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- affiliation: Imperial College London, UK
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2020 – today
- 2022
[j165]Alexander Ziller
, Tamara T. Mueller, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Privacy: An Axiomatic Approach. Entropy 24(5): 714 (2022)- [j164]Yassine Taoudi-Benchekroun, Daan Christiaens, Irina Grigorescu, Oliver Gale-Grant, Andreas Schuh, Maximilian Pietsch, Andrew Chew, Nicholas Harper, Shona Falconer, Tanya Poppe, Emer J. Hughes, Jana Hutter, Anthony N. Price, Jacques-Donald Tournier, Lucilio Cordero-Grande, Serena J. Counsell, Daniel Rueckert, Tomoki Arichi, Joseph V. Hajnal, A. David Edwards, Maria Deprez, Dafnis Batalle:
Predicting age and clinical risk from the neonatal connectome. NeuroImage 257: 119319 (2022) - [j163]Yutong Chen, Carola-Bibiane Schönlieb, Pietro Liò, Tim Leiner, Pier Luigi Dragotti, Ge Wang, Daniel Rueckert, David N. Firmin, Guang Yang:
AI-Based Reconstruction for Fast MRI - A Systematic Review and Meta-Analysis. Proc. IEEE 110(2): 224-245 (2022) - [j162]Dmitrii Usynin, Daniel Rueckert, Jonathan Passerat-Palmbach, Georgios Kaissis:
Zen and the art of model adaptation: Low-utility-cost attack mitigations in collaborative machine learning. Proc. Priv. Enhancing Technol. 2022(1): 274-290 (2022) - [j161]Tian-Rui Liu, Qingjie Meng, Junjie Huang, Athanasios Vlontzos, Daniel Rueckert, Bernhard Kainz:
Video Summarization Through Reinforcement Learning With a 3D Spatio-Temporal U-Net. IEEE Trans. Image Process. 31: 1573-1586 (2022) - [j160]Xi Jia, Alexander Thorley, Wei Chen, Huaqi Qiu, Linlin Shen, Iain B. Styles, Hyung Jin Chang, Ales Leonardis, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert, Jinming Duan:
Learning a Model-Driven Variational Network for Deformable Image Registration. IEEE Trans. Medical Imaging 41(1): 199-212 (2022) - [j159]Cheng Ouyang, Carlo Biffi, Chen Chen, Turkay Kart, Huaqi Qiu, Daniel Rueckert:
Self-Supervised Learning for Few-Shot Medical Image Segmentation. IEEE Trans. Medical Imaging 41(7): 1837-1848 (2022) - [j158]Qingjie Meng, Chen Qin, Wenjia Bai, Tianrui Liu, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert:
MulViMotion: Shape-Aware 3D Myocardial Motion Tracking From Multi-View Cardiac MRI. IEEE Trans. Medical Imaging 41(8): 1961-1974 (2022) - [c400]Vasiliki Sideri-Lampretsa, Georgios Kaissis, Daniel Rueckert:
Multi-Modal Unsupervised Brain Image Registration Using Edge Maps. ISBI 2022: 1-5 - [c399]Michael Tänzer, Pedro Ferreira, Andrew Scott, Zohya Khalique, Maria Dwornik, Dudley Pennell, Guang Yang, Daniel Rueckert, Sonia Nielles-Vallespin:
Faster Diffusion Cardiac MRI with Deep Learning-Based Breath Hold Reduction. MIUA 2022: 101-115 - [e10]Alessa Hering, Julia A. Schnabel, Miaomiao Zhang, Enzo Ferrante, Mattias P. Heinrich, Daniel Rueckert:
Biomedical Image Registration - 10th International Workshop, WBIR 2022, Munich, Germany, July 10-12, 2022, Proceedings. Lecture Notes in Computer Science 13386, Springer 2022, ISBN 978-3-031-11202-7 [contents] - [i172]Felix Meissen, Georgios Kaissis, Daniel Rueckert:
AutoSeg - Steering the Inductive Biases for Automatic Pathology Segmentation. CoRR abs/2201.09579 (2022) - [i171]Tamara T. Mueller, Johannes C. Paetzold, Chinmay Prabhakar, Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis:
Differentially Private Graph Classification with GNNs. CoRR abs/2202.02575 (2022) - [i170]Felix Meissen, Benedikt Wiestler, Georgios Kaissis, Daniel Rueckert:
On the Pitfalls of Using the Residual Error as Anomaly Score. CoRR abs/2202.03826 (2022) - [i169]Vasiliki Sideri-Lampretsa, Georgios Kaissis, Daniel Rueckert:
Multi-modal unsupervised brain image registration using edge maps. CoRR abs/2202.04647 (2022) - [i168]Qiang Ma, Liu Li, Emma C. Robinson, Bernhard Kainz, Daniel Rueckert, Amir Alansary:
CortexODE: Learning Cortical Surface Reconstruction by Neural ODEs. CoRR abs/2202.08329 (2022) - [i167]Helena Klause, Alexander Ziller, Daniel Rueckert, Kerstin Hammernik, Georgios Kaissis:
Differentially private training of residual networks with scale normalisation. CoRR abs/2203.00324 (2022) - [i166]Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis:
Beyond Gradients: Exploiting Adversarial Priors in Model Inversion Attacks. CoRR abs/2203.00481 (2022) - [i165]Tamara T. Mueller, Dmitrii Usynin, Johannes C. Paetzold, Daniel Rueckert, Georgios Kaissis:
SoK: Differential Privacy on Graph-Structured Data. CoRR abs/2203.09205 (2022) - [i164]Alexander Ziller, Tamara T. Mueller, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Privacy: An axiomatic approach. CoRR abs/2203.11586 (2022) - [i163]Kerstin Hammernik, Thomas Küstner, Burhaneddin Yaman, Zhengnan Huang, Daniel Rueckert, Florian Knoll, Mehmet Akçakaya:
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging. CoRR abs/2203.12215 (2022) - [i162]Simon Dahan, Abdulah Fawaz, Logan Z. J. Williams, Chunhui Yang, Timothy S. Coalson, Matthew F. Glasser, A. David Edwards, Daniel Rueckert, Emma C. Robinson:
Surface Vision Transformers: Attention-Based Modelling applied to Cortical Analysis. CoRR abs/2203.16414 (2022) - [i161]Jiahao Huang, Yingying Fang, Yang Nan, Huanjun Wu, Yinzhe Wu, Zhifan Gao, Yang Li, Zidong Wang, Pietro Liò, Daniel Rueckert, Yonina C. Eldar, Guang Yang:
Data and Physics Driven Learning Models for Fast MRI - Fundamentals and Methodologies from CNN, GAN to Attention and Transformers. CoRR abs/2204.01706 (2022) - [i160]Simon Dahan, Hao Xu, Logan Z. J. Williams, Abdulah Fawaz, Chunhui Yang, Timothy S. Coalson, Michelle C. Williams, David E. Newby, A. David Edwards, Matthew F. Glasser, Alistair A. Young, Daniel Rueckert, Emma C. Robinson:
Surface Vision Transformers: Flexible Attention-Based Modelling of Biomedical Surfaces. CoRR abs/2204.03408 (2022) - [i159]Dmitrii Usynin, Helena Klause, Daniel Rueckert, Georgios Kaissis:
Can collaborative learning be private, robust and scalable? CoRR abs/2205.02652 (2022) - [i158]Nicolas W. Remerscheid, Alexander Ziller, Daniel Rueckert, Georgios Kaissis:
SmoothNets: Optimizing CNN architecture design for differentially private deep learning. CoRR abs/2205.04095 (2022) - [i157]Liu Li, Qiang Ma, Matthew Sinclair, Antonios Makropoulos, Joseph V. Hajnal, A. David Edwards, Bernhard Kainz, Daniel Rueckert, Amir Alansary:
CAS-Net: Conditional Atlas Generation and Brain Segmentation for Fetal MRI. CoRR abs/2205.08239 (2022) - [i156]Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Daniel Rueckert, Georgios Kaissis:
Kernel Normalized Convolutional Networks. CoRR abs/2205.10089 (2022) - [i155]Tobias Bernecker, Annette Peters, Christopher L. Schlett, Fabian Bamberg, Fabian J. Theis, Daniel Rueckert, Jakob Weiß, Shadi Albarqouni:
FedNorm: Modality-Based Normalization in Federated Learning for Multi-Modal Liver Segmentation. CoRR abs/2205.11096 (2022) - [i154]Simon Dahan, Logan Z. J. Williams, Abdulah Fawaz, Daniel Rueckert, Emma C. Robinson:
Surface Analysis with Vision Transformers. CoRR abs/2205.15836 (2022) - [i153]Chen Chen, Zeju Li, Cheng Ouyang, Matthew Sinclair, Wenjia Bai, Daniel Rueckert:
MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation. CoRR abs/2206.01737 (2022) - [i152]Cosmin I. Bercea, Daniel Rueckert, Julia A. Schnabel:
What do we learn? Debunking the Myth of Unsupervised Outlier Detection. CoRR abs/2206.03698 (2022) - [i151]Chen Qin, Shuo Wang, Chen Chen, Wenjia Bai, Daniel Rueckert:
Generative Myocardial Motion Tracking via Latent Space Exploration with Biomechanics-informed Prior. CoRR abs/2206.03830 (2022) - [i150]Athanasios Vlontzos, Daniel Rueckert, Bernhard Kainz:
A Review of Causality for Learning Algorithms in Medical Image Analysis. CoRR abs/2206.05498 (2022) - [i149]Michael Tänzer, Pedro Ferreira, Andrew Scott, Zohya Khalique, Maria Dwornik, Dudley Pennell, Guang Yang, Daniel Rueckert, Sonia Nielles-Vallespin:
Faster Diffusion Cardiac MRI with Deep Learning-based breath hold reduction. CoRR abs/2206.10543 (2022) - [i148]Veronika A. Zimmer, Alberto Gómez, Emily Skelton, Robert Wright, Gavin Wheeler, Shujie Deng, Nooshin Ghavami, Karen Lloyd, Jacqueline Matthew, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel:
Placenta Segmentation in Ultrasound Imaging: Addressing Sources of Uncertainty and Limited Field-of-View. CoRR abs/2206.14746 (2022) - [i147]Martin J. Menten, Johannes C. Paetzold, Alina Dima, Bjoern H. Menze, Benjamin Knier, Daniel Rueckert:
Physiology-based simulation of the retinal vasculature enables annotation-free segmentation of OCT angiographs. CoRR abs/2207.11102 (2022) - [i146]Qingjie Meng, Chen Qin, Wenjia Bai, Tianrui Liu, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert:
MulViMotion: Shape-aware 3D Myocardial Motion Tracking from Multi-View Cardiac MRI. CoRR abs/2208.00034 (2022) - [i145]Robbie Holland, Oliver Leingang, Hrvoje Bogunovic, Sophie Riedl, Lars Fritsche, Toby Prevost, Hendrik P. N. Scholl, Ursula Schmidt-Erfurth, Sobha Sivaprasad, Andrew J. Lotery, Daniel Rueckert, Martin J. Menten:
Metadata-enhanced contrastive learning from retinal optical coherence tomography images. CoRR abs/2208.02529 (2022) - [i144]Cheng Ouyang, Shuo Wang, Chen Chen, Zeju Li, Wenjia Bai, Bernhard Kainz, Daniel Rueckert:
Improved post-hoc probability calibration for out-of-domain MRI segmentation. CoRR abs/2208.02870 (2022) - 2021
- [j157]Georgios Kaissis, Alexander Ziller, Jonathan Passerat-Palmbach, Théo Ryffel, Dmitrii Usynin, Andrew Trask, Ionésio Lima, Jason Mancuso, Friederike Jungmann, Marc-Matthias Steinborn, Andreas Saleh, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren:
End-to-end privacy preserving deep learning on multi-institutional medical imaging. Nat. Mach. Intell. 3(6): 473-484 (2021) - [j156]Dmitrii Usynin, Alexander Ziller, Marcus R. Makowski, Rickmer Braren, Daniel Rueckert, Ben Glocker, Georgios Kaissis, Jonathan Passerat-Palmbach:
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning. Nat. Mach. Intell. 3(9): 749-758 (2021) - [j155]Ralica Dimitrova, Maximilian Pietsch, Judit Ciarrusta, Sean P. Fitzgibbon, Logan Z. J. Williams, Daan Christiaens, Lucilio Cordero-Grande, Dafnis Batalle, Antonios Makropoulos, Andreas Schuh, Anthony N. Price, Jana Hutter, Rui Pedro A. G. Teixeira, Emer J. Hughes, Andrew Chew, Shona Falconer, Olivia Carney, Alexia Egloff, Jacques-Donald Tournier, Grainne M. McAlonan, Mary A. Rutherford, Serena J. Counsell, Emma C. Robinson, Joseph V. Hajnal, Daniel Rueckert, A. David Edwards, Jonathan O'Muircheartaigh:
Preterm birth alters the development of cortical microstructure and morphology at term-equivalent age. NeuroImage 243: 118488 (2021) - [j154]S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos, James S. Duncan, Bram van Ginneken, Anant Madabhushi, Jerry L. Prince, Daniel Rueckert, Ronald M. Summers:
A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises. Proc. IEEE 109(5): 820-838 (2021) - [j153]Qingjie Meng, Jacqueline Matthew, Veronika A. Zimmer, Alberto Gómez, David F. A. Lloyd, Daniel Rueckert, Bernhard Kainz:
Mutual Information-Based Disentangled Neural Networks for Classifying Unseen Categories in Different Domains: Application to Fetal Ultrasound Imaging. IEEE Trans. Medical Imaging 40(2): 722-734 (2021) - [c398]Kerstin Hammernik, Jiazhen Pan, Daniel Rueckert, Thomas Küstner:
Motion-Guided Physics-Based Learning for Cardiac MRI Reconstruction. ACSCC 2021: 900-907 - [c397]Patrick Henriksen, Kerstin Hammernik, Daniel Rueckert, Alessio Lomuscio:
Bias Field Robustness Verification of Large Neural Image Classifiers. BMVC 2021: 202 - [c396]Felix Meissen, Georgios Kaissis, Daniel Rueckert:
Challenging Current Semi-supervised Anomaly Segmentation Methods for Brain MRI. BrainLes@MICCAI (1) 2021: 63-74 - [c395]Ping Lu, Wenjia Bai, Daniel Rueckert, J. Alison Noble:
Multiscale Graph Convolutional Networks for Cardiac Motion Analysis. FIMH 2021: 264-272 - [c394]Ping Lu, Wenjia Bai, Daniel Rueckert, J. Alison Noble:
Dynamic Spatio-Temporal Graph Convolutional Networks For Cardiac Motion Analysis. ISBI 2021: 122-125 - [c393]Osama N. Hassan, Martin J. Menten, Hrvoje Bogunovic, Ursula Schmidt-Erfurth, Andrew J. Lotery, Daniel Rueckert:
Deep Learning Prediction Of Age And Sex From Optical Coherence Tomography. ISBI 2021: 238-242 - [c392]Jiazhen Pan, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik:
Efficient Image Registration Network for Non-Rigid Cardiac Motion Estimation. MLMIR@MICCAI 2021: 14-24 - [c391]Shuo Wang, Chen Qin, Nicoló Savioli, Chen Chen, Declan P. O'Regan, Stuart A. Cook, Yike Guo, Daniel Rueckert, Wenjia Bai:
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation. MICCAI (3) 2021: 14-24 - [c390]Patricia M. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus Van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius Staring, Eric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling, Matthew J. Muckley, Florian Knoll:
Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge. MLMIR@MICCAI 2021: 25-34 - [c389]Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Alexander Hammers, Daniel Rueckert:
Voxel-Level Importance Maps for Interpretable Brain Age Estimation. iMIMIC/TDA4MedicalData@MICCAI 2021: 65-74 - [c388]Qiang Ma, Emma C. Robinson, Bernhard Kainz, Daniel Rueckert, Amir Alansary:
PialNN: A Fast Deep Learning Framework for Cortical Pial Surface Reconstruction. MLCN@MICCAI 2021: 73-81 - [c387]Konstantinos Kamnitsas, Stefan Winzeck, Evgenios N. Kornaropoulos, Daniel Whitehouse, Cameron Englman, Poe Phyu, Norman Pao, David K. Menon, Daniel Rueckert, Tilak Das, Virginia F. J. Newcombe, Ben Glocker:
Transductive Image Segmentation: Self-training and Effect of Uncertainty Estimation. DART/FAIR@MICCAI 2021: 79-89 - [c386]Simon Dahan, Logan Z. J. Williams, Daniel Rueckert, Emma C. Robinson:
Improving Phenotype Prediction Using Long-Range Spatio-Temporal Dynamics of Functional Connectivity. MLCN@MICCAI 2021: 145-154 - [c385]Chen Chen, Kerstin Hammernik, Cheng Ouyang, Chen Qin, Wenjia Bai, Daniel Rueckert:
Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation. MICCAI (3) 2021: 149-159 - [c384]Samuel Budd, Matthew Sinclair, Thomas Day, Athanasios Vlontzos, Jeremy Tan, Tianrui Liu, Jacqueline Matthew, Emily Skelton, John M. Simpson, Reza Razavi, Ben Glocker, Daniel Rueckert, Emma C. Robinson, Bernhard Kainz:
Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-Specific Atlas Maps. MICCAI (7) 2021: 207-217 - [c383]Liu Li, Matthew Sinclair, Antonios Makropoulos, Joseph V. Hajnal, A. David Edwards, Bernhard Kainz, Daniel Rueckert, Amir Alansary:
CAS-Net: Conditional Atlas Generation and Brain Segmentation for Fetal MRI. UNSURE/PIPPI@MICCAI 2021: 221-230 - [c382]Turkay Kart, Wenjia Bai, Ben Glocker, Daniel Rueckert:
DeepMCAT: Large-Scale Deep Clustering for Medical Image Categorization. DGM4MICCAI/DALI@MICCAI 2021: 259-267 - [c381]Jeremy Tan, Benjamin Hou, Thomas Day, John M. Simpson, Daniel Rueckert, Bernhard Kainz:
Detecting Outliers with Poisson Image Interpolation. MICCAI (5) 2021: 581-591 - [c380]Alina Dima, Johannes C. Paetzold, Friederike Jungmann, Tristan Lemke, Philipp Raffler, Georgios Kaissis, Daniel Rueckert, Rickmer Braren:
Segmentation of Peripancreatic Arteries in Multispectral Computed Tomography Imaging. MLMI@MICCAI 2021: 596-605 - [c379]Huaqi Qiu, Chen Qin, Andreas Schuh, Kerstin Hammernik, Daniel Rueckert:
Learning Diffeomorphic and Modality-invariant Registration using B-splines. MIDL 2021: 645-664 - [c378]Seoin Chai, Daniel Rueckert, Ahmed E. Fetit:
Reducing Textural Bias Improves Robustness of Deep Segmentation Models. MIUA 2021: 294-304 - [e9]Cristina Oyarzun Laura, M. Jorge Cardoso, Michal Rosen-Zvi, Georgios Kaissis, Marius George Linguraru, Raj Shekhar, Stefan Wesarg, Marius Erdt, Klaus Drechsler, Yufei Chen, Shadi Albarqouni, Spyridon Bakas, Bennett A. Landman, Nicola Rieke, Holger Roth, Xiaoxiao Li, Daguang Xu, Maria Gabrani, Ender Konukoglu, Michal Guindy, Daniel Rueckert, Alexander Ziller, Dmitrii Usynin, Jonathan Passerat-Palmbach:
Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning - 10th Workshop, CLIP 2021, Second Workshop, DCL 2021, First Workshop, LL-COVID19 2021, and First Workshop and Tutorial, PPML 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings. Lecture Notes in Computer Science 12969, Springer 2021, ISBN 978-3-030-90873-7 [contents] - [i143]Ognjen Rudovic, Nicolas Tobis, Sebastian Kaltwang, Björn W. Schuller, Daniel Rueckert, Jeffrey F. Cohn, Rosalind W. Picard:
Personalized Federated Deep Learning for Pain Estimation From Face Images. CoRR abs/2101.04800 (2021) - [i142]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Shadi Albarqouni:
FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation. CoRR abs/2103.03705 (2021) - [i141]Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Julian O. Matschinske, Jan Baumbach, Daniel Rueckert, Georgios Kaissis:
HyFed: A Hybrid Federated Framework for Privacy-preserving Machine Learning. CoRR abs/2105.10545 (2021) - [i140]Aydan Gasimova, Giovanni Montana, Daniel Rueckert:
Automated Knee X-ray Report Generation. CoRR abs/2105.10702 (2021) - [i139]Xi Jia, Alexander Thorley, Wei Chen, Huaqi Qiu, Linlin Shen, Iain B. Styles, Hyung Jin Chang, Ales Leonardis, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert, Jinming Duan:
Learning a Model-Driven Variational Network for Deformable Image Registration. CoRR abs/2105.12227 (2021) - [i138]Tianrui Liu, Qingjie Meng, Junjie Huang, Athanasios Vlontzos, Daniel Rueckert, Bernhard Kainz:
Video Summarization through Reinforcement Learning with a 3D Spatio-Temporal U-Net. CoRR abs/2106.10528 (2021) - [i137]Chen Chen, Kerstin Hammernik, Cheng Ouyang, Chen Qin, Wenjia Bai, Daniel Rueckert:
Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation. CoRR abs/2107.01079 (2021) - [i136]Alexander Ziller, Dmitrii Usynin, Nicolas Remerscheid, Moritz Knolle, Marcus R. Makowski, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Differentially private federated deep learning for multi-site medical image segmentation. CoRR abs/2107.02586 (2021) - [i135]Jeremy Tan, Benjamin Hou, Thomas Day, John M. Simpson, Daniel Rueckert, Bernhard Kainz:
Detecting Outliers with Poisson Image Interpolation. CoRR abs/2107.02622 (2021) - [i134]Samuel Budd, Matthew Sinclair, Thomas Day, Athanasios Vlontzos, Jeremy Tan, Tianrui Liu, Jacqueline Matthew, Emily Skelton, John M. Simpson, Reza Razavi, Ben Glocker, Daniel Rueckert, Emma C. Robinson, Bernhard Kainz:
Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps. CoRR abs/2107.02643 (2021) - [i133]Shuo Wang, Chen Qin, Nicoló Savioli, Chen Chen, Declan P. O'Regan, Stuart A. Cook, Yike Guo, Daniel Rueckert, Wenjia Bai:
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation. CoRR abs/2107.03887 (2021) - [i132]Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kritika Prakash, Andrew Trask, Rickmer Braren, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis:
Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation. CoRR abs/2107.04265 (2021) - [i131]Moritz Knolle, Alexander Ziller, Dmitrii Usynin, Rickmer Braren, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis:
Differentially private training of neural networks with Langevin dynamics forcalibrated predictive uncertainty. CoRR abs/2107.04296 (2021) - [i130]Nicoló Savioli, Antonio de Marvao, Wenjia Bai, Shuo Wang, Stuart A. Cook, Calvin W. L. Chin, Daniel Rueckert, Declan P. O'Regan:
Joint Semi-supervised 3D Super-Resolution and Segmentation with Mixed Adversarial Gaussian Domain Adaptation. CoRR abs/2107.07975 (2021) - [i129]Konstantinos Kamnitsas, Stefan Winzeck, Evgenios N. Kornaropoulos, Daniel Whitehouse, Cameron Englman, Poe Phyu, Norman Pao, David K. Menon, Daniel Rueckert, Tilak Das, Virginia F. J. Newcombe, Ben Glocker:
Transductive image segmentation: Self-training and effect of uncertainty estimation. CoRR abs/2107.08964 (2021) - [i128]Moritz Knolle, Dmitrii Usynin, Alexander Ziller, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis:
NeuralDP Differentially private neural networks by design. CoRR abs/2107.14582 (2021) - [i127]Chen Chen, Chen Qin, Cheng Ouyang, Shuo Wang, Huaqi Qiu, Liang Chen, Giacomo Tarroni, Wenjia Bai, Daniel Rueckert:
Enhancing MR Image Segmentation with Realistic Adversarial Data Augmentation. CoRR abs/2108.03429 (2021) - [i126]Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Alexander Hammers, Daniel Rueckert:
Voxel-level Importance Maps for Interpretable Brain Age Estimation. CoRR abs/2108.05388 (2021) - [i125]Simon Dahan, Logan Z. J. Williams, Daniel Rueckert, Emma C. Robinson:
Improving Phenotype Prediction using Long-Range Spatio-Temporal Dynamics of Functional Connectivity. CoRR abs/2109.03115 (2021) - [i124]Georgios Kaissis, Moritz Knolle, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin, Daniel Rueckert:
A unified interpretation of the Gaussian mechanism for differential privacy through the sensitivity index. CoRR abs/2109.10528 (2021) - [i123]Dmitrii Usynin, Alexander Ziller, Moritz Knolle, Daniel Rueckert, Georgios Kaissis:
An automatic differentiation system for the age of differential privacy. CoRR abs/2109.10573 (2021) - [i122]Tamara T. Mueller, Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Friederike Jungmann, Daniel Rueckert, Georgios Kaissis:
Partial sensitivity analysis in differential privacy. CoRR abs/2109.10582 (2021) - [i121]Turkay Kart, Wenjia Bai, Ben Glocker, Daniel Rueckert:
DeepMCAT: Large-Scale Deep Clustering for Medical Image Categorization. CoRR abs/2110.00109 (2021) - [i120]Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kerstin Hammernik, Daniel Rueckert, Georgios Kaissis:
Complex-valued deep learning with differential privacy. CoRR abs/2110.03478 (2021) - [i119]Cheng Ouyang, Chen Chen, Surui Li, Zeju Li, Chen Qin, Wenjia Bai, Daniel Rueckert:
Causality-inspired Single-source Domain Generalization for Medical Image Segmentation. CoRR abs/2111.12525 (2021) - [i118]Stefán Páll Sturluson, Samuel Trew, Luis Muñoz-González, Matei Grama, Jonathan Passerat-Palmbach, Daniel Rueckert, Amir Alansary:
FedRAD: Federated Robust Adaptive Distillation. CoRR abs/2112.01405 (2021) - [i117]Philip Müller, Georgios Kaissis, Congyu Zou, Daniel Rueckert:
Joint Learning of Localized Representations from Medical Images and Reports. CoRR abs/2112.02889 (2021) - [i116]Huaqi Qiu, Kerstin Hammernik, Chen Qin, Daniel Rueckert:
GraDIRN: Learning Iterative Gradient Descent-based Energy Minimization for Deformable Image Registration. CoRR abs/2112.03915 (2021) - [i115]Dmitrii Usynin, Alexander Ziller, Daniel Rueckert, Jonathan Passerat-Palmbach, Georgios Kaissis:
Distributed Machine Learning and the Semblance of Trust. CoRR abs/2112.11040 (2021) - [i114]Yutong Chen, Carola-Bibiane Schönlieb, Pietro Liò, Tim Leiner, Pier Luigi Dragotti, Gerald Wang, Daniel Rueckert, David N. Firmin, Guang Yang:
AI-based Reconstruction for Fast MRI - A Systematic Review and Meta-analysis. CoRR abs/2112.12744 (2021) - 2020
- [j152]Muhammad Febrian Rachmadi, Maria del C. Valdés Hernández, Hongwei Li, Ricardo Guerrero, Rozanna Meijboom, Stewart Wiseman, Adam Waldman, Jianguo Zhang, Daniel Rueckert, Joanna M. Wardlaw, Taku Komura:
Limited One-time Sampling Irregularity Map (LOTS-IM) for Automatic Unsupervised Assessment of White Matter Hyperintensities and Multiple Sclerosis Lesions in Structural Brain Magnetic Resonance Images. Comput. Medical Imaging Graph. 79: 101685 (2020) - [j151]Georgios Kaissis, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren:
Secure, privacy-preserving and federated machine learning in medical imaging. Nat. Mach. Intell. 2(6): 305-311 (2020) - [j150]Daniel Rueckert, Julia A. Schnabel:
Model-Based and Data-Driven Strategies in Medical Image Computing. Proc. IEEE 108(1): 110-124 (2020) - [j149]Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni, Wenjia Bai, Antonio de Marvao, Ozan Oktay, Christian Ledig, Loïc Le Folgoc, Konstantinos Kamnitsas, Georgia Doumou, Jinming Duan, Sanjay K. Prasad, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert:
Explainable Anatomical Shape Analysis Through Deep Hierarchical Generative Models. IEEE Trans. Medical Imaging 39(6): 2088-2099 (2020) - [c377]Thomas Küstner, Jiazhen Pan, Christopher Gilliam, Haikun Qi, Gastão Cruz, Kerstin Hammernik, Bin Yang, Thierry Blu, Daniel Rueckert, René M. Botnar, Claudia Prieto, Sergios Gatidis:
Deep-learning based motion-corrected image reconstruction in 4D magnetic resonance imaging of the body trunk. APSIPA 2020: 976-985 - [c376]Veneta Haralampieva, Daniel Rueckert, Jonathan Passerat-Palmbach:
A Systematic Comparison of Encrypted Machine Learning Solutions for Image Classification. PPMLP@CCS 2020: 55-59 - [c375]Cheng Ouyang, Carlo Biffi, Chen Chen, Turkay Kart, Huaqi Qiu, Daniel Rueckert:
Self-supervision with Superpixels: Training Few-Shot Medical Image Segmentation Without Annotation. ECCV (29) 2020: 762-780 - [c374]Osama N. Hassan, Serhat Sahin, Vahid Mohammadzadeh, Xiaohe Yang, Navid Amini, Apoorva Mylavarapu, Jack Martinyan, Tae Hong, Golnoush Mahmoudinezhad, Daniel Rueckert, Kouros Nouri-Mahdavi, Fabien Scalzo:
Conditional GAN for Prediction of Glaucoma Progression with Macular Optical Coherence Tomography. ISVC (2) 2020: 761-772 - [c373]Athanasios Vlontzos, Samuel Budd, Benjamin Hou, Daniel Rueckert, Bernhard Kainz:
3D Probabilistic Segmentation and Volumetry from 2D Projection Images. TIA@MICCAI 2020: 48-57 - [c372]Ping Lu, Wenjia Bai, Daniel Rueckert, J. Alison Noble:
Modelling Cardiac Motion via Spatio-Temporal Graph Convolutional Networks to Boost the Diagnosis of Heart Conditions. M&Ms and EMIDEC/STACOM@MICCAI 2020: 56-65 - [c371]