Search Results for author: Sebastian Foersch

Found 4 papers, 2 papers with code

Unconditional Latent Diffusion Models Memorize Patient Imaging Data: Implications for Openly Sharing Synthetic Data

no code implementations1 Feb 2024 Salman Ul Hassan Dar, Marvin Seyfarth, Jannik Kahmann, Isabelle Ayx, Theano Papavassiliu, Stefan O. Schoenberg, Norbert Frey, Bettina Baeßler, Sebastian Foersch, Daniel Truhn, Jakob Nikolas Kather, Sandy Engelhardt

Collectively, our results emphasize the importance of carefully training generative models on private medical imaging datasets, and examining the synthetic data to ensure patient privacy before sharing it for medical research and applications.

Data Augmentation Image Generation +2

Medical Diffusion: Denoising Diffusion Probabilistic Models for 3D Medical Image Generation

1 code implementation7 Nov 2022 Firas Khader, Gustav Mueller-Franzes, Soroosh Tayebi Arasteh, Tianyu Han, Christoph Haarburger, Maximilian Schulze-Hagen, Philipp Schad, Sandy Engelhardt, Bettina Baessler, Sebastian Foersch, Johannes Stegmaier, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn

Furthermore, we demonstrate that synthetic images can be used in a self-supervised pre-training and improve the performance of breast segmentation models when data is scarce (dice score 0. 91 vs. 0. 95 without vs. with synthetic data).

Computed Tomography (CT) Denoising +3

Cannot find the paper you are looking for? You can Submit a new open access paper.