Steven McDonagh
Impact in
- Neurology top 5%
- Brain Tumor Detection and Classification
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
- Advanced Vision and Imaging
- Advanced Image Processing Techniques
Papers in
-
- Advanced Vision and Imaging 11
- Advanced Image Processing Techniques 8
- Image Enhancement Techniques 7
- Advanced Neural Network Applications 4
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- COVID-19 diagnosis using AI 4
- Co-authors
- Daniel Rueckert (11 shared papers)Bernhard Kainz (9 shared papers)Ben Glocker (9 shared papers)Martin Rajchl (3 shared papers)Konstantinos Kamnitsas (4 shared papers)Nick Pawlowski (2 shared papers)Enzo Ferrante (3 shared papers)Min young Lee (1 shared paper)
- Journals
- IEEE Transactions on Medical Imaging (3 papers)Computer Graphics Forum (2 papers)Neurocomputing (1 paper)Neural Networks (1 paper)ACM Transactions on Graphics (1 paper)
- Partner nations
- United KingdomSwedenChina
In The Last Decade
Steven McDonagh
37 papers receiving 904 citations
Peers
Comparison fields: 5 of 92
- Neurology 220
- Computer Vision and Pattern Recognition 568
- Computer Graphics and Computer-Aided Design 54
- Radiology, Nuclear Medicine and Imaging 192
- Health Informatics 10
Countries citing papers authored by Steven McDonagh
This map shows the geographic impact of Steven McDonagh'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 Steven McDonagh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven McDonagh more than expected).
Fields of papers citing papers by Steven McDonagh
This network shows the impact of papers produced by Steven McDonagh. 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 Steven McDonagh. The network helps show where Steven McDonagh may publish in the future.
Co-authors
The 25 scholars most cited alongside Steven McDonagh, 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 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 316 | |
| 2 | 2018 | 67 | |
| 3 | Unsupervised Lesion Detection in Brain CT using Bayesian Convolutional Autoencoders | 2018 | 55 |
| 4 | 2017 | 49 | |
| 5 | 2016 | 47 | |
| 6 | 2021 | 47 | |
| 7 | 2015 | 46 | |
| 8 | 2017 | 39 | |
| 9 | 2023 | 37 | |
| 10 | 2022 | 28 | |
| 11 | 2022 | 27 | |
| 12 | 2013 | 19 | |
| 13 | 2015 | 16 | |
| 14 | 2016 | 16 | |
| 15 | 2022 | 14 | |
| 16 | 2018 | 14 | |
| 17 | Using 3D information for classification of non-melanoma skin lesions | 2008 | 12 |
| 18 | 2017 | 10 | |
| 19 | Simultaneous registration of multi-view range images with adaptive kernel density estimation | 2013 | 10 |
| 20 | 2018 | 9 |
About Steven McDonagh
Steven McDonagh is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Media Technology, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 39 papers that have together received 948 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (11 papers), Advanced Image Processing Techniques (8 papers), Image Enhancement Techniques (7 papers), Domain Adaptation and Few-Shot Learning (6 papers), Robotics and Sensor-Based Localization (5 papers), Fetal and Pediatric Neurological Disorders (4 papers), COVID-19 diagnosis using AI (4 papers) and Advanced Neural Network Applications (4 papers). The work is most often cited by research in Neurology (220 citations), Computer Vision and Pattern Recognition (568 citations), Computer Graphics and Computer-Aided Design (54 citations), Radiology, Nuclear Medicine and Imaging (192 citations) and Health Informatics (10 citations). Steven McDonagh has collaborated with scholars based in United Kingdom, Sweden and China. Frequent co-authors include Daniel Rueckert, Bernhard Kainz, Ben Glocker, Martin Rajchl, Konstantinos Kamnitsas, Nick Pawlowski, Enzo Ferrante, Min young Lee, Wenjia Bai and Matthew Sinclair. Their work appears in journals such as IEEE Transactions on Medical Imaging, Computer Graphics Forum, Neurocomputing, Neural Networks and ACM Transactions on Graphics.
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.