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Related Experiment Video

Updated: May 18, 2026

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index
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Published on: January 2, 2012

Cortical thickness and central surface estimation.

Robert Dahnke1, Rachel Aine Yotter, Christian Gaser

  • 1Department of Psychiatry, University of Jena, Jahnstrasse 3, D-07743 Jena, Germany. robert.dahnke@uni-jena.de

Neuroimage
|October 9, 2012
PubMed
Summary
This summary is machine-generated.

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A new automated method accurately measures cortical thickness and reconstructs the brain's central surface (CS). This projection-based thickness (PBT) approach improves analysis of brain structure in neuropsychiatric disorders.

Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Brain Anatomy

Background:

  • Cortical thickness and gyrification correlate with neuropsychiatric disorders.
  • Accurate brain cortex representation is crucial for clinical applications.
  • Existing semi-automated methods for central surface (CS) reconstruction are error-prone and require manual interaction.

Purpose of the Study:

  • To present a novel, fully automated method for simultaneous measurement of cortical thickness and reconstruction of the brain's central surface (CS).
  • To overcome limitations of previous methods, including manual interaction and restricted validation.

Main Methods:

  • A fully automated method using tissue segmentation to estimate white matter (WM) distance.
  • Projection-based thickness (PBT) method that projects local maxima (cortical thickness) to gray matter (GM) voxels.

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Last Updated: May 18, 2026

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index
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Thinned-skull Cortical Window Technique for In Vivo Optical Coherence Tomography Imaging

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  • Validation using spherical and brain phantoms to assess accuracy across various parameters.

    • Main Results:

    • The PBT method accurately reconstructs the CS and measures cortical thickness in one step.
    • The approach effectively handles partial volume effects, sulcal blurring, and asymmetries without explicit sulcus reconstruction.
    • Validation confirms accurate CS construction and thickness measurement under diverse conditions.

    Conclusions:

    • The new automated method offers a robust and efficient alternative for brain cortex analysis.
    • This technique has the potential to advance the study and clinical application of neuropsychiatric disorders.
    • The method demonstrates comparable or superior quality and computational cost to existing approaches.