Suiren Wan
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces 5
- Signal Processing top 5%
- Blind Source Separation Techniques 5
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- Radiomics and Machine Learning in Medical Imaging 3
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- Image and Signal Denoising Methods 4
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- Photoacoustic and Ultrasonic Imaging 4
- Optical Coherence Tomography Applications 3
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- Bacteriophages and microbial interactions 3
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- Dementia and Cognitive Impairment Research 3
- Journals
- Journal of Nanoscience and Nanotechnology (5 papers)Oncotarget (2 papers)PLoS ONE (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Suiren Wan
28 papers receiving 758 citations
Peers
Comparison fields: 5 of 140
- Cognitive Neuroscience 290
- Signal Processing 146
- Radiology, Nuclear Medicine and Imaging 196
- Health Informatics 9
- Neurology 41
Countries citing papers authored by Suiren Wan
This map shows the geographic impact of Suiren Wan'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 Suiren Wan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suiren Wan more than expected).
Fields of papers citing papers by Suiren Wan
This network shows the impact of papers produced by Suiren Wan. 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 Suiren Wan. The network helps show where Suiren Wan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Suiren Wan, 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 | 2020 | 20 | |
| 2 | 2019 | 16 | |
| 3 | 2019 | 11 | |
| 4 | 2018 | 39 | |
| 5 | 2018 | 36 | |
| 6 | 2018 | 10 | |
| 7 | 2018 | 1 | |
| 8 | 2017 | 59 | |
| 9 | 2017 | 162 | |
| 10 | 2016 | 107 | |
| 11 | 2016 | 1 | |
| 12 | 2016 | 82 | |
| 13 | 2015 | 4 | |
| 14 | 2015 | 6 | |
| 15 | 2014 | 21 | |
| 16 | 2013 | 2 | |
| 17 | 2013 | 1 | |
| 18 | 2013 | 5 | |
| 19 | Noise Image Segmentation Using Fisher Criterion and Regularization Level Set Method | 2012 | 2 |
| 20 | Fourier-wavelet regularized deconvolution in medical ultrasound imaging | 2011 | 1 |
About Suiren Wan
Suiren Wan is a scholar working on Signal Processing, Cognitive Neuroscience and Radiology, Nuclear Medicine and Imaging, having authored 31 papers that have together received 779 indexed citations. Recurring topics across this work include Blind Source Separation Techniques (5 papers), EEG and Brain-Computer Interfaces (5 papers), Image and Signal Denoising Methods (4 papers), Photoacoustic and Ultrasonic Imaging (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Optical Coherence Tomography Applications (3 papers), Bacteriophages and microbial interactions (3 papers) and Dementia and Cognitive Impairment Research (3 papers). The work is most often cited by research in Cognitive Neuroscience (290 citations), Signal Processing (146 citations) and Radiology, Nuclear Medicine and Imaging (196 citations). Suiren Wan has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Duo Chen, Forrest Sheng Bao, Jing Xiang, Jing Yan, Yu Sun, Wei Ren, Bing Zhang, Renyuan Liu, Wenxuan Liang and Shuangshuang Li. Their work appears in journals such as Journal of Nanoscience and Nanotechnology, Oncotarget, PLoS ONE, Journal of Biophotonics and Journal of Biomedical Optics.
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.