Ahmed E. Fetit
Ahmed E. Fetit
Senior Research & Teaching Fellow, Imperial College London
Correu electrònic verificat a imperial.ac.uk
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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
En aquests moments el sistema no pot dur a terme l'operació. Torneu-ho a provar més tard.
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