Titlebook: Deformable Models; Theory and Biomateri Jasjit S. Suri,Aly A. Farag Book 2007 Springer-Verlag New York 2007 biomaterial.biomedical engineer

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Segmentation Of Brain Mr Images Using J-Divergence Based Active Contour Models,obustness of the algorithm when an image is corrupted by noise. J-divergence is then used to measure the “distance” between the local and global region probability density functions. The proposed method yields promising results on synthetic and real brain MR images.

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Morphometric Analysis Of Normal And Pathologic Brain Structure Via High-Dimensional Shape TransformRIs), is important for understanding the way in which a disease can affect brain anatomy, for constructing newdiagnostic methods utilizing image information, and for longitudinal follow-up studies evaluating potential drugs.

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Parametric Contour Model In Medical Image Segmentation,ation within a physical framework. Of the model-based techniques, the deformable model is most effectively used for its ability to unify image statistics — both local and global — in a geometrically constrained framework. The geometric constraint imparts a compact form of shape information.

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Parallel Co-Volume Subjective Surface Method For 3d Medical Image Segmentation,olume numerical scheme for solving the Riemannian mean curvature flowof graphs called the subjective surface method. The parallel method is introduced for massively parallel processor (MPP) architecture using the message passing interface (MPI) standard, so it is suitable, e.g., for clusters of Linu

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Volumetric Segmentation Using Shape Models In The Level Set Framework,r, expert-identified segmentation results are often available, and most of the structures to be extracted have a similar shape from one subject to another. Then to model the family of shapes and restricting the new structure to be extracted within the class is of particular interest. Generally, acti

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