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Neural networks for the classification of benign and malignant patterns in digital mammograms

chapter
posted on 06.12.2017, 00:00 by Brijesh VermaBrijesh Verma, Rinku PanchalRinku Panchal
This chapter presents neural network-based techniques for the classification of microcalcification patterns in digital mammograms. Artificial Neural Network (ANN) applications in digital mammography are mainly focused on feature extraction, feature selection and classification of microcalcification patterns into ‘benign’ and ‘malignant’. An extensive review of neural techniques in digital mammography is presented. Recent developments such as autoassociators and evolutionary neural networks for feature extraction and selection are presented. Experimental results using ANN techniques on a benchmark database are described and analyzed. Finally, a comparison of various neural network-based techniques is presented.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Editor

Fulcher J

Start Page

251

End Page

272

Number of Pages

22

ISBN-10

159140827X

Publisher

IGI

Place of Publication

USA

Open Access

No

External Author Affiliations

Faculty of Business and Informatics; TBA Research Institute;

Era Eligible

Yes

Number of Chapters

10