MRI Texture Analysis in Paediatric Oncology: A Preliminary Study. - Ahmed E. Fetit; Jan Novák; Daniel Rodríguez; Dorothee P. Auer; Chris A. Clark; Richard G. Grundy; Tim Jaspan; Andrew Peet; Theodoros N. Arvanitis (ICIMTH, 2013)

3D texture analysis of MR images to improve classification of paediatric brain tumours: a preliminary study. - Ahmed E. Fetit; Jan Novák; Andrew C. Peet; Theodoros N. Arvanitis (ICIMTH, 2014)

#DigitalHealth: Exploring Users' Perspectives through Social Media Analysis. - Soroosh Afyouni; Ahmed E. Fetit; Theodoros N. Arvanitis (ICIMTH, 2015)

An Extensible Neuroimaging e-Repository for Clinical Trials of Paediatric Brain Tumours. - Ahmed E. Fetit; Omar Khan; Soroosh Afyouni; Niloufar Zarinabad Nooralipour; Jan Novák; Andrew C. Peet; Theodoros N. Arvanitis (ICIMTH, 2015)

3D Texture Analysis of Heterogeneous MRI Data for Diagnostic Classification of Childhood Brain Tumours. - Ahmed E. Fetit; Jan Novák; Daniel Rodríguez; Dorothee P. Auer; Chris A. Clark; Richard G. Grundy; Tim Jaspan; Andrew C. Peet; Theodoros N. Arvanitis (ICIMTH, 2015)

Retinal Biomarker Discovery for Dementia in an Elderly Diabetic Population. - Ahmed E. Fetit; Siyamalan Manivannan; Sarah McGrory; Lucia Ballerini; Alexander S. Doney; Thomas J. MacGillivray; Ian J. Deary; Joanna M. Wardlaw; Fergus Doubal; Gareth J. McKay; Stephen J. McKenna; Emanuele Trucco (FIFI/OMIA@MICCAI, 2017)

XmoNet: A Fully Convolutional Network for Cross-Modality MR Image Inference. - Sophia Bano; Muhammad Asad 001; Ahmed E. Fetit; Islem Rekik (PRIME@MICCAI, 2018)

A deep learning approach to segmentation of the developing cortex in fetal brain MRI with minimal manual labeling. - Ahmed E. Fetit; Amir Alansary; Lucilio Cordero-Grande; John Cupitt; Alice B. Davidson; A. David Edwards; Joseph V. Hajnal; Emer J. Hughes; Konstantinos Kamnitsas; Vanessa Kyriakopoulou; Antonios Makropoulos; Prachi A. Patkee; et al. (MIDL, 2020)

Training deep segmentation networks on texture-encoded input: application to neuroimaging of the developing neonatal brain. - Ahmed E. Fetit; John Cupitt; Turkay Kart; Daniel Rueckert (MIDL, 2020)

Retinal Biomarkers Discovery for Cerebral Small Vessel Disease in an Older Population. - Lucia Ballerini; Ahmed E. Fetit; Stephan Wunderlich; Ruggiero Lovreglio; Sarah McGrory; Maria del Carmen Valdés Hernández; Tom J. MacGillivray; Fergus Doubal; Ian J. Deary; Joanna M. Wardlaw; Emanuele Trucco (MIUA, 2020)

Reducing Textural Bias Improves Robustness of Deep Segmentation CNNs. - Seoin Chai; Daniel Rueckert; Ahmed E. Fetit (CoRR, 2020)

Reducing Textural Bias Improves Robustness of Deep Segmentation Models. - Seoin Chai; Daniel Rueckert; Ahmed E. Fetit (MIUA, 2021)

How Effective is Adversarial Training of CNNs in Medical Image Analysis? - Yiming Xie; Ahmed E. Fetit (MIUA, 2022)

Reducing CNN Textural Bias With k-Space Artifacts Improves Robustness. - Yaniel Cabrera; Ahmed E. Fetit (IEEE Access, 2022)

Accurate segmentation of neonatal brain MRI with deep learning. - Leonie Richter; Ahmed E. Fetit (Frontiers Neuroinformatics, 2022)

Web-Based AI System for Medical Image Segmentation. - Hao Chen; Taowen Liu; Songyun Hu; Leyang Yu; Yiqi Li; Sihan Tao; Jacqueline Lee; Ahmed E. Fetit (MIUA, 2023)