Mutations in genes encoding condensin complex proteins cause microcephaly through decatenation failure at mitosis CA Martin, JE Murray, P Carroll, A Leitch, KJ Mackenzie, M Halachev, ... Genes & development 30 (19), 2158-2172, 2016 | 122* | 2016 |
Three‐dimensional textural features of conventional MRI improve diagnostic classification of childhood brain tumours AE Fetit, J Novak, AC Peet, TN Arvanitis NMR in Biomedicine 28 (9), 1174-1184, 2015 | 80 | 2015 |
Radiomics in paediatric neuro‐oncology: a multicentre study on MRI texture analysis AE Fetit, J Novak, D Rodriguez, DP Auer, CA Clark, RG Grundy, AC Peet, ... NMR in Biomedicine 31 (1), e3781, 2018 | 53 | 2018 |
A multimodal approach to cardiovascular risk stratification in patients with type 2 diabetes incorporating retinal, genomic and clinical features AE Fetit, AS Doney, S Hogg, R Wang, T MacGillivray, JM Wardlaw, ... Scientific reports 9 (1), 3591, 2019 | 24 | 2019 |
#DigitalHealth: Exploring Users' Perspectives through Social Media Analysis S Afyouni, AE Fetit, TN Arvanitis Studies in health technology and informatics 213, 243, 2015 | 20 | 2015 |
3D texture analysis of MR images to improve classification of paediatric brain tumours: a preliminary study AE Fetit, J Novak, A Peet, T Arvanitis Studies in health technology and informatics 202, 213-6, 2014 | 15* | 2014 |
A deep learning approach to segmentation of the developing cortex in fetal brain MRI with minimal manual labeling AE Fetit, A Alansary, L Cordero-Grande, J Cupitt, AB Davidson, ... Medical Imaging with Deep Learning, 241-261, 2020 | 14 | 2020 |
Training deep segmentation networks on texture-encoded input: application to neuroimaging of the developing neonatal brain AE Fetit, J Cupitt, T Kart, D Rueckert Medical Imaging with Deep Learning, 230-240, 2020 | 8 | 2020 |
3D Texture Analysis of Heterogeneous MRI Data for Diagnostic Classification of Childhood Brain Tumours. AE Fetit, J Novak, D Rodriguez, DP Auer, CA Clark, RG Grundy, T Jaspan, ... Studies in health technology and informatics 213, 19, 2015 | 8 | 2015 |
Accurate segmentation of neonatal brain MRI with deep learning L Richter, AE Fetit Frontiers in Neuroinformatics 16, 2022 | 5 | 2022 |
MRI texture analysis in paediatric oncology: a preliminary study. AE Fetit, J Novak, D Rodriguez, DP Auer, CA Clark, RG Grundy, T Jaspan, ... Studies in health technology and informatics 190, 169-171, 2013 | 5* | 2013 |
Maturational networks of human fetal brain activity reveal emerging connectivity patterns prior to ex-utero exposure VR Karolis, SP Fitzgibbon, L Cordero-Grande, SR Farahibozorg, AN Price, ... Communications Biology 6 (1), 661, 2023 | 3 | 2023 |
How Effective is Adversarial Training of CNNs in Medical Image Analysis? Y Xie, AE Fetit Annual Conference on Medical Image Understanding and Analysis, 443-457, 2022 | 3 | 2022 |
Reducing CNN textural bias with k-space artifacts improves robustness Y Cabrera, AE Fetit IEEE Access 10, 58431-58446, 2022 | 3 | 2022 |
Retinal Biomarkers Discovery for Cerebral Small Vessel Disease in an Older Population L Ballerini, AE Fetit, S Wunderlich, R Lovreglio, S McGrory, ... Medical Image Understanding and Analysis, 400-409, 2020 | 3 | 2020 |
XmoNet: A fully convolutional network for cross-modality MR image inference S Bano, M Asad, AE Fetit, I Rekik International Workshop on Predictive Intelligence in Medicine, 129-137, 2018 | 3 | 2018 |
Reducing textural bias improves robustness of deep segmentation models S Chai, D Rueckert, AE Fetit Medical Image Understanding and Analysis: 25th Annual Conference, MIUA 2021 …, 2021 | 2 | 2021 |
Maturational networks of fetal brain activity VR Karolis, SP Fitzgibbon, L Cordero-Grande, R Farahibozorg, AN Price, ... bioRxiv, 2022.06. 14.495883, 2022 | 1 | 2022 |
An Extensible Neuroimaging e-Repository for Clinical Trials of Paediatric Brain Tumours. AE Fetit, O Khan, S Afyouni, N Zarinabad, J Novak, AC Peet, TN Arvanitis Studies in health technology and informatics 213, 49, 2015 | 1 | 2015 |
Web-Based AI System for Medical Image Segmentation H Chen, T Liu, S Hu, L Yu, Y Li, S Tao, J Lee, AE Fetit Annual Conference on Medical Image Understanding and Analysis, 231-241, 2023 | | 2023 |