DocumentCode
1814045
Title
Application of Averaged Learning Subspace Method in MRI Classification
Author
Wang, Chuin-Mu ; Chen, Jau-An ; Chu, Jui-Hsing
Author_Institution
Dept. of Comput. Sci. & Inf. Eng., Nat. Chin-Yi Univ. of Technol., Taichung, Taiwan
Volume
1
fYear
2009
fDate
18-20 Aug. 2009
Firstpage
559
Lastpage
562
Abstract
The objective of this paper is to establish an "averaged learning subspace method" (ALSM) applicable for classification of multi-spectral MR images. By using the ALSM to process the massive amounts of information in multi-spectral MR images, and classification tissues of brain. The classification result of each tissue has shown by binary image, respectively. The classification results would assist doctor to diagnose more efficiently and more accurately and thus to gain more time for necessary action. In order to further evaluate the performance of ALSM, the high order statistics is adopted assessment and compare with perceptron neural network.
Keywords
biological tissues; biomedical MRI; brain; higher order statistics; image classification; learning (artificial intelligence); medical image processing; perceptrons; ALSM; averaged learning subspace method; binary image; brain tissue; high order statistics; medical diagnosis; multispectral MRI image classification; perceptron neural network; Biomedical imaging; Blood; Computed tomography; Covariance matrix; Hospitals; Laser radar; Magnetic resonance imaging; Statistics; Testing; X-rays; ALSM; Classification; MRI;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Assurance and Security, 2009. IAS '09. Fifth International Conference on
Conference_Location
Xian
Print_ISBN
978-0-7695-3744-3
Type
conf
DOI
10.1109/IAS.2009.275
Filename
5283796
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