Deep Learning for Medical Imaging: Learning Clinically Useful Information from Images

Differentially Private Graph Neural Networks for Whole-Graph Classification

Autori: Tamara T. Mueller, Johannes C. Paetzold, Chinmay Prabhakar, Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis
Pubblicato in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, ISSN 1939-3539
Editore: IEEE Computer Society
DOI: 10.1109/tpami.2022.3228315

Synthetic Optical Coherence Tomography Angiographs for Detailed Retinal Vessel Segmentation Without Human Annotations

Autori: Linus Kreitner, Johannes C. Paetzold, Nikolaus Rauch, Chen Chen, Ahmed M. Hagag, Alaa E. Fayed, Sobha Sivaprasad, Sebastian Rausch, Julian Weichsel, Bjoern H. Menze, Matthias Harders, Benjamin Knier, Daniel Rueckert, Martin J. Menten
Pubblicato in: IEEE Transactions on Medical Imaging, Numero 43, 2024, Pagina/e 2061-2073, ISSN 0278-0062
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmi.2024.3354408

CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy

Autori: Mengyun Qiao; Shuo Wang; Huaqi Qiu; Antonio De Marvao; Declan P. O’Regan; Daniel Rueckert; Wenjia Bai
Pubblicato in: IEEE Transactions on Medical Imaging, 2023, ISSN 1558-254X
Editore: IEEE Computer Society
DOI: 10.1109/tmi.2023.3331982

Topology Optimization in Medical Image Segmentation with Fast χ Euler Characteristic

Autori: Liu Li, Qiang Ma, Cheng Oyang, Johannes C. Paetzold, Daniel Rueckert, Bernhard Kainz
Pubblicato in: IEEE Transactions on Medical Imaging, 2025, Pagina/e 1-1, ISSN 0278-0062
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmi.2025.3589495

Specialized curricula for training vision language models in retinal image analysis

Autori: Robbie Holland, Thomas R. P. Taylor, Christopher Holmes, Sophie Riedl, Julia Mai, Maria Patsiamanidi, Dimitra Mitsopoulou, Paul Hager, Philip Müller, Johannes C. Paetzold, Hendrik P. N. Scholl, Hrvoje Bogunović, Ursula Schmidt-Erfurth, Daniel Rueckert, Sobha Sivaprasad, Andrew J. Lotery, Martin J. Menten, null null, Toby Prevost, Lars Fritsche, Kristina Pfau, Maximilian Pfau
Pubblicato in: npj Digital Medicine, Numero 8, 2025, ISSN 2398-6352
Editore: Springer Science and Business Media LLC
DOI: 10.1038/s41746-025-01893-8

Unlocking the diagnostic potential of electrocardiograms through information transfer from cardiac magnetic resonance imaging

Autori: Özgün Turgut, Philip Müller, Paul Hager, Suprosanna Shit, Sophie Starck, Martin J. Menten, Eimo Martens, Daniel Rueckert
Pubblicato in: Medical Image Analysis, Numero 101, 2025, Pagina/e 103451, ISSN 1361-8415
Editore: Elsevier BV
DOI: 10.1016/j.media.2024.103451

Enhancing MR image segmentation with realistic adversarial data augmentation

Autori: Chen Chen, Chen Qin, Cheng Ouyang, Zeju Li, Shuo Wang, Huaqi Qiu, Liang Chen, Giacomo Tarroni, Wenjia Bai, Daniel Rueckert
Pubblicato in: Medical Image Analysis, 2022, ISSN 1361-8415
Editore: Elsevier BV
DOI: 10.1016/j.media.2022.102597

Weakly Supervised Object Detection in Chest X-Rays With Differentiable ROI Proposal Networks and Soft ROI Pooling

Autori: Philip Müller, Felix Meissen, Georgios Kaissis, Daniel Rueckert
Pubblicato in: IEEE Transactions on Medical Imaging, Numero 44, 2025, Pagina/e 221-231, ISSN 0278-0062
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmi.2024.3435015

Deformable image registration of dark‐field chest radiographs for functional lung assessment

Autori: Fabian Drexel, Vasiliki Sideri‐Lampretsa, Henriette Bast, Alexander W. Marka, Thomas Koehler, Florian T. Gassert, Daniela Pfeiffer, Daniel Rueckert, Franz Pfeiffer
Pubblicato in: Medical Physics, Numero 52, 2025, ISSN 0094-2405
Editore: American Association of Physicists in Medicine
DOI: 10.1002/mp.18023

Motion-Compensated MR CINE Reconstruction With Reconstruction-Driven Motion Estimation

Autori: Jiazhen Pan, Wenqi Huang, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik
Pubblicato in: IEEE Transactions on Medical Imaging, Numero 43, 2024, Pagina/e 2420-2433, ISSN 0278-0062
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmi.2024.3364504

Using UK Biobank data to establish population-specific atlases from whole body MRI

Autori: Sophie Starck, Vasiliki Sideri-Lampretsa, Jessica J. M. Ritter, Veronika A. Zimmer, Rickmer Braren, Tamara T. Mueller, Daniel Rueckert
Pubblicato in: Communications Medicine, Numero 4, 2024, ISSN 2730-664X
Editore: Springer Science and Business Media LLC
DOI: 10.1038/s43856-024-00670-0

Diff-Def: Diffusion-Generated Deformation Fields for Conditional Atlases

Autori: Sophie Starck, Vasiliki Sideri-Lampretsa, Bernhard Kainz, Martin J. Menten, Tamara T. Mueller, Daniel Rueckert
Pubblicato in: IEEE Transactions on Medical Imaging, 2025, Pagina/e 1-1, ISSN 0278-0062
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmi.2025.3595421

A deep learning method for replicate-based analysis of chromosome conformation contacts using Siamese neural networks

Autori: Ediem Al-jibury, James W. D. King, Ya Guo, Boris Lenhard, Amanda G. Fisher, Matthias Merkenschlager, Daniel Rueckert
Pubblicato in: Nature Communications, Numero 14, 2023, ISSN 2041-1723
Editore: Nature Publishing Group
DOI: 10.1038/s41467-023-40547-9

Unrolled and rapid motion-compensated reconstruction for cardiac CINE MRI

Autori: Jiazhen Pan; Manal Hamdi; Wenqi Huang; Kerstin Hammernik; Thomas Kuestner; Daniel Rueckert
Pubblicato in: Medical Image Analysis, 2024, ISSN 1361-8415
Editore: Elsevier BV
DOI: 10.1016/j.media.2023.103017

Reconciling privacy and accuracy in AI for medical imaging

Autori: Alexander Ziller, Tamara T. Mueller, Simon Stieger, Leonhard F. Feiner, Johannes Brandt, Rickmer Braren, Daniel Rueckert, Georgios Kaissis
Pubblicato in: Nature Machine Intelligence, Numero 6, 2024, Pagina/e 764-774, ISSN 2522-5839
Editore: Springer Science and Business Media LLC
DOI: 10.1038/s42256-024-00858-y

Self-supervised feature learning for cardiac Cine MR image reconstruction

Autori: Siying Xu, Marcel Früh, Kerstin Hammernik, Andreas Lingg, Jens Kübler, Patrick Krumm, Daniel Rueckert, Sergios Gatidis, Thomas Küstner
Pubblicato in: IEEE Transactions on Medical Imaging, 2025, Pagina/e 1-1, ISSN 0278-0062
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmi.2025.3570226

FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Autori: Karim Lekadir, Alejandro F Frangi, Antonio R Porras, Ben Glocker, Celia Cintas, Curtis P Langlotz, Eva Weicken, Folkert W Asselbergs, Fred Prior, Gary S Collins, Georgios Kaissis, Gianna Tsakou, Irène Buvat, Jayashree Kalpathy-Cramer, John Mongan, Julia A Schnabel, Kaisar Kushibar, Katrine Riklund, Kostas Marias, Lameck M Amugongo, Lauren A Fromont, Lena Maier-Hein, Leonor Cerdá-Alberich, Luis M
Pubblicato in: BMJ, 2025, Pagina/e e081554, ISSN 1756-1833
Editore: BMJ
DOI: 10.1136/bmj-2024-081554

CortexODE: Learning Cortical Surface Reconstruction by Neural ODEs

Autori: Qiang Ma, Liu Li, Emma C Robinson, Bernhard Kainz, Daniel Rueckert, Amir Alansary
Pubblicato in: IEEE Transactions on Medical Imaging, 2022, ISSN 0278-0062
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmi.2022.3206221

DeepMesh: Mesh-based Cardiac Motion Tracking using Deep Learning

Autori: Qingjie Meng; Wenjia Bai; Declan P O’Regan; Daniel Rueckert
Pubblicato in: IEEE Transactions on Medical Imaging, 2023, ISSN 0278-0062
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmi.2023.3340118

Causality-inspired Single-source Domain Generalization for Medical Image Segmentation

Autori: Cheng Ouyang, Chen Chen, Surui Li, Zeju Li, Chen Qin, Wenjia Bai, Daniel Rueckert
Pubblicato in: IEEE Transactions on Medical Imaging, 2022, ISSN 0278-0062
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmi.2022.3224067

AI-driven preclinical disease risk assessment using imaging in UK biobank

Autori: Dmitrii Seletkov, Sophie Starck, Tamara T. Mueller, Yundi Zhang, Lisa Steinhelfer, Daniel Rueckert, Rickmer Braren
Pubblicato in: npj Digital Medicine, Numero 8, 2025, ISSN 2398-6352
Editore: Springer Science and Business Media LLC
DOI: 10.1038/s41746-025-01771-3

The Developing Human Connectome Project: A fast deep learning-based pipeline for neonatal cortical surface reconstruction

Autori: Qiang Ma, Kaili Liang, Liu Li, Saga Masui, Yourong Guo, Chiara Nosarti, Emma C. Robinson, Bernhard Kainz, Daniel Rueckert
Pubblicato in: Medical Image Analysis, Numero 100, 2024, Pagina/e 103394, ISSN 1361-8415
Editore: Elsevier BV
DOI: 10.1016/j.media.2024.103394

Preserving fairness and diagnostic accuracy in private large-scale AI models for medical imaging

Autori: Soroosh Tayebi Arasteh, Alexander Ziller, Christiane Kuhl, Marcus Makowski, Sven Nebelung, Rickmer Braren, Daniel Rueckert, Daniel Truhn, Georgios Kaissis
Pubblicato in: Communications Medicine, Numero 4, 2024, ISSN 2730-664X
Editore: Springer Science and Business Media LLC
DOI: 10.1038/s43856-024-00462-6

Self-Supervised Motion-Corrected Image Reconstruction Network for 4D Magnetic Resonance Imaging of the Body Trunk

Autori: Thomas Küstner, Jiazhen Pan, Christopher Gilliam, Haikun Qi, Gastao Cruz, Kerstin Hammernik, Thierry Blu, Daniel Rueckert, René Botnar, Claudia Prieto and Sergios Gatidis
Pubblicato in: APSIPA Transactions on Signal and Information Processing, 2022, ISSN 2048-7703
Editore: Cambridge University Press
DOI: 10.1561/116.00000039

Retinal small vessel pathology is associated with disease burden in multiple sclerosis

Autori: Rebecca Wicklein, Linus Kreitner, Anna Wild, Lilian Aly, Daniel Rueckert, Bernhard Hemmer, Thomas Korn, Martin J Menten, Benjamin Knier
Pubblicato in: Multiple Sclerosis Journal, Numero 30, 2025, Pagina/e 812-819, ISSN 1352-4585
Editore: SAGE Publications
DOI: 10.1177/13524585241247775

Evaluation and mitigation of the limitations of large language models in clinical decision-making

Autori: Paul Hager, Friederike Jungmann, Robbie Holland, Kunal Bhagat, Inga Hubrecht, Manuel Knauer, Jakob Vielhauer, Marcus Makowski, Rickmer Braren, Georgios Kaissis, Daniel Rueckert
Pubblicato in: Nature Medicine, Numero 30, 2024, Pagina/e 2613-2622, ISSN 1078-8956
Editore: Nature Publishing Group
DOI: 10.1038/s41591-024-03097-1

Neural Implicit k-Space for Binning-Free Non-Cartesian Cardiac MR Imaging

Autori: Wenqi Huang, Hongwei Bran Li, Jiazhen Pan, Gastao Cruz, Daniel Rueckert, Kerstin Hammernik
Pubblicato in: Information Processing in Medical Imaging, 2023
Editore: Springer
DOI: 10.1007/978-3-031-34048-2_42

Single-subject Multi-contrast MRI Super-resolution via Implicit Neural Representations

Autori: Julian McGinnis, Suprosanna Shit, Hongwei Bran Li, Vasiliki Sideri-Lampretsa, Robert Graf, Maik Dannecker, Jiazhen Pan, Nil Stolt-Ansó, Mark Mühlau, Jan S. Kirschke, Daniel Rueckert & Benedikt Wiestler
Pubblicato in: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023, 2023
Editore: Springer
DOI: 10.1007/978-3-031-43993-3_17

Learning-Based and Unrolled Motion-Compensated Reconstruction for Cardiac MR CINE Imaging

Autori: Jiazhen Pan, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik
Pubblicato in: Medical Image Computing and Computer Assisted Intervention – MICCAI 2022, 2022
Editore: Springer
DOI: 10.1007/978-3-031-16446-0_65

Propagation and Attribution of Uncertainty in Medical Imaging Pipelines

Autori: Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik, Paul Hager, Wenqi Huang, Daniel Rueckert, Rickmer F. Braren, Georgios Kaissis
Pubblicato in: International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2023
Editore: Springer
DOI: 10.1007/978-3-031-44336-7_1

Exploiting Segmentation Labels and Representation Learning to Forecast Therapy Response of PDAC Patients

Autori: Ziller, Alexander; Erdur, Ayhan Can; Jungmann, Friederike; Rueckert, Daniel; Braren, Rickmer; Kaissis, Georgios
Pubblicato in: IEEE International Symposium on Biomedical Imaging, 2023
Editore: IEEE Computer Society
DOI: 10.1109/isbi53787.2023.10230324

Efficient Image Registration Network for Non-Rigid Cardiac Motion Estimation

Autori: Jiazhen Pan, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik
Pubblicato in: International Workshop on Machine Learning for Medical Image Reconstruction, 2021
Editore: Springer
DOI: 10.1007/978-3-030-88552-6_2

Global k-Space Interpolation for Dynamic MRI Reconstruction Using Masked Image Modeling

Autori: Jiazhen Pan, Suprosanna Shit, Özgün Turgut, Wenqi Huang, Hongwei Bran Li, Nil Stolt-Ansó, Thomas Küstner, Kerstin Hammernik, Daniel Rueckert
Pubblicato in: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023, 2023
Editore: Springer
DOI: 10.1007/978-3-031-43999-5_22

Body Fat Estimation from Surface Meshes Using Graph Neural Networks.

Autori: Tamara T. Mueller, Siyu Zhou, Sophie Starck, Friederike Jungmann, Alexander Ziller, Orhun Aksoy, Danylo Movchan, Rickmer Braren, Georgios Kaissis, Daniel Rueckert
Pubblicato in: Shape in Medical Imaging, 2023
Editore: Springer
DOI: 10.1007/978-3-031-46914-5_9

Subspace Implicit Neural Representations for Real-Time Cardiac Cine MR Imaging

Autori: Wenqi Huang, Veronika Spieker, Siying Xu, Gastao Cruz, Claudia Prieto, Julia A. Schnabel, Kerstin Hammernik, Thomas Kuestner, Daniel Rueckert
Pubblicato in: Lecture Notes in Computer Science, Information Processing in Medical Imaging, 2025, Pagina/e 168-183
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-96628-6_12

ChEX: Interactive Localization and Region Description in Chest X-Rays

Autori: Philip Müller, Georgios Kaissis, Daniel Rueckert
Pubblicato in: Lecture Notes in Computer Science, Computer Vision – ECCV 2024, 2024, Pagina/e 92-111
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72664-4_6

Whole Heart 3D+T Representation Learning Through Sparse 2D Cardiac MR Images

Autori: Yundi Zhang, Chen Chen, Suprosanna Shit, Sophie Starck, Daniel Rueckert, Jiazhen Pan
Pubblicato in: Lecture Notes in Computer Science, Medical Image Computing and Computer Assisted Intervention – MICCAI 2024, 2024, Pagina/e 359-369
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72378-0_34

Self-supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representations

Autori: Veronika Spieker, Hannah Eichhorn, Jonathan K. Stelter, Wenqi Huang, Rickmer F. Braren, Daniel Rueckert, Francisco Sahli Costabal, Kerstin Hammernik, Claudia Prieto, Dimitrios C. Karampinos, Julia A. Schnabel
Pubblicato in: Lecture Notes in Computer Science, Medical Image Computing and Computer Assisted Intervention – MICCAI 2024, 2024, Pagina/e 614-624
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72104-5_59

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