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MRS Classification Based on Independent Component Analysis and Support Vector Machines
Rio de Janeiro, Brazil December 06-December 09
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICHIS.2005.76Fifth International Conference on Hyb ...
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Jian Ma, Zengqi Sun, "MRS Classification Based on Independent Component Analysis and Support Vector Machines," Hybrid Intelligent Systems, International Conference on, pp. 509-511, Fifth International Conference on Hybrid Intelligent Systems (HIS'05), 2005.
 
 
BibTex
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@article{ 10.1109/ICHIS.2005.76,
author = {Jian Ma and Zengqi Sun},
title = {MRS Classification Based on Independent Component Analysis and Support Vector Machines},
journal ={Hybrid Intelligent Systems, International Conference on},
volume = {0},
year = {2005},
isbn = {0-7695-2457-5},
pages = {509-511},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICHIS.2005.76},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Hybrid Intelligent Systems, International Conference on
TI - MRS Classification Based on Independent Component Analysis and Support Vector Machines
SN - 0-7695-2457-5
SP509
EP511
A1 - Jian Ma,
A1 - Zengqi Sun,
PY - 2005
KW - Support vector machines
KW - independent component analysis
KW - magnetic resonance spectra
KW - classification
KW - feature extraction
VL - 0
JA - Hybrid Intelligent Systems, International Conference on
ER -
 
Jian Ma, Tsinghua Univ., Beijing China
Zengqi Sun, Tsinghua Univ., Beijing China
A novel scheme is proposed in this paper which combines Independent Component Analysis (ICA) and Support Vector Machines (SVM) to classify MRS. ICA is used to extract features by decomposing MRS into components which correspond to biomedical metabolites. SVM is used to train a classifier based on features extracted by ICA. The new scheme can extract meaningful features and therefore obtain a classifier with good generalization. Experimental results show that the new method has better performance than others previous ones.
Index Terms:
Support vector machines, independent component analysis, magnetic resonance spectra, classification, feature extraction
Citation:
Jian Ma, Zengqi Sun, "MRS Classification Based on Independent Component Analysis and Support Vector Machines," his, pp.509-511, Fifth International Conference on Hybrid Intelligent Systems (HIS'05), 2005
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