A Framework for Incorporating Structural Prior Information into the Reconstruction and Restoration of Medical Images
Nov 30 1991
We propose a Bayesian model for medical image analysis that permits prior structural information to be incorporated into the estimation of image features. Inclusion of prior information is accomplished using the image model described in Johnson (1992). A distinguishing feature of this model is the specification of a hierarchical structure for image generation that explicitly incorporates region parameters. These parameters are the mechanism by which prior information regarding image structures is included into the reconstruction or restoration of the image scene. Importantly, these region identifiers allow prior information to be incorporated in anon-deterministic fashion, thus permitting prior structure information to be modified by image data with minimal introduction of residual artifacts. Furthermore, the resulting statistical model permits formation of previously unidentified structures based on the observed data likelihood.