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Automated landmark identification for human cortical surface-based registration.

Alan Anticevic1, Grega Repovs, Donna L Dierker

  • 1Department of Psychology, Washington University in St. Louis, USA. alan.anticevic@yale.edu

Neuroimage
|September 20, 2011
PubMed
Summary

Automated landmark identification (ALI) improves surface-based registration (SBR) in human neuroimaging. This method offers robust, accurate results with minimal manual correction, enabling large-scale brain analysis.

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Area of Science:

  • Neuroimaging
  • Computational anatomy
  • Brain mapping

Background:

  • Volume-based registration (VBR) is standard for human neuroimaging, but surface-based registration (SBR) better respects cortical topology.
  • Existing SBR methods show registration advantages over VBR, but manual landmark identification hinders widespread adoption.

Purpose of the Study:

  • To implement and evaluate an automated landmark identification (ALI) algorithm for surface-based registration to the PALS-B12 human brain atlas.
  • To assess ALI's performance against human raters for neuroimaging registration accuracy and efficiency.

Main Methods:

  • Developed and applied an automated landmark identification (ALI) algorithm for Landmark-SBR.
  • Compared ALI performance against two trained human raters and one expert anatomical rater (ENR).

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  • Utilized quantitative and qualitative quality assurance metrics, including hemispheric asymmetry analysis.

    • Main Results:

    • ALI demonstrated robust and largely accurate results across all quality assurance tests.
    • The automated method required only modest manual correction (under 10 minutes per subject).
    • ALI largely circumvented human error and bias, enabling high-throughput analysis.

    Conclusions:

    • Automated landmark identification (ALI) is a viable and efficient alternative to manual methods for surface-based registration.
    • ALI facilitates large-scale neuroimaging dataset analysis by enabling high-throughput, accurate inter-subject registration to an atlas.
    • This advancement supports broader adoption of SBR techniques in human neuroimaging research.