Title :
Detection of malignant tumors in mammograms using SVMs
Author_Institution :
Electr. & Comput. Eng. Dept., Lafayette Coll., Easton, PA, USA
Abstract :
This paper proposes an algorithm for automatic detection of malignant tumors in mammograms using support vector machines (SVM). The proposed algorithm is tested using real digital mammograms of normal, benign, or malignant tissue. The results show the potential of SVMs in handling data of high dimension. The contribution is in the preprocessing involved and in the training mechanism needed.
Keywords :
cancer; learning (artificial intelligence); mammography; medical computing; support vector machines; tumours; SVM; automatic tumour detection algorithm; benign tissue; malignant tumor detection; normal tissue; real digital mammogram; support vector machine; Cancer; Malignant tumors; Support vector machines; Testing;
Conference_Titel :
Bioengineering Conference, 2005. Proceedings of the IEEE 31st Annual Northeast
Print_ISBN :
0-7803-9105-5
Electronic_ISBN :
0-7803-9106-3
DOI :
10.1109/NEBC.2005.1431958
