• DocumentCode
    712922
  • Title

    Structural image representation for image registration

  • Author

    Aghajani, Khadijeh ; Shirpour, Mohsen ; Manzuri, M.T.

  • Author_Institution
    Dept. of Comput. Eng., Sharif Univ. of Technol., Tehran, Iran
  • fYear
    2015
  • fDate
    3-5 March 2015
  • Firstpage
    95
  • Lastpage
    100
  • Abstract
    Image registration is an important task in medical image processing. Assuming spatially stationary intensity relation among images, conventional area based algorithms such as CC (Correlation Coefficients) and MI (Mutual Information), show weaker results alongside spatially varying intensity distortion. In this research, a structural representation of images is introduced. It allows us to use simpler similarity metrics in multimodal images which are also robust against the mentioned distortion field. The efficiency of this presentation in non-rigid image registration in the presence of spatial varying distortion field is examined. Experimental results on synthetic and real-world data sets demonstrate the effectiveness of the proposed method for image registration tasks.
  • Keywords
    biomedical MRI; image registration; image representation; medical image processing; distortion field; image registration; medical image processing; multimodal images; nonrigid image registration; real-world data sets; similarity metrics; spatially stationary intensity relation; spatially varying intensity distortion; structural image representation; synthetic data sets; Additives; Algorithm design and analysis; Distortion; Entropy; Image registration; Mathematical model; Measurement; Image Registration; Phase Congruency; Structural Image Representation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Signal Processing (AISP), 2015 International Symposium on
  • Conference_Location
    Mashhad
  • Print_ISBN
    978-1-4799-8817-4
  • Type

    conf

  • DOI
    10.1109/AISP.2015.7123534
  • Filename
    7123534