International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 6, No. 4, 8 Mar. 2014
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Computer A ided Detection of Tumours in Mammograms
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Author(s)
Index Terms
Computer Aided Diagnosis, Mammography, Breast Tumor, Symlet, Singular Value Decomposition, Weighted Histograms
Abstract
Mammography is a special CT scan technique, which uses X-rays and high-resolution film to detect breast tumors efficiently. Mammography is used only in breast tumor detection, and images help physicians to detect diseases due to cells normal growth. Mammography is an effective imaging modality for early breast cancer abnormalities detection. Computer aided diagnosis helps the radiologists to detect abnormalities earlier than traditional procedures. In this paper, an automated mammogram classification method is presented. Symlet, singular value decomposition and weighted histograms are used for feature extraction in mammograms. The extracted features are classified using naïve bayes, random forest and neural network algorithms.
Cite This Paper
R.Ramani, N.Suthanthira Vanitha,"Computer A ided Detection of Tumours in Mammograms", IJIGSP, vol.6, no.4, pp.54-59, 2014. DOI: 10.5815/ijigsp.2014.04.07
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