| Photo-realistic single image super-resolution using a generative adversarial network C Ledig, L Theis, F Huszár, J Caballero, A Cunningham, A Acosta, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 13635 | 2016 |
| Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation K Kamnitsas, C Ledig, VFJ Newcombe, JP Simpson, AD Kane, DK Menon, ... Medical image analysis 36, 61-78, 2017 | 3699 | 2017 |
| Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research AIR Maas, DK Menon, PD Adelson, N Andelic, MJ Bell, A Belli, P Bragge, ... The Lancet Neurology 16 (12), 987-1048, 2017 | 2291 | 2017 |
| Real-time video super-resolution with spatio-temporal networks and motion compensation J Caballero, C Ledig, A Aitken, A Acosta, J Totz, Z Wang, W Shi Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 827 | 2017 |
| Unsupervised domain adaptation in brain lesion segmentation with adversarial networks K Kamnitsas, C Baumgartner, C Ledig, V Newcombe, J Simpson, A Kane, ... Information Processing in Medical Imaging: 25th International Conference …, 2017 | 576 | 2017 |
| ISLES 2015-A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI O Maier, BH Menze, J Von der Gablentz, L Häni, MP Heinrich, M Liebrand, ... Medical image analysis 35, 250-269, 2017 | 528 | 2017 |
| DeepMedic for brain tumor segmentation K Kamnitsas, E Ferrante, S Parisot, C Ledig, AV Nori, A Criminisi, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2016 | 414 | 2016 |
| Automatic whole brain MRI segmentation of the developing neonatal brain A Makropoulos, IS Gousias, C Ledig, P Aljabar, A Serag, JV Hajnal, ... IEEE transactions on medical imaging 33 (9), 1818-1831, 2014 | 409 | 2014 |
| Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge EE Bron, M Smits, WM Van Der Flier, H Vrenken, F Barkhof, P Scheltens, ... NeuroImage 111, 562-579, 2015 | 366 | 2015 |
| Cardiac image super-resolution with global correspondence using multi-atlas patchmatch W Shi, J Caballero, C Ledig, X Zhuang, W Bai, K Bhatia, ... Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013 | 307 | 2013 |
| Robust whole-brain segmentation: application to traumatic brain injury C Ledig, RA Heckemann, A Hammers, JC Lopez, VFJ Newcombe, ... Medical image analysis 21 (1), 40-58, 2015 | 208 | 2015 |
| Checkerboard artifact free sub-pixel convolution: A note on sub-pixel convolution, resize convolution and convolution resize A Aitken, C Ledig, L Theis, J Caballero, Z Wang, W Shi arXiv preprint arXiv:1707.02937, 2017 | 198 | 2017 |
| Differential diagnosis of neurodegenerative diseases using structural MRI data J Koikkalainen, H Rhodius-Meester, A Tolonen, F Barkhof, B Tijms, ... NeuroImage: Clinical 11, 435-449, 2016 | 188 | 2016 |
| Is the deconvolution layer the same as a convolutional layer? W Shi, J Caballero, L Theis, F Huszar, A Aitken, C Ledig, Z Wang arXiv preprint arXiv:1609.07009, 2016 | 186 | 2016 |
| Multi-atlas segmentation with augmented features for cardiac MR images W Bai, W Shi, C Ledig, D Rueckert Medical image analysis 19 (1), 98-109, 2015 | 186 | 2015 |
| Structural brain imaging in Alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database C Ledig, A Schuh, R Guerrero, RA Heckemann, D Rueckert Scientific reports 8 (1), 11258, 2018 | 180 | 2018 |
| Multi-scale 3D convolutional neural networks for lesion segmentation in brain MRI K Kamnitsas, L Chen, C Ledig, D Rueckert, B Glocker Ischemic stroke lesion segmentation 13, 46, 2015 | 169 | 2015 |
| A novel grading biomarker for the prediction of conversion from mild cognitive impairment to Alzheimer's disease T Tong, Q Gao, R Guerrero, C Ledig, L Chen, D Rueckert, ... IEEE Transactions on Biomedical Engineering 64 (1), 155-165, 2016 | 164 | 2016 |
| Super resolution using a generative adversarial network W Shi, C Ledig, Z Wang, L Theis, F Huszar US Patent 11,024,009, 2021 | 161 | 2021 |
| Automatic quantification of normal cortical folding patterns from fetal brain MRI R Wright, V Kyriakopoulou, C Ledig, MA Rutherford, JV Hajnal, ... Neuroimage 91, 21-32, 2014 | 144 | 2014 |
