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Related Experiment Video

Updated: Apr 23, 2026

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index
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UniSurf: Universal lifespan cortical surface reconstruction.

Zifeng Lian1, Jiameng Liu1, Jiawei Huang1

  • 1School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China.

Medical Image Analysis
|April 21, 2026
PubMed
Summary
This summary is machine-generated.

UniSurf offers a universal framework for brain MRI analysis across all ages. This method ensures accurate cortical surface reconstruction, crucial for understanding brain development and diagnosing disorders.

Keywords:
Cortical surface reconstructionLifespan MRI analysisLongitudinal neuroimagingUniversal surface modeling

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Area of Science:

  • Neuroimaging
  • Brain Development and Aging
  • Computational Neuroscience

Background:

  • Accurate cortical surface reconstruction from MRI is vital for studying brain development, maturation, and aging.
  • Current methods struggle with generalizability and longitudinal consistency due to variations in MRI data across ages and scanners.
  • These limitations hinder research and clinical applications in neurodevelopmental and neurodegenerative disorders.

Purpose of the Study:

  • To introduce UniSurf, a universal framework for robust and consistent lifespan cortical surface reconstruction.
  • To address the challenges of intensity and contrast variations in MRI data across the human lifespan.
  • To enable accurate tracking of brain structures for research and clinical translation.

Main Methods:

  • UniSurf utilizes intensity- and contrast-invariant anatomical information.
  • A differentiable iso-surface extraction algorithm ensures volume-surface consistency.
  • The framework was trained and validated on a large-scale dataset of 10,330 T1-weighted MRI scans (ages 0-100).

Main Results:

  • UniSurf significantly outperforms existing methods in lifespan cortical surface reconstruction.
  • Achieved average Chamfer distances of 0.317 mm (white-matter) and 0.467 mm (pial surfaces).
  • Demonstrates robust generalization across diverse populations and imaging conditions.

Conclusions:

  • UniSurf provides a robust and generalizable tool for lifespan cortical surface reconstruction.
  • Enables reliable, longitudinal tracking of cerebrum volume, cortical surface area, and mean cortical thickness.
  • Has significant potential for large-scale studies and clinical translation in neuroscience.