NDLI: Computer-Aided Breast Cancer Detection Using Mammograms: A Review

Content Provider	IEEE Xplore Digital Library
Author	Ganesan, K. Acharya, U.R. Chua, C.K. Min, L.C. Abraham, K.T. Ng, K.
Copyright Year	2008
Abstract	The American Cancer Society (ACS) recommends women aged 40 and above to have a mammogram every year and calls it a gold standard for breast cancer detection. Early detection of breast cancer can improve survival rates to a great extent. Inter-observer and intra-observer errors occur frequently in analysis of medical images, given the high variability between interpretations of different radiologists. Also, the sensitivity of mammographic screening varies with image quality and expertise of the radiologist. So, there is no golden standard for the screening process. To offset this variability and to standardize the diagnostic procedures, efforts are being made to develop automated techniques for diagnosis and grading of breast cancer images. A few papers have documented the general trend of computer-aided diagnosis of breast cancer, making a broad study of the several techniques involved. But, there is no definitive documentation focusing on the mathematical techniques used in breast cancer detection. This review aims at providing an overview about recent advances and developments in the field of Computer-Aided Diagnosis (CAD) of breast cancer using mammograms, specifically focusing on the mathematical aspects of the same, aiming to act as a mathematical primer for intermediates and experts in the field.
Page Count	22
File Size	2978539
Starting Page	77
Ending Page	98
File Format	PDF
ISSN	19373333
Volume Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Breast cancer Noise measurement Wavelet transforms Mammography Biomedical imaging Medical tests feature extraction techniques classifiers computer-aided diagnosis (CAD) digital mammography
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering

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