A multimodal comparison of latent denoising diffusion probabilistic models and generative adversaria...
A multimodal comparison of latent denoising diffusion probabilistic models and generative adversarial networks for medical image synthesis
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London: Nature Publishing Group UK
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English
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London: Nature Publishing Group UK
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Although generative adversarial networks (GANs) can produce large datasets, their limited diversity and fidelity have been recently addressed by denoising diffusion probabilistic models, which have demonstrated superiority in natural image synthesis. In this study, we introduce Medfusion, a conditional latent DDPM designed for medical image generat...
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A multimodal comparison of latent denoising diffusion probabilistic models and generative adversarial networks for medical image synthesis
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TN_cdi_doaj_primary_oai_doaj_org_article_d86a20b08d6d4d73b3035c5f2ff0fb9f
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_d86a20b08d6d4d73b3035c5f2ff0fb9f
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2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-023-39278-0
