23 citations · 39 across the 8 of their papers we have counts for
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eess.IV2023★ 6 cited
Retinal OCT Synthesis with Denoising Diffusion Probabilistic Models for Layer Segmentation
Yuli Wu, Weidong He, Dennis Eschweiler +5
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 syn…
eess.IV2023★ 4 cited
Denoising Diffusion Probabilistic Models for Generation of Realistic Fully-Annotated Microscopy Image Data Sets
Dennis Eschweiler, Rüveyda Yilmaz, Matisse Baumann +5
Recent advances in computer vision have led to significant progress in the generation of realistic image data, with denoising diffusion probabilistic models proving to be a particu…