DocumentCode :
2641458
Title :
Digital Mammogram Tumor Preprocessing Segmentation Feature Extraction and Classification
Author :
Raman, Valliappan ; Then, Patrick ; Sumari, Putra
Author_Institution :
Sch. of Comput. & Design, Swinburne Univ. of Technol., Kuching, Malaysia
Volume :
2
fYear :
2009
fDate :
March 31 2009-April 2 2009
Firstpage :
507
Lastpage :
511
Abstract :
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.
Keywords :
cancer; case-based reasoning; feature extraction; image segmentation; mammography; medical image processing; tumours; breast biopsy; breast carcinoma; case base reasoning method; clinical decision; digital mammogram; mammogram image; pectoral muscle identification; putative mass identification; region growing method; tumor preprocessing segmentation feature extraction; Breast cancer; Breast neoplasms; Cancer detection; Computer science; Feature extraction; Image processing; Image segmentation; Lesions; Mammography; Shape; case base reasoning; mammogram; segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
Type :
conf
DOI :
10.1109/CSIE.2009.872
Filename :
5171391
Link To Document :
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