Fuzzy soft set approach for classifying malignant and benign breast tumours
by S. Sreedevi; Elizabeth Sherly
International Journal of Healthcare Technology and Management (IJHTM), Vol. 18, No. 3/4, 2021

Abstract: Breast cancer is one of the most common health problems faced by women all over the world and mammography is an effective technique used for its early detection. This work is concentrated on developing machine learning algorithms combined with a mathematical model for classifying malignant or benign images in digital mammograms. The mathematical concept of fuzzy soft set theory is advocated here, which is an extension of crisp and fuzzy with parameterisation. Even though fuzzy and other soft computing techniques have made great progress in solving complex systems that involve uncertainties, imprecision and vagueness, the theory of soft sets opens up a new way for managing uncertain data with parameterisation. The classification is performed by using fuzzy soft aggregation operator to identify abnormality in a mammogram image as malignant or benign. This work is a fully automated computer aided detection method which involves automated noise removal, pectoral muscles removal, segmentation of ROI, identification of micro calcification clusters, feature extraction and feature selection followed by classification. The experiment is performed on images from MIAS dataset and gives 95.12% accuracy.

Online publication date: Fri, 26-Nov-2021

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 Healthcare Technology and Management (IJHTM):
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 subs@inderscience.com