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<p><b>Abstract</b>—A geometric approach for 3D object segmentation and representation is presented. The segmentation is obtained by deformable surfaces moving towards the objects to be detected in the 3D image. The model is based on curvature motion and the computation of surfaces with minimal areas, better known as <it>minimal surfaces</it>. The space where the surfaces are computed is induced from the 3D image (volumetric data) in which the objects are to be detected. The model links between classical deformable surfaces obtained via energy minimization, and intrinsic ones derived from curvature based flows. The new approach is stable, robust, and automatically handles changes in the surface topology during the deformation.</p>
3D segmentation, minimal surfaces, deformable models, mean curvature motion, medical images.
Vincent Caselles, Catalina Sbert, Guillermo Sapiro, Ron Kimmel, "Minimal Surfaces Based Object Segmentation", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 19, no. , pp. 394-398, April 1997, doi:10.1109/34.588023
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