Computer-aided grading and quantification of hip osteoarthritis severity employing shape descriptors of radiographic hip joint space.
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.
Boniatis
Ioannis
I
University of Patras, School of Medicine, Department of Medical Physics, 265 00 Patras, Greece.
Cavouras
Dionisis
D
Costaridou
Lena
L
Kalatzis
Ioannis
I
Panagiotopoulos
Elias
E
Panayiotakis
George
G
D000368:Aged; D000369:Aged, 80 and over; D003936:Diagnosis, Computer-Assisted; D006621:Hip Joint / Q000000981:diagnostic imaging* / Q000473:pathology; D006801:Humans; D008875:Middle Aged; D015207:Osteoarthritis, Hip / Q000145:classification / Q000000981:diagnostic imaging* / Q000473:pathology; D011857:Radiographic Image Interpretation, Computer-Assisted; D012720:Severity of Illness Index