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 | 386 | 2017 |
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 | 126 | 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 Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 92 | 2016 |
Human-level performance on automatic head biometrics in fetal ultrasound using fully convolutional neural networks M Sinclair, CF Baumgartner, J Matthew, W Bai, JC Martinez, Y Li, S Smith, ... 2018 40th annual international conference of the IEEE engineering in …, 2018 | 77 | 2018 |
Standard plane detection in 3d fetal ultrasound using an iterative transformation network Y Li, B Khanal, B Hou, A Alansary, JJ Cerrolaza, M Sinclair, J Matthew, ... International Conference on Medical Image Computing and Computer-Assisted …, 2018 | 70 | 2018 |
Beauty is in the AI of the beholder: are we ready for the clinical integration of artificial intelligence in radiography? An exploratory analysis of perceived AI knowledge … C Rainey, T O'Regan, J Matthew, E Skelton, N Woznitza, KY Chu, ... Frontiers in digital health 3, 739327, 2021 | 69 | 2021 |
Artificial Intelligence: Guidance for clinical imaging and therapeutic radiography professionals, a summary by the Society of Radiographers AI working group C Malamateniou, S McFadden, Y McQuinlan, A England, N Woznitza, ... Radiography 27 (4), 1192-1202, 2021 | 56 | 2021 |
Weakly supervised estimation of shadow confidence maps in fetal ultrasound imaging Q Meng, M Sinclair, V Zimmer, B Hou, M Rajchl, N Toussaint, O Oktay, ... IEEE transactions on medical imaging 38 (12), 2755-2767, 2019 | 55 | 2019 |
Deep learning with ultrasound physics for fetal skull segmentation JJ Cerrolaza, M Sinclair, Y Li, A Gomez, E Ferrante, J Matthew, C Gupta, ... 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 49 | 2018 |
Mutual information-based disentangled neural networks for classifying unseen categories in different domains: Application to fetal ultrasound imaging Q Meng, J Matthew, VA Zimmer, A Gomez, DFA Lloyd, D Rueckert, ... IEEE transactions on medical imaging 40 (2), 722-734, 2020 | 48 | 2020 |
Fast multiple landmark localisation using a patch-based iterative network Y Li, A Alansary, JJ Cerrolaza, B Khanal, M Sinclair, J Matthew, C Gupta, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 48 | 2018 |
Robotic-assisted ultrasound for fetal imaging: evolution from single-arm to dual-arm system S Wang, J Housden, Y Noh, D Singh, A Singh, E Skelton, J Matthew, ... Towards Autonomous Robotic Systems: 20th Annual Conference, TAROS 2019 …, 2019 | 46 | 2019 |
Fetal body MRI and its application to fetal and neonatal treatment: an illustrative review JR Davidson, A Uus, J Matthew, AM Egloff, M Deprez, I Yardley, ... The Lancet Child & Adolescent Health 5 (6), 447-458, 2021 | 41 | 2021 |
3d fetal skull reconstruction from 2dus via deep conditional generative networks JJ Cerrolaza, Y Li, C Biffi, A Gomez, M Sinclair, J Matthew, C Knight, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 40 | 2018 |
Exploring a new paradigm for the fetal anomaly ultrasound scan: Artificial intelligence in real time J Matthew, E Skelton, TG Day, VA Zimmer, A Gomez, G Wheeler, ... Prenatal diagnosis 42 (1), 49-59, 2022 | 37 | 2022 |
Confident head circumference measurement from ultrasound with real-time feedback for sonographers S Budd, M Sinclair, B Khanal, J Matthew, D Lloyd, A Gomez, N Toussaint, ... International conference on medical image computing and computer-assisted …, 2019 | 37 | 2019 |
LSTM spatial co-transformer networks for registration of 3D fetal US and MR brain images R Wright, B Khanal, A Gomez, E Skelton, J Matthew, JV Hajnal, ... Data Driven Treatment Response Assessment and Preterm, Perinatal, and …, 2018 | 36 | 2018 |
UK reporting radiographers’ perceptions of AI in radiographic image interpretation–Current perspectives and future developments C Rainey, T O'Regan, J Matthew, E Skelton, N Woznitza, KY Chu, ... Radiography 28 (4), 881-888, 2022 | 34 | 2022 |
Towards standardized acquisition with a dual-probe ultrasound robot for fetal imaging J Housden, S Wang, X Bao, J Zheng, E Skelton, J Matthew, Y Noh, ... IEEE robotics and automation letters 6 (2), 1059-1065, 2021 | 29 | 2021 |
Foetal lung volumes in pregnant women who deliver very preterm: a pilot study L Story, T Zhang, JK Steinweg, J Hutter, J Matthew, T Dassios, PT Seed, ... Pediatric research 87 (6), 1066-1071, 2020 | 26 | 2020 |