4 citations · 6 across the 4 of their papers we have counts for
3 papers · 1 filter
Ordinal Diffusion Models for Color Fundus Images
Gustav Schmidt, Philipp Berens, Sarah Müller
Generative image models such as diffusion models can improve performance on clinically relevant tasks by offering deep learning models supplementary training data. However, most co…
Disentangling representations of retinal images with generative models
Sarah Müller, Lisa M. Koch, Hendrik P. A. Lensch +1
Retinal fundus images play a crucial role in the early detection of eye diseases. However, the impact of technical factors on these images can pose challenges for reliable AI appli…
Generating Realistic Counterfactuals for Retinal Fundus and OCT Images using Diffusion Models
Indu Ilanchezian, Valentyn Boreiko, Laura Kühlewein +5
Counterfactual reasoning is often used in clinical settings to explain decisions or weigh alternatives. Therefore, for imaging based specialties such as ophthalmology, it would be…