Kernel Graph Cuts Segmentation for MR Images with Intensity Inhomogeneity Correction

Abstract:

Since the phenomena of intensity inhomogeneity in MR images are prominent and adversely affect quantitative image analysis .In this paper ,we propose a novel magnetic resonance (MR) image segmentation approach based on the kernel graph cuts technique .Because of automatic multiregion segmentation and global energy minimization ,the kernel graph cuts method can be applied to many kinds of images segmentation ,such as MR images and so on . To reduce or eliminate intensity inhomogeneity in MR images ,we add the intensity inhomogeneity correction step which is based on fuzzy c-means (FCM) algorithm before the segment procedure .Firstly , the real MR image data obtained after bias corrected by FCM algorithm .Secondly ,we segment the real MR image data by kernel graph cuts method .Experiments show that the kernel graph cuts method with intensity inhomogeneity correction have a better segment result in accuracy and over-segmentation .

• Periodical: Applied Mechanics and Materials (Volumes 333-335)
• Pages: 938-943
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.333-335.938
• Online since: July 2013
• Authors: Qing Luo, Wen Jian Qin, Jia Gu
• Keywords: Fuzzy C-Means, Intensity Inhomogeneity, Kernel Graph Cuts

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