Texture analysis of breast thermograms using neighbourhood grey tone difference matrix

Sathish, Dayakshini and Kamath, Surekha and Prasad, Keerthana and Rajagopal, K (2018) Texture analysis of breast thermograms using neighbourhood grey tone difference matrix. International Journal of Bioinformatics Research and Applications, 14 (1-2). pp. 36-45. ISSN 1744-5485

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Breast cancer is the leading cancer in women worldwide. Early detection can reduce the mortality rate of breast cancer. Breast thermography is a non-invasive and simple imaging technique used for early detection of breast cancer. Feature extraction and selection of appropriate features play a major role in computer-aided detection of breast cancer using breast thermograms. In this article, texture features are extracted from automatically segmented breast thermograms by computing neighbourhood grey tone difference matrix (NGTDM) and run length matrix (RLM). Significance of these features in differentiating the abnormal breast from the normal breast is found by statistical test. NGTDM extracted coarseness, busyness, complexity, strength and RLM extracted long run emphasis and run percentage are found to be significant by statistical test. Extracted features are computationally less expensive and attained an average accuracy of 80%, sensitivity of 94% and specificity of 71.4% using back propagation neural network classifier.

Item Type: Article
Uncontrolled Keywords: asymmetry analysis; breast cancer; breast thermography; neighbourhood grey tone difference matrix; statistical test
Subjects: Engineering > MIT Manipal > Instrumentation and Control
Depositing User: MIT Library
Date Deposited: 03 Feb 2018 11:00
Last Modified: 03 Feb 2018 11:00
URI: http://eprints.manipal.edu/id/eprint/150494

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