A General Framework for Image Segmentation Using Ordered Spatial Dependency

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.