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A Knowledge Based System for Analysis of Gated Blood Pool Studies
March 1985 (vol. 7 no. 3)
pp. 246-259
Heinrich Niemann, Lehrstuhl für Informatik 5 (Mustererkennung), University Erlangen-Nürnberg, West Germany.
Horst Bunke, Lehrstuhl für Informatik 5 (Mustererkennung), University Erlangen-Nürnberg, West Germany.
Ingrid Hofmann, Lehrstuhl für Informatik 5 (Mustererkennung), University Erlangen-Nürnberg, West Germany.
Gerhard Sagerer, Lehrstuhl für Informatik 5 (Mustererkennung), University Erlangen-Nürnberg, West Germany.
Friedrich Wolf, Institut and Poliklinik für Nuklear-medizin, University Erlangen-Nürnberg, West Germany.
Herbert Feistel, Institut and Poliklinik für Nuklear-medizin, University Erlangen-Nürnberg, West Germany.
A system for obtaining a complete diagnostic description of an image sequence taken in nuclear medicine from the human heart has been developed, implemented, and tested. The knowledge about these images is represented in a semantic net, conclusions are drawn by a production rule approach, and scoring of alternative diagnoses is based on fuzzy membership functions. On the low level, image pixels are smoothed and organ contours are extracted; these are the input for the high level processing. Tests with several image sequences gave correct descriptions as compared to the diagnosis of a physician.
Citation:
Heinrich Niemann, Horst Bunke, Ingrid Hofmann, Gerhard Sagerer, Friedrich Wolf, Herbert Feistel, "A Knowledge Based System for Analysis of Gated Blood Pool Studies," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 7, no. 3, pp. 246-259, March 1985, doi:10.1109/TPAMI.1985.4767655
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