Congbo Cai

1.9k total citations
103 papers, 1.3k citations indexed

About

Congbo Cai is a scholar working on Radiology, Nuclear Medicine and Imaging, Nuclear and High Energy Physics and Spectroscopy. According to data from OpenAlex, Congbo Cai has authored 103 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Radiology, Nuclear Medicine and Imaging, 27 papers in Nuclear and High Energy Physics and 26 papers in Spectroscopy. Recurrent topics in Congbo Cai's work include Advanced MRI Techniques and Applications (74 papers), NMR spectroscopy and applications (27 papers) and Advanced NMR Techniques and Applications (26 papers). Congbo Cai is often cited by papers focused on Advanced MRI Techniques and Applications (74 papers), NMR spectroscopy and applications (27 papers) and Advanced NMR Techniques and Applications (26 papers). Congbo Cai collaborates with scholars based in China, United States and Finland. Congbo Cai's co-authors include Zhong Chen, Shuhui Cai, Xiaobo Qu, Jianhui Zhong, Lijun Bao, Kun Zeng, Jian Wu, Lin Chen, Qinqin Yang and Weiru Zhang and has published in prestigious journals such as The Journal of Chemical Physics, NeuroImage and Journal of Materials Chemistry.

In The Last Decade

Congbo Cai

93 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Congbo Cai China 20 969 250 187 187 183 103 1.3k
Fan Lam United States 22 1.3k 1.3× 247 1.0× 64 0.3× 115 0.6× 262 1.4× 64 1.6k
Kecheng Liu China 16 1.6k 1.6× 176 0.7× 195 1.0× 95 0.5× 171 0.9× 38 2.0k
Ildar Khalidov Switzerland 10 980 1.0× 168 0.7× 56 0.3× 102 0.5× 63 0.3× 17 1.3k
Douglas A.C. Kelley United States 23 1.3k 1.3× 171 0.7× 113 0.6× 110 0.6× 337 1.8× 41 1.6k
Jeffrey Tsao Switzerland 20 1.5k 1.6× 139 0.6× 34 0.2× 59 0.3× 133 0.7× 30 1.7k
Ives R. Levesque Canada 21 1.3k 1.4× 93 0.4× 46 0.2× 102 0.5× 161 0.9× 44 1.6k
Anthony Christodoulou United States 20 1.2k 1.2× 131 0.5× 96 0.5× 28 0.1× 76 0.4× 82 1.4k
Antonio J. González Spain 29 1.5k 1.6× 347 1.4× 74 0.4× 244 1.3× 154 0.8× 196 2.5k
Yanqiu Feng China 21 678 0.7× 348 1.4× 99 0.5× 35 0.2× 43 0.2× 104 1.5k

Countries citing papers authored by Congbo Cai

Since Specialization
Citations

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

Fields of papers citing papers by Congbo Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Congbo Cai

This figure shows the co-authorship network connecting the top 25 collaborators of Congbo Cai. A scholar is included among the top collaborators of Congbo 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 Congbo Cai. Congbo 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.
Wang, Zi, Min Xiao, Chengyan Wang, et al.. (2025). Deep Separable Spatiotemporal Learning for Fast Dynamic Cardiac MRI. IEEE Transactions on Biomedical Engineering. 72(12). 3642–3654. 2 indexed citations
2.
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.
3.
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.
4.
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
5.
Lin, Liangjie, et al.. (2024). Spiral time-of-flight magnetic resonance angiography for intracranial vascular imaging: performance compared to conventional Cartesian angiogram. Quantitative Imaging in Medicine and Surgery. 14(5). 3417–3431.
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.
Zeng, Fantian, Sureya Nijiati, Qinqin Yang, et al.. (2023). Ferroptosis MRI for early detection of anticancer drug–induced acute cardiac/kidney injuries. Science Advances. 9(10). eadd8539–eadd8539. 44 indexed citations
10.
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
11.
Zhang, Chi, et al.. (2023). Toward Better Generalization Using Synthetic Data: A Domain Adaptation Framework for T2 Mapping via Multiple Overlapping-Echo Acquisition. IEEE Transactions on Medical Imaging. 44(9). 3504–3514. 4 indexed citations
12.
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
13.
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
14.
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
15.
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
16.
Sun, Liyan, Zhiwen Fan, Xinghao Ding, et al.. (2019). A divide-and-conquer approach to compressed sensing MRI. Magnetic Resonance Imaging. 63. 37–48. 3 indexed citations
17.
Zeng, Kun, et al.. (2018). Simultaneous single- and multi-contrast super-resolution for brain MRI images based on a convolutional neural network. Computers in Biology and Medicine. 99. 133–141. 101 indexed citations
18.
Zhang, Miao, et al.. (2015). Reduced field-of-view imaging for single-shot MRI with an amplitude-modulated chirp pulse excitation and Fourier transform reconstruction. Magnetic Resonance Imaging. 33(5). 503–515. 13 indexed citations
19.
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
20.
Zhang, Shengchun, Xiaoqin Zhu, Zhong Chen, et al.. (2008). Improvement in the contrast of CEST MRI via intermolecular double quantum coherences. Physics in Medicine and Biology. 53(14). N287–N296. 10 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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