
IEEE International Conference on Image Processing (ICIP 2008), San Diego, 12-15 October, 2008
Year:
2008
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 Record created 2008-06-09, last modified 2018-09-13

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