latent_diffusion
medical-imaging
diffusion
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@@ -3,6 +3,10 @@ license: other
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  license_name: nvidia-open-model-license-agreement
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  license_link: >-
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  https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/
 
 
 
 
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  ---
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  # Model Overview
@@ -29,14 +33,17 @@ 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] Rombach, Robin, et al. "High-resolution image synthesis with latent diffusion models." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022. https://openaccess.thecvf.com/content/CVPR2022/papers/Rombach_High-Resolution_Image_Synthesis_With_Latent_Diffusion_Models_CVPR_2022_paper.pdf
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- [2] Lvmin Zhang, Anyi Rao, Maneesh Agrawala; “Adding Conditional Control to Text-to-Image Diffusion Models. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 3836-3847.
 
 
 
 
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  https://openaccess.thecvf.com/content/ICCV2023/papers/Zhang_Adding_Conditional_Control_to_Text-to-Image_Diffusion_Models_ICCV_2023_paper.pdf
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- [3] Guo, Pengfei, et al. "Maisi: Medical ai for synthetic imaging." 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2025.
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- [4] 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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  ## Model Architecture:
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  **Architecture Type:** Convolutional Neural Network (CNN) <br>
 
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  license_name: nvidia-open-model-license-agreement
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  license_link: >-
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  https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/
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+ tags:
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+ - medical-imaging
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+ - diffusion
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+ arxiv: 2409.11169
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  ---
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  # Model Overview
 
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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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+ [2] Guo, Pengfei, et al. "Maisi: Medical ai for synthetic imaging." 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2025.
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+
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+ [3] Rombach, Robin, et al. "High-resolution image synthesis with latent diffusion models." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022. https://openaccess.thecvf.com/content/CVPR2022/papers/Rombach_High-Resolution_Image_Synthesis_With_Latent_Diffusion_Models_CVPR_2022_paper.pdf
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+
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+ [4] Lvmin Zhang, Anyi Rao, Maneesh Agrawala; “Adding Conditional Control to Text-to-Image Diffusion Models.” Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 3836-3847.
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  https://openaccess.thecvf.com/content/ICCV2023/papers/Zhang_Adding_Conditional_Control_to_Text-to-Image_Diffusion_Models_ICCV_2023_paper.pdf
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  ## Model Architecture:
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  **Architecture Type:** Convolutional Neural Network (CNN) <br>