Fractal Analysis of Mammograms

  • Fredrik Georgsson
  • Stefan Jansson
  • Christina Olsén
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)

Abstract

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.

Keywords

Fractal Dimension Local Dimension Fractal Analysis Domain Expert Fractal Geometry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Fredrik Georgsson
    • 1
  • Stefan Jansson
    • 1
  • Christina Olsén
    • 1
  1. 1.Department of Computing Science, Umeå University, SE-901 87 UmeåSweden

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