Shuhui Cai

3.8k total citations
217 papers, 3.0k citations indexed

About

Shuhui Cai is a scholar working on Radiology, Nuclear Medicine and Imaging, Nuclear and High Energy Physics and Spectroscopy. According to data from OpenAlex, Shuhui Cai has authored 217 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 122 papers in Radiology, Nuclear Medicine and Imaging, 89 papers in Nuclear and High Energy Physics and 84 papers in Spectroscopy. Recurrent topics in Shuhui Cai's work include Advanced MRI Techniques and Applications (115 papers), NMR spectroscopy and applications (89 papers) and Advanced NMR Techniques and Applications (83 papers). Shuhui Cai is often cited by papers focused on Advanced MRI Techniques and Applications (115 papers), NMR spectroscopy and applications (89 papers) and Advanced NMR Techniques and Applications (83 papers). Shuhui Cai collaborates with scholars based in China, United States and Finland. Shuhui Cai's co-authors include Zhong Chen, Congbo Cai, Karl Sohlberg, Xiaobo Qu, Yuqing Huang, Jianghua Feng, Di Guo, Jianhui Zhong, Yulan Lin and Lin Chen and has published in prestigious journals such as Journal of the American Chemical Society, Physical Review Letters and The Journal of Chemical Physics.

In The Last Decade

Shuhui Cai

206 papers receiving 2.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shuhui Cai China 29 1.5k 740 687 670 396 217 3.0k
K. J. Packer United Kingdom 30 1.5k 1.0× 1.2k 1.7× 2.1k 3.0× 459 0.7× 221 0.6× 91 3.5k
P. T. Callaghan New Zealand 31 1.0k 0.7× 763 1.0× 1.3k 1.9× 560 0.8× 240 0.6× 58 2.7k
Scott A. Smith United States 21 333 0.2× 1.0k 1.4× 341 0.5× 419 0.6× 202 0.5× 73 1.9k
Vikram S. Bajaj United States 30 537 0.4× 2.7k 3.6× 577 0.8× 1.8k 2.7× 216 0.5× 57 4.5k
Christopher G. Morgan United Kingdom 30 166 0.1× 405 0.5× 143 0.2× 1.1k 1.7× 503 1.3× 114 3.3k
Songi Han United States 47 548 0.4× 2.3k 3.1× 649 0.9× 2.1k 3.2× 557 1.4× 199 6.7k
Yoshihiro Mori Japan 24 181 0.1× 365 0.5× 223 0.3× 453 0.7× 317 0.8× 253 2.5k
Sarah E. Bohndiek United Kingdom 36 1.9k 1.2× 869 1.2× 179 0.3× 688 1.0× 2.8k 7.0× 156 4.9k
W. S. Hinshaw United Kingdom 20 1.4k 0.9× 647 0.9× 557 0.8× 347 0.5× 202 0.5× 54 2.2k
Wojciech Froncisz United States 33 782 0.5× 773 1.0× 199 0.3× 790 1.2× 177 0.4× 119 3.5k

Countries citing papers authored by Shuhui Cai

Since Specialization
Citations

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

Fields of papers citing papers by Shuhui Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuhui Cai

This figure shows the co-authorship network connecting the top 25 collaborators of Shuhui Cai. A scholar is included among the top collaborators of Shuhui Cai 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 Shuhui Cai. Shuhui Cai 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
1.
Wu, Fei, Haiyang Luo, Xiao Wang, et al.. (2025). Application of Anti‐Motion Ultra‐Fast Quantitative MRI in Neurological Disorder Imaging: Insights From Huntington's Disease. Journal of Magnetic Resonance Imaging. 61(6). 2455–2468.
2.
Wang, Lu, et al.. (2025). A versatile end-to-end deep learning framework for improved full-automatic MRI hemodynamic parameter estimation. Biomedical Signal Processing and Control. 108. 107889–107889.
3.
Wang, Lu, Qinqin Yang, Congbo Cai, et al.. (2024). Improved deep learning‐based IVIM parameter estimation via the use of more “realistic” simulated brain data. Medical Physics. 52(4). 2279–2294. 1 indexed citations
4.
5.
Zhang, Yuebin, et al.. (2024). Two-Dimensional Laplace NMR Reconstruction through Deep Learning Enhancement. Journal of the American Chemical Society. 146(31). 21591–21599. 4 indexed citations
6.
7.
Huang, Haitao, et al.. (2023). High-efficient Bloch simulation of magnetic resonance imaging sequences based on deep learning. Physics in Medicine and Biology. 68(8). 85002–85002. 3 indexed citations
8.
Yang, Qinqin, Lingceng Ma, Zihan Zhou, et al.. (2023). Rapid high‐fidelity T2* mapping using single‐shot overlapping‐echo acquisition and deep learning reconstruction. Magnetic Resonance in Medicine. 89(6). 2157–2170. 7 indexed citations
9.
Zhang, Hongyan, Yijie Yang, Yue Zhang, et al.. (2023). Positive Progesterone Receptor Expression in Meningioma May Increase the Transverse Relaxation: First Prospective Clinical Trial Using Single-Shot Ultrafast T2 Mapping. Academic Radiology. 31(1). 187–198. 5 indexed citations
10.
Yang, Qinqin, Jianfeng Bao, Xiaoyin Wang, et al.. (2022). MOdel-Based SyntheTic Data-Driven Learning (MOST-DL): Application in Single-Shot T2 Mapping With Severe Head Motion Using Overlapping-Echo Acquisition. IEEE Transactions on Medical Imaging. 41(11). 3167–3181. 24 indexed citations
11.
Wu, Jian, Jiazheng Wang, Liangjie Lin, et al.. (2022). IMPULSED model based cytological feature estimation with U‐Net: Application to human brain tumor at 3T. Magnetic Resonance in Medicine. 89(1). 411–422. 7 indexed citations
12.
Huang, Jianpan, Jian Wu, Lin Chen, et al.. (2022). Ultrafast water–fat separation using deep learning–based single‐shot MRI. Magnetic Resonance in Medicine. 87(6). 2811–2825. 7 indexed citations
13.
Ma, Lingceng, Jian Wu, Qinqin Yang, et al.. (2022). Single-shot multi-parametric mapping based on multiple overlapping-echo detachment (MOLED) imaging. NeuroImage. 263. 119645–119645. 15 indexed citations
14.
Huang, Yuqing, et al.. (2014). High-Resolution Two-Dimensional J-Resolved NMR Spectroscopy for Biological Systems. Biophysical Journal. 106(9). 2061–2070. 24 indexed citations
15.
Bao, Lijun, et al.. (2013). An aliasing artifacts reducing approach with random undersampling for spatiotemporally encoded single-shot MRI. Journal of Magnetic Resonance. 237. 115–124. 31 indexed citations
16.
Lin, Yanqin, et al.. (2011). High-resolution absorptive intermolecular multiple-quantum coherence NMR spectroscopy under inhomogeneous fields. Journal of Magnetic Resonance. 214(1). 289–295. 7 indexed citations
17.
Huang, Yuqing, et al.. (2010). High-resolution 2D NMR spectra in inhomogeneous fields based on intermolecular multiple-quantum coherences with efficient acquisition schemes. Journal of Magnetic Resonance. 208(1). 87–94. 9 indexed citations
18.
Xu, Jingjing, et al.. (2009). Metabonomics studies of intact hepatic and renal cortical tissues from diabetic db/db mice using high-resolution magic-angle spinning 1H NMR spectroscopy. Analytical and Bioanalytical Chemistry. 393(6-7). 1657–1668. 33 indexed citations
19.
Cai, Shuhui. (2005). Optimized Parameters in Intermolecular Multiple-quantum Coherence NMR with CRAZED Sequence. Journal of Xiamen University. 1 indexed citations
20.
Cai, Shuhui, et al.. (1995). Geochemical characteristics of cultivation profiles in Lake Honghu. UCL Discovery (University College London). 1 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by K. J. Packer Breakdown of academic impact, for papers by P. T. Callaghan Breakdown of academic impact, for papers by Scott A. Smith Breakdown of academic impact, for papers by Vikram S. Bajaj Breakdown of academic impact, for papers by Christopher G. Morgan Breakdown of academic impact, for papers by Songi Han Breakdown of academic impact, for papers by Yoshihiro Mori Breakdown of academic impact, for papers by Sarah E. Bohndiek Breakdown of academic impact, for papers by W. S. Hinshaw Breakdown of academic impact, for papers by Wojciech Froncisz
Rankless by CCL
2026