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Proceedings Paper

Computer interpretation of thallium SPECT studies based on neural network analysis
Author(s): David C. Wang; K. C. Karvelis
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Paper Abstract

A class of artificial intelligence (Al) programs known as neural networks are well suited to pattern recognition. A neural network is trained rather than programmed to recognize patterns. This differs from "expert system" Al programs in that it is not following an extensive set of rules determined by the programmer, but rather bases its decision on a gestalt interpretation of the image. The "bullseye" images from cardiac stress thallium tests performed on 50 male patients, as well as several simulated images were used to train the network. The network was able to accurately classify all patients in the training set. The network was then tested against 50 unknown patients and was able to correctly categorize 77% of the areas of ischemia and 92% of the areas of infarction. While not yet matching the ability of a trained physician, the neural network shows great promise in this area and has potential application in other areas of medical imaging.

Paper Details

Date Published: 1 June 1991
PDF: 2 pages
Proc. SPIE 1445, Medical Imaging V: Image Processing, (1 June 1991); doi: 10.1117/12.45254
Show Author Affiliations
David C. Wang, Henry Ford Hospital (United States)
K. C. Karvelis, Henry Ford Hospital (United States)


Published in SPIE Proceedings Vol. 1445:
Medical Imaging V: Image Processing
Murray H. Loew, Editor(s)

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