Model-based recognition of anatomical objects from medical images

摘要

We present both a high-level symbolic model of the human brain, and a method of using this model to aid in the recognition of objects from medical images. The model is stored as a frame-based semantic network consisting of three coexisting graphs (a spatial adjacency graph, a part hierarchy and an inheritance graph). We propose a method similar to assumption-based truth maintenance systems for the collating and reasoning processes required in the labelling of input images.