Machine learning in quantitative histopathology |
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Authors: | P H Bartels J E Weber L Duckstein |
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Institution: | Department of Optical Sciences, University of Arizona, Tucson 85721. |
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Abstract: | The role of expert systems functioning as process controllers in learning image understanding systems is discussed. Numeric learning systems already have found a number of applications in cytologic and histopathologic diagnosis. Depending on the required capabilities, systems of increasing complexity are needed. Expert systems to guide scene segmentation in histopathologic imagery require model-based reasoning. Diagnostic image interpretation with learning capability demands a full model of the human expert's competence, including a considerable variety of knowledge representation schemes and inference strategies, coordinated by a meta-process controller. |
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