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Segmentation of medical images is one of the fundamental problems in image processing field. It aims to provide a crucial decision support to physicians. There are several methods to perform segmentation. Hidden Markov Random Fields (HMRF) constitutes an elegant way to model the problem of segmentation. This modelling leads to the minimization of an energy function. In this paper we focus on Particles...
Medical imaging applications produce large sets of similar images. The huge amount of data makes the manual analysis and interpretation a fastidious task. Medical image segmentation is thus an important process in image processing used to partition the images into different regions (e.g. gray matter, white matter and cerebrospinal fluid). Hidden Markov Random Field (HMRF) Model and Gibbs distributions...
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