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General Information
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2010 Vol.2(4): 586-590 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2010.V2.206

An Enhanced Implementation of Brain Tumor Detection Using Segmentation Based on Soft Computing

T.Logeswari and M.Karnan
Abstract—Image Segmentation is an important and challenging factor in the medical image segmentation. This paper describes segmentation method consisting of two phases. In the first phase, the MRI brain image is acquired from patients database, In that film artifact and noise are removed. After that Hierarchical Self Organizing Map (HSOM) is applied for image segmentation. The HSOM is the extension of the conventional self organizing map used to classify the image row by row. In this lowest level of weight vector, a higher value of tumor pixels, computation speed is achieved by the HSOM with vector quantization.

Index Terms—Image analysis, segmentation, HSOM, tumor detection.

T.Logeswari is a Research Scholar, with the Dept of computer Science, Mother Teresa Women’s University,Kodaikanal, India(email: Saralogu4uin@gmail.com).
M.KARNAN is with the department of Computer Science and Engineering,Tamilnadu College of Engineering,Coimbatore, India(email: drmkarnan@gmail.com).


Cite: T.Logeswari and M.Karnan, "An Enhanced Implementation of Brain Tumor Detection Using Segmentation Based on Soft Computing," International Journal of Computer Theory and Engineering vol. 2, no. 4, pp. 586-590, 2010.

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