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--- |
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license: apache-2.0 |
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tags: |
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- pytorch |
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- unet |
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- chest-ct |
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- survival-analysis |
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- time-to-event |
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- model-3d |
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model-index: |
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- name: DenseNet-TTE |
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results: [] |
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--- |
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# DenseNet Checkpoint |
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This is a PyTorch Lightning `.ckpt` checkpoint for a DenseNet model trained on chest CT images with TTE objective. |
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## Usage |
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A quickstart script is below. |
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```python |
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import torch |
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from src.networks import DenseNet121 |
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model = DenseNet121(spatial_dims=3, in_channels=1, out_channels=2).to(device) |
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state_dict = torch.load( |
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loadmodel_path, map_location=f"cuda:{torch.cuda.current_device()}" |
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) |
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model.load_state_dict(state_dict) |
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``` |
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For detailed instructions please follow the [README in Github repo](https://github.com/som-shahlab/tte-pretraining/tree/main?tab=readme-ov-file#evaluation). |
