Multispectral pattern recognition of MR imagery for the noninvasive analysis of atherosclerosis

An image processing, pattern recognition, and computer graphics system is described for the noninvasive identification and evaluation of atherosclerosis using multidimensional magnetic resonance imaging (MRI). Particular emphasis has been placed on the problem of developing a pattern recognition system for noninvasively identifying the different plaque classes involved in atherogenesis using minimal a priori information. A rapid 3-D display system is also described for the simultaneous display of multiple data classes resulting from the tissue identification process. The results of this work provide a high-information-content display, which will aid in the diagnosis and analysis of the atherosclerotic disease process, and permit detailed and quantitative studies to assess the effectiveness of therapies, such as drug, exercise, and dietary regimens.<
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