Model-based interpretation of anatomical structures in cranial MR images

A hierarchical model of the brain has been developed, based on the ARTTM system, in which nodes represent the structures of interest, and arcs represent 3-D topographical relationships between organs and part-of relationships. The nodes contain attributes of the organs which encode their expected shape and identifying features; they also attach to the recognition rules, which use the measured attributes and relationships to identify the structures. In this paper the image data is pre-processed to create a Laplacian Pyramid by using multiple Difference of Gaussian (DoG) filters (see Figure 2). Most of the reasoning used in the recognition rules is based on zero crossing features of the DoG images, which may be tracked between scales, or between images of adjacent slices.