anonymous

Polish model card with badges and cleaner layout

5a1bb1c 3 months ago

2.73 kB

license: mit
library_name: pytorch
tags:
  - medical-imaging
  - ct
  - trauma-detection
  - abdominal-trauma
  - dinov3
  - vision-transformer
  - pytorch
pipeline_tag: image-classification

TraumaNet DINOv3 ViT-Large Backbone

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
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:

https://github.com/facebookresearch/dinov3

We also acknowledge the RSNA 2023 Abdominal Trauma Detection AI Challenge and its public challenge setting:

License

This checkpoint repository is released under the MIT License.