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Ahmed E. Fetit
Ahmed E. Fetit
Verified email at imperial.ac.uk - Homepage
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Cited by
Year
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
120*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
792015
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
522018
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
232019
#DigitalHealth: Exploring Users' Perspectives through Social Media Analysis
S Afyouni, AE Fetit, TN Arvanitis
Studies in health technology and informatics 213, 243, 2015
202015
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
152020
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
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
82020
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
82015
Accurate segmentation of neonatal brain MRI with deep learning
L Richter, AE Fetit
Frontiers in Neuroinformatics 16, 2022
52022
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
Reducing CNN textural bias with k-space artifacts improves robustness
Y Cabrera, AE Fetit
IEEE Access 10, 58431-58446, 2022
32022
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
32018
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
22023
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
22022
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
22021
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
22020
Maturational networks of fetal brain activity
VR Karolis, SP Fitzgibbon, L Cordero-Grande, SR Farahibozorg, AN Price, ...
bioRxiv, 2022.06. 14.495883, 2022
12022
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
12015
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
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