Ahmed E. Fetit
Ahmed E. Fetit
Senior Research & Teaching Fellow, Imperial College London
Verified email at imperial.ac.uk
Title
Cited by
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
78*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
532015
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
322018
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
14*2014
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), 1-10, 2019
102019
#DigitalHealth: Exploring Users' Perspectives through Social Media Analysis
S Afyouni, AE Fetit, TN Arvanitis
Studies in health technology and informatics 213, 243, 2015
102015
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
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
42015
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
32020
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
22020
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
22018
Reducing Textural Bias Improves Robustness of Deep Segmentation Models
S Chai, D Rueckert, AE Fetit
Annual Conference on Medical Image Understanding and Analysis, 294-304, 2021
2021
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
2020
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
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, 150-158, 2017
2017
Corrigendum: Mutations in genes encoding condensins cause microcephaly through decatenation failure at mitosis
CA Martin, JE Murray, P Carroll, A Leitch, KJ MacKenzie, M Halachev, ...
Genes & development 31 (9), 953, 2017
2017
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
2015
Radiomics in paediatric neuro-oncology: MRI textural features as diagnostic and prognostic biomarkers
AE Fetit
University of Warwick, 2015
2015
The system can't perform the operation now. Try again later.
Articles 1–18