Fujun Liu
Impact in
- Biophysics top 2%
- Cell Image Analysis Techniques
- Health Informatics top 10%
Papers in
-
- AI in cancer detection 7
-
- Medical Image Segmentation Techniques 2
- Co-authors
- Lin Yang (13 shared papers)Fuyong Xing (12 shared papers)Hai Su (9 shared papers)Yuanpu Xie (7 shared papers)Xiaoshuang Shi (5 shared papers)Manish Sapkota (5 shared papers)Jinzheng Cai (4 shared papers)Jyothi Mula (2 shared papers)
- Journals
- Nature Machine Intelligence (3 papers)American Journal Of Pathology (2 papers)Pattern Recognition (2 papers)The Journals of Gerontology Series A (1 paper)Neurocomputing (1 paper)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Fujun Liu
19 papers receiving 883 citations
Peers
Comparison fields: 5 of 120
- Biophysics 138
- Health Informatics 19
- Computer Vision and Pattern Recognition 285
- Artificial Intelligence 424
- Radiology, Nuclear Medicine and Imaging 216
Countries citing papers authored by Fujun Liu
This map shows the geographic impact of Fujun Liu'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 Fujun Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fujun Liu more than expected).
Fields of papers citing papers by Fujun Liu
This network shows the impact of papers produced by Fujun Liu. 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 Fujun Liu. The network helps show where Fujun Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Fujun Liu, 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 | 2017 | 298 | |
| 2 | 2019 | 198 | |
| 3 | 2018 | 69 | |
| 4 | 2015 | 68 | |
| 5 | 2012 | 53 | |
| 6 | 2015 | 50 | |
| 7 | 2015 | 44 | |
| 8 | 2018 | 41 | |
| 9 | 2014 | 26 | |
| 10 | 2016 | 21 | |
| 11 | 2018 | 7 | |
| 12 | 2014 | 4 | |
| 13 | 2019 | 3 | |
| 14 | 2011 | 2 | |
| 15 | 2019 | 2 | |
| 16 | 2017 | 2 | |
| 17 | 2021 | 2 | |
| 18 | 2012 | 1 | |
| 19 | 2016 | 1 | |
| 20 | Improved VSM Algorithm and Its Application in FAQ | 2012 | 0 |
About Fujun Liu
Fujun Liu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Biophysics and Computer Networks and Communications, having authored 21 papers that have together received 892 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), Muscle Physiology and Disorders (5 papers), Cell Image Analysis Techniques (3 papers), Medical Image Segmentation Techniques (2 papers), Image Processing Techniques and Applications (2 papers), Nutrition and Health in Aging (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Body Composition Measurement Techniques (1 paper). The work is most often cited by research in Biophysics (138 citations), Health Informatics (19 citations), Computer Vision and Pattern Recognition (285 citations), Artificial Intelligence (424 citations) and Radiology, Nuclear Medicine and Imaging (216 citations). Fujun Liu has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Lin Yang, Fuyong Xing, Hai Su, Yuanpu Xie, Xiaoshuang Shi, Manish Sapkota, Jinzheng Cai, Jyothi Mula, Charlotte A. Peterson and Jonah D. Lee. Their work appears in journals such as Nature Machine Intelligence, American Journal Of Pathology, Pattern Recognition, The Journals of Gerontology Series A and Neurocomputing.
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.