Los Angeles, CA
March 31, 2009 to April 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.872
Mammography has been one of the most reliable methods for early detection of breast carcinomas. The main objective of this paper is to detect and segment the tumor from mammogram images that helps to provide support for the clinical decision to perform biopsy of the breast. In this paper, there are two aspects to segmentation in mammography. First is to separate out the mammogram from the background and the identification of putative masses and the pectoral muscle. The extraction approach is done using basic region growing method to identify the tumor. Second is to extract the features from segmented masses and classifies the masses by case base reasoning method. The experimental results are shown in this paper till the first phase of mass segmentation.
mammogram, segmentation, case base reasoning
Patrick Then, Valliappan Raman, "Digital Mammogram Tumor Preprocessing Segmentation Feature Extraction and Classification", CSIE, 2009, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 507-511, doi:10.1109/CSIE.2009.872