Fractal dimension in the analysis of medical images

Abstract
The analysis of cardiac magnetic resonance (MR) images and X-rays of bone is considered. Each image type is approached using a different form of fractal parameterization. For the MR images, the goal of the study is segmentation, and to this end small regions of the image are assigned a local value of fractal dimension. For the bone X-rays, rather than segmentation, the large-scale structure is parameterized by its fractal dimension. In both cases, the use of fractals leads to the classification of the parameters of interest. When applied to segmentation, this analysis yields boundary discrimination unavailable through previous methods. For the X-rays, texture changes are quantified and correlated with physical changes in the subject. In both cases, the parameterizations are robust with regard to noise present in the images, as well as to variable contrast and brightness.

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