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Soft clustering and Support Vector Machine based technique for the classification of abnormalities in digital mammograms

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3 Author(s)
Peter Mc Leod ; School of Computing Sciences, CQUniversity Rockhampton QLD 4702, Australia ; Brijesh Verma ; Minyeop Park

This paper presents a novel technique which is the amalgamation of a clustering mechanism and a support vector machine classifier. The technique is called Soft Clustering based support vector machine and is designed to provide a fast converging network with good generalization ability leading to an appropriate classification as a benign or malignant class for the classification of suspicious areas in digital mammograms. The proposed technique has been evaluated on a benchmark database. The experimental results and analysis of results are included in this paper.

Published in:

Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2009 5th International Conference on

Date of Conference:

7-10 Dec. 2009