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This paper describes the rationale and importance of utilizing a priori, model based information to guide segmentation and classification in complex medical images represented by Magnetic Resonance Imaging (MRI). The incorporation of such a priori, model based information requires the development of a "top down" model driven system, rather than the more traditional "bottom up" data driven system. Two different examples which incorporate such model based a priori information are discussed: (1) The segmentation and classification of tissues involved in atherosclerosis; and (2) The segmentation and classification of brain tissue for neurosurgical applications.
Engineering in Medicine and Biology Society, 1992 14th Annual International Conference of the IEEE (Volume:7 )
Date of Conference: Oct. 29 1992-Nov. 1 1992