USCorUNet

USCorUNet is the ultrasound deformation estimation model released with "Robotic Ultrasound Makes CBCT Alive". It estimates dense bidirectional deformation fields between adjacent ultrasound frames and is used for deformation-aware CBCT slice updating in robotic ultrasound-assisted workflows.

This Hugging Face repository stores model checkpoints only. The inference code and examples are released separately in the project code repository: github.com/ziyuan-li/robotic-us-cbct-updating.

Model Description

USCorUNet combines:

• a ResUNet-style context encoder-decoder operating on adjacent ultrasound frames and simple gradient cues;
• a shared-weight correlation encoder;
• local correlation volumes for efficient dense deformation estimation.

For an adjacent ultrasound pair (I0, I1), the model predicts:

• F01: forward flow from I0 to I1, defined on the I0 grid;
• F10: backward flow from I1 to I0, defined on the I1 grid.

These flows can be used to warp ultrasound frames directly or to propagate a corresponding CBCT slice across time.

Checkpoints

File	Model	Recommended use
uscorunet_base.pth	USCorUNet-Base	General ultrasound deformation estimation
uscorunet_probe_adapted.pth	USCorUNet-Probe-Adapted	Probe-induced deformation and CBCT updating demos
uscorunet_external_adapted.pth	USCorUNet-External-Adapted	Externally induced deformation

Usage

Download the checkpoints from the code repository with:

python download_checkpoints.py

or download a single file through the Hugging Face Hub:

from huggingface_hub import hf_hub_download

ckpt_path = hf_hub_download(
    repo_id="ziyuan-li/uscorunet",
    filename="uscorunet_base.pth",
)

The checkpoints are PyTorch state dictionaries intended to be loaded with the USCorUNet architecture provided in the accompanying code release.

Intended Use

These checkpoints are intended for non-commercial academic research on:

• ultrasound-based dense deformation estimation;
• robotic ultrasound;
• deformation-aware CBCT slice updating;
• ultrasound-guided image registration;
• intraoperative motion visualization.

Limitations

• The checkpoints are released for research use only.
• They are not approved for clinical, diagnostic, therapeutic, or other medical decision-making use.
• Performance may vary for imaging devices, acquisition protocols, anatomies, and motion regimes outside those studied in the paper.

Citation

If you use USCorUNet or these checkpoints, please cite:

@article{li2026robotic,
  title={Robotic Ultrasound Makes CBCT Alive},
  author={Li, Feng and Li, Ziyuan and Jiang, Zhongliang and Navab, Nassir and Bi, Yuan},
  journal={arXiv preprint arXiv:2603.10220},
  year={2026}
}

License

The model checkpoints are released under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. Commercial use requires permission from the authors.