SUGAR: Spherical Ultrafast Graph Attention Framework for Cortical Surface Registration
Paper • 2307.00511 • Published
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The SUGAR pretrained weights are distributed by the upstream
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requires separate authorization from the upstream authors).
The ilex bundle preserves these terms verbatim. Access is
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educational use. The GATv2Conv-based architecture is
itself Apache-2.0 (upstream code); the JAX / Equinox
re-expression in ilex.models.sugar inherits that
architecture under Apache-2.0 but does NOT override the
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SUGAR (cortical-surface registration) -- Left-hemisphere non-rigid (fsaverage3)
Description
SUGAR (Spherical Ultrafast Graph Attention Registration) is a GATv2-based spherical UNet for fast cortical-surface registration that DeepPrep pins for its surface-registration stage. The architecture is a Generic_GatUNet parameterised by the finest FreeSurfer fsaverage level: an encoder of ResEncodingBlocks (each is two stacked GATv2Conv layers with a LeakyReLU between and an optional residual add) pooling down through fsaverage{N..0}, a bottom block at fsaverage0 (12 vertices), a decoder mirroring the encoder with mid-edge unpooling + skip-concat, and a 3-channel output head producing per-vertex XYZ-Euler rotations. The rigid variant mean-reduces the per-vertex Euler field to a single (1, 3) global rotation. Ten variants (per hemisphere rigid + 4 per-hemisphere non-rigid at fsaverage{3,4,5,6}) compose into a coarse-to-fine cascade. The trained checkpoints were saved as full nn.Module pickles against PyTorch Geometric 2.2.0; ilex stages them via a transitional unpickle env, dumps state_dict, and ships canonical safetensors. Architecture consumes per-vertex sulc features (z-scored against the bundled training-set per-vertex stats); cascade driver applies barycentric resampling between the subject sphere and fsaverage at each stage.
Intended use
fsaverage3-resolution non-rigid refinement of the lh.rigid output. Per-vertex Euler-angle field over 162 vertices.
Usage
from ilex.models.sugar import SUGAR
model = SUGAR.from_pretrained('ilex-hub/sugar.lh.norigid.fsaverage3.1')
Authors
Ren J., An N., Lin C., Zhang Y., Sun Z., Zhang W., Li S., Guo N., Cui W., Hu Q., Wang W., Wu X., Wang Y., Jiang T., Satterthwaite T. D., Wang D., Liu H.
Citation
Ren J., An N., Lin C., Zhang Y., Sun Z., Zhang W., Li S., Guo N., Cui W., Hu Q., Wang W., Wu X., Wang Y., Jiang T., Satterthwaite T. D., Wang D., Liu H. (2023). SUGAR: spherical ultrafast graph attention framework for cortical surface registration. arXiv:2307.00511.
References
- Ren J., An N., Lin C., Zhang Y., Sun Z., Zhang W., Li S., Guo N., Cui W., Hu Q., Wang W., Wu X., Wang Y., Jiang T., Satterthwaite T. D., Wang D., Liu H. (2023). SUGAR: spherical ultrafast graph attention framework for cortical surface registration. arXiv:2307.00511. https://arxiv.org/abs/2307.00511
- Brody S., Alon U., Yahav E. (2022). How Attentive are Graph Attention Networks? ICLR 2022. arXiv:2105.14491. (The GATv2 attention primitive SUGAR builds on.)
License
HF Hub license tag: other
HF Hub license slug: sugar-research-only
Effective terms: SUGAR Research-Only License (per the upstream README at https://github.com/NingAnMe/SUGAR). Academic research use free; commercial use of the pretrained weights requires separate authorization from the upstream authors. The network architecture and training code are Apache-2.0 (the NingAnMe/SUGAR upstream); the FreeSurfer fsaverage topology files bundled inside the package (auxi_data/fsaverage*.sphere + _upsample_neighbors.npz) ship from the upstream's utils/auxi_data/ under the same Apache-2.0 terms. The ilex JAX / Equinox port code is separately licensed under Apache-2.0 / GPL-3.0 for the port code itself, but the ilex license does NOT override the upstream Research-Only terms governing the pretrained weights.
Upstream license reference: https://github.com/NingAnMe/SUGAR
Copyright
Network architecture and training code: copyright (c) the SUGAR contributors, distributed under Apache-2.0 at https://github.com/NingAnMe/SUGAR (with the DeepPrep fork at https://github.com/pBFSLab/SUGAR). Pretrained weights distributed by the SUGAR authors carry a non-OSI Research-Only notice in line with the upstream README; commercial use of the weights requires separate authorization from the upstream authors. The ilex JAX / Equinox port code is separately licensed under Apache-2.0 / GPL-3.0 for the port code itself, but the ilex license does NOT override or re-license the upstream Research-Only terms governing the pretrained weights. The bundled FreeSurfer fsaverage topology files (.sphere binaries + _upsample_neighbors.npz) ship from the upstream SUGAR repo's utils/auxi_data/ directory under the same Apache-2.0 terms as the SUGAR code.
Upstream source
Original weights / reference implementation: https://github.com/NingAnMe/SUGAR
Provenance
This artefact was produced by ilex's
save/load pipeline. The architecture is implemented in
ilex.models.sugar.SUGAR and the weights have been converted
from their upstream format. See the upstream source above
for the canonical reference.
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