Prior Knowledge, Random Walks and Human Skeletal Muscle Segmentation

Abstract : In this paper, we propose a novel approach for segmenting the skeletal muscles in MRI automatically. In order to deal with the absence of contrast between the different muscle classes, we proposed a principled mathematical formulation that integrates prior knowledge with a random walks graph-based formulation. Prior knowledge is repre- sented using a statistical shape atlas that once coupled with the random walks segmentation leads to an efficient iterative linear optimization sys- tem. We reveal the potential of our approach on a challenging set of real clinical data.
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Pierre-Yves Baudin, Noura Azzabou, Pierre Carlier, Nikos Paragios. Prior Knowledge, Random Walks and Human Skeletal Muscle Segmentation. Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2012, France. pp.569-576. ⟨hal-00773665⟩

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