Initial commit for densenet-TTE model

.gitattributes

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+*.pth filter=lfs diff=lfs merge=lfs -text

README.md

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

config.json

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+{
+  "model_type": "model_3d",
+  "model_name": "densenet",
+  "pretrain_type": "time-to-event",
+  "num_class": 8192
+}

densenet_tte.pth

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