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The automatic segmentation and labelling of anatomical structures in 3D medical imagesis a challenging task of practical importance. We describe amodel- based approach which allows robust and accurate interpretation using explicit anatomical knowledge. Our method is based on the extension to 3D of Point Distribution Models (PDMs) and associated image search algorithms. Acombination of global, GeneticAlgorithm (GA), and local, Active Shape Model (ASM), search is used. We have built a 3D PDM of the human brain describing a number of major structures. Using this model we have obtained automatic interpretations for 30 3D Magnetic Resonance head images from different individuals. The results have been evaluated quantitativelyand support our claim of robust and accurate interpretation.
Hill et al. (Fri,) studied this question.