Ahmed E. Fetit

426 citations
12 papers · 169 · h-index 7

Impact in

Papers in

Ahmed E. Fetit

11 papers receiving 167 citations

Peers

Ahmed E. Fetit
Comparison fields: 5 of 53
  • Health Informatics 15
  • Radiology, Nuclear Medicine and Imaging 122
  • Genetics 51
  • Neurology 20
  • Ophthalmology 12
Replace Amir Shafaat with:
Amir Shafaat Iran
Rania Abdelkhaleq United States
Debanjan Haldar United States
Domenique M. J. Müller Netherlands
Amer Alaref Canada
Seyyed Ali Hosseini Iran
Alain Jungo Switzerland
Marko Grahovac Austria
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Countries citing papers authored by Ahmed E. Fetit

Since Specialization
Citations

This map shows the geographic impact of Ahmed E. Fetit's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ahmed E. Fetit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ahmed E. Fetit more than expected).

Fields of papers citing papers by Ahmed E. Fetit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ahmed E. Fetit. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ahmed E. Fetit. The network helps show where Ahmed E. Fetit may publish in the future.

Co-authors

The 25 scholars most cited alongside Ahmed E. Fetit, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ahmed E. Fetit Line = papers co-authored together Ahmed E. Fetit links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 201556
2 201744
3 201923
4
3D texture analysis of MR images to improve classification of paediatric brain tumours: a preliminary study.
201412
5 20239
6
3D Texture Analysis of Heterogeneous MRI Data for Diagnostic Classification of Childhood Brain Tumours.
20157
7 20157
8 20225
9
A deep learning approach to segmentation of the developing cortex in fetal brain MRI with minimal manual labeling
20202
10
An Extensible Neuroimaging e-Repository for Clinical Trials of Paediatric Brain Tumours.
20152
11
MRI texture analysis in paediatric oncology: a preliminary study.
20132
12
Training deep segmentation networks on texture-encoded input: application to neuroimaging of the developing neonatal brain
20200

About Ahmed E. Fetit

Ahmed E. Fetit is a scholar working on Radiology, Nuclear Medicine and Imaging, Pediatrics, Perinatology and Child Health, Computer Vision and Pattern Recognition, Genetics and Artificial Intelligence, having authored 12 papers that have together received 169 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), Neonatal and fetal brain pathology (4 papers), Brain Tumor Detection and Classification (2 papers), Fetal and Pediatric Neurological Disorders (2 papers), Medical Image Segmentation Techniques (2 papers), Glioma Diagnosis and Treatment (2 papers), Advanced Neural Network Applications (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Health Informatics (15 citations), Radiology, Nuclear Medicine and Imaging (122 citations), Genetics (51 citations), Neurology (20 citations) and Ophthalmology (12 citations). Ahmed E. Fetit has collaborated with scholars based in United Kingdom, Spain and Germany. Frequent co-authors include Theodoros N. Arvanitis, Andrew C. Peet, Jan Novák, Daniel Rodriguez Gutierrez, Dorothee P. Auer, Richard G. Grundy, Chris Clark, Soroosh Afyouni, Ruixuan Wang and S.J. McKenna. Their work appears in journals such as NMR in Biomedicine, Scientific Reports, Frontiers in Neuroinformatics, Communications Biology and Studies in health technology and informatics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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