Denoising diffusion probabilistic models for 3D medical image generation
Denoising diffusion probabilistic models for 3D medical image generation
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Author / Creator
Khader, Firas , Müller-Franzes, Gustav , Tayebi Arasteh, Soroosh , Han, Tianyu , Haarburger, Christoph , Schulze-Hagen, Maximilian , Schad, Philipp , Engelhardt, Sandy , Baeßler, Bettina , Foersch, Sebastian , Stegmaier, Johannes , Kuhl, Christiane , Nebelung, Sven , Kather, Jakob Nikolas and Truhn, Daniel
Publisher
London: Nature Publishing Group UK
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Language
English
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Publisher
London: Nature Publishing Group UK
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Contents
Recent advances in computer vision have shown promising results in image generation. Diffusion probabilistic models have generated realistic images from textual input, as demonstrated by DALL-E 2, Imagen, and Stable Diffusion. However, their use in medicine, where imaging data typically comprises three-dimensional volumes, has not been systematical...
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Full title
Denoising diffusion probabilistic models for 3D medical image generation
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TN_cdi_doaj_primary_oai_doaj_org_article_6d53a2241c8d4a1986fd4547c137f299
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6d53a2241c8d4a1986fd4547c137f299
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-023-34341-2
