Renkai Wu
Impact in
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- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
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- Brain Tumor Detection and Classification
Papers in
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- Medical Image Segmentation Techniques 4
- Advanced Neural Network Applications 3
- Digital Imaging for Blood Diseases 2
- Oncology 6
- Cutaneous Melanoma Detection and Management 4
- Co-authors
- Qing Chang (13 shared papers)Pengchen Liang (9 shared papers)Yinghao Liu (6 shared papers)Xuan Huang (3 shared papers)Yuandong Gu (2 shared papers)Haiqin Zhu (2 shared papers)Guochen Ning (1 shared paper)Xiaoxu Cui (2 shared papers)
- Journals
- Computers in Biology and Medicine (2 papers)International Journal of Radiation Oncology*Biology*Physics (2 papers)Biomedical Signal Processing and Control (2 papers)IEEE Journal of Biomedical and Health Informatics (2 papers)Scientific Reports (1 paper)
- Partner nations
- ChinaUnited KingdomHong Kong
In The Last Decade
Renkai Wu
11 papers receiving 163 citations
Renkai Wu's Hit Papers
Peers
Comparison fields: 5 of 39
- Computer Vision and Pattern Recognition 81
- Neurology 20
- Artificial Intelligence 64
- Oncology 54
- Radiology, Nuclear Medicine and Imaging 31
Countries citing papers authored by Renkai Wu
This map shows the geographic impact of Renkai Wu'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 Renkai Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Renkai Wu more than expected).
Fields of papers citing papers by Renkai Wu
This network shows the impact of papers produced by Renkai Wu. 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 Renkai Wu. The network helps show where Renkai Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Renkai Wu, 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 | 2023 | 48 | |
| 2 | H-vmunet: High-order Vision Mamba UNet for medical image segmentation Hit paper breakdown → | 2025 | 46 |
| 3 | UltraLight VM-UNet: Parallel Vision Mamba significantly reduces parameters for skin lesion segmentation Hit paper breakdown → | 2025 | 30 |
| 4 | 2023 | 24 | |
| 5 | 2025 | 6 | |
| 6 | 2024 | 5 | |
| 7 | 2022 | 2 | |
| 8 | 2024 | 1 | |
| 9 | 2025 | 1 | |
| 10 | 2024 | 1 | |
| 11 | 2025 | 1 | |
| 12 | 2024 | 0 | |
| 13 | 2025 | 0 | |
| 14 | 2024 | 0 | |
| 15 | 2023 | 0 |
About Renkai Wu
Renkai Wu is a scholar working on Computer Vision and Pattern Recognition, Oncology, Artificial Intelligence, Otorhinolaryngology and Radiology, Nuclear Medicine and Imaging, having authored 15 papers that have together received 165 indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (4 papers), AI in cancer detection (4 papers), Medical Image Segmentation Techniques (4 papers), Advanced Neural Network Applications (3 papers), Head and Neck Cancer Studies (3 papers), Digital Imaging for Blood Diseases (2 papers), COVID-19 diagnosis using AI (2 papers) and Robotics and Sensor-Based Localization (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (81 citations), Neurology (20 citations), Artificial Intelligence (64 citations), Oncology (54 citations) and Radiology, Nuclear Medicine and Imaging (31 citations). Renkai Wu has collaborated with scholars based in China, United Kingdom and Hong Kong. Frequent co-authors include Qing Chang, Pengchen Liang, Yinghao Liu, Xuan Huang, Yuandong Gu, Haiqin Zhu, Guochen Ning, Xiaoxu Cui, Lin Pan and Xianjin Wang. Their work appears in journals such as Computers in Biology and Medicine, International Journal of Radiation Oncology*Biology*Physics, Biomedical Signal Processing and Control, IEEE Journal of Biomedical and Health Informatics and Scientific Reports.
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.