latent_diffusion
medical-imaging
diffusion
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@@ -32,6 +32,15 @@ By using this model, you are agreeing to the [terms and conditions](https://docs
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  Training and inference code are in:
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  [https://github.com/NVIDIA-Medtech/NV-Generate-CTMR/tree/main](https://github.com/NVIDIA-Medtech/NV-Generate-CTMR/tree/main).
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  ## References:
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  [1] Zhao, Can, et al. "Maisi-v2: Accelerated 3d high-resolution medical image synthesis with rectified flow and region-specific contrastive loss." arXiv preprint arXiv:2508.05772 (2025).
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  Training and inference code are in:
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  [https://github.com/NVIDIA-Medtech/NV-Generate-CTMR/tree/main](https://github.com/NVIDIA-Medtech/NV-Generate-CTMR/tree/main).
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+ ## Download
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+ For example, to download the VAE, you can run:
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+ ```
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+ pip install -U huggingface_hub
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+ huggingface-cli download nvidia/NV-Generate-CT \
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+ models/autoencoder_v1.pt \
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+ --local-dir ./models
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+ ```
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+
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  ## References:
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  [1] Zhao, Can, et al. "Maisi-v2: Accelerated 3d high-resolution medical image synthesis with rectified flow and region-specific contrastive loss." arXiv preprint arXiv:2508.05772 (2025).
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