The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 53-354
Full Name: Raj Rajkumar
Position: Student
Age: ON
Sex: Male
Address: 30c,thammana street,komarapalayam,namakkal dist,tamilnadu,india
Country: INDIA
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E-mail address: sivamanirajkumar@gmail.com
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Title of the Paper: Magnetic Resonance Image Classification of Corpus Callosum to Perceive Musical Talent
Authors as they appear in the Paper: Rajkumar S, Tamijeselvy P, Palanisamy P
Email addresses of all the authors: sivamanirajkumar@gmail.com,tamijeselvy@gmail.com
Number of paper pages: 10
Abstract: Brain is one of the most important parts in our body. The corpus callosum is the main band of interhemispheric axonal fibers in the human brain. The specific application is the classification of Magnetic Resonance Image of human brain according to the nature of the corpus callosum. It categories MR image of human brain into musicians and non musicians. The proposed system contains two phases. In First phase, Image Segmentation, Gaussian multiresolution EM (GMEM) algorithm is used for segmentation. GMEM algorithm provides high reliability and performance under different levels. The segmentation results can possibly be employed to identify the regions of interest and objects in the scene that is very advantageous to the subsequent image analysis. A Sobel edge detection technique is used to extract corpus callosum from segmented MR Image of human brain. In Second phase, Classification, Extracted corpus callosum is given as input to the classification techniques. The c!
lassification task involves measuring the degree of similarity of a test or unknown corpus callosum. A decision tree based technique is applied. The results show that the performance of proposed approach is both efficient and effectual for medical data analysis.
Keywords: Data Mining, MRI, Corpus Callosum, Epilepsy, Expectation Maximization (EM)Algorithm, Sobel operator, Decision tree.
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