Sven Nebelung - RankMe

44 papers Journal 37Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Agentic retrieval-augmented reasoning reshapes collective reliability under model variability in radiology question answering. CoRR Mina Farajiamiri, Jeta Sopa, Saba Afza, Lisa Adams, Felix Barajas Ordonez, Tri-Thien Nguyen, Mahshad Lotfinia, Sebastian Wind, Keno K. Bressem, Sven Nebelung, Daniel Truhn, Soroosh Tayebi Arasteh
2026	J	`jnl`	Beyond benchmarks: Towards robust artificial intelligence bone segmentation in socio-technical systems. Expert Syst. Appl. Kunpeng Xie, Lennart Johannes Gruber, Martin Crampen, Yao Li, André Ferreira, Elias Tappeiner, Maxime Gillot, Jan Schepers, Jiangchang Xu, Tobias Pankert, Michel Beyer, Negar Shahamiri, Reinier ten Brink, Gauthier Dot, Charlotte Weschke, Niels van Nistelrooij, Pieter-Jan Verhelst, Yan Guo, Zhibin Xu, Jonas Bienzeisler, Ashkan Rashad, Tabea Flügge, Ross Cotton, Shankeeth Vinayahalingam, Robert R. Ilesan, Stefan Raith, Dennis Madsen, Constantin Seibold, Tong Xi, Stefaan Berge', Sven Nebelung, Oldrich Kodym, Osku Sundqvist, Florian M. Thieringer, Hans Lamecker, Antoine Coppens, Thomas Potrusil, Joep Kraeima, Max J. H. Witjes, Guomin Wu, Xiaojun Chen, Adriaan Lambrechts, Lucia H. S. Cevidanes, Stefan Zachow, Alexander Hermans, Daniel Truhn, Victor Alves, Jan Egger, Rainer Röhrig, Frank Hölzle, Behrus Hinrichs-Puladi
2026	J	`jnl`	Can Agents Distinguish Visually Hard-to-Separate Diseases in a Zero-Shot Setting? A Pilot Study. CoRR Zihao Zhao, Frederik Hauke, Juliana De Castilhos, Sven Nebelung, Daniel Truhn
2026	J	`jnl`	Differential privacy representation geometry for medical image analysis. CoRR Soroosh Tayebi Arasteh, Marziyeh Mohammadi, Sven Nebelung, Daniel Truhn
2026	J	`jnl`	Reducing manual workload in CT and MRI annotation with the Segment Anything Model 2. BMC Medical Imaging Leo Misera, Sven Nebelung, Zunamys I. Carrero, Keno K. Bressem, Marta Ligero, Jens-Peter Kühn, Ralf-Thorsten Hoffmann, Daniel Truhn, Jakob Nikolas Kather
2026	J	`jnl`	The role of self-supervised pretraining in differentially private medical image analysis. CoRR Soroosh Tayebi Arasteh, Mina Farajiamiri, Mahshad Lotfinia, Behrus Hinrichs-Puladi, Jonas Bienzeisler, Mohamed Alhaskir, Mirabela Rusu, Christiane Kuhl, Sven Nebelung, Daniel Truhn
2025	J	`jnl`	Effect of Reporting Mode and Clinical Experience on Radiologists' Gaze and Image Analysis Behavior in Chest Radiography. CoRR Mahta Khoobi, Marc Sebastian von der Stueck, Felix Barajas Ordonez, Anca-Maria Iancu, Eric Corban, Julia Nowak, Aleksandar Kargaliev, Valeria Perelygina, Anna-Sophie Schott, Daniel Pinto dos Santos, Christiane Kuhl, Daniel Truhn, Sven Nebelung, Robert Siepmann
2025	J	`jnl`	Hallucination Filtering in Radiology Vision-Language Models Using Discrete Semantic Entropy. CoRR Patrick Wienholt, Anne-Sophie Caselitz, Robert Siepmann, Philipp Bruners, Keno K. Bressem, Christiane Kuhl, Jakob Nikolas Kather, Sven Nebelung, Daniel Truhn
2025	J	`jnl`	Large Language Model-Based Uncertainty-Adjusted Label Extraction for Artificial Intelligence Model Development in Upper Extremity Radiography. CoRR Hanna Kreutzer, Anne-Sophie Caselitz, Thomas Dratsch, Daniel Pinto dos Santos, Christiane Kuhl, Daniel Truhn, Sven Nebelung
2025	J	`jnl`	MedicalPatchNet: A Patch-Based Self-Explainable AI Architecture for Chest X-ray Classification. CoRR Patrick Wienholt, Christiane Kuhl, Jakob Nikolas Kather, Sven Nebelung, Daniel Truhn
2025	J	`jnl`	Resolution scaling governs DINOv3 transfer performance in chest radiograph classification. CoRR Soroosh Tayebi Arasteh, Mina Shaigan, Christiane Kuhl, Jakob Nikolas Kather, Sven Nebelung, Daniel Truhn
2025	J	`jnl`	Three-dimensional end-to-end deep learning for brain MRI analysis. CoRR Radhika Juglan, Marta Ligero, Zunamys I. Carrero, Asier Rabasco Meneghetti, Tim Lenz, Leo Misera, Gregory Patrick Veldhuizen, Paul Kuntke, Hagen H. Kitzler, Sven Nebelung, Daniel Truhn, Jakob Nikolas Kather
2024	J	`jnl`	An Ordinal Regression Framework for a Deep Learning Based Severity Assessment for Chest Radiographs. CoRR Patrick Wienholt, Alexander Hermans, Firas Khader, Behrus Puladi, Bastian Leibe, Christiane Kuhl, Sven Nebelung, Daniel Truhn
2024	J	`jnl`	Compute-Efficient Medical Image Classification with Softmax-Free Transformers and Sequence Normalization. CoRR Firas Khader, Omar S. M. El Nahhas, Tianyu Han, Gustav Müller-Franzes, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn
2024	J	`jnl`	Encrypted federated learning for secure decentralized collaboration in cancer image analysis. Medical Image Anal. Daniel Truhn, Soroosh Tayebi Arasteh, Oliver Lester Saldanha, Gustav Müller-Franzes, Firas Khader, Philip Quirke, Nicholas P. West, Richard Gray, Gordon G. A. Hutchins, Jacqueline A. James, Maurice B. Loughrey, Manuel Salto-Tellez, Hermann Brenner, Alexander Brobeil, Tanwei Yuan, Jenny Chang-Claude, Michael Hoffmeister, Sebastian Foersch, Tianyu Han, Sebastian Keil, Maximilian Schulze-Hagen, Peter Isfort, Philipp Bruners, Georgios Kaissis, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather
2024	J	`jnl`	Medical Slice Transformer: Improved Diagnosis and Explainability on 3D Medical Images with DINOv2. CoRR Gustav Müller-Franzes, Firas Khader, Robert Siepmann, Tianyu Han, Jakob Nikolas Kather, Sven Nebelung, Daniel Truhn
2024	J	`jnl`	Medical large language models are susceptible to targeted misinformation attacks. npj Digit. Medicine Tianyu Han, Sven Nebelung, Firas Khader, Tianci Wang, Gustav Müller-Franzes, Christiane Kuhl, Sebastian Försch, Jens Kleesiek, Christoph Haarburger, Keno K. Bressem, Jakob Nikolas Kather, Daniel Truhn
2024	—	`conf`	On Instabilities of Unsupervised Denoising Diffusion Models in Magnetic Resonance Imaging Reconstruction. MICCAI (7) Tianyu Han, Sven Nebelung, Firas Khader, Jakob Nikolas Kather, Daniel Truhn
2024	J	`jnl`	On Instabilities of Unsupervised Denoising Diffusion Models in Magnetic Resonance Imaging Reconstruction. CoRR Tianyu Han, Sven Nebelung, Firas Khader, Jakob Nikolas Kather, Daniel Truhn
2024	J	`jnl`	RadioRAG: Factual Large Language Models for Enhanced Diagnostics in Radiology Using Dynamic Retrieval Augmented Generation. CoRR Soroosh Tayebi Arasteh, Mahshad Lotfinia, Keno K. Bressem, Robert Siepmann, Dyke Ferber, Christiane Kuhl, Jakob Nikolas Kather, Sven Nebelung, Daniel Truhn
2023	—	`conf`	Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers. MLMI@MICCAI (2) Firas Khader, Jakob Nikolas Kather, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn
2023	J	`jnl`	Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers. CoRR Firas Khader, Jakob Nikolas Kather, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn
2023	J	`jnl`	Empowering Clinicians and Democratizing Data Science: Large Language Models Automate Machine Learning for Clinical Studies. CoRR Soroosh Tayebi Arasteh, Tianyu Han, Mahshad Lotfinia, Christiane Kuhl, Jakob Nikolas Kather, Daniel Truhn, Sven Nebelung
2023	J	`jnl`	Enhancing Network Initialization for Medical AI Models Using Large-Scale, Unlabeled Natural Images. CoRR Soroosh Tayebi Arasteh, Leo Misera, Jakob Nikolas Kather, Daniel Truhn, Sven Nebelung
2023	J	`jnl`	Fibroglandular Tissue Segmentation in Breast MRI using Vision Transformers - A multi-institutional evaluation. CoRR Gustav Müller-Franzes, Fritz Müller-Franzes, Luisa Huck, Vanessa Raaff, Eva Kemmer, Firas Khader, Soroosh Tayebi Arasteh, Teresa Nolte, Jakob Nikolas Kather, Sven Nebelung, Christiane Kuhl, Daniel Truhn
2023	J	`jnl`	Medical Foundation Models are Susceptible to Targeted Misinformation Attacks. CoRR Tianyu Han, Sven Nebelung, Firas Khader, Tianci Wang, Gustav Mueller-Franzes, Christiane Kuhl, Sebastian Försch, Jens Kleesiek, Christoph Haarburger, Keno K. Bressem, Jakob Nikolas Kather, Daniel Truhn
2023	J	`jnl`	Mind the Gap: Federated Learning Broadens Domain Generalization in Diagnostic AI Models. CoRR Soroosh Tayebi Arasteh, Christiane Kuhl, Marwin-Jonathan Saehn, Peter Isfort, Daniel Truhn, Sven Nebelung
2023	—	`conf`	Multi-View Abnormality Detection in Clinical Knee MRI Studies Using Transformers. ISBI Firas Khader, Johannes Stegmaier, Sven Nebelung, Daniel Truhn
2023	J	`jnl`	Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacy. CoRR Soroosh Tayebi Arasteh, Mahshad Lotfinia, Teresa Nolte, Marwin Saehn, Peter Isfort, Christiane Kuhl, Sven Nebelung, Georgios Kaissis, Daniel Truhn
2023	J	`jnl`	Private, fair and accurate: Training large-scale, privacy-preserving AI models in radiology. CoRR Soroosh Tayebi Arasteh, Alexander Ziller, Christiane Kuhl, Marcus R. Makowski, Sven Nebelung, Rickmer Braren, Daniel Rueckert, Daniel Truhn, Georgios Kaissis
2023	J	`jnl`	Reconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative Pretraining. CoRR Tianyu Han, Laura Zigutyte, Luisa Huck, Marc Huppertz, Robert Siepmann, Yossi Gandelsman, Christian Blüthgen, Firas Khader, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn
2023	J	`jnl`	Transformers for CT Reconstruction From Monoplanar and Biplanar Radiographs. CoRR Firas Khader, Gustav Müller-Franzes, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn
2023	—	`conf`	Transformers for CT Reconstruction from Monoplanar and Biplanar Radiographs. SASHIMI@MICCAI Firas Khader, Gustav Müller-Franzes, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn
2023	—	`conf`	Vector-Quantized Latent Flows for Medical Image Synthesis and Out-Of-Distribution Detection. ISBI Firas Khader, Gustav Müller-Franzes, Soroosh Tayebi Arasteh, Tianyu Han, Jakob Nikolas Kather, Johannes Stegmaier, Sven Nebelung, Daniel Truhn
2022	J	`jnl`	Collaborative Training of Medical Artificial Intelligence Models with non-uniform Labels. CoRR Soroosh Tayebi Arasteh, Peter Isfort, Marwin Saehn, Gustav Mueller-Franzes, Firas Khader, Jakob Nikolas Kather, Christiane Kuhl, Sven Nebelung, Daniel Truhn
2022	J	`jnl`	Diffusion Probabilistic Models beat GANs on Medical Images. CoRR Gustav Müller-Franzes, Jan Moritz Niehues, Firas Khader, Soroosh Tayebi Arasteh, Christoph Haarburger, Christiane Kuhl, Tianci Wang, Tianyu Han, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn
2022	J	`jnl`	Image prediction of disease progression for osteoarthritis by style-based manifold extrapolation. Nat. Mac. Intell. Tianyu Han, Jakob Nikolas Kather, Federico Pedersoli, Markus Zimmermann, Sebastian Keil, Maximilian Schulze-Hagen, Marc Terwoelbeck, Peter Isfort, Christoph Haarburger, Fabian Kiessling, Christiane Kuhl, Volkmar Schulz, Sven Nebelung, Daniel Truhn
2022	J	`jnl`	Medical Diagnosis with Large Scale Multimodal Transformers: Leveraging Diverse Data for More Accurate Diagnosis. CoRR Firas Khader, Gustav Mueller-Franzes, Tianci Wang, Tianyu Han, Soroosh Tayebi Arasteh, Christoph Haarburger, Johannes Stegmaier, Keno K. Bressem, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn
2022	J	`jnl`	Medical Diffusion - Denoising Diffusion Probabilistic Models for 3D Medical Image Generation. CoRR 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
2022	—	`conf`	Monoplanar CT Reconstruction with GANs. IPTA Justus Schock, Yu-Chia Lan, Daniel Truhn, Marcin Kopaczka, Stefan Conrad, Sven Nebelung, Dorit Merhof
2021	J	`jnl`	A Novel Combined Level Set Model for Carpus Segmentation from Magnetic Resonance Images with Prior Knowledge aligned in Polar Coordinate System. Comput. Methods Programs Biomed. Jianzhang Li, Sven Nebelung, Justus Schock, Björn Rath, Markus Tingart, Yu Liu, Nad Siroros, Jörg Eschweiler
2021	J	`jnl`	Predicting Osteoarthritis Progression in Radiographs via Unsupervised Representation Learning. CoRR Tianyu Han, Jakob Nikolas Kather, Federico Pedersoli, Markus Zimmermann, Sebastian Keil, Maximilian Schulze-Hagen, Marc Terwoelbeck, Peter Isfort, Christoph Haarburger, Fabian Kiessling, Volkmar Schulz, Christiane Kuhl, Sven Nebelung, Daniel Truhn
2020	—	`conf`	A Method for Semantic Knee Bone and Cartilage Segmentation with Deep 3D Shape Fitting Using Data from the Osteoarthritis Initiative. ShapeMI@MICCAI Justus Schock, Marcin Kopaczka, Benjamin Agthe, Jie Huang, Paul Kruse, Daniel Truhn, Stefan Conrad, Gerald Antoch, Christiane Kuhl, Sven Nebelung, Dorit Merhof
2020	J	`jnl`	Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization. CoRR Tianyu Han, Sven Nebelung, Federico Pedersoli, Markus Zimmermann, Maximilian Schulze-Hagen, Michael Ho, Christoph Haarburger, Fabian Kiessling, Christiane Kuhl, Volkmar Schulz, Daniel Truhn