metadata
license: mit
tags:
- medical
- mri
- pet
- brain-image-analysis
- multimodal
- alzheimer
arxiv: 2605.13059
BrainAnytime Checkpoints
Finetuned checkpoints for BrainAnytime: Anatomy-Aware Cross-Modal Pretraining for Brain Image Analysis with Arbitrary Modality Availability.
Paper
- Title: BrainAnytime: Anatomy-Aware Cross-Modal Pretraining for Brain Image Analysis with Arbitrary Modality Availability
- arXiv: 2605.13059
- PDF: https://arxiv.org/pdf/2605.13059
Model Sources
- Repository: https://github.com/guangqianyang/BrainAnytime
- Paper: https://arxiv.org/abs/2605.13059
- Demo: https://huggingface.co/spaces/Simmonstt/BrainAnytime-Demo
Checkpoints
| File | Task | Type |
|---|---|---|
CN_vs_AD_seed_0_best.pth |
CN vs AD | Classification |
CN_vs_MCI_seed_0_best.pth |
CN vs MCI | Classification |
MMSE_seed_0_best.pth |
MMSE | Regression |
AGE_seed_0_best.pth |
AGE | Regression |
Usage
from huggingface_hub import hf_hub_download
ckpt = hf_hub_download(
repo_id="Simmonstt/BrainAnytime",
filename="CN_vs_AD_seed_0_best.pth",
)
Citation
If you use these checkpoints, please cite:
@misc{yang2026brainanytimeanatomyawarecrossmodalpretraining,
title={BrainAnytime: Anatomy-Aware Cross-Modal Pretraining for Brain Image Analysis with Arbitrary Modality Availability},
author={Guangqian Yang and Tong Ding and Wenlong Hou and Yue Xun and Ye Du and Qian Niu and Shujun Wang},
year={2026},
eprint={2605.13059},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2605.13059},
}
Paper page: https://arxiv.org/abs/2605.13059