| 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 | 1538 | 2018 |
| Characterising virtual eigensignatures for general purpose face recognition DB Graham, NM Allinson Face recognition: from theory to applications, 446-456, 1998 | 747 | 1998 |
| A comprehensive review of current local features for computer vision J Li, NM Allinson Neurocomputing 71 (10-12), 1771-1787, 2008 | 413 | 2008 |
| Automated brain tumour detection and segmentation using superpixel-based extremely randomized trees in FLAIR MRI M Soltaninejad, G Yang, T Lambrou, N Allinson, TL Jones, TR Barrick, ... International journal of computer assisted radiology and surgery 12, 183-203, 2017 | 307 | 2017 |
| Proton radiography and tomography with application to proton therapy G Poludniowski, NM Allinson, PM Evans The British journal of radiology 88 (1053), 20150134, 2015 | 203 | 2015 |
| Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels M Soltaninejad, G Yang, T Lambrou, N Allinson, TL Jones, TR Barrick, ... Computer methods and programs in biomedicine 157, 69-84, 2018 | 175 | 2018 |
| Self-organizing mixture networks for probability density estimation H Yin, NM Allinson IEEE Transactions on Neural Networks 12 (2), 405-411, 2001 | 172 | 2001 |
| Multitraining support vector machine for image retrieval J Li, N Allinson, D Tao, X Li IEEE Transactions on Image Processing 15 (11), 3597-3601, 2006 | 168 | 2006 |
| Automatic individual pig detection and tracking in pig farms L Zhang, H Gray, X Ye, L Collins, N Allinson Sensors 19 (5), 1188, 2019 | 115 | 2019 |
| The yield enhancement of field-programmable gate arrays NJ Howard, AM Tyrrell, NM Allinson IEEE Transactions on Very Large Scale Integration (VLSI) Systems 2 (1), 115-123, 1994 | 109 | 1994 |
| Identifying the best machine learning algorithms for brain tumor segmentation S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... progression assessment, and overall survival prediction in the BRATS …, 2018 | 99 | 2018 |
| Image denoising using self-organizing map-based nonlinear independent component analysis M Haritopoulos, H Yin, NM Allinson Neural Networks 15 (8-9), 1085-1098, 2002 | 94 | 2002 |
| On the distribution and convergence of feature space in self-organizing maps H Yin, NM Allinson Neural computation 7 (6), 1178-1187, 1995 | 94 | 1995 |
| Recent advances with the growing hierarchical self-organizing map N Allinson, H Yin, L Allinson, J Slack, M Dittenbach, A Rauber, D Merkl Advances in Self-Organising Maps, 140-145, 2001 | 74 | 2001 |
| Face recognition from unfamiliar views: Subspace methods and pose dependency DB Graham, NM Allinson Proceedings Third IEEE International Conference on Automatic Face and …, 1998 | 74 | 1998 |
| MRI brain tumor segmentation and patient survival prediction using random forests and fully convolutional networks M Soltaninejad, L Zhang, T Lambrou, G Yang, N Allinson, X Ye Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2018 | 71 | 2018 |
| Development of non-intensified charge-coupled device area X-ray detectors NM Allinson Journal of Synchrotron Radiation 1 (1), 54-62, 1994 | 70 | 1994 |
| Automated encoding of footwear patterns for fast indexing M Pavlou, NM Allinson Image and Vision Computing 27 (4), 402-409, 2009 | 56 | 2009 |
| PRaVDA: The first solid-state system for proton computed tomography M Esposito, C Waltham, JT Taylor, S Manger, B Phoenix, T Price, ... Physica Medica 55, 149-154, 2018 | 53 | 2018 |
| Application of the CMAC input encoding scheme in the N-tuple approximation network A Kolcz, NM Allinson IEE Proceedings-Computers and Digital Techniques 141 (3), 177-183, 1994 | 53 | 1994 |
