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Segmentation of CT brain images using unsupervised clusterings

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Abstract

In this paper, we present non-identical unsupervised clustering techniques for the segmentation of CT brain images. Prior to segmentation, we enhance the visualization of the original image. Generally, for the presence of abnormal regions in the brain images, we partition them into 3 segments, which are the abnormal regions itself, the cerebrospinal fluid (CSF) and the brain matter. However, for the absence of abnormal regions in the brain images, the final segmented regions will consist of CSF and brain matter only. Therefore, our system is divided into two stages of clustering. The initial clustering technique is for the detection of the abnormal regions. The later clustering technique is for the segmentation of the CSF and brain matter. The system has been tested with a number of real CT head images and has achieved satisfactory results.

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Correspondence to Tong Hau Lee.

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Tong Hau Lee: He received his M.Sc. (IT) in 2001 from University Sains Malaysia. He works in Multimedia University as a lecturer since 2001. His research interest is in digital image processing such as image segmentation and semantics-based image retrieval.

Mohammad Faizal Ahmad Fauzi: He received the B.Eng. degree in electrical and electronic engineering from Imperial College, London, UK in 1999, and the Ph.D. degree in electronics and computer science from University of Southampton, Southampton, UK in 2004. He is currently attached to the Multimedia University, Malaysia as a lecturer/researcher. His main research interests are in the area of signal processing, analysis, retrieval and compression of image, audio and video data, as well as biometrics.

Ryoichi Komiya: He received the B.E. and Ph.D. degrees from Waseda University, Tokyo, Japan, in 1967 and 1986, respectively. Since 1998, he has been at Multimedia University Malaysia, where he has been responsible for research and development of next generation telecommunication systems, services, terminals, IP network, virtual education environment, e-commerce terminal and Intelligent Transportation System. From 2006 to 2008, he was at National Institute of Information and Communication Technology, Japan where he has been promoting R&D on medical ICT. He is currently a visiting professor at Faculty of Software and Information of Iwate Prefectural University, Japan.

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Lee, T.H., Fauzi, M.F.A. & Komiya, R. Segmentation of CT brain images using unsupervised clusterings. J Vis 12, 131–138 (2009). https://doi.org/10.1007/BF03181955

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  • DOI: https://doi.org/10.1007/BF03181955

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