Ke Chen

7.6k total citations · 1 hit paper
355 papers, 5.2k citations indexed

About

Ke Chen is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Electrical and Electronic Engineering. According to data from OpenAlex, Ke Chen has authored 355 papers receiving a total of 5.2k indexed citations (citations by other indexed papers that have themselves been cited), including 132 papers in Computer Vision and Pattern Recognition, 67 papers in Computational Mechanics and 53 papers in Electrical and Electronic Engineering. Recurrent topics in Ke Chen's work include Medical Image Segmentation Techniques (75 papers), Image and Signal Denoising Methods (44 papers) and Sparse and Compressive Sensing Techniques (29 papers). Ke Chen is often cited by papers focused on Medical Image Segmentation Techniques (75 papers), Image and Signal Denoising Methods (44 papers) and Sparse and Compressive Sensing Techniques (29 papers). Ke Chen collaborates with scholars based in China, United Kingdom and United States. Ke Chen's co-authors include Jianping Zhang, Carlos Brito‐Loeza, Lavdie Rada, Yalin Zheng, Simon Harding, Yitian Zhao, Tony F. Chan, Paul J. Harris, Noor Badshah and Bo Yu and has published in prestigious journals such as Physical Review Letters, Advanced Materials and SHILAP Revista de lepidopterología.

In The Last Decade

Ke Chen

329 papers receiving 4.9k citations

Hit Papers

Automated Vessel Segmentation Using Infinite Perimeter Ac... 2015 2026 2018 2022 2015 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ke Chen China 36 1.8k 814 684 609 466 355 5.2k
Klaus Mueller United States 40 3.1k 1.7× 867 1.1× 1.5k 2.2× 222 0.4× 587 1.3× 268 6.4k
Yao Wang China 38 2.5k 1.4× 1.1k 1.4× 277 0.4× 728 1.2× 634 1.4× 246 6.3k
Boaz Nadler Israel 31 1.1k 0.6× 564 0.7× 197 0.3× 293 0.5× 888 1.9× 82 4.8k
Jeffrey C. Lagarias United States 39 1.2k 0.6× 760 0.9× 358 0.5× 1.2k 1.9× 1.3k 2.8× 192 10.8k
Thomas F. Coleman United States 36 602 0.3× 938 1.2× 351 0.5× 1.1k 1.9× 774 1.7× 122 9.2k
Ming Li China 39 1.1k 0.6× 470 0.6× 151 0.2× 1.0k 1.6× 1.2k 2.6× 450 7.9k
Shanshan Wang China 46 1.0k 0.6× 547 0.7× 2.2k 3.1× 503 0.8× 777 1.7× 416 7.9k
Xiaoping Yang China 29 723 0.4× 258 0.3× 528 0.8× 198 0.3× 397 0.9× 262 3.6k
Donald Goldfarb United States 39 2.5k 1.4× 3.8k 4.6× 589 0.9× 1.1k 1.8× 1.2k 2.5× 104 11.8k
Yan Wang China 49 590 0.3× 745 0.9× 196 0.3× 887 1.5× 949 2.0× 698 9.7k

Countries citing papers authored by Ke Chen

Since Specialization
Citations

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

Fields of papers citing papers by Ke Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ke Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Ke Chen. A scholar is included among the top collaborators of Ke Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ke Chen. Ke Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
2.
Xiong, Xiaofeng, Luyao Wu, Jian Liu, et al.. (2025). Comprehensive Characterization of the Oxidative Stress Profiles in Neonatal Necrotizing Enterocolitis. International Journal of Medical Sciences. 22(9). 2139–2154. 1 indexed citations
3.
Chen, Ke, et al.. (2025). Ricci Curvature Tensor-Based Volumetric Segmentation. International Journal of Computer Vision. 133(9). 6491–6512.
4.
Chen, Ke, et al.. (2024). Time multiscale regularization for nonlinear image registration. Computerized Medical Imaging and Graphics. 112. 102331–102331. 1 indexed citations
5.
Zhu, Jun, Ying Hao, Ting Wang, et al.. (2024). Transformation and environmental risk of 90Sr and 137Cs under extreme rainstorm at a proposed nuclear facility site in China. Journal of Environmental Radioactivity. 278. 107498–107498. 2 indexed citations
6.
Wang, Ding, Ke Chen, Jun Xu, Shan Xu, & Fan Kong. (2024). Efficient simulation method of fully nonstationary stochastic vector processes via generalized harmonic wavelet. Mechanical Systems and Signal Processing. 222. 111801–111801. 2 indexed citations
7.
Lei, Na, et al.. (2024). Ricci curvature based volumetric segmentation. Image and Vision Computing. 150. 105192–105192. 2 indexed citations
8.
Fan, Xiaohong, et al.. (2024). MVMS-RCN: A Dual-Domain Unified CT Reconstruction With Multi-Sparse-View and Multi-Scale Refinement-Correction. IEEE Transactions on Computational Imaging. 10. 1749–1762. 1 indexed citations
9.
Lan, Tian, et al.. (2024). Comparison of long-read sequencing and MLPA combined with long-PCR sequencing of CYP21A2 mutations in patients with 21-OHD. Frontiers in Genetics. 15. 1472516–1472516. 1 indexed citations
10.
Pang, Zhi‐Feng, et al.. (2023). Image Segmentation Based on the Hybrid Bias Field Correction. Applied Mathematics and Computation. 452. 128050–128050. 8 indexed citations
11.
Chen, Ke, et al.. (2023). A fractional-order image segmentation model with application to low-contrast and piecewise smooth images. Computers & Mathematics with Applications. 153. 159–171. 2 indexed citations
12.
Chen, Ke, et al.. (2023). An ultrasensitive Cd2+ detection biosensor based on DNAzyme and CRISPR/Cas12a coupled with hybridization chain reaction. Analytica Chimica Acta. 1283. 341950–341950. 15 indexed citations
13.
Chen, Ke, et al.. (2023). Topology-preserving image registration with novel multi-dimensional Beltrami regularization. Applied Mathematical Modelling. 125. 539–556. 2 indexed citations
15.
Yu, Xinyue, Yan Sun, Yan Lv, et al.. (2023). Incidence of Thrombosis at Different Sites During the Follow-Up Period in Essential Thrombocythemia: A Systematic Review and Meta-Analysis. Clinical and Applied Thrombosis/Hemostasis. 29. 2995362621–2995362621. 3 indexed citations
16.
Fan, Xiaohong, et al.. (2023). Nest-DGIL: Nesterov-Optimized Deep Geometric Incremental Learning for CS Image Reconstruction. IEEE Transactions on Computational Imaging. 9. 819–833. 5 indexed citations
17.
Chen, Ke, Hongyuan Xiao, Xuemin Cheng, et al.. (2022). Computational ghost imaging with PSF-guiding deep learning through various unknown turbid scattering media. Journal of Optics. 24(11). 115603–115603. 4 indexed citations
18.
Qian, Yanlin, et al.. (2018). Dichromatic Gray Pixel for Camera-agnostic Color Constancy.. arXiv (Cornell University). 1 indexed citations
19.
Chan, Tony F., et al.. (2007). Iterative methods for solving the dual formulation arising from image restoration. ETNA - Electronic Transactions on Numerical Analysis. 26. 299–311. 21 indexed citations
20.
Chen, Ke. (1999). DISCRETE WAVELET TRANSFORMS ACCELERATED SPARSE PRECONDITIONERS FOR DENSE BOUNDARY ELEMENT SYSTEMS. 8. 138–153. 26 indexed citations

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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