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- affiliation: Imperial College London, UK
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2020 – today
- 2021
[j152]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)- [j151]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) - [c380]Ping Lu, Wenjia Bai, Daniel Rueckert, J. Alison Noble:
Multiscale Graph Convolutional Networks for Cardiac Motion Analysis. FIMH 2021: 264-272 - [c379]Ping Lu, Wenjia Bai, Daniel Rueckert, J. Alison Noble:
Dynamic Spatio-Temporal Graph Convolutional Networks For Cardiac Motion Analysis. ISBI 2021: 122-125 - [c378]Osama N. Hassan, Martin J. Menten, Hrvoje Bogunovic, Ursula Schmidt-Erfurth, Andrew Lotery, Daniel Rueckert:
Deep Learning Prediction Of Age And Sex From Optical Coherence Tomography. ISBI 2021: 238-242 - [c377]Seoin Chai, Daniel Rueckert, Ahmed E. Fetit:
Reducing Textural Bias Improves Robustness of Deep Segmentation Models. MIUA 2021: 294-304 - [i128]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) - [i127]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Shadi Albarqouni:
FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation. CoRR abs/2103.03705 (2021) - [i126]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) - [i125]Aydan Gasimova, Giovanni Montana, Daniel Rueckert:
Automated Knee X-ray Report Generation. CoRR abs/2105.10702 (2021) - [i124]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) - [i123]Tianrui Liu, Qingjie Meng, Jun-Jie Huang, Athanasios Vlontzos, Daniel Rueckert, Bernhard Kainz:
Video Summarization through Reinforcement Learning with a 3D Spatio-Temporal U-Net. CoRR abs/2106.10528 (2021) - [i122]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) - [i121]Alexander Ziller, Dmitrii Usynin, Nicolas Remerscheid, Moritz Knolle, Marcus Makowski, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Differentially private federated deep learning for multi-site medical image segmentation. CoRR abs/2107.02586 (2021) - [i120]Jeremy Tan, Benjamin Hou, Thomas Day, John M. Simpson, Daniel Rueckert, Bernhard Kainz:
Detecting Outliers with Poisson Image Interpolation. CoRR abs/2107.02622 (2021) - [i119]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) - [i118]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) - [i117]Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kritika Prakash, Andrew Trask, Rickmer Braren, Marcus Makowski, Daniel Rueckert, Georgios Kaissis:
Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation. CoRR abs/2107.04265 (2021) - [i116]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) - [i115]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) - [i114]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) - 2020
- [j150]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) - [j149]Daniel Rueckert, Julia A. Schnabel:
Model-Based and Data-Driven Strategies in Medical Image Computing. Proc. IEEE 108(1): 110-124 (2020) - [j148]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) - [c376]Thomas Küstner, Jiazhen Pan, Christopher Gilliam, Haikun Qi, Gastao 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 - [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]Shuo Wang, Giacomo Tarroni, Chen Qin, Yuanhan Mo, Chengliang Dai, Chen Chen, Ben Glocker, Yike Guo, Daniel Rueckert, Wenjia Bai:
Deep Generative Model-Based Quality Control for Cardiac MRI Segmentation. MICCAI (4) 2020: 88-97 - [c370]Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Arinbjörn Kolbeinsson, Alexander Hammers, Daniel Rueckert:
Patch-Based Brain Age Estimation from MR Images. MLCN/RNO-AI@MICCAI 2020: 98-107 - [c369]Qingjie Meng, Daniel Rueckert, Bernhard Kainz:
Unsupervised Cross-domain Image Classification by Distance Metric Guided Feature Alignment. ASMUS/PIPPI@MICCAI 2020: 146-157 - [c368]Vitalis Vosylius, Andy Wang, Cemlyn Waters, Alexey Zakharov, Francis Ward, Loïc Le Folgoc, John Cupitt, Antonios Makropoulos, Andreas Schuh, Daniel Rueckert, Amir Alansary:
Geometric Deep Learning for Post-Menstrual Age Prediction Based on the Neonatal White Matter Cortical Surface. UNSURE/GRAIL@MICCAI 2020: 174-186 - [c367]Guy Leroy, Daniel Rueckert, Amir Alansary:
Communicative Reinforcement Learning Agents for Landmark Detection in Brain Images. MLCN/RNO-AI@MICCAI 2020: 177-186 - [c366]Jeremy Tan, Anselm Au, Qingjie Meng, Sandy FinesilverSmith, John M. Simpson, Daniel Rueckert, Reza Razavi, Thomas Day, David Lloyd, Bernhard Kainz:
Automated Detection of Congenital Heart Disease in Fetal Ultrasound Screening. ASMUS/PIPPI@MICCAI 2020: 243-252 - [c365]Esther Puyol-Antón, Chen Chen, James R. Clough, Bram Ruijsink, Baldeep S. Sidhu, Justin Gould, Bradley Porter, Mark Elliott, Vishal Mehta, Daniel Rueckert, Christopher A. Rinaldi, Andrew P. King:
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction. MICCAI (1) 2020: 284-293 - [c364]Chen Qin, Shuo Wang, Chen Chen, Huaqi Qiu, Wenjia Bai, Daniel Rueckert:
Biomechanics-Informed Neural Networks for Myocardial Motion Tracking in MRI. MICCAI (3) 2020: 296-306 - [c363]Aydan Gasimova, Gavin Seegoolam, Liang Chen, Paul Bentley, Daniel Rueckert:
Spatial Semantic-Preserving Latent Space Learning for Accelerated DWI Diagnostic Report Generation. MICCAI (7) 2020: 333-342 - [c362]Tianrui Liu, Qingjie Meng, Athanasios Vlontzos, Jeremy Tan, Daniel Rueckert, Bernhard Kainz:
Ultrasound Video Summarization Using Deep Reinforcement Learning. MICCAI (3) 2020: 483-492 - [c361]Chen Chen, Chen Qin, Huaqi Qiu, Cheng Ouyang, Shuo Wang, Liang Chen, Giacomo Tarroni, Wenjia Bai, Daniel Rueckert:
Realistic Adversarial Data Augmentation for MR Image Segmentation. MICCAI (1) 2020: 667-677 - [c360]Robert Robinson, Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Marius de Groot, Ronald M. Summers, Daniel Rueckert, Ben Glocker:
Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks. MICCAI (7) 2020: 710-719 - [c359]Ahmed E. Fetit, John Cupitt, Turkay Kart, Daniel Rueckert:
Training deep segmentation networks on texture-encoded input: application to neuroimaging of the developing neonatal brain. MIDL 2020: 230-240 - [c358]Ahmed E. Fetit, Amir Alansary, Lucilio Cordero-Grande, John Cupitt, Alice B. Davidson, A. David Edwards, Joseph V. Hajnal, Emer J. Hughes, Konstantinos Kamnitsas, Vanessa Kyriakopoulou, Antonios Makropoulos, Prachi A. Patkee, Anthony N. Price, Mary A. Rutherford, Daniel Rueckert:
A deep learning approach to segmentation of the developing cortex in fetal brain MRI with minimal manual labeling. MIDL 2020: 241-261 - [c357]Jack Weatheritt, Daniel Rueckert, Robin Wolz:
Transfer Learning for Brain Segmentation: Pre-task Selection and Data Limitations. MIUA 2020: 118-130 - [c356]Ping Lu, Huaqi Qiu, Chen Qin, Wenjia Bai, Daniel Rueckert, J. Alison Noble:
Going Deeper into Cardiac Motion Analysis to Model Fine Spatio-Temporal Features. MIUA 2020: 294-306 - [i113]Qingjie Meng, Daniel Rueckert, Bernhard Kainz:
Learning Cross-domain Generalizable Features by Representation Disentanglement. CoRR abs/2003.00321 (2020) - [i112]Zhaohan Xiong, Qing Xia, Zhiqiang Hu, Ning Huang, Cheng Bian, Yefeng Zheng, Sulaiman Vesal, Nishant Ravikumar, Andreas K. Maier, Xin Yang, Pheng-Ann Heng, Dong Ni, Caizi Li, Qianqian Tong, Weixin Si, Élodie Puybareau, Younes Khoudli, Thierry Géraud, Chen Chen, Wenjia Bai, Daniel Rueckert, Lingchao Xu, Xiahai Zhuang, Xinzhe Luo, Shuman Jia, Maxime Sermesant, Yashu Liu, Kuanquan Wang, Davide Borra, Alessandro Masci, Cristiana Corsi, Coen de Vente, Mitko Veta, Rashed Karim, Chandrakanth Jayachandran Preetha, Sandy Engelhardt, Mengyun Qiao, Yuanyuan Wang, Qian Tao, Marta Nuñez Garcia, Oscar Camara, Nicoló Savioli, Pablo Lamata, Jichao Zhao:
A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging. CoRR abs/2004.12314 (2020) - [i111]Masahiro Oda, Natsuki Shimizu, Kenichi Karasawa, Yukitaka Nimura, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, Kensaku Mori:
Regression Forest-Based Atlas Localization and Direction Specific Atlas Generation for Pancreas Segmentation. CoRR abs/2005.03345 (2020) - [i110]Tianrui Liu, Qingjie Meng, Athanasios Vlontzos, Jeremy Tan, Daniel Rueckert, Bernhard Kainz:
Ultrasound Video Summarization using Deep Reinforcement Learning. CoRR abs/2005.09531 (2020) - [i109]Chen Qin, Shuo Wang, Chen Chen, Huaqi Qiu, Wenjia Bai, Daniel Rueckert:
Biomechanics-informed Neural Networks for Myocardial Motion Tracking in MRI. CoRR abs/2006.04725 (2020) - [i108]Xiahai Zhuang, Jiahang Xu, Xinzhe Luo, Chen Chen, Cheng Ouyang, Daniel Rueckert, Víctor M. Campello, Karim Lekadir, Sulaiman Vesal, Nishant Ravikumar, Yashu Liu, Gongning Luo, Jingkun Chen, Hongwei Li, Buntheng Ly, Maxime Sermesant, Holger Roth, Wentao Zhu, Jiexiang Wang, Xinghao Ding, Xinyue Wang, Sen Yang, Lei Li:
Cardiac Segmentation on Late Gadolinium Enhancement MRI: A Benchmark Study from Multi-Sequence Cardiac MR Segmentation Challenge. CoRR abs/2006.12434 (2020) - [i107]Athanasios Vlontzos, Samuel Budd, Benjamin Hou, Daniel Rueckert, Bernhard Kainz:
3D Probabilistic Segmentation and Volumetry from 2D projection images. CoRR abs/2006.12809 (2020) - [i106]Chen Chen, Chen Qin, Huaqi Qiu, Cheng Ouyang, Shuo Wang, Liang Chen, Giacomo Tarroni, Wenjia Bai, Daniel Rueckert:
Realistic Adversarial Data Augmentation for MR Image Segmentation. CoRR abs/2006.13322 (2020) - [i105]Shuo Wang, Giacomo Tarroni, Chen Qin, Yuanhan Mo, Chengliang Dai, Chen Chen, Ben Glocker, Yike Guo, Daniel Rueckert, Wenjia Bai:
Deep Generative Model-based Quality Control for Cardiac MRI Segmentation. CoRR abs/2006.13379 (2020) - [i104]Esther Puyol-Antón, Chen Chen, James R. Clough, Bram Ruijsink, Baldeep S. Sidhu, Justin Gould, Bradley Porter, Mark Elliott, Vishal Mehta, Daniel Rueckert, Christopher A. Rinaldi, Andrew P. King:
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction. CoRR abs/2006.13811 (2020) - [i103]Robert Robinson, Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Marius de Groot, Ronald M. Summers, Daniel Rueckert, Benjamin M. Glocker:
Image-level Harmonization of Multi-Site Data using Image-and-Spatial Transformer Networks. CoRR abs/2006.16741 (2020) - [i102]Chen Qin, Jo Schlemper, Kerstin Hammernik, Jinming Duan, Ronald M. Summers, Daniel Rueckert:
Deep Network Interpolation for Accelerated Parallel MR Image Reconstruction. CoRR abs/2007.05993 (2020) - [i101]Cheng Ouyang, Carlo Biffi, Chen Chen, Turkay Kart, Huaqi Qiu, Daniel Rueckert:
Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation. CoRR abs/2007.09886 (2020) - [i100]Vitalis Vosylius, Andy Wang, Cemlyn Waters, Alexey Zakharov, Francis Ward, Loïc Le Folgoc, John Cupitt, Antonios Makropoulos, Andreas Schuh, Daniel Rueckert, Amir Alansary:
Geometric Deep Learning for Post-Menstrual Age Prediction based on the Neonatal White Matter Cortical Surface. CoRR abs/2008.06098 (2020) - [i99]Jeremy Tan, Anselm Au, Qingjie Meng, Sandy FinesilverSmith, John M. Simpson, Daniel Rueckert, Reza Razavi, Thomas Day, David Lloyd, Bernhard Kainz:
Automated Detection of Congenital Heart Disease in Fetal Ultrasound Screening. CoRR abs/2008.06966 (2020) - [i98]Guy Leroy, Daniel Rueckert, Amir Alansary:
Communicative Reinforcement Learning Agents for Landmark Detection in Brain Images. CoRR abs/2008.08055 (2020) - [i97]Qingjie Meng, Daniel Rueckert, Bernhard Kainz:
Unsupervised Cross-domain Image Classification by Distance Metric Guided Feature Alignment. CoRR abs/2008.08433 (2020) - [i96]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: Image traits, technology trends, case studies with progress highlights, and future promises. CoRR abs/2008.09104 (2020) - [i95]Athanasios Vlontzos, Henrique Bergallo Rocha, Daniel Rueckert, Bernhard Kainz:
Causal Future Prediction in a Minkowski Space-Time. CoRR abs/2008.09154 (2020) - [i94]Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Arinbjörn Kolbeinsson, Alexander Hammers, Daniel Rueckert:
Patch-based Brain Age Estimation from MR Images. CoRR abs/2008.12965 (2020) - [i93]Moritz Knolle, Georgios Kaissis, Friederike Jungmann, Sebastian Ziegelmayer, Daniel Sasse, Marcus Makowski, Daniel Rueckert, Rickmer Braren:
Efficient, high-performance pancreatic segmentation using multi-scale feature extraction. CoRR abs/2009.00872 (2020) - [i92]Matei Grama, Maria Musat, Luis Muñoz-González, Jonathan Passerat-Palmbach, Daniel Rueckert, Amir Alansary:
Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare. CoRR abs/2009.08294 (2020) - [i91]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. CoRR abs/2010.04552 (2020) - [i90]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. CoRR abs/2011.00739 (2020) - [i89]Veneta Haralampieva, Daniel Rueckert, Jonathan Passerat-Palmbach:
A Systematic Comparison of Encrypted Machine Learning Solutions for Image Classification. CoRR abs/2011.05296 (2020) - [i88]Harry Cai, Daniel Rueckert, Jonathan Passerat-Palmbach:
2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments. CoRR abs/2011.07516 (2020) - [i87]Seoin Chai, Daniel Rueckert, Ahmed E. Fetit:
Reducing Textural Bias Improves Robustness of Deep Segmentation CNNs. CoRR abs/2011.15093 (2020) - [i86]Alexander Ziller, Jonathan Passerat-Palmbach, Theo Ryffel, Dmitrii Usynin, Andrew Trask, Ionésio Da Lima Costa Junior, Jason Mancuso, Marcus Makowski, Daniel Rueckert, Rickmer Braren, Georgios Kaissis:
Privacy-preserving medical image analysis. CoRR abs/2012.06354 (2020)
2010 – 2019
- 2019
- [j147]Igor R. R. Xavier, Gilson A. Giraldi, Stuart James Gibson, Gilka J. F. Gattas, Daniel Rueckert, Carlos E. Thomaz:
Age-related craniofacial differences based on spatio-temporal face image atlases. IET Image Process. 13(9): 1561-1568 (2019) - [j146]Amir Alansary, Ozan Oktay, Yuanwei Li, Loïc Le Folgoc, Benjamin Hou, Ghislain Vaillant, Konstantinos Kamnitsas, Athanasios Vlontzos, Ben Glocker, Bernhard Kainz, Daniel Rueckert:
Evaluating reinforcement learning agents for anatomical landmark detection. Medical Image Anal. 53: 156-164 (2019) - [j145]Jo Schlemper, Ozan Oktay, Michiel Schaap, Mattias P. Heinrich, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Attention gated networks: Learning to leverage salient regions in medical images. Medical Image Anal. 53: 197-207 (2019) - [j144]Ilkay Öksüz, Bram Ruijsink, Esther Puyol-Antón, James R. Clough, Gastao Cruz, Aurélien Bustin, Claudia Prieto, René M. Botnar, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning. Medical Image Anal. 55: 136-147 (2019) - [j143]Juan J. Cerrolaza, Mirella López Picazo, Ludovic Humbert, Yoshinobu Sato, Daniel Rueckert, Miguel Ángel González Ballester, Marius George Linguraru:
Computational anatomy for multi-organ analysis in medical imaging: A review. Medical Image Anal. 56: 44-67 (2019) - [j142]Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert:
Self-supervised learning for medical image analysis using image context restoration. Medical Image Anal. 58 (2019) - [j141]Matteo Bastiani, Jesper L. R. Andersson, Lucilio Cordero-Grande, Maria Murgasova, Jana Hutter, Anthony N. Price, Antonios Makropoulos, Sean P. Fitzgibbon, Emer J. Hughes, Daniel Rueckert, Suresh Victor, Mary A. Rutherford, A. David Edwards, Stephen M. Smith, Jacques-Donald Tournier, Joseph V. Hajnal, Saâd Jbabdi, Stamatios N. Sotiropoulos:
Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project. NeuroImage 185: 750-763 (2019) - [j140]Gabriel Balaban, Brian Halliday, Wenjia Bai, Bradley Porter, Carlotta Malvuccio, Pablo Lamata, Christopher A. Rinaldi, Gernot Plank, Daniel Rueckert, Sanjay K. Prasad, Martin J. Bishop:
Scar shape analysis and simulated electrical instabilities in a non-ischemic dilated cardiomyopathy patient cohort. PLoS Comput. Biol. 15(10) (2019) - [j139]Chen Qin, Jo Schlemper, Jose Caballero, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert:
Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction. IEEE Trans. Medical Imaging 38(1): 280-290 (2019) - [j138]Giacomo Tarroni, Ozan Oktay, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Jonathan Passerat-Palmbach, Antonio de Marvao, Declan P. O'Regan, Stuart A. Cook, Ben Glocker, Paul M. Matthews, Daniel Rueckert:
Learning-Based Quality Control for Cardiac MR Images. IEEE Trans. Medical Imaging 38(5): 1127-1138 (2019) - [j137]Jinming Duan, Ghalib Bello, Jo Schlemper, Wenjia Bai, Timothy J. W. Dawes, Carlo Biffi, Antonio de Marvao, Georgia Doumou, Declan P. O'Regan, Daniel Rueckert:
Automatic 3D Bi-Ventricular Segmentation of Cardiac Images by a Shape-Refined Multi- Task Deep Learning Approach. IEEE Trans. Medical Imaging 38(9): 2151-2164 (2019) - [j136]Qingjie Meng, James Housden, Jacqueline Matthew, Daniel Rueckert, Julia A. Schnabel, Bernhard Kainz, Matthew Sinclair, Veronika A. Zimmer, Benjamin Hou, Martin Rajchl, Nicolas Toussaint, Ozan Oktay, Jo Schlemper, Alberto Gómez:
Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging. IEEE Trans. Medical Imaging 38(12): 2755-2767 (2019) - [c355]Miguel Monteiro, Konstantinos Kamnitsas, Enzo Ferrante, Francois Mathieu, Steven McDonagh, Sam Cook, Susan Stevenson, Tilak Das, Aneesh Khetani, Tom Newman, Fred Zeiler, Richard Digby, Jonathan P. Coles, Daniel Rueckert, David K. Menon, Virginia F. J. Newcombe, Ben Glocker:
TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation. BrainLes@MICCAI (1) 2019: 13-22 - [c354]Chen Qin, Bibo Shi, Rui Liao, Tommaso Mansi, Daniel Rueckert, Ali Kamen:
Unsupervised Deformable Registration for Multi-modal Images via Disentangled Representations. IPMI 2019: 249-261 - [c353]Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni, Antonio de Marvao, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert:
3D High-Resolution Cardiac Segmentation Reconstruction From 2D Views Using Conditional Variational Autoencoders. ISBI 2019: 1643-1646 - [c352]Esther Puyol-Antón, Bram Ruijsink, James R. Clough, Ilkay Öksüz, Daniel Rueckert, Reza Razavi, Andrew P. King:
Assessing the Impact of Blood Pressure on Cardiac Function Using Interpretable Biomarkers and Variational Autoencoders. STACOM@MICCAI 2019: 22-30 - [c351]Qingjie Meng, Nick Pawlowski, Daniel Rueckert, Bernhard Kainz:
Representation Disentanglement for Multi-task Learning with Application to Fetal Ultrasound. SUSI/PIPPI@MICCAI 2019: 47-55 - [c350]Jo Schlemper, Seyed Sadegh Mohseni Salehi, Prantik Kundu, Carole Lazarus, Hadrien Dyvorne, Daniel Rueckert, Michal Sofka:
Nonuniform Variational Network: Deep Learning for Accelerated Nonuniform MR Image Reconstruction. MICCAI (3) 2019: 57-64 - [c349]Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert:
Intelligent Image Synthesis to Attack a Segmentation CNN Using Adversarial Learning. SASHIMI@MICCAI 2019: 90-99 - [c348]Benjamin Hou, Athanasios Vlontzos, Amir Alansary, Daniel Rueckert, Bernhard Kainz:
Flexible Conditional Image Generation of Missing Data with Learned Mental Maps. MLMIR@MICCAI 2019: 139-150 - [c347]Huaqi Qiu, Chen Qin, Loïc Le Folgoc, Benjamin Hou, Jo Schlemper, Daniel Rueckert:
Deep Learning for Cardiac Motion Estimation: Supervised vs. Unsupervised Training. STACOM@MICCAI 2019: 186-194 - [c346]Chen Chen, Cheng Ouyang, Giacomo Tarroni, Jo Schlemper, Huaqi Qiu, Wenjia Bai, Daniel Rueckert:
Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation. STACOM@MICCAI 2019: 209-219 - [c345]Athanasios Vlontzos, Amir Alansary, Konstantinos Kamnitsas, Daniel Rueckert, Bernhard Kainz:
Multiple Landmark Detection Using Multi-agent Reinforcement Learning. MICCAI (4) 2019: 262-270 - [c344]Robert Wright, Nicolas Toussaint, Alberto Gómez, Veronika A. M. Zimmer, Bishesh Khanal, Jacqueline Matthew, Emily Skelton, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel:
Complete Fetal Head Compounding from Multi-view 3D Ultrasound. MICCAI (3) 2019: 384-392 - [c343]Chen Qin, Jo Schlemper, Jinming Duan, Gavin Seegoolam, Anthony Price, Joseph V. Hajnal, Daniel Rueckert:
k-t NEXT: Dynamic MR Image Reconstruction Exploiting Spatio-Temporal Correlations. MICCAI (2) 2019: 505-513 - [c342]Chen Chen, Carlo Biffi, Giacomo Tarroni, Steffen E. Petersen, Wenjia Bai, Daniel Rueckert:
Learning Shape Priors for Robust Cardiac MR Segmentation from Multi-view Images. MICCAI (2) 2019: 523-531 - [c341]Wenjia Bai, Chen Chen, Giacomo Tarroni, Jinming Duan, Florian Guitton, Steffen E. Petersen, Yike Guo, Paul M. Matthews, Daniel Rueckert:
Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction. MICCAI (2) 2019: 541-549 - [c340]Cheng Ouyang, Konstantinos Kamnitsas, Carlo Biffi, Jinming Duan, Daniel Rueckert:
Data Efficient Unsupervised Domain Adaptation For Cross-modality Image Segmentation. MICCAI (2) 2019: 669-677 - [c339]Ilkay Öksüz, James R. Clough, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastao Cruz, Claudia Prieto, Daniel Rueckert, Andrew P. King, Julia A. Schnabel:
Detection and Correction of Cardiac MRI Motion Artefacts During Reconstruction from k-space. MICCAI (4) 2019: 695-703 - [c338]Gavin Seegoolam, Jo Schlemper, Chen Qin, Anthony Price, Joseph V. Hajnal, Daniel Rueckert:
Exploiting Motion for Deep Learning Reconstruction of Extremely-Undersampled Dynamic MRI. MICCAI (4) 2019: 704-712 - [c337]Jinming Duan, Jo Schlemper, Chen Qin, Cheng Ouyang, Wenjia Bai, Carlo Biffi, Ghalib Bello, Ben Statton, Declan P. O'Regan, Daniel Rueckert:
VS-Net: Variable Splitting Network for Accelerated Parallel MRI Reconstruction. MICCAI (4) 2019: 713-722 - [c336]Ognjen (Oggi) Rudovic, Yuria Utsumi, Ricardo Guerrero, Kelly Peterson, Daniel Rueckert, Rosalind W. Picard:
Meta-Weighted Gaussian Process Experts for Personalized Forecasting of AD Cognitive Changes. MLHC 2019: 181-196 - [e8]Florian Knoll, Andreas Maier, Daniel Rueckert, Jong Chul Ye:
Machine Learning for Medical Image Reconstruction - Second International Workshop, MLMIR 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Lecture Notes in Computer Science 11905, Springer 2019, ISBN 978-3-030-33842-8 [contents] - [i85]Robert Robinson, Vanya V. Valindria, Wenjia Bai, Ozan Oktay, Bernhard Kainz, Hideaki Suzuki, Mihir M. Sanghvi, Nay Aung, José Miguel Paiva, Filip Zemrak, Kenneth Fung, Elena Lukaschuk, Aaron M. Lee, Valentina Carapella, Young Jin Kim, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Chris Page, Paul M. Matthews, Daniel Rueckert, Ben Glocker:
Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study. CoRR abs/1901.09351 (2019) - [i84]Cheng Ouyang, Jo Schlemper, Carlo Biffi, Gavin Seegoolam, Jose Caballero, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert:
Generalising Deep Learning MRI Reconstruction across Different Domains. CoRR abs/1902.10815 (2019) - [i83]Carlo Biffi, Juan J. Cerrolaza,