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 objec...

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Bibliographic Details
Main Authors: Houhou, N., Lemkaddem, A., Duay, V., Allal, A., Thiran, J.-P.
Format: Conference Proceeding
Language:English
Subjects:
active contour segmentation
Active contours
Biomedical imaging
Image segmentation
Laboratories
Level set
Object detection
Oncology
Principal component analysis
Shape
Signal processing
Statistical shape
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Description
Summary: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.
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2008.4712247