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Proceedings Paper

Scaling index method: a novel nonlinear technique for the analysis of high-resolution MRI of human bones
Author(s): Roberto A. Monetti; Holger Bohm; Dirk Muller; David Newitt; Sharmila Majumdar; Ernst Rummeny; Thomas M. Link; Christoph Rath
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Paper Abstract

The scaling index method (SIM) is a novel non-linear technique to extract structural information from arbitrary data sets. The tomographic images of a three dimensional object can be interpreted as a pixel distribution in a four dimensional space. The SIM provides a distribution of pointwise dimensions which characterizes the structural information of images. The SIM is applied to high resolution magnetic resonance images of human spinal and femoral bone specimens IN VITRO in order to derive a 3d non-linear texture measure which is compared to standard 2d morphometric parameters and bone mineral density in the prediction of biomechanical strength of trabecular bone. Our results show that structural non-linear parameters associated with the trabecular substructure of the bone can effectively predict the mechanical properties of trabecular bone in vitro. This indicates that the trabecular architecture contributes substantially to the biomechanical properties of the bone.

Paper Details

Date Published: 15 May 2003
PDF: 10 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.481099
Show Author Affiliations
Roberto A. Monetti, Max-Planck-Institut fur extraterrestrische Physik (Germany)
Holger Bohm, Technische Univ. Munchen (Germany)
Dirk Muller, Technische Univ. Munchen (Germany)
David Newitt, Univ. of California/San Francisco (United States)
Sharmila Majumdar, Univ. of California/San Francisco (United States)
Ernst Rummeny, Technische Univ. Munchen (Germany)
Thomas M. Link, Technische Univ. Munchen (Germany)
Christoph Rath, Max-Planck-Institut fur extraterrestrische Physik (Germany)


Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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