Magnetic Resonance Image Intensity Inhomogeneity Correction Based on Coherent Local Intensity Clustering

doi:10.11938/cjmr20170205

Abstract

Abstract: We proposed a novel method for correcting intensity inhomogeneity in magnetic resonance images based on the coherent local intensity clustering (CLIC) model. The method used edge information to help identify tissue boundaries. A large Gaussian kernel was used to keep the bias field smooth. Split Bregman iteration was used to accelerate convergence. Phantom and in vivo images were used to evaluate the performance of the proposed method.

Key words: magnetic resonance imaging (MRI), coherent local intensity clustering (CLIC), intensity inhomogeneity, split Bregman iteration

CLC Number:

O482.53

ZHAO Xian-ce, XIE Hai-bin, ZHENG Hui, GUO Tian, YANG Guang. Magnetic Resonance Image Intensity Inhomogeneity Correction Based on Coherent Local Intensity Clustering[J]. Chinese Journal of Magnetic Resonance, 2017, 34(2): 164-174.

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