A deformable region model using stochastic processes applied to echocardiographic images

Abstract

The problem of improving an initial segmentation of medical data by making use of gray level, texture, and gradient information is addressed. The mathematical environment is that of Markov random fields and stochastic processes. This yields two major advantages: automatic selection of program parameters and ergonomic software that can be used to test homogeneity properties of regions. The method is applied to echocardiographic images in order to segment cardiac cavities.<>