Hongbo Guo

1.6k total citations
94 papers, 1.2k citations indexed

About

Hongbo Guo is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Biophysics. According to data from OpenAlex, Hongbo Guo has authored 94 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Biomedical Engineering, 46 papers in Radiology, Nuclear Medicine and Imaging and 15 papers in Biophysics. Recurrent topics in Hongbo Guo's work include Optical Imaging and Spectroscopy Techniques (44 papers), Photoacoustic and Ultrasonic Imaging (40 papers) and Spectroscopy Techniques in Biomedical and Chemical Research (12 papers). Hongbo Guo is often cited by papers focused on Optical Imaging and Spectroscopy Techniques (44 papers), Photoacoustic and Ultrasonic Imaging (40 papers) and Spectroscopy Techniques in Biomedical and Chemical Research (12 papers). Hongbo Guo collaborates with scholars based in China, Germany and United Kingdom. Hongbo Guo's co-authors include Xiaowei He, Haitao Lei, Rui Cao, Jingjing Yu, Zhenhua Hu, Kai Guo, Wei Zhang, Jie Tian, Xialiang Li and Muhan Liu and has published in prestigious journals such as Advanced Materials, Angewandte Chemie International Edition and SHILAP Revista de lepidopterología.

In The Last Decade

Hongbo Guo

81 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hongbo Guo China 20 567 356 346 235 205 94 1.2k
Defu Chen China 24 856 1.5× 155 0.4× 143 0.4× 246 1.0× 338 1.6× 113 1.6k
Hongji Liu China 21 639 1.1× 122 0.3× 136 0.4× 673 2.9× 90 0.4× 60 1.3k
Jianlong Yang China 25 361 0.6× 591 1.7× 707 2.0× 550 2.3× 622 3.0× 82 2.1k
Tianxiong Wang China 19 345 0.6× 403 1.1× 127 0.4× 853 3.6× 431 2.1× 34 2.0k
Mu He China 25 185 0.3× 132 0.4× 635 1.8× 323 1.4× 700 3.4× 66 2.0k
Jinyuan Liu China 21 262 0.5× 451 1.3× 25 0.1× 588 2.5× 429 2.1× 95 1.4k
Xiuli Li China 20 239 0.4× 52 0.1× 137 0.4× 158 0.7× 439 2.1× 70 1.1k
Wei Yan China 27 557 1.0× 107 0.3× 32 0.1× 927 3.9× 596 2.9× 122 2.0k
Weiye Song China 16 312 0.6× 166 0.5× 124 0.4× 517 2.2× 288 1.4× 62 995

Countries citing papers authored by Hongbo Guo

Since Specialization
Citations

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

Fields of papers citing papers by Hongbo Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hongbo Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Hongbo Guo. A scholar is included among the top collaborators of Hongbo Guo 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 Hongbo Guo. Hongbo Guo 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, Beilei, Shuangchen Li, Jia Li, et al.. (2025). Deep system prior based graph convolution network for NIR-II fluorescence molecular tomography. Computer Methods and Programs in Biomedicine. 270. 108948–108948.
2.
Yang, Lijuan, Yunxiang Ma, Xiaowei He, et al.. (2025). Exploring the neural mechanisms of ADHD in children: a multifeature cross-task fNIRS analysis. Cerebral Cortex. 35(6).
3.
De, Wei, et al.. (2025). SETDN: Signal-extraction and target-detection network for dynamic fluorescence molecular tomography. Expert Systems with Applications. 297. 129441–129441. 1 indexed citations
4.
He, Xiaowei, et al.. (2025). Iterative Up-and-Down Sampling Network Based on Pyramid Pooling and Attention Mechanism for 3-D System Matrix Recovery in MPI. IEEE Transactions on Instrumentation and Measurement. 74. 1–12.
5.
Zhang, Li‐Zhi, Jintao Li, Fang Ge, et al.. (2024). Current reconstruction approaches of magnetic particle imaging: A review. Journal of Magnetism and Magnetic Materials. 594. 171894–171894. 6 indexed citations
6.
Guo, Hongbo, et al.. (2024). Dynamic fluorescence molecular tomography metabolic parameters solution based on problem decomposition and prior refactor. Journal of Biophotonics. 17(4). e202300445–e202300445. 1 indexed citations
7.
Yi, Huangjian, Ruigang Yang, Yihan Wang, et al.. (2024). Enhanced model iteration algorithm with graph neural network for diffuse optical tomography. Biomedical Optics Express. 15(3). 1910–1910. 1 indexed citations
8.
Liang, Zuozhong, Guojun Zhou, Jieling Zhang, et al.. (2024). Constructing Co4(SO4)4 Clusters within Metal–Organic Frameworks for Efficient Oxygen Electrocatalysis. Advanced Materials. 36(38). e2408094–e2408094. 31 indexed citations
9.
Zhang, Lizhi, Hongbo Guo, Jintao Li, et al.. (2023). Multi-target reconstruction strategy based on blind source separation of surface measurement signals in FMT. Biomedical Optics Express. 14(3). 1159–1159. 4 indexed citations
10.
Zhao, Yizhe, Shuangchen Li, Xuelei He, et al.. (2023). Liver injury monitoring using dynamic fluorescence molecular tomography based on a time-energy difference strategy. Biomedical Optics Express. 14(10). 5298–5298. 4 indexed citations
11.
Guo, Hongbo, et al.. (2023). Multi-target reconstruction based on subspace decision optimization for bioluminescence tomography. Computer Methods and Programs in Biomedicine. 240. 107711–107711. 1 indexed citations
12.
Wang, Beilei, Shuangchen Li, Lizhi Zhang, et al.. (2023). A review of methods for solving the optical molecular tomography. Journal of Applied Physics. 133(13). 11 indexed citations
13.
Li, Jintao, Lizhi Zhang, Jia Liu, et al.. (2023). An adaptive parameter selection strategy based on maximizing the probability of data for robust fluorescence molecular tomography reconstruction. Journal of Biophotonics. 16(8). e202300031–e202300031. 2 indexed citations
14.
Yin, Lin, Hongbo Guo, Peng Zhang, et al.. (2022). System matrix recovery based on deep image prior in magnetic particle imaging. Physics in Medicine and Biology. 68(3). 35006–35006. 18 indexed citations
15.
Guo, Hongbo, Jingjing Yu, Xuelei He, et al.. (2021). Total Variation Constrained Graph Manifold Learning Strategy for Cerenkov Luminescence Tomography. Optics Express. 30(2). 1422–1422. 10 indexed citations
16.
Guo, Hongbo, et al.. (2021). Correntropy-induced metric with Laplacian kernel for robust fluorescence molecular tomography. Biomedical Optics Express. 12(10). 5991–5991. 6 indexed citations
17.
Guo, Hongbo, et al.. (2020). Sparse‐graph manifold learning method for bioluminescence tomography. Journal of Biophotonics. 13(4). e201960218–e201960218. 14 indexed citations
18.
Guo, Hongbo, et al.. (2020). OCSID: Orthogonal Accessing Control Without Spectrum Spreading for Massive RFID Network. IEEE Internet of Things Journal. 8(6). 4329–4338. 1 indexed citations
19.
Cao, Xin, Linzhi Su, Lin Wang, et al.. (2019). A fuzzy artificial neural network-based method for Cerenkov luminescence tomography. AIP Advances. 9(6). 4 indexed citations
20.
He, Xiaowei, Hongbo Guo, Jingjing Yu, Xu Zhang, & Yuqing Hou. (2015). Effective and robust approach for fluorescence molecular tomography based on CoSaMP and SP3 model. Journal of Innovative Optical Health Sciences. 9(6). 1650024–1650024. 15 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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