Chunliang Wang
- Artificial Intelligence top 2%
- Oncology top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Biomedical Engineering top 10%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Örjan SmedbyAmirreza MahbodGerald SchaeferRupert EckerIsabella EllingerGeorg DorffnerAlain PitiotMehdi Astaraki
- Topics
- Medical Image Segmentation Techniques (18 papers)Quantum optics and atomic interactions (12 papers)Retinal Imaging and Analysis (7 papers)
- Journals
- Proceedings of the National Academy of SciencesSHILAP Revista de lepidopterologíaPhysical Review A
- Partner nations
- SwedenChinaUnited Kingdom
In The Last Decade
Chunliang Wang
63 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 122
- Artificial Intelligence 526
- Oncology 480
- Radiology, Nuclear Medicine and Imaging 480
- Biomedical Engineering 271
- Computer Vision and Pattern Recognition 254
Countries citing papers authored by Chunliang Wang
This map shows the geographic impact of Chunliang Wang'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 Chunliang Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chunliang Wang more than expected).
Fields of papers citing papers by Chunliang Wang
This network shows the impact of papers produced by Chunliang Wang. 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 Chunliang Wang. The network helps show where Chunliang Wang may publish in the future.
Co-authorship network of co-authors of Chunliang Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Chunliang Wang. A scholar is included among the top collaborators of Chunliang Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chunliang Wang. Chunliang Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 10 | |
| 8 | 18 | |
| 9 | 21 | |
| 10 | 31 | |
| 11 | 4 | |
| 12 | 41 | |
| 13 | 45 | |
| 14 | 26 | |
| 15 | 185 | |
| 16 | Automatic multi-organ segmentation using fast model based level set method and hierarchical shape priors | 6 |
| 17 | Vessel Segmentation Using Implicit Model-Guided Level Sets | 20 |
| 18 | 12 | |
| 19 | 5 | |
| 20 | 119 |
About Chunliang Wang
Chunliang Wang is a scholar working on Acoustics and Ultrasonics, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 67 papers that have together received 1.5k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (18 papers), Quantum optics and atomic interactions (12 papers) and Retinal Imaging and Analysis (7 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (480 citations), Acoustics and Ultrasonics (16 citations) and Health Informatics (24 citations). Chunliang Wang has collaborated with scholars based in Sweden, China and United Kingdom. Frequent co-authors include Örjan Smedby, Amirreza Mahbod, Gerald Schaefer, Rupert Ecker, Isabella Ellinger, Georg Dorffner, Alain Pitiot, Mehdi Astaraki, Jin-Yue Gao and Zhi‐Hui Kang. Their work appears in journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Physical Review A.
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.