Design, analysis and classifier evaluation for a CAD tool for breast cancer detection from digital mammograms
by Subodh Srivastava; Neeraj Sharma; Sanjay Kumar Singh; Rajeev Srivastava
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 13, No. 3, 2013

Abstract: In this paper, the design, analysis, and classifier evaluation for a computer aided diagnostics (CAD) tool for early breast cancer detection from mammograms is presented. The design steps of a CAD tool include enhancement, segmentation, feature extraction and selection, and classification of images. A contrast limited histogram equalisation method is used for image enhancement followed by cropping of region of interests. The fuzzy C-means method is used for segmenting abnormalities present in the images. A total of 88 hybrid features are extracted for each image. For feature selection, minimum redundancy and maximum relevancy approach has been used. For decision making, the various classifiers examined for their efficacy, for 322 images available in MIAS database, include SVMs for its various kernel choices, k-NN, and ANN. Finally, it is observed that the SVM classifier for the MLP kernel choice is performing better in comparison to all other classifiers in consideration along with the other design steps as above.

Online publication date: Sat, 27-Sep-2014

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 Biomedical Engineering and Technology (IJBET):
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