Kang Li
Impact in
- Health Informatics top 1%
-
- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
- Human Pose and Action Recognition
Papers in
-
- Medical Image Segmentation Techniques 27
- Advanced Neural Network Applications 22
- Advanced Vision and Imaging 15
-
- AI in cancer detection 16
- Co-authors
- Milan Sonka (5 shared papers)Yun Fu (6 shared papers)Xiaodong Wu (3 shared papers)Shaoting Zhang (31 shared papers)Takeo Kanade (7 shared papers)Xiaoping Qian (7 shared papers)Eric D. Miller (3 shared papers)Guotai Wang (16 shared papers)
- Journals
- Journal of Biomechanics (14 papers)Medical Image Analysis (11 papers)IEEE Transactions on Medical Imaging (8 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (4 papers)IEEE Access (4 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Kang Li
344 papers receiving 5.6k citations
Kang Li's Hit Papers
Peers
Comparison fields: 5 of 205
- Health Informatics 131
- Computer Vision and Pattern Recognition 1.6k
- Biophysics 386
- Radiology, Nuclear Medicine and Imaging 1.1k
- Artificial Intelligence 1.3k
Countries citing papers authored by Kang Li
This map shows the geographic impact of Kang Li'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 Kang Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kang Li more than expected).
Fields of papers citing papers by Kang Li
This network shows the impact of papers produced by Kang Li. 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 Kang Li. The network helps show where Kang Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Kang Li, 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 381 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Optimal Surface Segmentation in Volumetric Images-A Graph-Theoretic Approach Hit paper breakdown → | 2006 | 489 |
| 2 | 2020 | 329 | |
| 3 | 2008 | 258 | |
| 4 | 2014 | 149 | |
| 5 | 2011 | 140 | |
| 6 | 2014 | 127 | |
| 7 | 2005 | 106 | |
| 8 | 2015 | 80 | |
| 9 | 2022 | 75 | |
| 10 | 2014 | 73 | |
| 11 | 2006 | 67 | |
| 12 | 2009 | 66 | |
| 13 | 2014 | 64 | |
| 14 | 2019 | 64 | |
| 15 | 2011 | 63 | |
| 16 | 2021 | 60 | |
| 17 | 2012 | 59 | |
| 18 | 2016 | 59 | |
| 19 | 2021 | 56 | |
| 20 | 2018 | 51 |
About Kang Li
Kang Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Surgery, having authored 381 papers that have together received 5.8k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (33 papers), Medical Image Segmentation Techniques (27 papers), Advanced Neural Network Applications (22 papers), AI in cancer detection (16 papers), Total Knee Arthroplasty Outcomes (15 papers), Advanced Vision and Imaging (15 papers), Medical Imaging and Analysis (15 papers) and COVID-19 diagnosis using AI (15 papers). The work is most often cited by research in Health Informatics (131 citations), Computer Vision and Pattern Recognition (1.6k citations), Biophysics (386 citations), Radiology, Nuclear Medicine and Imaging (1.1k citations) and Artificial Intelligence (1.3k citations). Kang Li has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Milan Sonka, Yun Fu, Xiaodong Wu, Shaoting Zhang, Takeo Kanade, Xiaoping Qian, Eric D. Miller, Guotai Wang, Phil G. Campbell and Lee E. Weiss. Their work appears in journals such as Journal of Biomechanics, Medical Image Analysis, IEEE Transactions on Medical Imaging, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Access.
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.