Automated Characterization of Breast Cancer Using Steerable Filters

Fujita, Hamido and Raghavendra, U and Gudigar, Anjan and Vadakkepat, Vinoy Vishnu and Acharya, Rajendra U (2017) Automated Characterization of Breast Cancer Using Steerable Filters. In: New Trends in Intelligent Software Methodologies, Tools and Techniques. IOS Press, pp. 321-327.

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Breast cancer is one of the highly researched topic in medical image analysis. Digital mammogram analysis is one of the techniques which helps in determining severity of breast cancer within the context of medical image analysis. In this work, a novel technique using steerable co-occurrence features and the independent component analysis (ICA) is proposed. Our method is evaluated using 1000 mammogram images and can efficiently classify normal, benign and malignant classes with a promising performance of 88.60% accuracy, using only ten features. The proposed method is completely automatic and it does not require any segmentation technique in the breast region.

Item Type: Book Section
Uncontrolled Keywords: CAD tool, Breast cancer, Mammography, Steerable filters.
Subjects: Engineering > MIT Manipal > Instrumentation and Control
Depositing User: MIT Library
Date Deposited: 28 Nov 2017 05:03
Last Modified: 28 Nov 2017 05:03

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