Statistical Texture Modeling for Medical Volume Using Linear Tensor Coding | Zendy

Junping Deng | Zendy; Qiao Xu | Zendy; YenWei Chen | Zendy

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Statistical Texture Modeling for Medical Volume Using Linear Tensor Coding

Author(s) -

Junping Deng,

Qiao Xu,

YenWei Chen

Publication year - 2013

Publication title -

computational and mathematical methods in medicine

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.462

H-Index - 48

eISSN - 1748-6718

pISSN - 1748-670X

DOI - 10.1155/2013/630902

Subject(s) - basis (linear algebra) , coding (social sciences) , pattern recognition (psychology) , tensor (intrinsic definition) , mathematics , linear model , artificial intelligence , volume (thermodynamics) , computer science , statistics , geometry , physics , quantum mechanics

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.

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