DocumentCode :
2973629
Title :
Classification of Mammograms Using Decision Trees
Author :
Vibha, L. ; HarshaVardhan, G.M. ; Pranaw, K. ; Shenoy, P. Deepa ; Venugopal, K.R. ; Patnaik, L.M.
Author_Institution :
Dept. of Comput. Sci. & Eng., Bangalore Univ.
fYear :
2006
fDate :
Dec. 2006
Firstpage :
263
Lastpage :
266
Abstract :
Mammography is a medical imaging technique that combines, low-dose radiation and high-contrast, high-resolution 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
Keywords :
cancer; decision trees; diagnostic radiography; image classification; image resolution; mammography; medical image processing; tumours; breast cancer; decision trees; low-dose radiation; mammogram classification; medical imaging technique; random forest decision classifier; Biomedical engineering; Biomedical imaging; Breast cancer; Classification tree analysis; Data mining; Decision trees; Educational institutions; Feature extraction; Mammography; Neoplasms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Database Engineering and Applications Symposium, 2006. IDEAS '06. 10th International
Conference_Location :
Delhi
ISSN :
1098-8068
Print_ISBN :
0-7695-2577-6
Type :
conf
DOI :
10.1109/IDEAS.2006.14
Filename :
4041628
Link To Document :
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