Structural scene analysis and content-based image retrieval applied to bone age assessment

Benedikt Fischer; André Brosig; Thomas M. Deserno; Bastian Ott; Rolf W. Günther

doi:10.1117/12.811632

27 February 2009 Structural scene analysis and content-based image retrieval applied to bone age assessment

Benedikt Fischer, André Brosig, Thomas M. Deserno, Bastian Ott, Rolf W. Günther

Author Affiliations +

Proceedings Volume 7260, Medical Imaging 2009: Computer-Aided Diagnosis; 726004 (2009) https://doi.org/10.1117/12.811632
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Radiological bone age assessment is based on global or local image regions of interest (ROI), such as epiphyseal regions or the area of carpal bones. Usually, these regions are compared to a standardized reference and a score determining the skeletal maturity is calculated. For computer-assisted diagnosis, automatic ROI extraction is done so far by heuristic approaches. In this work, we apply a high-level approach of scene analysis for knowledge-based ROI segmentation. Based on a set of 100 reference images from the IRMA database, a so called structural prototype (SP) is trained. In this graph-based structure, the 14 phalanges and 5 metacarpal bones are represented by nodes, with associated location, shape, as well as texture parameters modeled by Gaussians. Accordingly, the Gaussians describing the relative positions, relative orientation, and other relative parameters between two nodes are associated to the edges. Thereafter, segmentation of a hand radiograph is done in several steps: (i) a multi-scale region merging scheme is applied to extract visually prominent regions; (ii) a graph/sub-graph matching to the SP robustly identifies a subset of the 19 bones; (iii) the SP is registered to the current image for complete scene-reconstruction (iv) the epiphyseal regions are extracted from the reconstructed scene. The evaluation is based on 137 images of Caucasian males from the USC hand atlas. Overall, an error rate of 32% is achieved, for the 6 middle distal and medial/distal epiphyses, 23% of all extractions need adjustments. On average 9.58 of the 14 epiphyseal regions were extracted successfully per image. This is promising for further use in content-based image retrieval (CBIR) and CBIR-based automatic bone age assessment.

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Benedikt Fischer, André Brosig, Thomas M. Deserno, Bastian Ott, and Rolf W. Günther "Structural scene analysis and content-based image retrieval applied to bone age assessment", Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 726004 (27 February 2009); https://doi.org/10.1117/12.811632

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