Eli Gibson
- Health Informatics top 2%
- Archeology top 5%
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- Radiomics and Machine Learning in Medical Imaging 15
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- Advanced Neural Network Applications 15
- Medical Image Segmentation Techniques 13
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- Prostate Cancer Diagnosis and Treatment 28
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- Superconducting Materials and Applications 23
- Medical Imaging and Analysis 12
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- Physics of Superconductivity and Magnetism 21
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- AI in cancer detection 17
- Co-authors
- J. D. VerhoevenDean C. BarrattYipeng HuEster BonmatiO.D. McMastersJ. E. OstensonH. L. DowningFrançois Kayser
- Journals
- Journal of Applied Physics (12 papers)Applied Physics Letters (7 papers)Medical Image Analysis (6 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Eli Gibson
143 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Health Informatics 82
- Archeology 47
- Radiology, Nuclear Medicine and Imaging 1.0k
- Computer Vision and Pattern Recognition 706
- Electronic, Optical and Magnetic Materials 551
Countries citing papers authored by Eli Gibson
This map shows the geographic impact of Eli Gibson'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 Eli Gibson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eli Gibson more than expected).
Fields of papers citing papers by Eli Gibson
This network shows the impact of papers produced by Eli Gibson. 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 Eli Gibson. The network helps show where Eli Gibson may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Eli Gibson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 1 | |
| 7 | 2022 | 14 | |
| 8 | 2020 | 36 | |
| 9 | NiftyNet: a deep-learning platform for medical imagingbreakdown → | 2018 | 363 |
| 10 | Automatic Multi-Organ Segmentation on Abdominal CT With Dense V-Networksbreakdown → | 2018 | 472 |
| 11 | 2018 | 250 | |
| 12 | 2018 | 4 | |
| 13 | 2017 | 19 | |
| 14 | 2015 | 28 | |
| 15 | 2015 | 24 | |
| 16 | 2013 | 16 | |
| 17 | 2013 | 11 | |
| 18 | 2012 | 55 | |
| 19 | 2010 | 17 | |
| 20 | 1973 | 21 |
About Eli Gibson
Eli Gibson is a scholar working on Condensed Matter Physics, Archeology and Radiology, Nuclear Medicine and Imaging, having authored 152 papers that have together received 3.7k indexed citations. Recurring topics across this work include Prostate Cancer Diagnosis and Treatment (28 papers), Superconducting Materials and Applications (23 papers), Physics of Superconductivity and Magnetism (21 papers), AI in cancer detection (17 papers), Advanced Neural Network Applications (15 papers), Radiomics and Machine Learning in Medical Imaging (15 papers), Medical Image Segmentation Techniques (13 papers) and Medical Imaging and Analysis (12 papers). The work is most often cited by research in Health Informatics (82 citations), Archeology (47 citations) and Radiology, Nuclear Medicine and Imaging (1.0k citations). Eli Gibson has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include J. D. Verhoeven, Dean C. Barratt, Yipeng Hu, Ester Bonmati, O.D. McMasters, J. E. Ostenson, H. L. Downing, François Kayser, H. J. Leamy and Kurinchi Selvan Gurusamy. Their work appears in journals such as Journal of Applied Physics, Applied Physics Letters, Medical Image Analysis, IEEE Transactions on Magnetics and Journal of Materials Science.
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.