The Science of Fractal Images
Texture description and segmentation through fractal geometry
Computer Vision, Graphics, and Image Processing
Unsupervised segmentation of ultrasonic liver images by multiresolution fractal feature vector
Information Sciences: an International Journal
Pectoral muscle segmentation: A review
Computer Methods and Programs in Biomedicine
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In this paper it is shown that there is a difference in local fractal dimension between imaged glandular tissue, supporting tissue and muscle tissue based on an assessment from a mammogram. By estimating the density difference at four different local dimensions (2.06, 2.33, 2.48, 2.70) from 142 mammograms we can define a measure and by using this measure we are able to distinguish between the tissue types. A ROC-analysis gives us an area under the curve-value of 0.9998 for separating glandular tissue from muscular tissue and 0.9405 for separating glandular tissue from supporting tissue. To some extent we can say that the measured difference in fractal properties is due to different fractal properties of the unprojected tissue. For example, to a large extent muscle tissue seems to have different fractal properties than glandular or supportive tissue. However, a large variance in the local dimension densities makes it difficult to make proper use of the proposed measure for segmentation purposes.