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10th International Database Engineering and Applications Symposium (IDEAS'06)
Classification of Mammograms Using Decision Trees
Delhi, India
December 11-December 14
ISBN: 0-7695-2577-6
L. Vibha, Bangalore University, Bangalore, INDIA
G M Harshavardhan, Bangalore University, Bangalore, INDIA
K Pranaw, Bangalore University, Bangalore, INDIA
P Deepa Shenoy, Bangalore University, Bangalore, INDIA
K R Venugopal, Bangalore University, Bangalore, INDIA
L M Patnaik, Microprocessor Applications Laboratory, Indian Institute of Science, Bangalore, INDIA
Mammography is a medical imaging technique that combines, low-dose radiation and high-contrast, highresolution film for examination of the breast and screening for breast cancer. This paper proposes a Random Forest Decision Classifier (RFDC) for classifying mammograms. Results of screening the mammograms are organised by classification and finally grouped into three categories i.e., Normal, Cancerous and Benign. Experimental results show that this method performs well with the classification accuracy reaching nearly 90% in comparison with the already existing algorithms.
Citation:
L. Vibha, G M Harshavardhan, K Pranaw, P Deepa Shenoy, K R Venugopal, L M Patnaik, "Classification of Mammograms Using Decision Trees," ideas, pp.263-266, 10th International Database Engineering and Applications Symposium (IDEAS'06), 2006
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