Automated radiographic absorptiometry system for quantitative rheumatoid arthritis assessment

Vivek Swarnakar; Bo Fan; Harry K. Genant

doi:10.1117/12.431086

3 July 2001 Automated radiographic absorptiometry system for quantitative rheumatoid arthritis assessment

Vivek Swarnakar, Bo Fan, Harry K. Genant

Proceedings Volume 4322, Medical Imaging 2001: Image Processing; (2001) https://doi.org/10.1117/12.431086
Event: Medical Imaging 2001, 2001, San Diego, CA, United States

Abstract

Quantifying disease progression of patients with early stage Rheumatoid Arthritis (RA) presents special challenges. Establishing a robust and reliable method that combines the ACR criteria with bone and soft-tissue measurement techniques, would make possible the diagnosis of early RA and/or the monitoring of the progress of the disease. In this paper an automated, reliable and robust system that combines the ACR criteria with radiographic absorptiometry based bone and soft-tissue density measurement techniques is presented. The system is comprised of an image digitization component and an automated image analysis component. Radiographs of the hands and the calibration wedges are acquired and digitized following a standardized procedure. The image analysis system segments the relevant joints into soft-tissue and bone regions and computes density values of each of these regions relative to the density of the reference wedges. Each of the joints are also scored by trained radiologists using the well established ACR criteria. The results of this work indicate that use of standardized imaging procedures and robust image analysis techniques can significantly improve the reliability of quantitative measurements for rheumatoid arthritis assessment. Furthermore, the methodology has the potential to be clinically used in assessing disease condition of early stage RA subjects.

Citation Download Citation

Vivek Swarnakar, Bo Fan, and Harry K. Genant "Automated radiographic absorptiometry system for quantitative rheumatoid arthritis assessment", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); https://doi.org/10.1117/12.431086

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