Published December 13, 2025 | Version 2.0.0
Model Open

GOUHFI: Generalized and Optimized segmentation tool for Ultra-High Field Images

  • 1. ROR icon Norwegian University of Science and Technology
  • 2. ROR icon St Olav's University Hospital

Description

The Generalized and Optimized segmentation tool for Ultra-High Field Images (GOUHFI) is a deep learning-based fully automatic brain segmentation tool optimized for ultra-high field MRI (i.e., ≥ 7T MRI). Using the domain randomization approach proposed in SynthSeg (Billot et al., 2023), GOUHFI is able to segment images of any contrast, resolution and even field strength, making it broadly applicable across scanners, protocols and imaging centers. 

UPDATE 13/12/2025: GOUHFI 2.0 trained model wieghts are now available! The improved subcortical segmentation tool is available with the `brain_seg.zip` file whereas the cortical parcellation model is the `_parc.zip` one. The original GOUHFI subcortical segmentation model is still available with the `GOUHF.zip` file.

Files

GOUHFI.zip

Files (22.4 GB)

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Additional details

Additional titles

Alternative title
GOUHFI 2.0

Related works

Is supplement to
Journal article: 10.1162/IMAG.a.960 (DOI)
Preprint: 10.48550/arXiv.2601.09006 (DOI)

Software

Repository URL
https://github.com/mafortin/GOUHFI
Programming language
Python
Development Status
Wip