Asymmetry analysis of breast thermograms using automated segmentation and texture features

Dayakshini, S and Kamath, Surekha and Keerthana, Prasad and Rajagopal, KV and Martis, Roshan J (2017) Asymmetry analysis of breast thermograms using automated segmentation and texture features. Signal, Image and Video Processing, 11 (4). pp. 745-752. ISSN 18631703

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Abstract

In this article, we present a new approach for breast thermogram image analysis by developing a fully automatic segmentation of right and left breast for asymmetry analysis, using shape features of the breast and Polynomial curve fitting. Segmentation results are validated with their respective Ground Truths. Histogram and grey level co-occurrence matrix-based texture features are extracted from the segmented images. Statistical test shows that features are highly significant in detection of breast cancer. We have obtained an accuracy of 90%, sensitivity of 87.5% and specificity of 92.5% for a set of eighty images with forty normal and forty abnormal using SVM RBF classifier.

Item Type: Article
Uncontrolled Keywords: Breast cancer · Breast thermography · Asymme- try analysis · Texture features · Bifurcation line · S
Subjects: Engineering > MIT Manipal > Instrumentation and Control
Information Sciences > MCIS Manipal
Medicine > KMC Manipal > Radiology
Depositing User: MIT Library
Date Deposited: 27 Jun 2018 10:14
Last Modified: 27 Jun 2018 10:14
URI: http://eprints.manipal.edu/id/eprint/151385

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