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Updated: May 31, 2026

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Fast segmentation with the NextBrain histological atlas.

Oula Puonti1,2, Jackson Nolan2, Robert Dicamillo2

  • 1Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.

Imaging Neuroscience (Cambridge, Mass.)
|May 29, 2026
PubMed

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Summary
This summary is machine-generated.

A new open-source tool significantly accelerates brain subregion segmentation for neuroimaging studies. This method provides accurate, high-resolution anatomical analysis at a fraction of the original computational cost.

Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Medical Image Analysis

Background:

  • Subregion brain analysis is crucial for understanding aging and neurodegenerative diseases.
  • The NextBrain histological atlas aids fine-grained investigations but has computationally intensive segmentation.
  • Existing methods are prohibitive for large-scale neuroimaging studies.

Purpose of the Study:

  • To develop an open-source tool for rapid, accurate brain subregion segmentation.
  • To overcome the computational limitations of previous segmentation frameworks.
  • To enable large-scale, high-resolution anatomical analysis.

Main Methods:

  • A hybrid approach combining machine learning, contrast-adaptive segmentation, image synthesis, and diffeomorphic registration.
Keywords:
brain MRI segmentationdomain-agnostic neuroimaginghistological atlas

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  • GPU acceleration for all key computational steps.
  • Validation across four modalities (in vivo MRI, ex vivo MRI, HiP-CT, photography) and ~4,000 scans.

    • Main Results:

    • The accelerated tool achieves segmentation comparable in accuracy (Dice scores) to the original method.
    • Runtime is reduced by over an order of magnitude (<5 minutes on GPU).
    • The method is effective across diverse MRI resolutions and contrasts, including in vivo and ex vivo scans.

    Conclusions:

    • This work provides a practical, computationally efficient solution for high-resolution brain anatomical analysis at scale.
    • The tool democratizes detailed neuroanatomical studies, facilitating research in aging and neurodegeneration.
    • Public availability in FreeSurfer enhances accessibility for the neuroimaging community.