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LOCALLY ADAPTIVE AUTOREGRESSIVE ACTIVE MODELS FOR SEGMENTATION OF 3D ANATOMICAL STRUCTURES
2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Many techniques of knowledge-based segmentation consist of building statistical models that describe the deformations of the structure of interest, and then fit these models to the image data. In this paper, we introduce a novel family of shape prior models that aim to capture such varying support. To this end, 3D segmentation is considered progressively with 2D slices segmented in a qualitative fashion, starting from the ones with strong data support toward the ones of limited support.doi:10.1109/isbi.2007.357072 dblp:conf/isbi/FlorinPFW07 fatcat:kbjugueamjhjphbuvg4dkdzzhe