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Markov Random Fields (MRF) have proven to be extremely useful models for efficient and accurate image segmentation.Recent literature points to an increased effort towards incorporating useful priors (shape, geometry, context) in a MRF framework. However, topological priors, considered extremely crucial in biological and natural image sequences have been less explored. This work proposes a strategy wherein free parameters of the MRF are used to make it topology aware using a semantic graphicaldoi:10.1109/icip.2012.6466855 dblp:conf/icip/JagadeeshMAJMF12 fatcat:ueexomb3efedvfdjqktxtlgihy