3D Matrix Pattern Based Support Vector Machines for Identifying Pulmonary Cancer in CT Scanned Images

Authors:
Qing-Zhu Wang;Ke Wang;Xin-Zhu Wang;A-Lin Hou;Yong Li;Bin Wang
Affiliations:
College of Communication Engineering, Jilin University, Changchun, China;College of Communication Engineering, Jilin University, Changchun, China;College of Communication Engineering, Jilin University, Changchun, China;College of Computer Science and Engineering, Changchun University of Technology, Changchun, China;College of Information Engineering, Jilin Teachers' Institute of Engineering & Technology, Changchun, China;Abdomal, Jilin Tumor Hospital, Changchun, China
Venue:
Journal of Medical Systems
Year:
2012

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Abstract

A novel algorithm of Three Dimension matrix (3D matrix) pattern based Minimum Within-Class Scatter Support Vector Machines (MCSVMs3Dmatrix) is presented. Combining Minimum Within-Class Scatter Support Vector Machines (MCSVMs) and higher-order tensor technology, decision functions of MCSVMs3Dmatrix are calculated along with three orthogonal directions in the 3D space. And then the final decision is made by Majority Vote Method. In previous reports, each CT image is solely processed and the relation among successive CT scanned images is neglected. The case results in defective judgment at whiles. The proposed method solves the problem effectively and improves the accuracy of classification to a certain extent.