Reuben Dorent
Impact in
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- Brain Tumor Detection and Classification
Papers in
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- Medical Image Segmentation Techniques 4
- Advanced Neural Network Applications 4
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- Meningioma and schwannoma management 6
- Co-authors
- Tom Vercauteren (13 shared papers)Sébastien Ourselin (10 shared papers)Jonathan Shapey (8 shared papers)Shakeel R. Saeed (5 shared papers)Robert Bradford (5 shared papers)Sotirios Bisdas (4 shared papers)Neil Kitchen (6 shared papers)Ian Paddick (3 shared papers)
- Journals
- International Journal of Computer Assisted Radiology and Surgery (3 papers)Scientific Data (2 papers)European Radiology (1 paper)Neurosurgery (1 paper)Journal of neurosurgery (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Reuben Dorent
17 papers receiving 269 citations
Peers
Comparison fields: 5 of 45
- Health Informatics 7
- Neurology 37
- Radiology, Nuclear Medicine and Imaging 72
- Computer Vision and Pattern Recognition 67
- Epidemiology 85
Countries citing papers authored by Reuben Dorent
This map shows the geographic impact of Reuben Dorent'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 Reuben Dorent with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Reuben Dorent more than expected).
Fields of papers citing papers by Reuben Dorent
This network shows the impact of papers produced by Reuben Dorent. 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 Reuben Dorent. The network helps show where Reuben Dorent may publish in the future.
Co-authors
The 25 scholars most cited alongside Reuben Dorent, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 78 | |
| 2 | 2021 | 49 | |
| 3 | 2020 | 39 | |
| 4 | 2020 | 20 | |
| 5 | 2021 | 19 | |
| 6 | 2024 | 18 | |
| 7 | 2023 | 8 | |
| 8 | 2023 | 8 | |
| 9 | 2022 | 8 | |
| 10 | 2021 | 8 | |
| 11 | 2024 | 7 | |
| 12 | 2022 | 4 | |
| 13 | 2023 | 2 | |
| 14 | 2025 | 1 | |
| 15 | 2024 | 1 | |
| 16 | 2023 | 1 | |
| 17 | 2021 | 1 | |
| 18 | 2025 | 0 | |
| 19 | 2024 | 0 | |
| 20 | 2024 | 0 |
About Reuben Dorent
Reuben Dorent is a scholar working on Computer Vision and Pattern Recognition, Epidemiology, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering, having authored 21 papers that have together received 272 indexed citations. Recurring topics across this work include Meningioma and schwannoma management (6 papers), Domain Adaptation and Few-Shot Learning (5 papers), Medical Image Segmentation Techniques (4 papers), Advanced Neural Network Applications (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Medical Imaging and Analysis (3 papers), Hand Gesture Recognition Systems (2 papers) and Vascular Malformations Diagnosis and Treatment (2 papers). The work is most often cited by research in Health Informatics (7 citations), Neurology (37 citations), Radiology, Nuclear Medicine and Imaging (72 citations), Computer Vision and Pattern Recognition (67 citations) and Epidemiology (85 citations). Reuben Dorent has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Tom Vercauteren, Sébastien Ourselin, Jonathan Shapey, Shakeel R. Saeed, Robert Bradford, Sotirios Bisdas, Neil Kitchen, Ian Paddick, Alexis Dimitriadis and Guotai Wang. Their work appears in journals such as International Journal of Computer Assisted Radiology and Surgery, Scientific Data, European Radiology, Neurosurgery and Journal of neurosurgery.
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.