| 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 | 3288 | 2018 |
| 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 | 951 | 2019 |
| 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 | 673 | 2017 |
| MIND: Modality independent neighbourhood descriptor for multi-modal deformable registration MP Heinrich, M Jenkinson, M Bhushan, T Matin, FV Gleeson, M Brady, ... Medical image analysis 16 (7), 1423-1435, 2012 | 605 | 2012 |
| Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge K Murphy, B Van Ginneken, JM Reinhardt, S Kabus, K Ding, X Deng, ... IEEE transactions on medical imaging 30 (11), 1901-1920, 2011 | 478 | 2011 |
| 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 | 429 | 2017 |
| MRF-based deformable registration and ventilation estimation of lung CT MP Heinrich, M Jenkinson, SM Brady, JA Schnabel IEEE Transaction on Medical Imaging 32 (7), 1239-48, 2013 | 257 | 2013 |
| Evaluation of algorithms for multi-modality whole heart segmentation: an open-access grand challenge X Zhuang, L Li, C Payer, D Štern, M Urschler, MP Heinrich, J Oster, ... Medical image analysis 58, 101537, 2019 | 203 | 2019 |
| Cloud-based evaluation of anatomical structure segmentation and landmark detection algorithms: VISCERAL anatomy benchmarks O Jimenez-del-Toro, H Müller, M Krenn, K Gruenberg, AA Taha, ... IEEE transactions on medical imaging 35 (11), 2459-2475, 2016 | 180 | 2016 |
| Towards realtime multimodal fusion for image-guided interventions using self-similarities MP Heinrich, M Jenkinson, BW Papież, SM Brady, JA Schnabel Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013 | 177 | 2013 |
| Evaluating fibre orientation dispersion in white matter: Comparison of diffusion MRI, histology and polarized light imaging J Mollink, M Kleinnijenhuis, AMC van Walsum, SN Sotiropoulos, ... Neuroimage 157, 561-574, 2017 | 149 | 2017 |
| Evaluation of six registration methods for the human abdomen on clinically acquired CT Z Xu, CP Lee, MP Heinrich, M Modat, D Rueckert, S Ourselin, ... IEEE Transactions on Biomedical Engineering 63 (8), 1563-1572, 2016 | 136 | 2016 |
| ISLES 2016 and 2017-benchmarking ischemic stroke lesion outcome prediction based on multispectral MRI S Winzeck, A Hakim, R McKinley, JA Pinto, V Alves, C Silva, M Pisov, ... Frontiers in neurology 9, 679, 2018 | 134 | 2018 |
| An implicit sliding-motion preserving regularisation via bilateral filtering for deformable image registration BW Papież, MP Heinrich, J Fehrenbach, L Risser, JA Schnabel Medical image analysis 18 (8), 1299-1311, 2014 | 99 | 2014 |
| Closing the Gap between Deep and Conventional Image Registration using Probabilistic Dense Displacement Networks MP Heinrich MICCAI 2019, 1-9, 2019 | 84 | 2019 |
| Estimation of large motion in lung CT by integrating regularized keypoint correspondences into dense deformable registration J Rühaak, T Polzin, S Heldmann, IJA Simpson, H Handels, J Modersitzki, ... IEEE transactions on medical imaging 36 (8), 1746-1757, 2017 | 84 | 2017 |
| Stratified Decision Forests for Accurate Anatomical Landmark Localization O Oktay, W Bai, R Guerrero, M Rajchl, A de Marvao, DO Regan, S Cook, ... IEEE Transactions on Medical Imaging, 2016 | 74 | 2016 |
| Deformable image registration by combining uncertainty estimates from supervoxel belief propagation MP Heinrich, IJA Simpson, BŁW Papież, M Brady, JA Schnabel Medical image analysis 27, 57-71, 2016 | 74 | 2016 |
| OBELISK-Net: Fewer layers to solve 3D multi-organ segmentation with sparse deformable convolutions MP Heinrich, O Oktay, N Bouteldja Medical image analysis 54, 1-9, 2019 | 70 | 2019 |
| Globally Optimal Deformable Registration on a Minimum Spanning Tree Using Dense Displacement Sampling M Heinrich, M Jenkinson, S Brady, J Schnabel Medical Image Computing and Computer-Assisted Intervention–MICCAI 2012, 115-122, 2012 | 63 | 2012 |
Julia A SchnabelTechnical University of Munich, Helmholtz Munich and King's College LondonVerified email at tum.de
