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We propose a graph-based segmentation model that takes into account both topological information and intensity similarity to segment non-small-cell lung carcinoma (NSCLC) from PET volumes. The proposed model estimates the probabilities of each voxel belonging to the given foreground and background labels. The topological information is derived from our region of interest topological skeleton tree...
We propose a novel joint probabilistic model that correlates a new probabilistic shape model with the corresponding global intensity distribution to segment multiple abdominal organs simultaneously. Our probabilistic shape model estimates the probability of an individual voxel belonging to the estimated shape of the object. The probability density of the estimated shape is derived from a combination...
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