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Proceedings Paper

Using a statistical appearance model to predict the fracture load of the proximal femur
Author(s): Benedikt Schuler; Karl D. Fritscher; Volker Kuhn; Felix Eckstein; Rainer Schubert
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Paper Abstract

Nowadays clinical diagnostic techniques like e.g. dual-energy X-ray absorptiometry are used to quantify bone quality. However, bone mineral density alone is not sufficient to predict biomechanical properties like the fracture load for an individual patient. Therefore, the development of tools, which can assess the bone quality in order to predicting individual biomechanics of a bone, would mean a significant improvement for the prevention of fractures. In this paper an approach to predict the fracture load of proximal femora by using a statistical appearance model will be presented. For this purpose, 96 CT-datasets of anatomical specimen of human femora are used to create statistical models for the prediction of the individual fracture load. Calculating statistical appearance models in different regions of interest by using principal component analysis (PCA) makes it possible to use geometric as well as structural information about the proximal femur. By regressing the output of PCA against the individual fracture load of 96 femora multi-linear regression models using a leave-one-out cross validation scheme have been created. The resulting correlations are comparable to studies that partly use higher image resolutions.

Paper Details

Date Published: 13 March 2009
PDF: 10 pages
Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72610W (13 March 2009); doi: 10.1117/12.811557
Show Author Affiliations
Benedikt Schuler, Institute for Biomedial Image Analysis, UMIT (Austria)
Karl D. Fritscher, Institute for Biomedial Image Analysis, UMIT (Austria)
Volker Kuhn, Innsbruck Medical Univ. (Austria)
Felix Eckstein, Institute of Anatomy & Musculoskeletal, PMU (Austria)
Rainer Schubert, Institute for Biomedial Image Analysis, UMIT (Austria)


Published in SPIE Proceedings Vol. 7261:
Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling
Michael I. Miga; Kenneth H. Wong, Editor(s)

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