---
license: apache-2.0
library_name: pytorch
pipeline_tag: image-feature-extraction
tags:
- medical-imaging
- ct
- abdominal-ct
- radiology
- vision-transformer
- dinov2
- pytorch
- feature-extraction
---

# AbdomenNet

Public release assets for:

> **Acute abdomen on non-contrast CT: a foundation model for diagnosis, risk stratification and emergency triage**

## Files

- `teacher_checkpoint.pth`
  - released pretraining teacher checkpoint for AbdomenNet / AbCT

## Checkpoint format

`teacher_checkpoint.pth` is a backbone-style release checkpoint.

- top-level key: `teacher`
- no optimizer state
- no scheduler state
- no epoch / scaler / results payload

## Minimal loading example

```python
import torch

ckpt = torch.load("teacher_checkpoint.pth", map_location="cpu")
teacher_state = ckpt["teacher"]
backbone_state = {
    k.replace("backbone.", "", 1): v
    for k, v in teacher_state.items()
    if k.startswith("backbone.")
}
print(len(backbone_state))
```

## Code

Source code and training / fine-tuning details:

- https://anonymous.4open.science/r/Acute_abdomen/readme.md

## Notes

- This repository only hosts the released checkpoint.
- Large qualitative test-case bundles are not included in the default public release.