Instructions to use mlii0117/sd1.5_MPECT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mlii0117/sd1.5_MPECT with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mlii0117/sd1.5_MPECT", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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**Model Type**: Fine-tuned `Stable Diffusion v1.5` for medical image-to-image translation
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**Paper**: _Text-Conditioned Latent Diffusion Model for Synthesis of Contrast-Enhanced CT from Non-Contrast CT_
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**Conference**: AAPM 2025 (Oral)
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**Authors**: Mingjie Li, Yizheng Chen, Lei Xing, Michael Gensheimer
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**Affiliation**:
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**Model Type**: Fine-tuned `Stable Diffusion v1.5` for medical image-to-image translation
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**Paper**: _Text-Conditioned Latent Diffusion Model for Synthesis of Contrast-Enhanced CT from Non-Contrast CT_
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**Conference**: AAPM 2025 (Oral)
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**Authors**: Mingjie Li, Yizheng Chen, Lei Xing, Michael F. Gensheimer
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**Affiliation**: Department of Radiation Oncology - Medical Physics Divison, Stanford University
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