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 < 0.001 ) with the values predicted by the regression model. The system may contribute to OA-patient management.
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