• DocumentCode
    2604685
  • Title

    Multi-modality Image Registration Using Mutual Information Based on Gradient Vector Flow

  • Author

    Yujun Guo ; Cheng-Chang Lu

  • Author_Institution
    Dept. of Comput. Sci., Kent State Univ., OH
  • Volume
    3
  • fYear
    2006
  • fDate
    20-24 Aug. 2006
  • Firstpage
    697
  • Lastpage
    700
  • Abstract
    Similarity measure plays a critical role in image registration. Mutual information (MI) has been proved to be a promising measure used widely in multi-modality image registration. However, mutual information only takes statistical information into consideration, while spatial information is not even considered. In this paper, a novel approach is proposed to incorporate spatial information into MI through gradient vector flow (GVF). Mutual information now is calculated from the GVF-intensity (GVFI) map of the original images instead of their intensity values. Multi-modality brain image registration was performed to test the accuracy and robustness of the proposed method. Experimental results showed that the success rate of our method is higher than that of traditional MI-based registration
  • Keywords
    gradient methods; image registration; gradient vector flow; multimodality image registration; mutual information; Biomedical imaging; Brain; Computer science; Fluid flow measurement; Image registration; Medical diagnostic imaging; Mutual information; Performance evaluation; Robustness; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.826
  • Filename
    1699621