diffusers and Awesome-Diffusion-Models-in-Medical-Imaging
B is a specialized research collection and application of the general-purpose diffusion model framework provided by A, making them complements where A serves as the foundational library that B's medical imaging implementations would build upon.
About diffusers
huggingface/diffusers
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
Provides modular, composable building blocks—including interchangeable noise schedulers, pretrained models, and end-to-end pipelines—enabling both quick inference and custom system design via the Hugging Face Model Hub. Emphasizes transparency and customizability over abstraction, allowing developers to inspect and modify individual diffusion components rather than treating them as black boxes.
About Awesome-Diffusion-Models-in-Medical-Imaging
amirhossein-kz/Awesome-Diffusion-Models-in-Medical-Imaging
Diffusion Models in Medical Imaging (Published in Medical Image Analysis Journal)
Curated repository organizing 500+ research papers on diffusion model applications across medical imaging tasks including segmentation, reconstruction, anomaly detection, and image restoration. Covers both foundational diffusion theory and domain-specific implementations integrated with frameworks like MONAI, spanning modalities from CT/MRI to 3D volumetric data and multimodal generation workflows.
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