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Proceedings Paper

Biomedical image texture analysis based on high-order fractals
Author(s): Huinian Xiao; Al Chu; Kerrie S. Holton; Richard A. Robb
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Paper Abstract

Since the fractal dimension alone is not sufficient to characterize natural texture, we explore higher order geometry to accurately identify texture in biomedical images. The calculation of the fractal dimension set is based on the texture description: known as the Pseudo Matrix of the Fractal (PMF). In our research, the variants of the PMF are tested, a set of the fractal parameters are defined, and different discriminant functions are investigated. A new approach to texture classification is described. Using vectors derived from the PMF, the inner products of these normalized vectors obtained from the training groups and the test image form the measures for classification. This method is easily implemented and produces reliable classification results. The new algorithm significantly simplifies the calculation of the fractal dimension set, and the classification of texture in medical images becomes more sensitive and specific. Preliminary results have demonstrated an improved accuracy in classification on one group of eight types of realistic texture data and one set of MRI brain data.

Paper Details

Date Published: 26 June 1992
PDF: 11 pages
Proc. SPIE 1660, Biomedical Image Processing and Three-Dimensional Microscopy, (26 June 1992); doi: 10.1117/12.59592
Show Author Affiliations
Huinian Xiao, Mayo Foundation (United States)
Al Chu, St. Mary's Hospital (United States)
Kerrie S. Holton, Mayo Foundation (United States)
Richard A. Robb, Mayo Foundation (United States)

Published in SPIE Proceedings Vol. 1660:
Biomedical Image Processing and Three-Dimensional Microscopy
Raj S. Acharya; Carol J. Cogswell; Dmitry B. Goldgof, Editor(s)

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