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Proceedings Paper

Texture analysis of clinical radiographs using radon transform on a local scale for differentiation between post-menopausal women with and without hip fracture
Author(s): Holger F. Boehm M.D.; Markus Körner M.D.; Bernhard Baumert M.D.; Ulrich Linsenmaier M.D.; Maximilian Reiser M.D.
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Paper Abstract

Osteoporosis is a chronic condition characterized by demineralization and destruction of bone tissue. Fractures associated with the disease are becoming an increasingly relevant issue for public health institutions. Prediction of fracture risk is a major focus research and, over the years, has been approched by various methods. Still, bone mineral density (BMD) obtained by dual-energy X-ray absorptiometry (DXA) remains the clinical gold-standard for diagnosis and follow-up of osteoporosis. However, DXA is restricted to specialized diagnostic centers and there exists considerable overlap in BMD results between populations of individuals with and without fractures. Clinically far more available than DXA is conventional x-ray imaging depicting trabecular bone structure in great detail. In this paper, we demonstrate that bone structure depicted by clinical radiographs can be analysed quantitatively by parameters obtained from the Radon Transform (RT). RT is a global analysis-tool for detection of predefined, parameterized patterns, e.g. straight lines or struts, representing suitable approximations of trabecular bone texture. The proposed algorithm differentiates between patients with and without fractures of the hip by application of various texture-metrics based on the Radon-Transform to standard x-ray images of the proximal femur. We consider three different regions-of-interest in the proximal femur (femoral head, neck, and inter-trochanteric area), and conduct an analysis with respect to correct classification of the fracture status. Performance of the novel approach is compared to DXA. We draw the conclusion that performance of RT is comparable to DXA and may become a useful supplement to densitometry for the prediction of fracture risk.

Paper Details

Date Published: 10 March 2011
PDF: 7 pages
Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79620L (10 March 2011);
Show Author Affiliations
Holger F. Boehm M.D., Ludwig-Maximilians-Univ. München (Germany)
Markus Körner M.D., Ludwig-Maximilians-Univ. München (Germany)
Bernhard Baumert M.D., Ludwig-Maximilians-Univ. München (Germany)
Ulrich Linsenmaier M.D., Ludwig-Maximilians-Univ. München (Germany)
Maximilian Reiser M.D., Ludwig-Maximilians-Univ. München (Germany)

Published in SPIE Proceedings Vol. 7962:
Medical Imaging 2011: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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