| 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 |
| 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 |
| 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 |
| Reducing CNN textural bias with k-space artifacts improves robustness Y Cabrera, AE Fetit IEEE Access 10, 58431-58446, 2022 | 3 | 2022 |
| MRI segmentation of the developing neonatal brain: Pipeline and training strategies for label scarcity L Richter, AE Fetit Medical Imaging Meets NeurIPS, 2022 | | 2022 |
| Simulating k-space artifacts for robust CNNs Y Cabrera, AE Fetit Medical Imaging Meets NeurIPS, 2022 | | 2022 |
| Accurate segmentation of neonatal brain MRI with deep learning L Richter, AE Fetit Frontiers in Neuroinformatics 16, 2022 | 5 | 2022 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| Analysis of retinal vasculature for MACE risk stratification in patients with diabetes AE Fetit, S Hogg, R Wang, ASF Doney, G McKay, SJ McKenna, E Trucco Royal Society Science+ meeting, London, UK, 2018 | | 2018 |
| 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 |
| Mutations in genes encoding condensins cause microcephaly through decatenation failure at mitosis (vol 30, pg 2158, 2016) CA Martin, JE Murray, P Carroll, A Leitch, KJ MacKenzie, M Halachev, ... GENES & DEVELOPMENT 31 (9), 953-953, 2017 | | 2017 |
| Retinal biomarker discovery for dementia in an elderly diabetic population AE Fetit, S Manivannan, S McGrory, L Ballerini, A Doney, TJ MacGillivray, ... Fetal, Infant and Ophthalmic Medical Image Analysis: International Workshop …, 2017 | | 2017 |
| 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 |
Theodoros N. ArvanitisProfessor of Digital Health Technology & Head Dept. Electronic, Electrical & Systems Engineering UoBVerified email at bham.ac.uk
