Kevin Leung
- Health Informatics top 5%
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- Radiomics and Machine Learning in Medical Imaging 10
- Medical Imaging Techniques and Applications 8
- Rheumatology top 10%
- Osteoarthritis Treatment and Mechanisms 2
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- Advanced X-ray and CT Imaging 4
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- Neurological disorders and treatments 2
- Parkinson's Disease Mechanisms and Treatments 2
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- Total Knee Arthroplasty Outcomes 3
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- Prostate Cancer Treatment and Research 3
- Co-authors
- Cem M. DenizGregory ChangMartin G. PomperKyunghyun ChoYong DuJames S. BabbBofei ZhangSteven P. Rowe
- Partner nations
- United StatesCanadaIran
In The Last Decade
Kevin Leung
17 papers receiving 384 citations
Peers
Comparison fields: 5 of 59
- Health Informatics 26
- Radiology, Nuclear Medicine and Imaging 195
- Rheumatology 90
- Biomedical Engineering 106
- Neurology 31
Countries citing papers authored by Kevin Leung
This map shows the geographic impact of Kevin Leung'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 Kevin Leung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Leung more than expected).
Fields of papers citing papers by Kevin Leung
This network shows the impact of papers produced by Kevin Leung. 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 Kevin Leung. The network helps show where Kevin Leung may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kevin Leung, 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 | 2024 | 25 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 16 | |
| 4 | 2022 | 23 | |
| 5 | 2022 | 3 | |
| 6 | 2021 | 37 | |
| 7 | 2020 | 5 | |
| 8 | 2020 | 146 | |
| 9 | Characterization of Segmented 18F-DCFPyL PET/CT Lesions in the Context of PSMA-RADS Structured Reporting | 2019 | 3 |
| 10 | 2019 | 74 | |
| 11 | HiResPET: high resolution PET image generation using deep convolution encoder decoder network | 2019 | 6 |
| 12 | Simultaneous Attenuation Correction and Reconstruction of PET Images Using Deep Convolutional Encoder Decoder Networks from Emission Data | 2019 | 5 |
| 13 | A fully automated deep-learning based method for lesion segmentation in 18F-DCFPyL PSMA PET images of patients with prostate cancer | 2019 | 7 |
| 14 | PSFNET: ultrafast generation of PSF-modelled-like PET images using deep convolutional neural network | 2019 | 6 |
| 15 | Total Knee Replacement prediction using Structural MRIs and 3D Convolutional Neural Networks | 2019 | 5 |
| 16 | A deep-learning-based fully automated segmentation approach to delineate tumors in FDG-PET images of patients with lung cancer | 2018 | 6 |
| 17 | 2018 | 21 |
About Kevin Leung
Kevin Leung is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology and Rheumatology, having authored 17 papers that have together received 389 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (10 papers), Medical Imaging Techniques and Applications (8 papers), Advanced X-ray and CT Imaging (4 papers), Total Knee Arthroplasty Outcomes (3 papers), Prostate Cancer Treatment and Research (3 papers), Neurological disorders and treatments (2 papers), Parkinson's Disease Mechanisms and Treatments (2 papers) and Osteoarthritis Treatment and Mechanisms (2 papers). The work is most often cited by research in Health Informatics (26 citations), Radiology, Nuclear Medicine and Imaging (195 citations) and Rheumatology (90 citations). Kevin Leung has collaborated with scholars based in United States, Canada and Iran. Frequent co-authors include Cem M. Deniz, Gregory Chang, Martin G. Pomper, Kyunghyun Cho, Yong Du, James S. Babb, Bofei Zhang, Steven P. Rowe, Yiqiu Shen and Krzysztof J. Geras. Their work appears in journals such as Scientific Reports, Radiology and Journal of Nuclear Medicine.
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.