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