Ahmed E. Fetit

According to our database, Ahmed E. Fetit authored at least 16 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

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

Proceedings of the Medical Image Understanding and Analysis - 27th Annual Conference, 2023

2022

Accurate segmentation of neonatal brain MRI with deep learning.

Leonie Richter, Ahmed E. Fetit

Frontiers Neuroinformatics, 2022

Reducing CNN Textural Bias With k-Space Artifacts Improves Robustness.

Yaniel Cabrera, Ahmed E. Fetit

IEEE Access, 2022

How Effective is Adversarial Training of CNNs in Medical Image Analysis?

Yiming Xie, Ahmed E. Fetit

Proceedings of the Medical Image Understanding and Analysis - 26th Annual Conference, 2022

2021

Reducing Textural Bias Improves Robustness of Deep Segmentation Models.

Seoin Chai, Daniel Rueckert, Ahmed E. Fetit

Proceedings of the Medical Image Understanding and Analysis - 25th Annual Conference, 2021

2020

Reducing Textural Bias Improves Robustness of Deep Segmentation CNNs.

Seoin Chai, Daniel Rueckert, Ahmed E. Fetit

CoRR, 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

Proceedings of the Medical Image Understanding and Analysis - 24th Annual Conference, 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

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

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, Anthony N. Price, Mary A. Rutherford, Daniel Rueckert

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

2018

XmoNet: A Fully Convolutional Network for Cross-Modality MR Image Inference.

Sophia Bano, Muhammad Asad, Ahmed E. Fetit, Islem Rekik

Proceedings of the PRedictive Intelligence in MEdicine - First International Workshop, 2018

2017

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

Proceedings of the Fetal, Infant and Ophthalmic Medical Image Analysis, 2017

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

Proceedings of the Enabling Health Informatics Applications [ICIMTH 2015, 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

Proceedings of the Enabling Health Informatics Applications [ICIMTH 2015, 2015

#DigitalHealth: Exploring Users' Perspectives through Social Media Analysis.

Soroosh Afyouni, Ahmed E. Fetit, Theodoros N. Arvanitis

Proceedings of the Enabling Health Informatics Applications [ICIMTH 2015, 2015

2014

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

Proceedings of the Integrating Information Technology and Management for Quality of Care [ICIMTH 2014, 2014

2013

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

Proceedings of the Informatics, 2013