Yaolei Qi
- Computer Vision and Pattern Recognition top 10%
- Radiology, Nuclear Medicine and Imaging
- Industrial and Manufacturing Engineering top 10%
- Civil and Structural Engineering
- Artificial Intelligence
- Co-authors
- Guanyu YangXiaoming QiYuting HeYuan ZhangZehang LiJean-Louis CoatrieuxHuazhong ShuYouyong Kong
- Topics
- Cardiac Imaging and Diagnostics (3 papers)Radiomics and Machine Learning in Medical Imaging (2 papers)Digital Image Processing Techniques (1 paper)
- Cited by
- Computer Vision and Pattern RecognitionIndustrial and Manufacturing EngineeringMedia Technology
- Journals
- IEEE Transactions on Image ProcessingNeurocomputingIEEE Journal of Biomedical and Health Informatics
- Partner nations
- ChinaChileUnited States
In The Last Decade
Yaolei Qi
5 papers receiving 266 citations
Hit Papers
Peers
Comparison fields: 5 of 64
- Computer Vision and Pattern Recognition 125
- Radiology, Nuclear Medicine and Imaging 48
- Industrial and Manufacturing Engineering 41
- Civil and Structural Engineering 37
- Artificial Intelligence 31
Countries citing papers authored by Yaolei Qi
This map shows the geographic impact of Yaolei Qi'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 Yaolei Qi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yaolei Qi more than expected).
Fields of papers citing papers by Yaolei Qi
This network shows the impact of papers produced by Yaolei Qi. 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 Yaolei Qi. The network helps show where Yaolei Qi may publish in the future.
Co-authorship network of co-authors of Yaolei Qi
This figure shows the co-authorship network connecting the top 25 collaborators of Yaolei Qi. A scholar is included among the top collaborators of Yaolei Qi 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 Yaolei Qi. Yaolei Qi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 8 | |
| 4 | 1 | |
| 5 | Dynamic Snake Convolution based on Topological Geometric Constraints for Tubular Structure Segmentationbreakdown → | 247 |
| 6 | 11 |
About Yaolei Qi
Yaolei Qi is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 6 papers that have together received 269 indexed citations. Recurring topics across this work include Cardiac Imaging and Diagnostics (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Digital Image Processing Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (125 citations), Industrial and Manufacturing Engineering (41 citations) and Media Technology (29 citations). Yaolei Qi has collaborated with scholars based in China, Chile and United States. Frequent co-authors include Guanyu Yang, Xiaoming Qi, Yuting He, Yuan Zhang, Yuan Zhang, Zehang Li, Jean-Louis Coatrieux, Huazhong Shu, Youyong Kong and Shengxian Tu. Their work appears in journals such as IEEE Transactions on Image Processing, Neurocomputing and IEEE Journal of Biomedical and Health Informatics.
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.