Paper
15 May 2003 Analyzing and selecting texture measures for quantifying trabecular bone structures using surrogates
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Abstract
The method of surrogates is applied to three-dimensional MR images to assess and select texture measures for the quantitative characterization of trabecular bone structures for patients with and without osteoporotic bone fractures. Using methods borrowed from the analysis of nonlinear time series, it is possible to generate for a given 3D image surrogate images which have the same linear correlations and the same intensity distribution as the original one whereas all higher-order correlations are wiped out. For bone data (distal radius) from osteoporotic and healthy patients, surrogates are generated by using iterative techniques. In order to test for the presence of nonlinear correlations we calculate the spectrum of weighted scaling indices as a nonlinear texture measure sensitive to morphological image features. It is shown that a significant discrimination between original and surrogate data is possible by comparing the respective spectra. This proves that nonlinear correlations are relevant for bone images and must be taken into account in the texture analysis. The use of nonlinear measures becomes mandatory for an effective description of the image content. Generally, it turns out that the method of surrogate data is a vital tool for assessing the quality of texture measures for any kind of medical images.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christoph Rath, Roberto A. Monetti, Dirk Muller, Holger Bohm, Ernst Rummeny, and Thomas M. Link "Analyzing and selecting texture measures for quantifying trabecular bone structures using surrogates", Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); https://doi.org/10.1117/12.480448
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Cited by 1 scholarly publication.
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KEYWORDS
Bone

3D image processing

Magnetic resonance imaging

Nonlinear dynamics

Distance measurement

Statistical analysis

Fourier transforms

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