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Usynin, Dmitrii;Ziller, Alexander;Makowski, Marcus;Braren, Rickmer;Rueckert, Daniel;Glocker, Ben;Kaissis, Georgios;Passerat-Palmbach, Jonathan.Adversarial interference and its mitigations in privacy-preserving collaborative machine learning.Nature Machine Intelligence.2021.3.9.749-758

Knolle, Moritz;Kaissis, Georgios;Jungmann, Friederike;Ziegelmayer, Sebastian;Sasse, Daniel;Makowski, Marcus;Rueckert, Daniel;Braren, Rickmer.Efficient, high-performance semantic segmentation using multi-scale feature extraction.PLOS ONE.2021.16.8.e0255397

Harder, Felix N.;Jungmann, Friederike;Kaissis, Georgios A.;Lohöfer, Fabian K.;Ziegelmayer, Sebastian;Havel, Daniel;Quante, Michael;Reichert, Maximillian;Schmid, Roland M.;Demir, Ihsan Ekin;Friess, Helmut;Wildgruber, Moritz;Siveke, Jens;Muckenhuber, Alexander;Steiger, Katja;Weichert, Wilko;Rauscher, Isabel;Eiber, Matthias;Makowski, Marcus R.;Braren, Rickmer F..[18F]FDG PET/MRI enables early chemotherapy response prediction in pancreatic ductal adenocarcinoma.EJNMMI Research.2021.11.1

Ziller, Alexander;Usynin, Dmitrii;Braren, Rickmer;Makowski, Marcus;Rueckert, Daniel;Kaissis, Georgios.Medical imaging deep learning with differential privacy.Scientific Reports.2021.11.1

Kaissis, Georgios;Ziller, Alexander;Passerat-Palmbach, Jonathan;Ryffel, Théo;Usynin, Dmitrii;Trask, Andrew;Lima, Ionésio, Jr;Mancuso, Jason;Jungmann, Friederike;Steinborn, Marc-Matthias;Saleh, Andreas;Makowski, Marcus;Rueckert, Daniel;Braren, Rickmer.End-to-end privacy preserving deep learning on multi-institutional medical imaging.Nature Machine Intelligence.2021.3.6.473-484

Meissen, Felix;Kaissis, Georgios;Rueckert, Daniel.Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI.2021

Paetzold, Johannes C.;McGinnis, Julian;Shit, Suprosanna;Ezhov, Ivan;Büschl, Paul;Prabhakar, Chinmay;Todorov, Mihail I.;Sekuboyina, Anjany;Kaissis, Georgios;Ertürk, Ali;Günnemann, Stephan;Menze, Bjoern H..Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience (VesselGraph).2021

Ziller, Alexander;Usynin, Dmitrii;Knolle, Moritz;Prakash, Kritika;Trask, Andrew;Braren, Rickmer;Makowski, Marcus;Rueckert, Daniel;Kaissis, Georgios.Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation.2021

Knolle, Moritz;Ziller, Alexander;Usynin, Dmitrii;Braren, Rickmer;Makowski, Marcus R.;Rueckert, Daniel;Kaissis, Georgios.Differentially private training of neural networks with Langevin dynamics for calibrated predictive uncertainty.2021