A hybrid strategy to integrate surface-based and mutual-information-based methods for co-registering brain SPECT and MR images

Yuan Lin Liao, Yung Nien Sun*, Wan Yuo Guo, Yuan Hwa Chou, Jen Chuen Hsieh, Yu Te Wu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Co-registration of brain SPECT and MR images has been used extensively in clinical applications. The complementary features of two major co-registration methods-surface- and mutual-information-based (MI-based)-motivated us to study a hybrid-based scheme that uses the surface-based method to achieve a quick alignment, followed by the MI-based method for fine tuning. Computer simulations were conducted to evaluate the accuracy and robustness of surface-, MI-, and hybrid-based registration methods by designing different levels of noise and mismatch in the registration experiments. Results demonstrated that the hybrid surface-MI-based scheme outperforms both the surface- and MI-based methods in providing superior accuracy and success rates. Specifically, the translational and rotational errors were no more than 1 mm and 2°, respectively, with consistent success rates over 98%. Besides, the hybrid-based method saved 12-53% of the computation efforts, compared with using the MI-based method alone. We recommend the use of hybrid-based method when the orientational differences between the floating and reference images exceed 10°.

Original languageEnglish
Pages (from-to)671-685
Number of pages15
JournalMedical and Biological Engineering and Computing
Volume49
Issue number6
DOIs
StatePublished - Jun 2011

Keywords

  • Image registration
  • Magnetic resonance imaging
  • Mutual information
  • Single photon emission computed tomography
  • Surfaces

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