Guobing Liu

1.4k total citations
78 papers, 923 citations indexed

About

Guobing Liu is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Surgery. According to data from OpenAlex, Guobing Liu has authored 78 papers receiving a total of 923 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Radiology, Nuclear Medicine and Imaging, 18 papers in Pulmonary and Respiratory Medicine and 10 papers in Surgery. Recurrent topics in Guobing Liu's work include Medical Imaging Techniques and Applications (30 papers), Radiomics and Machine Learning in Medical Imaging (17 papers) and Advanced MRI Techniques and Applications (11 papers). Guobing Liu is often cited by papers focused on Medical Imaging Techniques and Applications (30 papers), Radiomics and Machine Learning in Medical Imaging (17 papers) and Advanced MRI Techniques and Applications (11 papers). Guobing Liu collaborates with scholars based in China, United States and United Kingdom. Guobing Liu's co-authors include Haojun Yu, Hongcheng Shi, Pengcheng Hu, Yiqiu Zhang, Hui Tan, Yan Hu, Dengfeng Cheng, Hongcheng Shi, Hongcheng Shi and Jianying Gu and has published in prestigious journals such as Biomaterials, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Guobing Liu

73 papers receiving 912 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guobing Liu China 17 492 221 184 116 95 78 923
Michael Hentschel Germany 17 598 1.2× 164 0.7× 231 1.3× 126 1.1× 66 0.7× 59 1.0k
Natale Quartuccio Italy 20 381 0.8× 82 0.4× 258 1.4× 169 1.5× 100 1.1× 76 966
Silvia Chiesa Italy 16 248 0.5× 111 0.5× 330 1.8× 106 0.9× 179 1.9× 76 972
Steve Cho United States 18 481 1.0× 474 2.1× 408 2.2× 172 1.5× 265 2.8× 74 1.4k
Hui Tan China 17 530 1.1× 206 0.9× 191 1.0× 100 0.9× 36 0.4× 46 875
Felipe de Galiza Barbosa Switzerland 18 659 1.3× 99 0.4× 436 2.4× 100 0.9× 48 0.5× 50 1.0k
Lucia Baratto United States 16 540 1.1× 104 0.5× 304 1.7× 38 0.3× 123 1.3× 66 918
Jürgen Debus Germany 15 542 1.1× 253 1.1× 332 1.8× 127 1.1× 337 3.5× 50 1.2k
Kalliopi Platoni Greece 14 156 0.3× 93 0.4× 208 1.1× 88 0.8× 162 1.7× 89 711
Oreste Bagni Italy 15 405 0.8× 51 0.2× 283 1.5× 163 1.4× 112 1.2× 63 832

Countries citing papers authored by Guobing Liu

Since Specialization
Citations

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

Fields of papers citing papers by Guobing Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guobing Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Guobing Liu. A scholar is included among the top collaborators of Guobing Liu 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 Guobing Liu. Guobing Liu 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.
2.
Pang, Lifang, Guobing Liu, Shuguang Chen, et al.. (2024). Comparison of the Accuracy of a Deep Learning Method for Lesion Detection in PET/CT and PET/MRI Images. Molecular Imaging and Biology. 26(5). 802–811. 1 indexed citations
3.
Zhang, Shaoyuan, Guobing Liu, Dongxian Jiang, et al.. (2024). ASO Visual Abstract: Development and Validation of PET/CT-Based Nomogram for Preoperative Prediction of Lymph Node Status in Esophageal Squamous Cell Carcinoma. Annals of Surgical Oncology. 31(6). 3864–3865. 1 indexed citations
4.
Liu, Guobing, et al.. (2023). Dynamic total-body PET/CT imaging with reduced acquisition time shows acceptable performance in quantification of [18F]FDG tumor kinetic metrics. European Journal of Nuclear Medicine and Molecular Imaging. 51(5). 1371–1382. 4 indexed citations
5.
Liu, Guobing, Wujian Mao, Haojun Yu, et al.. (2023). One-stop [18F]FDG and [68Ga]Ga-DOTA-FAPI-04 total-body PET/CT examination with dual-low activity: a feasibility study. European Journal of Nuclear Medicine and Molecular Imaging. 50(8). 2271–2281. 22 indexed citations
6.
Pang, Lifang, Wujian Mao, Yiqiu Zhang, et al.. (2023). Comparison of 18F-FDG PET/MR and PET/CT for pretreatment TNM staging of hilar cholangiocarcinoma. Abdominal Radiology. 48(8). 2537–2546. 2 indexed citations
7.
Liu, Guobing, Hui Tan, Xiuli Sui, et al.. (2023). One-tenth-activity total-body positron emission tomography versus full-activity imaging in patients with a complex of hepatic malignant tumors: a retrospective study. Quantitative Imaging in Medicine and Surgery. 13(12). 8517–8530. 1 indexed citations
8.
Zhang, Yiqiu, Pengcheng Hu, Haojun Yu, et al.. (2022). Ultrafast 30-s total-body PET/CT scan: a preliminary study. European Journal of Nuclear Medicine and Molecular Imaging. 49(8). 2504–2513. 18 indexed citations
9.
Liu, Guobing, Pengcheng Hu, Haojun Yu, et al.. (2021). Ultra-low-activity total-body dynamic PET imaging allows equal performance to full-activity PET imaging for investigating kinetic metrics of 18F-FDG in healthy volunteers. European Journal of Nuclear Medicine and Molecular Imaging. 48(8). 2373–2383. 69 indexed citations
10.
Zhang, Shaoyuan, Dong Lin, Qiqi Cao, et al.. (2021). Which will carry more weight when CTR > 0.5, solid component size, CTR, tumor size or SUVmax?. Lung Cancer. 164. 14–22. 7 indexed citations
11.
Qiu, Lin, Qingyu Lin, Hui Tan, et al.. (2020). A Pretargeted Imaging Strategy for EGFR-Positive Colorectal Carcinoma via Modulation of Tz-Radioligand Pharmacokinetics. Molecular Imaging and Biology. 23(1). 38–51. 8 indexed citations
12.
Sui, Xiuli, Guobing Liu, Pengcheng Hu, et al.. (2020). Total-Body PET/Computed Tomography Highlights in Clinical Practice. PET Clinics. 16(1). 9–14. 29 indexed citations
13.
14.
Liu, Guobing, et al.. (2018). Variations of the liver standardized uptake value in relation to background blood metabolism. Medicine. 97(19). e0699–e0699. 11 indexed citations
15.
Hu, Yan, Guobing Liu, He Zhang, et al.. (2017). A Comparison of [99mTc]Duramycin and [99mTc]Annexin V in SPECT/CT Imaging Atherosclerotic Plaques. Molecular Imaging and Biology. 20(2). 249–259. 27 indexed citations
16.
Liu, Guobing, Yan Hu, Jie Xiao, et al.. (2016). 99mTc-labelled anti-CD11b SPECT/CT imaging allows detection of plaque destabilization tightly linked to inflammation. Scientific Reports. 6(1). 20900–20900. 20 indexed citations
17.
Li, Xiao, Cong Wang, Hui Tan, et al.. (2016). Gold nanoparticles-based SPECT/CT imaging probe targeting for vulnerable atherosclerosis plaques. Biomaterials. 108. 71–80. 66 indexed citations
18.
Wu, Guangyao, Xiangquan Kong, Guofeng Zhou, et al.. (2012). Resting-state, functional MRI on regional homogeneity changes of brain in the heavy smokers. Zhonghua fangshexian yixue zazhi. 46(3). 215–219. 1 indexed citations
19.
Liu, Guobing. (2008). ON THE USE OF LINKING ADVERBIALS IN SPOKEN ENGLISH: A CORPUS-BASED STUDY.
20.
Liu, Guobing. (2005). Analysis on Safety Supervision System of Chinese Coal Mines. 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.

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