Retinal OCT Synthesis with Denoising Diffusion Probabilistic Models for Layer Segmentation

Modern biomedical image analysis using deep learning often encounters the challenge of limited annotated data. To overcome this issue, deep generative models can be employed to synthesize realistic biomedical images.

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Yuli Wu, Weidong He, Dennis Eschweiler, Zixin Fan, Peter Walter, Shengli Mi, Ningxin Dou, Johannes Stegmaier (2024). Dataset: Retinal OCT Synthesis with Denoising Diffusion Probabilistic Models for Layer Segmentation. https://doi.org/10.57702/sal9pso4

DOI retrieved: December 16, 2024

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2311.05479
Author Yuli Wu
More Authors
Weidong He
Dennis Eschweiler
Zixin Fan
Peter Walter
Shengli Mi
Ningxin Dou
Johannes Stegmaier
Homepage https://doi.org/10.1007/978-3-030-85960-1_34