Computer-aided grading and quantification of hip osteoarthritis severity employing shape descriptors of radiographic hip joint space

  • Authors:

  • Ioannis Boniatis;Dionisis Cavouras;Lena Costaridou;Ioannis Kalatzis;Elias Panagiotopoulos;George Panayiotakis

  • Affiliations:

  • University of Patras, School of Medicine, Department of Medical Physics, 265 00 Patras, Greece;Technological Educational Institute of Athens, Department of Medical Instrumentation Technology, 122 10 Athens, Greece;University of Patras, School of Medicine, Department of Medical Physics, 265 00 Patras, Greece;Technological Educational Institute of Athens, Department of Medical Instrumentation Technology, 122 10 Athens, Greece;University of Patras, School of Medicine, Department of Orthopaedics, 265 00 Patras, Greece;University of Patras, School of Medicine, Department of Medical Physics, 265 00 Patras, Greece

  • Venue:
  • Computers in Biology and Medicine
  • Year:
  • 2007

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Abstract

A computer-based system was designed for the grading and quantification of hip osteoarthritis (OA) severity. Employing an active-contours segmentation model, 64 hip joint space (HJS) images (18 normal, 46 osteoarthritic) were obtained from the digitized radiographs of 32 unilateral and bilateral OA-patients. Shape features, generated from the HJS-images, and a hierarchical decision tree structure was used for the grading of OA. A shape features based regression model quantified the OA-severity. The system accomplished high accuracies in characterizing hips as ''Normal'' (100%), of ''mild/moderate''-OA (93.8%) or ''severe''-OA (96.7%). OA-severity values, as expressed by HJS-narrowing, correlated highly (r=0.9,p