| You said that? JS Chung, A Jamaludin, A Zisserman British Machine Vision Conference 2017, 2017 | 248 | 2017 |
| ISSLS Prize in Bioengineering Science 2017: Automation of reading of radiological features from magnetic resonance images (MRIs) of the lumbar spine without human intervention … A Jamaludin, M Lootus, T Kadir, A Zisserman, J Urban, MC Battié, ... | 172* | 2017 |
| You said that?: Synthesising talking faces from audio A Jamaludin, JS Chung, A Zisserman International Journal of Computer Vision 127, 1767-1779, 2019 | 163 | 2019 |
| SpineNet: Automated classification and evidence visualization in spinal MRIs A Jamaludin, T Kadir, A Zisserman Medical Image Analysis 41, 63-73, 2017 | 130 | 2017 |
| Self-supervised learning for spinal MRIs A Jamaludin, T Kadir, A Zisserman Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2017 | 79 | 2017 |
| SpineNet: automatically pinpointing classification evidence in spinal MRIs A Jamaludin, T Kadir, A Zisserman International Conference on Medical Image Computing and Computer-Assisted …, 2016 | 76 | 2016 |
| Could automated machine-learned MRI grading aid epidemiological studies of lumbar spinal stenosis? Validation within the Wakayama spine study Y Ishimoto, A Jamaludin, C Cooper, K Walker-Bone, H Yamada, ... BMC Musculoskeletal Disorders 21, 1-6, 2020 | 18 | 2020 |
| A convolutional approach to vertebrae detection and labelling in whole spine MRI R Windsor, A Jamaludin, T Kadir, A Zisserman Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 18 | 2020 |
| Automatic Modic changes classification in spinal MRI A Jamaludin, T Kadir, A Zisserman International Workshop and Challenge on Computational Methods and Clinical …, 2015 | 18 | 2015 |
| Automatic intervertebral discs localization and segmentation: a vertebral approach A Jamaludin, M Lootus, T Kadir, A Zisserman International Workshop and Challenge on Computational Methods and Clinical …, 2015 | 13 | 2015 |
| External validation of the deep learning system “SpineNet” for grading radiological features of degeneration on MRIs of the lumbar spine A Grob, M Loibl, A Jamaludin, S Winklhofer, JCT Fairbank, T Fekete, ... European Spine Journal 31 (8), 2137-2148, 2022 | 12 | 2022 |
| Identifying Scoliosis in Population‑Based Cohorts: Automation of a Validated Method Based on Total Body Dual Energy X‑ray Absorptiometry Scans J Amir, J Fairbank, I Harding, K Timor, TJ Peters, A Zisserman, EM Clark Calcified Tissue International 107 (2), 201-201, 2020 | 12* | 2020 |
| Pattern recognition in musculoskeletal imaging using artificial intelligence N Gorelik, J Chong, DJ Lin Seminars in musculoskeletal radiology 24 (01), 38-49, 2020 | 12 | 2020 |
| Self-supervised multi-modal alignment for whole body medical imaging R Windsor, A Jamaludin, T Kadir, A Zisserman Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 11 | 2021 |
| Accurate prediction of lumbar microdecompression level with an automated MRI grading system BL Roller, RD Boutin, TJ O’Gara, ZO Knio, A Jamaludin, J Tan, L Lenchik Skeletal Radiology 50, 69-78, 2021 | 11 | 2021 |
| Context-aware transformers for spinal cancer detection and radiological grading R Windsor, A Jamaludin, T Kadir, A Zisserman International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 8 | 2022 |
| Predicting Scoliosis in DXA Scans Using Intermediate Representations A Jamaludin, T Kadir, E Clark, A Zisserman | 8 | 2018 |
| Vision-language modelling for radiological imaging and reports in the low data regime R Windsor, A Jamaludin, T Kadir, A Zisserman arXiv preprint arXiv:2303.17644, 2023 | 7 | 2023 |
| A deep learning approach to private data sharing of medical images using conditional generative adversarial networks (GANs) H Sun, J Plawinski, S Subramaniam, A Jamaludin, T Kadir, A Readie, ... Plos one 18 (7), e0280316, 2023 | 5* | 2023 |
| SpineNetV2: automated detection, labelling and radiological grading of clinical MR scans R Windsor, A Jamaludin, T Kadir, A Zisserman arXiv preprint arXiv:2205.01683, 2022 | 5 | 2022 |
Andrew ZissermanUniversity of OxfordAdresse e-mail validée de robots.ox.ac.uk
