MAP Segmentation of Magnetic Resonance Images Using Mean Field Annealing

An algorithm is described which segments magnetic resonance images while removing the noise from the images wihout blurring or other distortion of edges. The problem of segmentation and noise removal is posed as a restoration of an uncorrupted image, given additive white Gaussian noise and a segmentation cost. The problem is solved using a strategy called Mean Field Annealing. An a priori statistical model of the image, which includes the region classification, is chosen which drives the minimization toward solutions