SIMULTANEOUS REGISTRATION, SEGMENTATION AND MODELLING OF STRUCTURE IN GROUPS OF MEDICAL IMAGES

We address the problem of extracting information from groups of medical images of the same anatomy. We describe an algorithm which simultaneously segments and registers a set of such images, incrementally constructing a model of their structure and the correspondences across the set. The framework explicitly models the fraction of each tissue type, rather than the expected intensity in each voxel, to decouple the model from details of the imaging sequence and modality. When estimating the optimal deformation field, the current image is compared to a reconstructed image, generated from the model tissue fractions and the current estimate of intensity distributions for each tissue type in the current image (i.e. an estimate of how the model would appear given the imaging conditions for that image). We describe the algorithm in detail and present results of applying it to a set of MR images of the brain