A multimodal comparison of latent denoising diffusion probabilistic models and generative adversarial networks for medical image synthesis G Müller-Franzes, JM Niehues, F Khader, ST Arasteh, C Haarburger, ... Scientific Reports 13 (1), 12098, 2023 | 161 | 2023 |
Denoising diffusion probabilistic models for 3D medical image generation F Khader, G Müller-Franzes, S Tayebi Arasteh, T Han, C Haarburger, ... Scientific Reports 13 (1), 7303, 2023 | 136 | 2023 |
Radiomics feature reproducibility under inter-rater variability in segmentations of CT images C Haarburger, G Müller-Franzes, L Weninger, C Kuhl, D Truhn, D Merhof Scientific reports 10 (1), 12688, 2020 | 106 | 2020 |
Medical diffusion: denoising diffusion probabilistic models for 3D medical image generation F Khader, G Mueller-Franzes, ST Arasteh, T Han, C Haarburger, ... arXiv preprint arXiv:2211.03364, 2022 | 62 | 2022 |
Using machine learning to reduce the need for contrast agents in breast MRI through synthetic images G Müller-Franzes, L Huck, S Tayebi Arasteh, F Khader, T Han, V Schulz, ... Radiology 307 (3), e222211, 2023 | 42 | 2023 |
Encrypted federated learning for secure decentralized collaboration in cancer image analysis D Truhn, ST Arasteh, OL Saldanha, G Müller-Franzes, F Khader, P Quirke, ... Medical image analysis 92, 103059, 2024 | 40 | 2024 |
Extracting structured information from unstructured histopathology reports using generative pre‐trained transformer 4 (GPT‐4) D Truhn, CML Loeffler, G Müller‐Franzes, S Nebelung, KJ Hewitt, ... The Journal of Pathology 262 (3), 310-319, 2024 | 34 | 2024 |
Multimodal deep learning for integrating chest radiographs and clinical parameters: a case for transformers F Khader, G Müller-Franzes, T Wang, T Han, S Tayebi Arasteh, ... Radiology 309 (1), e230806, 2023 | 32 | 2023 |
Artificial intelligence for clinical interpretation of bedside chest radiographs F Khader, T Han, G Müller-Franzes, L Huck, P Schad, S Keil, E Barzakova, ... Radiology 307 (1), e220510, 2022 | 24 | 2022 |
Medical transformer for multimodal survival prediction in intensive care: integration of imaging and non-imaging data F Khader, JN Kather, G Müller-Franzes, T Wang, T Han, S Tayebi Arasteh, ... Scientific Reports 13 (1), 10666, 2023 | 21 | 2023 |
Collaborative training of medical artificial intelligence models with non-uniform labels S Tayebi Arasteh, P Isfort, M Saehn, G Mueller-Franzes, F Khader, ... Scientific Reports 13 (1), 6046, 2023 | 20 | 2023 |
In-context learning enables multimodal large language models to classify cancer pathology images D Ferber, G Wölflein, IC Wiest, M Ligero, S Sainath, N Ghaffari Laleh, ... Nature Communications 15 (1), 10104, 2024 | 16 | 2024 |
Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report EMC Huijben, ML Terpstra, S Pai, A Thummerer, P Koopmans, M Afonso, ... Medical image analysis 97, 103276, 2024 | 14 | 2024 |
Novel machine learning algorithm can identify patients at risk of poor overall survival following curative resection for colorectal liver metastases I Amygdalos, G Müller‐Franzes, J Bednarsch, Z Czigany, TF Ulmer, ... Journal of Hepato‐Biliary‐Pancreatic Sciences 30 (5), 602-614, 2023 | 12 | 2023 |
Fibroglandular tissue segmentation in breast MRI using vision transformers: a multi-institutional evaluation G Müller-Franzes, F Müller-Franzes, L Huck, V Raaff, E Kemmer, ... Scientific Reports 13 (1), 14207, 2023 | 11 | 2023 |
Fast, accurate, and robust T2 mapping of articular cartilage by neural networks G Müller-Franzes, T Nolte, M Ciba, J Schock, F Khader, A Prescher, ... Diagnostics 12 (3), 688, 2022 | 10 | 2022 |
Radiomic feature stability analysis based on probabilistic segmentations C Haarburger, J Schock, D Truhn, P Weitz, G Mueller-Franzes, ... 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1188-1192, 2020 | 10 | 2020 |
The ecological footprint of medical AI D Truhn, G Müller-Franzes, JN Kather European Radiology 34 (2), 1176-1178, 2024 | 9 | 2024 |
A radiomics approach to predict the emergence of new hepatocellular carcinoma in computed tomography for high-risk patients with liver cirrhosis E Tietz, D Truhn, G Müller-Franzes, ML Berres, K Hamesch, SA Lang, ... Diagnostics 11 (9), 1650, 2021 | 9 | 2021 |
Wearable activity data can predict functional recovery after musculoskeletal injury: Feasibility of a machine learning approach BJ Braun, T Histing, MM Menger, SC Herath, GA Mueller-Franzes, ... Injury 55 (2), 111254, 2024 | 6 | 2024 |