Fractal Applications in Digital Mammogram Analysis for the Early Detection of Breast Cancer

Authors

  • V. Sivakumar
  • P. Shanmugavadivu
  • Vinesh Thiruchelvam

Abstract

Breast cancer is one of the frequent and leading causes of mortality among women in the world. Women with early-stage breast cancers are expected to have greater probability of survival. Digital mammogram is emerged as a most reliable screening technique for the early diagnosis of breast cancer and the presence of masses in mammograms is an important early indication of breast cancer. Fractal geometry is an efficient mathematical approach that deals with self-similar, irregular geometric objects called fractals. As the breast background tissues have high local self-similarity, which is the basic property of fractals, fractal analysis finds its place in the effective analysis of digital mammograms. This chapter emphasizes the recent facts on breast cancer risk and projects the significance of fractal applications in the early diagnosis of breast cancer that includes suppression of pectoral muscles, removal of artifacts, detection and segmentation of masses in digital mammograms. The fractal applications in the analysis of digital mammograms are discussed using suitable illustrative research experiments.

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Published

2020-02-07

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Section

Articles