Image understanding in expert systems in histopathology

The use of model-based reasoning, combined with locally adaptive selection of segmentation procedures, has already been found productive in expert-system-guided scene segmentation of histopathologic imagery. It applies human understanding of segmentation problems, with suitable remedial procedures, and knowledge of the structure of the tissues to the segmentation. Expert-system-guided scene segmentation thus implements certain aspects of image understanding to attain robustness. For diagnostic expert systems, though, image understanding in a much broader sense is required. A pathologist's verbal description of histopathologic patterns must be related to specific information extraction and analytic processes, which are to be executed by the automated system.< >