Overview
This repository hosts the TraumaNet DINOv3 ViT-Large backbone checkpoint used for downstream multi-task abdominal trauma detection on contrast-enhanced CT.
The checkpoint stored here is the pretrained backbone initialization used before downstream TraumaNet fine-tuning.
Project Links
- Hosted checkpoint repository: https://huggingface.co/frankzhang/Traumanet_ViT_DINOv3
- Source code repository: https://github.com/FrankZhangRp/TraumaNet
File
traumanet_dinov3_pretrain_backbone.pth
Intended Use
This checkpoint is intended to be used as the dinov3_pretrained initialization file in the TraumaNet downstream pipeline.
It is not a standalone end-to-end prediction package. To reproduce the downstream task, users should combine this checkpoint with the TraumaNet source code repository.
Expected Downstream Setting
The downstream TraumaNet pipeline uses:
- contrast-enhanced abdominal CT
- HU soft-tissue windowing
- window center =
40 - window width =
350
- window center =
- depth standardization to
240 - 2.5D grouping with 3 adjacent slices per group
- DINOv3 ViT-Large backbone loading from this checkpoint
Limitations
- This repository provides the backbone checkpoint only.
- It does not provide the trauma dataset.
- It does not provide train / validation / test labels.
- It does not provide external evaluation data.
- It does not provide a standalone inference API.
Acknowledgments
We acknowledge the upstream DINOv3 project:
We also acknowledge the RSNA 2023 Abdominal Trauma Detection AI Challenge and its public challenge setting:
- https://www.rsna.org/rsnai/ai-image-challenge/abdominal-trauma-detection-ai-challenge
- https://www.kaggle.com/c/rsna-2023-abdominal-trauma-detection
License
This checkpoint repository is released under the MIT License.