1 July 1990 Automation of arthritis measures in hand radiographs
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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
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tod S. Levitt, Tod S. Levitt, Marcus W. Hedgcock, Marcus W. Hedgcock, John Dye, John Dye, Scott E. Johnston, Scott E. Johnston, } "Automation of arthritis measures in hand radiographs", Proc. SPIE 1233, Medical Imaging IV: Image Processing, (1 July 1990); doi: 10.1117/12.18926; https://doi.org/10.1117/12.18926

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