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--- |
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license: mit |
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tags: |
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- medical-imaging |
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- diffusion |
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- CXR |
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- CTPA |
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- pulmonary-embolism |
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--- |
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# Pulmonary Embolism Classifier 🧠 |
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This is a classification model for pulmonary embolism classification from CTPA scans. |
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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. |
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The input to the classification model are CTPA scan latents of size 32 x 32 x 64. |
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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. |
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This model is used in this git repository: https://github.com/NoaCahan/X-ray2CTPA |
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## 🧩 Model Details |
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- **Architecture:** 3D 121-DenseNet |
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- **Framework:** PyTorch |
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- **Input:** 3D volumes (64×32×32) |
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- **Output:** PE Binary Classification probability |
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## 🧠 How to Use |
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```python |
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from huggingface_hub import hf_hub_download |
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import torch |
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model_path = hf_hub_download("username/medical-diffusion-classifier", "classification_model_256.pth.tar") |
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model = torch.load(model_path, weights_only=False) |
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``` |
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## 🧾 Citation |
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If you use this model, please cite our work: |
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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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