Volumetric Texture Analysis in Biomedical Imaging

Reyes-Aldasoro, Constantino Carlos and Bhalerao, Abhir (2010) Volumetric Texture Analysis in Biomedical Imaging. In: Pereira, Manuela and Freire, Mario (eds.) Biomedical Diagnostics and Clinical Technologies: Applying High-Performance Cluster and Grid Computing. IGI, PA, USA, pp. 200-248. ISBN 9781605662800

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In recent years, the development of new and powerful image acquisition techniques has lead to a shift from purely qualitative observation of biomedical images towards more a quantitative examination of the data, which linked with statistical analysis and mathematical modeling has provided more interesting and solid results than the purely visual monitoring of an experiment. The resolution of the imaging equipment has increased considerably and the data provided in many cases is not just a simple image, but a three-dimensional volume. Texture provides interesting information that can characterize anatomical regions or cell populations whose intensities may not be different enough to discriminate between them. This chapter presents a tutorial on volumetric texture analysis. The chapter begins with different definitions of texture together with a literature review focused on the medical and biological applications of texture. A review of texture extraction techniques follows, with a special emphasis on the analysis of volumetric data and examples to visualize the techniques. By the end of the chapter, a review of advantages and disadvantages of all techniques is presented together with some important considerations regarding the classification of the measurement space.

Item Type: Book Section
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Subjects: R Medicine > R Medicine (General) > R856 Biomedical engineering. Electronics. Instrumentation
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Depositing User: Constantino Reyes Aldasoro
Date Deposited: 24 Apr 2012 09:21
Last Modified: 30 Nov 2012 17:12
URI: http://sro.sussex.ac.uk/id/eprint/38691
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