Universiti Teknologi Malaysia Institutional Repository

MRI brain classification using support vector machine

Othman, Mohd. Fauzi and Abdullah, N. B. and Kamal, N. F. B. (2011) MRI brain classification using support vector machine. In: 2011 4th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO). IEEE, Massachusetts, 001-004. ISBN 978-1-4577-0003-3

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Official URL: http://dx.doi.org/10.1109/ICMSAO.2011.5775605

Abstract

The field of medical imaging gains its importance with increase in the need of automated and efficient diagnosis in a short period of time. Other than that, medical image retrieval system is to provide a tool for radiologists to retrieve the images similar to query image in content. Magnetic resonance imaging (MRI) is an imaging technique that has played an important role in neuroscience research for studying brain images. Classification is an important part in retrieval system in order to distinguish between normal patients and those who have the possibility of having abnormalities or tumor. In this paper, we have obtained the feature related to MRI images using discrete wavelet transformation. An advanced kernel based techniques such as Support Vector Machine (SVM) for the classification of volume of MRI data as normal and abnormal will be deployed.

Item Type:Book Section
Uncontrolled Keywords:biomedical imaging, brain, feature extraction, magnetic resonance imaging, support vector machines, wavelet transforms
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:29473
Deposited By: Liza Porijo
Deposited On:12 Mar 2013 04:30
Last Modified:04 Feb 2017 08:41

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