Enhancement of Magnetic Resonance Images Using Soft Computing Based Segmentation

Javed, Arshad and Wang, Yin Chai and Rakan Alenezi, Abdulhameed and Kulathuramaiyer, Narayan (2014) Enhancement of Magnetic Resonance Images Using Soft Computing Based Segmentation. International Journal of Machine Learning and Computing, 4 (1). pp. 73-78. ISSN 2010-3700

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Segmentation is the process of extracting points, lines or regions, which are then used as inputs for complementary tasks such as registration, measurement, movement analysis, visualization , etc in MRI. The noise in MR images degrades the image quality and also affect on the segmentation process which can lead to wrong diagnosis. The main aim of this study is to suggest a system to enhance the quality of the human brain MRI. In the proposed system, median filter is used for image enhancement of brain MRI and fuzzy c-means for segmentation purpose. The proposed method is completely automatic that is there is no user involvement in the proposed system. The system is tested on different kinds of brain MR images and proved robust against noise as well as segments the images fast with improvements.

Item Type: Article
Additional Information: Universiti Malaysia Sarawak, UNIMAS
Uncontrolled Keywords: Universiti Malaysia Sarawak, UNIMAS, Magic resonance image, soft computing, research, IPTA, education, sarawak, malaysia, kuching, samarahan, universiti, university
Subjects: Q Science > Q Science (General)
T Technology > T Technology (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Karen Kornalius
Date Deposited: 20 Feb 2014 03:37
Last Modified: 23 Mar 2015 06:15
URI: http://ir.unimas.my/id/eprint/594

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