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Segmentation of liver from volumetric images forms the basis for surgical planning required for living donor transplantations and tumor resections surgeries. This paper introduces a novel idea of using sparse representations of liver shapes in a learned structured dictionary to produce an accurate preliminary segmentation, which is further evolved using a joint image and shape based level-set framework...
This paper presents a new algorithm for real time tracking of the exterior and interior surfaces of organs using sparse sampling of the exterior surfaces. The tracking is based on identifying subspaces in which the coefficients of spherical harmonic representations of the surfaces live. It uses pre operative CT/MRI scans during training, and needlescopic images acquired during tracking. We study different...
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