A Novel Technique for Mammogram Mass Segmentation Using Fractal Adaptive Thresholding

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 291)

Abstract

Digital mammogram is emerged as a most reliable screening technique for the early diagnosis of breast cancer and it paves an opportunity for researchers to develop novel algorithms for computer aided detection. Presence of clusters of microcalcifications as 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, a new fractal method is proposed in this paper for the detection and segmentation of circumscribed masses from mammograms. The median filtering, label removal and contrast enhancement are done as pre-processing measures which makes the process of segmentation of masses, easier. The proposed technique then segments the circumscribed masses using Fractal adaptive thresholding with the application of morphological operations. This Fractal based mammogram mass segmentation is able to produce encouraging results that substantiate the merit of the proposed technique.

Keywords

Fractal dimension Median filtering Mammogram Thresholding Image segmentation 

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Copyright information

© Springer Science+Business Media Singapore 2014

Authors and Affiliations

  1. 1.Department of Computer Science and ApplicationsGandhigram Rural Institute, Deemed UniversityGandhigramIndia

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