A general framework for image segmentation using ordered spatial dependency

Authors:
Mikaël Rousson;Chenyang Xu
Affiliations:
Department of Imaging and Visualization, Siemens Corporate Research, Princeton, NJ;Department of Imaging and Visualization, Siemens Corporate Research, Princeton, NJ
Venue:
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Year:
2006

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Abstract

The segmentation problem appears in most medical imaging applications. Many research groups are pushing toward a whole body segmentation based on atlases. With a similar objective, we propose a general framework to segment several structures. Rather than inventing yet another segmentation algorithm, we introduce inter-structure spatial dependencies to work with existing segmentation algorithms. Ranking the structures according to their dependencies, we end up with a hierarchical approach that improves each individual segmentation and provides automatic initializations. The best ordering of the structures can be learned off-line. We apply this framework to the segmentation of several structures in brain MR images.