| Learning From Noisy Labels By Regularized Estimation Of Annotator Confusion R Tanno, A Saeedi, S Sankaranarayanan, DC Alexander, N Silberman Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 181 | 2019 |
| Adaptive Neural Trees R Tanno, K Arulkumaran, DC Alexander, A Criminisi, A Nori International Conference on Machine Learning (ICML), 2019 | 157 | 2019 |
| Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution R Tanno, D E. Worrall, A Ghosh, E Kaden, S N. Sotiropoulos, A Criminisi, ... MICCAI, Best Paper Award 10433, 611-619, 2017 | 156 | 2017 |
| Image quality transfer and applications in diffusion MRI DC Alexander, D Zikic, A Ghosh, R Tanno, V Wottschel, J Zhang, E Kaden, ... NeuroImage 152, 283-298, 2017 | 115 | 2017 |
| Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement R Tanno, D E. Worrall, E Kaden, A Gosh, F Grussu, A Bizzi, ... NeuroImage, 2020 | 106* | 2020 |
| Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms CMW Tax, F Grussu, E Kaden, L Ning, U Rudrapatna, CJ Evans, ... NeuroImage 195, 285-299, 2019 | 103* | 2019 |
| Semi-Supervised Learning via Compact Latent Space Clustering K Kamnitsas, DC Castro, LL Folgoc, I Walker, R Tanno, D Rueckert, ... International Conference on Machine Learning (ICML), 2018, 2018 | 94 | 2018 |
| Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels FJS Bragman*, R Tanno*, S Ourselin, DC Alexander, MJ Cardoso Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2019 | 65 | 2019 |
| Disentangling Human Error from the Ground Truth in Segmentation of Medical Images L Zhang*, R Tanno*, M Xu, C Jin, J Jacob, O Ciccarelli, F Barkhof, ... Neural Information Processing Systems (NeurIPS) 34, 2020 | 59 | 2020 |
| Uncertainty in Multitask Learning: Joint Representations for Probabilistic MR-only Radiotherapy Planning F J.S. Bragman*, R Tanno*, Z Eaton-Rosen, W Li, D J. Hawkes, ... International Conference on Medical Image Computing and Computer-Assisted …, 2018 | 56* | 2018 |
| Deeper image quality transfer: Training low-memory neural networks for 3D images SB Blumberg, R Tanno, I Kokkinos, DC Alexander International Conference on Medical Image Computing and Computer-Assisted …, 2018 | 52 | 2018 |
| Evaluation of deep learning to augment image-guided radiotherapy for head and neck and prostate cancers O Oktay, J Nanavati, A Schwaighofer, D Carter, M Bristow, R Tanno, ... JAMA network open 3 (11), e2027426-e2027426, 2020 | 48 | 2020 |
| Active label cleaning: Improving dataset quality under resource constraints M Bernhardt*, DC Castro*, R Tanno*, A Schwaighofer, KC Tezcan, ... Nature Communications, 2021 | 30 | 2021 |
| Bayesian Image Quality Transfer R Tanno, A Ghosh, F Grussu, E Kaden, A Criminisi, DC Alexander Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016 …, 2016 | 28 | 2016 |
| Let's agree to disagree: learning highly debatable multirater labelling CH Sudre, BG Anson, S Ingala, CD Lane, D Jimenez, L Haider, ... International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 24 | 2019 |
| Multi-Stage Prediction Networks for Data Harmonization SB Blumberg, M Palombo, CS Khoo, CMW Tax, R Tanno, DC Alexander International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 22 | 2019 |
| Learning to Downsample for Segmentation of Ultra-High Resolution Images C Jin, R Tanno, T Mertzanidou, E Panagiotaki, DC Alexander International Conference on Learning Representations (ICLR), 2022 | 20 | 2022 |
| Learning to Segment When Experts Disagree L Zhang*, R Tanno*, K Bronik, C Jin, P Nachev, F Barkhof, O Ciccarelli, ... International Conference on Medical Image Computing and Computer-Assisted …, 2020 | 16 | 2020 |
| Deep learning for low-field to high-field MR: image quality transfer with probabilistic decimation simulator H Lin, M Figini, R Tanno, SB Blumberg, E Kaden, G Ogbole, BJ Brown, ... Machine Learning for Medical Image Reconstruction: Second International …, 2019 | 16 | 2019 |
| Autodvt: Joint real-time classification for vein compressibility analysis in deep vein thrombosis ultrasound diagnostics R Tanno, A Makropoulos, S Arslan, O Oktay, S Mischkewitz, F Al-Noor, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 12 | 2018 |
Daniel C. AlexanderProfessor of Imaging Science, Centre for Medical Image Computing, Department of Computer Science在 cs.ucl.ac.uk 的电子邮件经过验证
