Fangde Liu
Impact in
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- Advanced MRI Techniques and Applications
- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
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- Image and Signal Denoising Methods
- Advanced Image Processing Techniques
Papers in
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- Robotic Path Planning Algorithms 3
- Medical Image Segmentation Techniques 2
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- Soft Robotics and Applications 4
- Co-authors
- Yike Guo (3 shared papers)David Firmin (1 shared paper)Xujiong Ye (1 shared paper)Pier Luigi Dragotti (1 shared paper)Greg Slabaugh (1 shared paper)Simiao Yu (1 shared paper)Guang Yang (2 shared papers)Simon Arridge (1 shared paper)
- Journals
- IEEE Transactions on Medical Imaging (1 paper)IEEE Transactions on Cybernetics (1 paper)IEEE Robotics and Automation Letters (1 paper)Nature (1 paper)Medical Image Analysis (1 paper)
- Partner nations
- United KingdomChinaUnited States
In The Last Decade
Fangde Liu
10 papers receiving 792 citations
Fangde Liu's Hit Papers
Peers
Comparison fields: 5 of 81
- Radiology, Nuclear Medicine and Imaging 489
- Computer Vision and Pattern Recognition 213
- Acoustics and Ultrasonics 8
- Computational Mechanics 179
- Health Informatics 9
Countries citing papers authored by Fangde Liu
This map shows the geographic impact of Fangde 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 Fangde Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fangde Liu more than expected).
Fields of papers citing papers by Fangde Liu
This network shows the impact of papers produced by Fangde 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 Fangde Liu. The network helps show where Fangde Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Fangde 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
| # | Work | ||
|---|---|---|---|
| 1 | DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction Hit paper breakdown → | 2017 | 674 |
| 2 | Atomic Bose–Einstein condensate in twisted-bilayer optical lattices Hit paper breakdown → | 2023 | 81 |
| 3 | 2016 | 29 | |
| 4 | 2012 | 6 | |
| 5 | 2015 | 5 | |
| 6 | 2020 | 4 | |
| 7 | 2013 | 3 | |
| 8 | 2024 | 2 | |
| 9 | 2015 | 2 | |
| 10 | Deep Poincare Map For Robust Medical Image Segmentation. | 2017 | 1 |
| 11 | 2022 | 0 |
About Fangde Liu
Fangde Liu is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Control and Systems Engineering, Aerospace Engineering and Atomic and Molecular Physics, and Optics, having authored 11 papers that have together received 807 indexed citations. Recurring topics across this work include Soft Robotics and Applications (4 papers), Robotics and Sensor-Based Localization (3 papers), Robotic Path Planning Algorithms (3 papers), Strong Light-Matter Interactions (2 papers), Cold Atom Physics and Bose-Einstein Condensates (2 papers), Robot Manipulation and Learning (2 papers), Quantum, superfluid, helium dynamics (2 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (489 citations), Computer Vision and Pattern Recognition (213 citations), Acoustics and Ultrasonics (8 citations), Computational Mechanics (179 citations) and Health Informatics (9 citations). Fangde Liu has collaborated with scholars based in United Kingdom, China and United States. Frequent co-authors include Yike Guo, David Firmin, Xujiong Ye, Pier Luigi Dragotti, Greg Slabaugh, Simiao Yu, Guang Yang, Simon Arridge, Hao Dong and Jennifer Keegan. Their work appears in journals such as IEEE Transactions on Medical Imaging, IEEE Transactions on Cybernetics, IEEE Robotics and Automation Letters, Nature and Medical Image Analysis.
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.