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3D cardiac segmentation with pose-invariant higher-order MRFs
2012
2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)
This paper proposes a novel pose-invariant segmentation approach for left ventricle in 3D CT images. The proposed formulation is modular with respect to the image support (i.e. landmarks, edges and regional statistics). The prior is represented as a third-order Markov Random Field (MRF) where triplets of points result to a low-rank statistical prior while inheriting invariance to global transformations. The ventricle surface is determined through triangulation where image discontinuities can be
doi:10.1109/isbi.2012.6235836
dblp:conf/isbi/XiangWDRP12
fatcat:7jvx5bumhbbv7mfhtmugdndofy