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

Research output: Contribution to journalArticle

5 Citations (Scopus)

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
Publication statusPublished - 2011 Jun 1

Fingerprint

Brain
Tuning
Computer simulation
Experiments

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Computer Science Applications

Cite this

@article{3d508e7d25694e16bf5ba1f844bcda85,
title = "A hybrid strategy to integrate surface-based and mutual-information-based methods for co-registering brain SPECT and MR images",
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°.",
author = "Liao, {Yuan Lin} and Yung-Nien Sun and Guo, {Wan Yuo} and Chou, {Yuan Hwa} and Hsieh, {Jen Chuen} and Wu, {Yu Te}",
year = "2011",
month = "6",
day = "1",
doi = "10.1007/s11517-010-0724-9",
language = "English",
volume = "49",
pages = "671--685",
journal = "Medical and Biological Engineering and Computing",
issn = "0140-0118",
publisher = "Springer Verlag",
number = "6",

}

A hybrid strategy to integrate surface-based and mutual-information-based methods for co-registering brain SPECT and MR images. / Liao, Yuan Lin; Sun, Yung-Nien; Guo, Wan Yuo; Chou, Yuan Hwa; Hsieh, Jen Chuen; Wu, Yu Te.

In: Medical and Biological Engineering and Computing, Vol. 49, No. 6, 01.06.2011, p. 671-685.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A hybrid strategy to integrate surface-based and mutual-information-based methods for co-registering brain SPECT and MR images

AU - Liao, Yuan Lin

AU - Sun, Yung-Nien

AU - Guo, Wan Yuo

AU - Chou, Yuan Hwa

AU - Hsieh, Jen Chuen

AU - Wu, Yu Te

PY - 2011/6/1

Y1 - 2011/6/1

N2 - 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°.

AB - 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°.

UR - http://www.scopus.com/inward/record.url?scp=79959882643&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79959882643&partnerID=8YFLogxK

U2 - 10.1007/s11517-010-0724-9

DO - 10.1007/s11517-010-0724-9

M3 - Article

VL - 49

SP - 671

EP - 685

JO - Medical and Biological Engineering and Computing

JF - Medical and Biological Engineering and Computing

SN - 0140-0118

IS - 6

ER -