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The use of appearance and shape priors in image segmentation is known to improve accuracy; however, existing techniques have several drawbacks. For instance, most active shape and appearance models require landmark points and assume unimodal shape and appearance distributions, and the level set representation does not support construction of local priors. In this paper, we present novel appearance...
Multiple surface searching with only image intensity information is a difficult job in the presence of high noise and weak edges. We present in this paper a novel method for globally optimal multi-surface searching with a shape prior represented by convex pairwise energies. A 3-D graph-theoretic framework is employed. An arc-weighted graph is constructed based on a shape model built from training...
In this paper, we propose a novel segmentation method that incorporates geometric shape priors, which do not require statistical training, with the graph cuts technique for robust and efficient segmentations of medical images. We introduce novel terms accounting for shape prior/segmentation and shape prior/image fit to the graph cuts representation. The latter prevents a vicious cycle of inaccurate...
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