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This repo contains the checkpoints for SAT.
We offer SAT-Pro, SAT-Nano (both trained on 72 datasets) and another 5 different variants of SAT-Nano (all trained on 49 datasets):
- SAT-Pro: ./Pro
- SAT-Nano: ./Nano
- UNET-Ours: ./Others/UNET-Ours
- UNET-CPT: ./Others/UNET-CPT
- UNET-BB: ./Others/UNET-BaseBERT
- UMamba-CPT: ./Others/UMamba-CPT
- SwinUNETR-CPT: ./Others/SwinUNETR-CPT
Check our paper for more details, and github repo for usage instruction.
⚠️ Each model should be used with paired checkpoint and text encoder checkpoint.
In addition, we provide multiple pretrained encoders at ./Pretrain. Enhanced with multi-modal human anatomy knowledge, they significantly boost the segmentation performance and are potentially beneficial for other tasks:
- A version pretrained only with the textual knowledge (
textual_only.pth). - A version further pretrained with SAT-DS (
multimodal_sat_ds.pth). It can be used to reproduce results in our paper. - A version further pretrained with 10% training data from CVPR 2025: FOUNDATION MODELS FOR TEXT-GUIDED 3D BIOMEDICAL IMAGE SEGMENTATION (
multimodal_cvpr25.pth). It's explicitly optimized for the challenge.
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