Application of Bayesian Methods to Segmentation in Medical Images

Two applications of Bayesian image analysis in medicine are discussed, simultaneous segmentation of 3D X-ray Computerized Tomography (CT) scenes and detection of microcalcifications in mammograms. Segmentation by iterative optimization based on Bayesian decision theory appears to be very fruitful if suitable models can be designed to capture prior knowledge of the structure of the image. In practice this requires development of spatial models in which the use of local context is extended from nearest neighbour relations to more complex descriptions.