| Attention u-net: Learning where to look for the pancreas O Oktay, J Schlemper, LL Folgoc, M Lee, M Heinrich, K Misawa, K Mori, ... arXiv preprint arXiv:1804.03999, 2018 | 271 | 2018 |
| Anatomically constrained neural networks (ACNNs): application to cardiac image enhancement and segmentation O Oktay, E Ferrante, K Kamnitsas, M Heinrich, W Bai, J Caballero, ... IEEE transactions on medical imaging 37 (2), 384-395, 2017 | 271 | 2017 |
| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 235 | 2018 |
| Ensembles of multiple models and architectures for robust brain tumour segmentation K Kamnitsas, W Bai, E Ferrante, S McDonagh, M Sinclair, N Pawlowski, ... International MICCAI Brainlesion Workshop, 450-462, 2017 | 178 | 2017 |
| Magnetic resonance–derived 3-dimensional blood flow patterns in the main pulmonary artery as a marker of pulmonary hypertension and a measure of elevated mean pulmonary … G Reiter, U Reiter, G Kovacs, B Kainz, K Schmidt, R Maier, H Olschewski, ... Circulation: Cardiovascular Imaging 1 (1), 23-30, 2008 | 176 | 2008 |
| Automated cardiovascular magnetic resonance image analysis with fully convolutional networks W Bai, M Sinclair, G Tarroni, O Oktay, M Rajchl, G Vaillant, AM Lee, ... Journal of Cardiovascular Magnetic Resonance 20 (1), 65, 2018 | 136 | 2018 |
| Deepcut: Object segmentation from bounding box annotations using convolutional neural networks M Rajchl, MCH Lee, O Oktay, K Kamnitsas, J Passerat-Palmbach, W Bai, ... IEEE transactions on medical imaging 36 (2), 674-683, 2016 | 128 | 2016 |
| Fast volume reconstruction from motion corrupted stacks of 2D slices B Kainz, M Steinberger, W Wein, M Kuklisova-Murgasova, ... IEEE transactions on medical imaging 34 (9), 1901-1913, 2015 | 93 | 2015 |
| SonoNet: real-time detection and localisation of fetal standard scan planes in freehand ultrasound CF Baumgartner, K Kamnitsas, J Matthew, TP Fletcher, S Smith, LM Koch, ... IEEE transactions on medical imaging 36 (11), 2204-2215, 2017 | 77 | 2017 |
| Attention gated networks: Learning to leverage salient regions in medical images J Schlemper, O Oktay, M Schaap, M Heinrich, B Kainz, B Glocker, ... Medical image analysis 53, 197-207, 2019 | 72 | 2019 |
| OmniKinect: real-time dense volumetric data acquisition and applications B Kainz, S Hauswiesner, G Reitmayr, M Steinberger, R Grasset, L Gruber, ... Proceedings of the 18th ACM symposium on Virtual reality software and …, 2012 | 71 | 2012 |
| Automated fetal brain segmentation from 2D MRI slices for motion correction K Keraudren, M Kuklisova-Murgasova, V Kyriakopoulou, C Malamateniou, ... NeuroImage 101, 633-643, 2014 | 69 | 2014 |
| ScatterAlloc: Massively parallel dynamic memory allocation for the GPU M Steinberger, M Kenzel, B Kainz, D Schmalstieg 2012 Innovative Parallel Computing (InPar), 1-10, 2012 | 64 | 2012 |
| Ray casting of multiple volumetric datasets with polyhedral boundaries on manycore GPUs B Kainz, M Grabner, A Bornik, S Hauswiesner, J Muehl, D Schmalstieg ACM Transactions on Graphics (TOG) 28 (5), 1-9, 2009 | 64 | 2009 |
| Softshell: dynamic scheduling on GPUs M Steinberger, B Kainz, B Kerbl, S Hauswiesner, M Kenzel, ... ACM Transactions on Graphics (TOG) 31 (6), 1-11, 2012 | 49 | 2012 |
| Dltk: State of the art reference implementations for deep learning on medical images N Pawlowski, SI Ktena, MCH Lee, B Kainz, D Rueckert, B Glocker, ... arXiv preprint arXiv:1711.06853, 2017 | 39 | 2017 |
| Fast fully automatic segmentation of the human placenta from motion corrupted MRI A Alansary, K Kamnitsas, A Davidson, R Khlebnikov, M Rajchl, ... International Conference on Medical Image Computing and Computer-Assisted …, 2016 | 37 | 2016 |
| Automatic differentiation for GPU-accelerated 2D/3D registration M Grabner, T Pock, T Gross, B Kainz Advances in automatic differentiation, 259-269, 2008 | 35 | 2008 |
| Attention-gated networks for improving ultrasound scan plane detection J Schlemper, O Oktay, L Chen, J Matthew, C Knight, B Kainz, B Glocker, ... arXiv preprint arXiv:1804.05338, 2018 | 34 | 2018 |
| Real-time standard scan plane detection and localisation in fetal ultrasound using fully convolutional neural networks CF Baumgartner, K Kamnitsas, J Matthew, S Smith, B Kainz, D Rueckert International conference on medical image computing and computer-assisted …, 2016 | 32 | 2016 |
Daniel RueckertProfessor of Visual Information Processing, Imperial College LondonVerified email at imperial.ac.uk
