Agentification of Markov model-based segmentation: Application to magnetic resonance brain scans

摘要

ObjectiveMarkov random field (MRF) models have been traditionally applied to the task of robust-to-noise image segmentation. Most approaches estimate MRF parameters on the whole image via a global expectation–maximization (EM) procedure. The resulting estimated parameters are likely to be uncharacteristic of local image features. Instead, we propose to distribute a set of local MRF models within a multiagent framework.