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

  • ZHENG Hui ,
  • GUO Tian ,
  • YANG Guang ,
  • ZHAO Xian-ce ,
  • XIE Hai-bin
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  • 1. Shanghai Key Laboratory of Magnetic Resonance, Department of Physics, East China Normal University, Shanghai 200062, China;
    2. Shanghai Colorful Magnetic Resonance Technology Co. Ltd., Shanghai 201614, China

Received date: 2016-04-20

  Revised date: 2017-04-17

  Online published: 2017-06-05

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.

Cite this article

ZHENG Hui , GUO Tian , YANG Guang , ZHAO Xian-ce , XIE Hai-bin . Magnetic Resonance Image Intensity Inhomogeneity Correction Based on Coherent Local Intensity Clustering[J]. Chinese Journal of Magnetic Resonance, 2017 , 34(2) : 164 -174 . DOI: 10.11938/cjmr20170205

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