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.
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;
Conference_Titel :
Database Engineering and Applications Symposium, 2006. IDEAS '06. 10th International
Conference_Location :
Delhi
Print_ISBN :
0-7695-2577-6
DOI :
10.1109/IDEAS.2006.14