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---
license: mit
tags:
- medical-imaging
- diffusion
- CXR
- CTPA
- pulmonary-embolism
---
# Pulmonary Embolism Classifier 🧠
This is a classification model for pulmonary embolism classification from CTPA scans.
This classification model is used to aid a classification task to a diffusion model that generated 3D CTPA scans from a single 2D chest X-ray.
The input to the classification model are CTPA scan latents of size 32 x 32 x 64.
This model was trained on CTPAs that were downscaled from size 256 x 256 x 64 in a 2D slice-by-slice manner using a VAE.
This model is used in this git repository: https://github.com/NoaCahan/X-ray2CTPA
## 🧩 Model Details
- **Architecture:** 3D 121-DenseNet
- **Framework:** PyTorch
- **Input:** 3D volumes (64×32×32)
- **Output:** PE Binary Classification probability
## 🧠 How to Use
```python
from huggingface_hub import hf_hub_download
import torch
model_path = hf_hub_download("username/medical-diffusion-classifier", "classification_model_256.pth.tar")
model = torch.load(model_path, weights_only=False)
```
## 🧾 Citation
If you use this model, please cite our work:
Cahan, N. et al. X-ray2CTPA: leveraging diffusion models to enhance pulmonary embolism classification. npj Digit. Med. 8, 439 (2025). https://doi.org/10.1038/s41746-025-01857-y
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