GRACE / README.md

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license: cc-by-nc-sa-4.0
tags:
  - medical-imaging
  - mri
  - segmentation
  - neuroscience
  - unetr

GRACE — Whole-Head MRI Segmentation

GRACE is a UNETR-based model for automated whole-head MRI segmentation into 12 tissue classes, developed by the SMILE Lab.

Variants

grace_native.pth — operates in native MRI space
grace_fs.pth — operates in FreeSurfer conformed space (256³ @ 1mm isotropic)

Tissue Classes

See labels.json for the full 12-class label map.

Usage

Install the CROWN CLI and download this model:

pip install crown-cli
crown models download grace-native
crown segment input.nii.gz --model grace-native

Citation Stolte, S. E., Indahlastari, A., Chen, J., Albizu, A., Dunn, A., Pedersen, S., See, K. B., Woods, A. J., & Fang, R. (2024). Precise and Rapid Whole-Head Segmentation from Magnetic Resonance Images of Older Adults using Deep Learning. Imaging neuroscience (Cambridge, Mass.), 2, imag-2-00090. https://doi.org/10.1162/imag_a_00090

Terms By downloading these weights you agree to use them for non-commercial research purposes only. Redistribution of the weights is not permitted.