Robust automatic classification of benign and malignant microcalcification and mass in digital mammography
by J.S. Leena Jasmine; S. Mary Joans
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 11, No. 3, 2016

Abstract: Breast cancer is the most dangerous cancer among women and second mortality among them. Mammography is the efficient methodology used in early finding of breast cancer. However, mammograms requires high amount of skill and there is a possibility of radiologist to misunderstand it. Hence, computer aided diagnosis are used for finding the abnormalities in mammograms. Automated classification of mass and microcalcification system is proposed in this work using NSCT and SVM. The classification of abnormalities is achieved by extracting the microcalcification and mass features from the contourlet coefficients of the image and the results are used as an input to the SVM. The proposed automated system classifies the mammogram as normal or abnormal and result is abnormal, then it classifies the abnormal severity as benign or malignant. The evaluation of the proposed system is conceded on MIAS database. The experimentation result shows that the proposed system contributes improved classification rate.

Online publication date: Thu, 26-Jan-2017

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Intelligence and Data Mining (IJBIDM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email