A Fast and Automatic Method to Correct Intensity Inhomogeneity in MR Brain Images

  • Zujun Hou
  • Su Huang
  • Qingmao Hu
  • Wieslaw L. Nowinski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)


This paper presents a method to improve the semi-automatic method for intensity inhomogeneity correction by Dawant et al. through introducing a fully automatic approach to reference points generation, which is based on order statistics and integrates information from the fine to coarse scale representations of the input image. The method has been validated and compared with two popular methods, N3 and BFC. Advantages of the proposed method are demonstrated.


Magnetic Resonance Brain Image Coarse Scale Neighboring Block Intensity Inhomogeneity Candidate Block 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Zujun Hou
    • 1
  • Su Huang
    • 2
  • Qingmao Hu
    • 2
  • Wieslaw L. Nowinski
    • 2
  1. 1.Dept. of Interactive MediaInstitute for Infocomm ResearchSingapore
  2. 2.Biomedical Imaging LabSingapore Bioimaging ConsortiumSingapore

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