Medical Diffusion: Denoising Diffusion Probabilistic Models for 3D Medical Image Generation
Abstract
Recent advances in computer vision have shown promising results in image generation. Diffusion probabilistic models in particular have generated realistic images from textual input, as demonstrated by DALL-E 2, Imagen and Stable Diffusion. However, their use in medicine, where image data typically comprises three-dimensional volumes, has not been systematically evaluated. Synthetic images may play a crucial role in privacy preserving artificial intelligence and can also be used to augment small datasets. Here we show that diffusion probabilistic models can synthesize high quality medical imaging data, which we show for Magnetic Resonance Images (MRI) and Computed Tomography (CT) images. We provide quantitative measurements of their performance through a reader study with two medical experts who rated the quality of the synthesized images in three categories: Realistic image appearance, anatomical correctness and consistency between slices. Furthermore, we demonstrate that synthetic images can be used in a self-supervised pre-training and improve the performance of breast segmentation models when data is scarce (dice score 0.91 vs. 0.95 without vs. with synthetic data). The code is publicly available on GitHub: https://github.com/FirasGit/medicaldiffusion.
Authors 14
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Affiliation as printed
Department of Diagnostic and Interventional Radiology , University Hospital Aachen , Germany
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Affiliation as printed
Ocumeda AG , Germany
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Affiliation as printed
Department of Diagnostic and Interventional Radiology , University Hospital Aachen , Germany
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Affiliation as printed
Department of Diagnostic and Interventional Radiology , University Hospital Aachen , Germany
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University Hospital Heidelberg
Affiliation as printed
Artificial Intelligence in Cardiovascular Medicine , University Hospital Heidelberg
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Johannes Gutenberg University Mainz · University Medical Center of the Johannes Gutenberg University Mainz
Affiliation as printed
Medical Clinic I , University of Mainz , Mainz , Germany
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Affiliation as printed
Institute of Imaging and Computer Vision , RWTH Aachen , Germany
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Affiliation as printed
Department of Diagnostic and Interventional Radiology , University Hospital Aachen , Germany
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Affiliation as printed
Department of Diagnostic and Interventional Radiology , University Hospital Aachen , Germany
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Affiliation as printed
Department of Diagnostic and Interventional Radiology , University Hospital Aachen , Germany
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