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2020 – today
- 2024
- [j3]Daniel Truhn
, Soroosh Tayebi Arasteh
Encrypted federated learning for secure decentralized collaboration in cancer image analysis. Medical Image Anal. 92: 103059 (2024) - [c7]Tianyu Han, Sven Nebelung, Firas Khader, Jakob Nikolas Kather, Daniel Truhn:
On Instabilities of Unsupervised Denoising Diffusion Models in Magnetic Resonance Imaging Reconstruction. MICCAI (7) 2024: 509-517 - [i20]Patrick Wienholt
An Ordinal Regression Framework for a Deep Learning Based Severity Assessment for Chest Radiographs. CoRR abs/2402.05685 (2024) - [i19]Firas Khader, Omar S. M. El Nahhas, Tianyu Han, Gustav Müller-Franzes, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn:
Compute-Efficient Medical Image Classification with Softmax-Free Transformers and Sequence Normalization. CoRR abs/2406.01314 (2024) - [i18]Tianyu Han, Sven Nebelung, Firas Khader, Jakob Nikolas Kather, Daniel Truhn:
On Instabilities of Unsupervised Denoising Diffusion Models in Magnetic Resonance Imaging Reconstruction. CoRR abs/2406.16983 (2024) - [i17]Soroosh Tayebi Arasteh, Mahshad Lotfinia, Keno K. Bressem, Robert Siepmann, Dyke Ferber, Christiane Kuhl, Jakob Nikolas Kather, Sven Nebelung, Daniel Truhn:
RadioRAG: Factual Large Language Models for Enhanced Diagnostics in Radiology Using Dynamic Retrieval Augmented Generation. CoRR abs/2407.15621 (2024) - 2023
- [c6]Firas Khader, Gustav Müller-Franzes, Soroosh Tayebi Arasteh
Vector-Quantized Latent Flows for Medical Image Synthesis and Out-Of-Distribution Detection. ISBI 2023: 1-5 - [c5]Firas Khader, Johannes Stegmaier, Sven Nebelung, Daniel Truhn:
Multi-View Abnormality Detection in Clinical Knee MRI Studies Using Transformers. ISBI 2023: 1-4 - [c4]Firas Khader, Gustav Müller-Franzes, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn:
Transformers for CT Reconstruction from Monoplanar and Biplanar Radiographs. SASHIMI@MICCAI 2023: 1-10 - [c3]Firas Khader, Jakob Nikolas Kather, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn:
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers. MLMI@MICCAI (2) 2023: 417-426 - [i16]Soroosh Tayebi Arasteh, Alexander Ziller, Christiane Kuhl, Marcus R. Makowski, Sven Nebelung, Rickmer Braren, Daniel Rueckert, Daniel Truhn, Georgios Kaissis:
Private, fair and accurate: Training large-scale, privacy-preserving AI models in radiology. CoRR abs/2302.01622 (2023) - [i15]Gustav Müller-Franzes, Fritz Müller-Franzes, Luisa Huck, Vanessa Raaff, Eva Kemmer, Firas Khader, Soroosh Tayebi Arasteh
Fibroglandular Tissue Segmentation in Breast MRI using Vision Transformers - A multi-institutional evaluation. CoRR abs/2304.08972 (2023) - [i14]Firas Khader, Jakob Nikolas Kather, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn:
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers. CoRR abs/2305.06963 (2023) - [i13]Firas Khader, Gustav Müller-Franzes, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn:
Transformers for CT Reconstruction From Monoplanar and Biplanar Radiographs. CoRR abs/2305.06965 (2023) - [i12]Soroosh Tayebi Arasteh, Mahshad Lotfinia, Teresa Nolte, Marwin Saehn, Peter Isfort, Christiane Kuhl, Sven Nebelung, Georgios Kaissis, Daniel Truhn:
Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacy. CoRR abs/2306.06503 (2023) - [i11]Soroosh Tayebi Arasteh, Leo Misera, Jakob Nikolas Kather, Daniel Truhn, Sven Nebelung:
Enhancing Network Initialization for Medical AI Models Using Large-Scale, Unlabeled Natural Images. CoRR abs/2308.07688 (2023) - [i10]Soroosh Tayebi Arasteh
Empowering Clinicians and Democratizing Data Science: Large Language Models Automate Machine Learning for Clinical Studies. CoRR abs/2308.14120 (2023) - [i9]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:
Medical Foundation Models are Susceptible to Targeted Misinformation Attacks. CoRR abs/2309.17007 (2023) - [i8]Tianyu Han, Laura Zigutyte, Luisa Huck, Marc Huppertz, Robert Siepmann
Reconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative Pretraining. CoRR abs/2309.17123 (2023) - [i7]Soroosh Tayebi Arasteh
Mind the Gap: Federated Learning Broadens Domain Generalization in Diagnostic AI Models. CoRR abs/2310.00757 (2023) - 2022
- [j2]Tianyu Han
Image prediction of disease progression for osteoarthritis by style-based manifold extrapolation. Nat. Mac. Intell. 4(11): 1029-1039 (2022) - [c2]Justus Schock, Yu-Chia Lan
Monoplanar CT Reconstruction with GANs. IPTA 2022: 1-6 - [i6]Firas Khader, Gustav Mueller-Franzes, Soroosh Tayebi Arasteh
Medical Diffusion - Denoising Diffusion Probabilistic Models for 3D Medical Image Generation. CoRR abs/2211.03364 (2022) - [i5]Soroosh Tayebi Arasteh
Collaborative Training of Medical Artificial Intelligence Models with non-uniform Labels. CoRR abs/2211.13606 (2022) - [i4]Gustav Müller-Franzes, Jan Moritz Niehues, Firas Khader, Soroosh Tayebi Arasteh
Diffusion Probabilistic Models beat GANs on Medical Images. CoRR abs/2212.07501 (2022) - [i3]Firas Khader, Gustav Mueller-Franzes, Tianci Wang, Tianyu Han, Soroosh Tayebi Arasteh
Medical Diagnosis with Large Scale Multimodal Transformers: Leveraging Diverse Data for More Accurate Diagnosis. CoRR abs/2212.09162 (2022) - 2021
- [j1]Jianzhang Li, Sven Nebelung
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. 208: 106245 (2021) - [i2]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:
Predicting Osteoarthritis Progression in Radiographs via Unsupervised Representation Learning. CoRR abs/2111.11439 (2021) - 2020
- [c1]Justus Schock, Marcin Kopaczka, Benjamin Agthe, Jie Huang, Paul Kruse, Daniel Truhn, Stefan Conrad, Gerald Antoch, Christiane Kuhl, Sven Nebelung, Dorit Merhof:
A Method for Semantic Knee Bone and Cartilage Segmentation with Deep 3D Shape Fitting Using Data from the Osteoarthritis Initiative. ShapeMI@MICCAI 2020: 85-94 - [i1]Tianyu Han, Sven Nebelung, Federico Pedersoli, Markus Zimmermann, Maximilian Schulze-Hagen, Michael Ho, Christoph Haarburger, Fabian Kiessling, Christiane Kuhl, Volkmar Schulz, Daniel Truhn:
Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization. CoRR abs/2011.13011 (2020)
Coauthor Index
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last updated on 2024-10-11 17:28 CEST by the dblp team
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