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Proceedings Paper

Fractal-based characterization of structural changes in biomedical images
Author(s): Vivek Swarnakar; Raj S. Acharya; Claudio H. Sibata; Kyu H. Shin
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Paper Abstract

In the present work, distinct structures appearing in biomedical images are modeled as fractals. Within an image, the relevant structures are associated to a fractal dimension. Changes in the dimension values, as a function of time, reflect alterations of structural properties. Accurate and robust estimation of this dimension, leads to a precise characterization of changes undergone by the structure. The Continuous Pyramidal Alternating Sequential Filter method is proposed as a robust and accurate fractal dimension estimator. A study on bedrest data of human subjects was conducted. Bedrest is an accepted model for the study of osteoporosis. Here the spine is modeled as a fractal structure. Fractal model were also applied towards analysis of breast cancer and brain tumors. Results from these different studies confirm that fractals can suitably model a variety of biological structures. These studies also suggest that fractal models can be effectively utilized to detect temporal changes undergone by the structures.

Paper Details

Date Published: 8 April 1996
PDF: 12 pages
Proc. SPIE 2709, Medical Imaging 1996: Physiology and Function from Multidimensional Images, (8 April 1996); doi: 10.1117/12.237887
Show Author Affiliations
Vivek Swarnakar, Roswell Park Cancer Institute (United States)
Raj S. Acharya, SUNY/Buffalo (United States)
Claudio H. Sibata, Roswell Park Cancer Institute (United States)
Kyu H. Shin, Roswell Park Cancer Institute (United States)


Published in SPIE Proceedings Vol. 2709:
Medical Imaging 1996: Physiology and Function from Multidimensional Images
Eric A. Hoffman, Editor(s)

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