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8 April 1996 Fractal-based characterization of structural changes in biomedical images
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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.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vivek Swarnakar, Raj S. Acharya, Claudio H. Sibata, and Kyu H. Shin "Fractal-based characterization of structural changes in biomedical images", Proc. SPIE 2709, Medical Imaging 1996: Physiology and Function from Multidimensional Images, (8 April 1996); https://doi.org/10.1117/12.237887
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