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Titlebook: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006; 9th International Co Rasmus Larsen,Mads Nielsen,Jon Sporring Conf

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0302-9743 at the Tivoli Concert Hall with satellite workshops and tutorials at the IT University of Copenhagen, October 1-6, 2006. The conference has become the premier international conference with - depth full length papers in the multidisciplinary ?elds of medical image c- puting, computer-assisted interv
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4D Shape Priors for a Level Set Segmentation of the Left Myocardium in SPECT Sequences correspondences which is known to be quite challenging, especially in higher dimensions. Experimental results on the segmentation of SPECT sequences of the left myocardium confirm that the 4D shape model outperforms respective 3D models, because it takes into account a statistical model of the temporal shape evolution.
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Improving Segmentation of the Left Ventricle Using a Two-Component Statistical ModelD AAM segmentation. We interconnect a set of 2D AAMs by a 3D shape model. We show that our approach is able to cope with imperfect data and improves segmentations by 11% on average compared to 3D AAMs.
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Conference proceedings 2006voli Concert Hall with satellite workshops and tutorials at the IT University of Copenhagen, October 1-6, 2006. The conference has become the premier international conference with - depth full length papers in the multidisciplinary ?elds of medical image c- puting, computer-assisted intervention, an
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Quantitative Vertebral Morphometry Using Neighbor-Conditional Shape Models radiographs with in total 78 fractures. The distance between prediction and true shape is 1.0 mm for unfractured vertebrae and 3.7 mm for fractures, which makes it possible to diagnose and assess the severity of a fracture.
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Anisotropy Creases Delineate White Matter Structure in Diffusion Tensor MRIquality polygonal models of crease surfaces, then demonstrate the method on a measured diffusion tensor dataset, and visualize the result in combination with tractography to confirm its anatomic relevance.
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