Skeletal maturity is assessed visually by comparing hand radiographs to a standardized reference image atlas. Most
common are the methods by Greulich & Pyle and Tanner & Whitehouse. For computer-aided diagnosis (CAD), local
image regions of interest (ROI) such as the epiphysis or the carpal areas are extracted and evaluated. Heuristic
approaches trying to automatically extract, measure and classify bones and distances between bones suffer from the high
variability of biological material and the differences in bone development resulting from age, gender and ethnic origin.
Content-based image retrieval (CBIR) provides a robust solution without delineating and measuring bones. In this work,
epiphyseal ROIs (eROIS) of a hand radiograph are compared to previous cases with known age, mimicking a human
observer. Leaving-one-out experiments are conducted on 1,102 left hand radiographs and 15,428 metacarpal and
phalangeal eROIs from the publicly available USC hand atlas. The similarity of the eROIs is assessed by a combination
of cross-correlation, image distortion model, and Tamura texture features, yielding a mean error rate of 0.97 years and a
variance of below 0.63 years. Furthermore, we introduce a publicly available online-demonstration system, where
queries on the USC dataset as well as on uploaded radiographs are performed for instant CAD. In future, we plan to
evaluate physician with CBIR-CAD against physician without CBIR-CAD rather than physician vs. CBIR-CAD.