Siping Chen

6.7k citations
281 papers · 5.3k · h-index 39

Impact in

Papers in

Siping Chen

266 papers receiving 5.2k citations

Peers

Siping Chen
Comparison fields: 5 of 171
  • Computer Vision and Pattern Recognition 1.1k
  • Radiology, Nuclear Medicine and Imaging 1.0k
  • Health Informatics 63
  • Artificial Intelligence 1.6k
  • Biophysics 215
Replace Takeshi Hara with:
Takeshi Hara Japan
Xinjian Chen China
Xiaofeng Yang United States
Hongjie Hu China
Hongwei Li China
F Yin United States
Baowei Fei United States
Jiani Hu China
Yi Gao China
Shuqiang Wang China
Siping Chen relative to Takeshi Hara Japan Takeshi Hara's profile →
Citations per field
00.5×4.1×
Takeshi Hara · 1×
Citations per year

Countries citing papers authored by Siping Chen

Since Specialization
Citations

This map shows the geographic impact of Siping Chen'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 Siping Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Siping Chen more than expected).

Fields of papers citing papers by Siping Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Siping Chen. 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 Siping Chen. The network helps show where Siping Chen may publish in the future.

Co-authors

The 25 scholars most cited alongside Siping Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Siping Chen Line = papers co-authored together Siping Chen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 281 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015238
2 2020220
3 2017215
4 2018201
5 2016187
6 2017156
7 2018139
8 2013118
9 2017106
10 201998
11 201995
12 201787
13 201786
14 201382
15 201480
16 201176
17 202074
18 201471
19 201967
20 201766

About Siping Chen

Siping Chen is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence and Molecular Biology, having authored 281 papers that have together received 5.3k indexed citations. Recurring topics across this work include Ultrasound Imaging and Elastography (55 papers), Photoacoustic and Ultrasonic Imaging (39 papers), Ultrasound and Hyperthermia Applications (36 papers), AI in cancer detection (26 papers), Electrical and Bioimpedance Tomography (20 papers), Ultrasonics and Acoustic Wave Propagation (19 papers), Domain Adaptation and Few-Shot Learning (15 papers) and Medical Image Segmentation Techniques (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Radiology, Nuclear Medicine and Imaging (1.0k citations), Health Informatics (63 citations), Artificial Intelligence (1.6k citations) and Biophysics (215 citations). Siping Chen has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Tianfu Wang, Baiying Lei, Dong Ni, Ling Zhang, Xin Chen, Youyi Song, Feng Zhou, Xudong Jiang, Shengli Li and Haoming Lin. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, Ultrasound in Medicine & Biology, Biomedical Signal Processing and Control, IEEE Access and Ultrasonics.

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.

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