Xiaobo Qu
Impact in
- Computational Mathematics top 2%
- Media Technology top 0.5%
- Advanced Image Fusion Techniques
- Remote-Sensing Image Classification
Papers in
-
- Advanced MRI Techniques and Applications 70
- Medical Imaging Techniques and Applications 17
-
- Sparse and Compressive Sensing Techniques 57
- Co-authors
- Di GuoZhong ChenJingwen YanJian‐Feng CaiYunsong LiuZhifang ZhanVladislav OrekhovYingkun Hou
- Journals
- Journal of Magnetic Resonance (9 papers)IEEE Transactions on Instrumentation and Measurement (5 papers)Magnetic Resonance Imaging (5 papers)Medical Image Analysis (5 papers)IEEE Transactions on Biomedical Engineering (5 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Xiaobo Qu
127 papers receiving 3.6k citations
Peers
Comparison fields: 5 of 131
- Computational Mathematics 52
- Media Technology 696
- Radiology, Nuclear Medicine and Imaging 1.8k
- Computational Mechanics 1.3k
- Computer Vision and Pattern Recognition 1.1k
Countries citing papers authored by Xiaobo Qu
This map shows the geographic impact of Xiaobo Qu'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 Xiaobo Qu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaobo Qu more than expected).
Fields of papers citing papers by Xiaobo Qu
This network shows the impact of papers produced by Xiaobo Qu. 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 Xiaobo Qu. The network helps show where Xiaobo Qu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiaobo Qu, 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 | 2025 | 2 | |
| 2 | 2025 | 2 | |
| 3 | 2025 | 3 | |
| 4 | 2025 | 12 | |
| 5 | 2025 | 0 | |
| 6 | 2025 | 0 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 1 | |
| 9 | 2024 | 19 | |
| 10 | 2024 | 31 | |
| 11 | 2023 | 0 | |
| 12 | 2022 | 6 | |
| 13 | 2021 | 14 | |
| 14 | 2020 | 1 | |
| 15 | 2019 | 3 | |
| 16 | 2016 | 43 | |
| 17 | 2015 | 14 | |
| 18 | 2015 | 33 | |
| 19 | 2014 | 17 | |
| 20 | A New Research on Image Fusion | 2007 | 2 |
About Xiaobo Qu
Xiaobo Qu is a scholar working on Radiology, Nuclear Medicine and Imaging, Computational Mechanics, Media Technology, Computer Vision and Pattern Recognition and Nuclear and High Energy Physics, having authored 140 papers that have together received 3.7k indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (70 papers), Sparse and Compressive Sensing Techniques (57 papers), Image and Signal Denoising Methods (36 papers), NMR spectroscopy and applications (23 papers), Advanced Image Fusion Techniques (19 papers), Photoacoustic and Ultrasonic Imaging (18 papers), Medical Imaging Techniques and Applications (17 papers) and Advanced Image Processing Techniques (10 papers). The work is most often cited by research in Computational Mathematics (52 citations), Media Technology (696 citations), Radiology, Nuclear Medicine and Imaging (1.8k citations), Computational Mechanics (1.3k citations) and Computer Vision and Pattern Recognition (1.1k citations). Xiaobo Qu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Di Guo, Zhong Chen, Jingwen Yan, Jian‐Feng Cai, Yunsong Liu, Zhifang Zhan, Vladislav Orekhov, Yingkun Hou, Shuhui Cai and Hengfa Lu. Their work appears in journals such as Journal of Magnetic Resonance, IEEE Transactions on Instrumentation and Measurement, Magnetic Resonance Imaging, Medical Image Analysis and IEEE Transactions on Biomedical Engineering.
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.