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Digital Knowledge and Diagnostic Information
Published online by Cambridge University Press: 02 July 2020
Extract
Digital representation of diagnostic imagery offers mensuration, numeric data for diagnostic clue expression, objective assessment, and the option to define standards. Quantitative measurement allows the detection and documentation of very small differences and of diagnostic information that is visually not perceived. The automated extraction of such information from microscopic imagery is beginning to yield to knowledge guided image processing and the development of image understanding systems for machine vision. In a machine vision system, knowledge guidance may be provided by an expert system that controls a top to bottom scene segmentation with constant checks on local bottom-up derived segmentation results for compliance with model specifications and final scene reconstruction. Knowledge guidance is based on a knowledge file for the fully autonomous processing of scenes from a given domain. The knowledge file includes all entities representing traditional diagnostic and histologic terms and concepts: epithelium, stroma, lumen, nucleus, secretory cell, basal cell, stroma cell, chromatin, to name a few.
- Type
- Advanced Microscopy and Image Analysis of Cells and Tissue
- Information
- Microscopy and Microanalysis , Volume 6 , Issue S2: Proceedings: Microscopy & Microanalysis 2000, Microscopy Society of America 58th Annual Meeting, Microbeam Analysis Society 34th Annual Meeting, Microscopical Society of Canada/Societe de Microscopie de Canada 27th Annual Meeting, Philadelphia, Pennsylvania August 13-17, 2000 , August 2000 , pp. 1008 - 1009
- Copyright
- Copyright © Microscopy Society of America