DocumentCode :
3279141
Title :
Application of color spaces fusion approach in MRI classification
Author :
Wang, Chuin-Mu ; Kuo, Chio-Tan ; Da-Peng Yang
Author_Institution :
Coll. of Electr. Eng. & Comput. Sci., Nat. Chin-Yi Univ. of Technol., Taichung, Taiwan
Volume :
4
fYear :
2011
fDate :
10-13 July 2011
Firstpage :
1672
Lastpage :
1677
Abstract :
This paper presents a new detection approach to magnetic resonance (MR) image classification. It is called color space fusion method. MRI produces a sequence of multiple spectral images of tissues with a variety of contrasts using three magnetic resonance parameters, spin-lattice (T1), spin-spin (T2) and dual echo-echo proton density (PD) as signals impinging upon the color space RGB. Therefore, the fusion method and the improved K-means algorithm can be applied. A series of experiments are conducted and compared for performance evaluation. The results show that the proposed method is a promising and effective technique for MR image classification.
Keywords :
biomedical MRI; image classification; image colour analysis; image fusion; medical image processing; MR image classification; color spaces fusion approach; dual echo-echo proton density; improved K-means algorithm; magnetic resonance image classification; spin-lattice; spin-spin; Classification algorithms; Clustering algorithms; Image color analysis; Image segmentation; Magnetic resonance imaging; Signal to noise ratio; Classification; Color space; Fusion of segmentation; Magnetic resonance imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
Conference_Location :
Guilin
ISSN :
2160-133X
Print_ISBN :
978-1-4577-0305-8
Type :
conf
DOI :
10.1109/ICMLC.2011.6017029
Filename :
6017029
Link To Document :
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