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Proceedings Paper

Automation of arthritis measures in hand radiographs
Author(s): Tod S. Levitt; Marcus W. Hedgcock M.D.; John Dye; Scott E. Johnston
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Paper Abstract

Hand radiographs provide a valuable index of disease in arthritis and other generalized diseases such as secondary hyperparathyroidism and osteoporosis. Measures such as cortical volume intercortical width average and periarticular demineralization provide diagnostic indicators for these diseases. However visual analysis of hand radiographs is not quantitative and is compromised by both interobserver and intraobserver variation. Automation of these measures would provide repeatable comparable quantities to assist in diagnosis and disease and therapy monitoring. The computer calculations to perform these measures are straightforward. The key problem is automatic segmentation of the hand anatomy that is recognizing the pixels that correspond to specific imaged bones and joints. Our approach incorporates computer-represented hand models in addition to more traditional image processing algorithms. We describe our techniques for using a combination of predictive models and image processing evidence to automatically fmd bone and tissue boundaries and identify specific bone and joints. 2. COMPUTING ARTHRITIS MEASURES Digital scanners and radiograph digitizers make the radiograph available as a data source for computer algorithms that analyze medical imagery. This is significant because radiographs comprise more than 80 of all medical imagery at this time and they are considerably quicker and less costly than other digital modalities such as CT and Mill. Quantitative measures from digital radiographs can aid physicians in diagnosis tracking disease progress and in therapy planning and evaluation. We have begun studying diagnostic measures in arthritis

Paper Details

Date Published: 1 July 1990
PDF: 8 pages
Proc. SPIE 1233, Medical Imaging IV: Image Processing, (1 July 1990); doi: 10.1117/12.18926
Show Author Affiliations
Tod S. Levitt, San Francisco VA Medical Ctr. (United States)
Univ. of California/San Francisco (United States)
Advanced Decision Systems (United States)
Marcus W. Hedgcock M.D., San Francisco VA Medical Ctr. (United States)
Univ. of California/San Francisco (United States)
John Dye, Advanced Decision Systems (United States)
Scott E. Johnston, Advanced Decision Systems (United States)

Published in SPIE Proceedings Vol. 1233:
Medical Imaging IV: Image Processing
Murray H. Loew, Editor(s)

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