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Editor-in-chief

 
Faculty of Science, University of Brunei Darussalam, Brunei Darussalam   
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IJIEE 2017 Vol.7(1): 11-17 ISSN: 2010-3719
DOI: 10.18178/IJIEE.2017.7.1.654

The Recognition of Basal Ganglia Area in the Brain MRI Image with Hybrid Classifier

Min-Chi Wu, Chiun-Li Chin, Wen-Chi Chin, Jian-Shiun Wu, Wan-Jou Li, and Ting-Yu Liu
Abstract—To understand the relationship between the volume of basal ganglia and parkinson’s disease, this paper proposes the recognition of basal ganglia in the brain MRI image with hybrid classifier. It can locate the position of basal ganglia in the 2D brain MRI image. It employs three feature extraction methods to extract the texture feature of basal ganglia. The three feature extraction methods include GLCM, Law’s mask and Hu’s method .Next, we uses rank search method and genetic search method to perform feature selection. It can reduce computation complexity. Finally, hybrid classifier combining neuro-fuzzy system and adaboost algorithm is used to achieve recognition. From experimental result, we discovered that our proposed method has the high recognition rate.

Index Terms—Parkinson's disease, magnetic resonance imaging, basal ganglia, feature pooling, neural-fuzzy-based adaboost.

Wen-Chi Chin, Jian-Shiun Wu, Wan-Jou Li, Ting-Yu Liu and Chiun-Li Chin are with the Department of Medical Informatics, Chung Shan Medical University, Taichung, Taiwan (e-mail: nemocandy5@gmail.com, lover0258020@gmail.com, jou1348572906738@gmail.com, joy5960829@gmail.com, ernestli@csmu.edu.tw).
Ming-Chi Wu is with the Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan (e-mail: hao620620@gmail.com).

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Cite:Min-Chi Wu, Chiun-Li Chin, Wen-Chi Chin, Jian-Shiun Wu, Wan-Jou Li, and Ting-Yu Liu, "The Recognition of Basal Ganglia Area in the Brain MRI Image with Hybrid Classifier," International Journal of Information and Electronics Engineering vol. 7, no. 1, pp. 11-17, 2017.

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