Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/131608
Title: Extraction of brain tumor from MR images using one-class support vector machine
Authors: Zhou, J.
Chan, K.L.
Chong, V.F.H. 
Krishnan, S.M.
Keywords: Image segmentation
MR image
Support vector machine
Issue Date: 2005
Source: Zhou, J., Chan, K.L., Chong, V.F.H., Krishnan, S.M. (2005). Extraction of brain tumor from MR images using one-class support vector machine. Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings 7 VOLS : 6411-6414. ScholarBank@NUS Repository.
Abstract: A novel image segmentation approach by exploring one-class support vector machine (SVM) has been developed for the extraction of brain tumor from magnetic resonance (MR) images. Based on one-class SVM, the proposed method has the ability of learning the nonlinear distribution of the image data without prior knowledge, via the automatic procedure of SVM parameters training and an implicit learning kernel. After the learning process, the segmentation task is performed. The proposed technique is applied to 24 clinical MR images of brain tumor for both visual and quantitative evaluations. Experimental results suggest that the proposed query-based approach provides an effective and promising method for brain tumor extraction from MR images with high accuracy. © 2005 IEEE.
Source Title: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/131608
ISBN: 0780387406
ISSN: 05891019
Appears in Collections:Staff Publications

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