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Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 630902, 10 pages
Research Article

Statistical Texture Modeling for Medical Volume Using Linear Tensor Coding

1College of Information Science and Engineering, Ritsumeikan University, Kusatsu 5250072, Japan
2School of Control Science and Engineering, Shandong University, Jinan 250100, China
3College of Computer Science and Information Technology, Central South University of Forestry and Technology, Hunan 410004, China

Received 17 January 2013; Revised 9 May 2013; Accepted 27 May 2013

Academic Editor: Norio Tagawa

Copyright © 2013 Junping Deng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We introduced a compact representation method named Linear Tensor Coding (LTC) for medical volume. With LTC, medical volumes can be represented by a linear combination of bases which are mutually independent. Furthermore, it is possible to choose the distinctive basis for classification. Before classification, correlations between category labels and the coefficients of LTC basis are used to choose the basis. Then we use the selected basis for classification. The classification accuracy can be significantly improved by the use of selected distinctive basis.