Xiaozhu Lin

1.4k total citations
72 papers, 922 citations indexed

About

Xiaozhu Lin is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Biomedical Engineering. According to data from OpenAlex, Xiaozhu Lin has authored 72 papers receiving a total of 922 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Radiology, Nuclear Medicine and Imaging, 21 papers in Oncology and 14 papers in Biomedical Engineering. Recurrent topics in Xiaozhu Lin's work include Pancreatic and Hepatic Oncology Research (18 papers), Radiomics and Machine Learning in Medical Imaging (16 papers) and Advanced X-ray and CT Imaging (13 papers). Xiaozhu Lin is often cited by papers focused on Pancreatic and Hepatic Oncology Research (18 papers), Radiomics and Machine Learning in Medical Imaging (16 papers) and Advanced X-ray and CT Imaging (13 papers). Xiaozhu Lin collaborates with scholars based in China, United States and Switzerland. Xiaozhu Lin's co-authors include Xiaohua Qian, Kemin Chen, Jun Li, Biao Li, Fuhua Yan, Shudong Hu, Xin‐Yun Huang, Peijie Lv, Weimin Chai and Qi Song and has published in prestigious journals such as International Journal of Radiation Oncology*Biology*Physics, IEEE Transactions on Medical Imaging and Human Brain Mapping.

In The Last Decade

Xiaozhu Lin

69 papers receiving 906 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaozhu Lin China 19 567 290 229 137 111 72 922
Zhenchao Tang China 15 1.3k 2.3× 212 0.7× 405 1.8× 352 2.6× 202 1.8× 31 1.5k
Robertus H.C. Bisschops Netherlands 9 455 0.8× 108 0.4× 195 0.9× 320 2.3× 169 1.5× 11 939
Alessandro Stefano Italy 25 880 1.6× 298 1.0× 124 0.5× 431 3.1× 207 1.9× 82 1.3k
Jiangfen Wu China 21 755 1.3× 199 0.7× 78 0.3× 374 2.7× 93 0.8× 44 981
Pierre Decazes France 19 451 0.8× 111 0.4× 181 0.8× 198 1.4× 90 0.8× 55 831
Fides R. Schwartz United States 15 393 0.7× 271 0.9× 72 0.3× 70 0.5× 102 0.9× 54 643
Wansheng Long China 16 558 1.0× 134 0.5× 76 0.3× 342 2.5× 116 1.0× 50 722
Rajarsi Gupta United States 18 643 1.1× 288 1.0× 155 0.7× 82 0.6× 468 4.2× 51 1.3k

Countries citing papers authored by Xiaozhu Lin

Since Specialization
Citations

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

Fields of papers citing papers by Xiaozhu Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaozhu Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaozhu Lin. A scholar is included among the top collaborators of Xiaozhu Lin 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 Xiaozhu Lin. Xiaozhu Lin 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.
Song, Huijia, et al.. (2024). ACP-ESM2: The prediction of anticancer peptides based on pre-trained classifier. Computational Biology and Chemistry. 110. 108091–108091. 3 indexed citations
2.
Zhang, Miao, Lijun Wang, Xiaozhu Lin, et al.. (2024). Topographic metabolism‐function relationships in Alzheimer's disease: A simultaneous PET/MRI study. Human Brain Mapping. 45(2). e26604–e26604. 3 indexed citations
3.
Lin, Xiaozhu, Song Liu, Chengyuan Liu, & Yang Wang. (2024). Dynamic Modeling of Robotic Fish considering Background Flow using Koopman Operators. 11843–11848.
4.
5.
Tang, Hao, Yijun Cheng, Hong Yao, et al.. (2023). DRD2 expression based on 18F-fallypride PET/MR predicts the dopamine agonist resistance of prolactinomas: a pilot study. Endocrine. 80(2). 419–424. 4 indexed citations
6.
Wang, Weishen, Siwen Wang, Xin‐Yun Huang, et al.. (2023). The value of 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance whole-body scans and local enhancement scans in the preoperative staging and resectability assessment of pancreatic adenocarcinoma. Quantitative Imaging in Medicine and Surgery. 13(3). 1768–1778. 2 indexed citations
7.
Zhang, Miao, Xiaohang Qian, Yaoyu Zhang, et al.. (2023). Integrating TSPO PET imaging and transcriptomics to unveil the role of neuroinflammation and amyloid-β deposition in Alzheimer’s disease. European Journal of Nuclear Medicine and Molecular Imaging. 51(2). 455–467. 15 indexed citations
8.
Shi, Minmin, Zhichong Wu, Meilin Xue, et al.. (2023). LIPH contributes to glycolytic phenotype in pancreatic ductal adenocarcinoma by activating LPA/LPAR axis and maintaining ALDOA stability. Journal of Translational Medicine. 21(1). 838–838. 10 indexed citations
9.
10.
Li, Jun, et al.. (2021). Model-Driven Deep Learning Method for Pancreatic Cancer Segmentation Based on Spiral-Transformation. IEEE Transactions on Medical Imaging. 41(1). 75–87. 25 indexed citations
11.
Li, Binyin, Miao Zhang, Xiaozhu Lin, et al.. (2021). Amyloid-Beta Influences Memory via Functional Connectivity During Memory Retrieval in Alzheimer's Disease. Frontiers in Aging Neuroscience. 13. 721171–721171. 6 indexed citations
12.
Guo, Rui, Xiaobin Hu, Pengpeng Xu, et al.. (2021). Weakly supervised deep learning for determining the prognostic value of 18F-FDG PET/CT in extranodal natural killer/T cell lymphoma, nasal type. European Journal of Nuclear Medicine and Molecular Imaging. 48(10). 3151–3161. 30 indexed citations
13.
Tuan, Jeffrey, et al.. (2020). Evaluation of the Prostate Gland Contour Variations Based on CT-alone, CT/TPUS and CT/MRI Images. International Journal of Radiation Oncology*Biology*Physics. 108(3). e262–e262. 1 indexed citations
14.
Lin, Xiaozhu, et al.. (2020). Combined Spiral Transformation and Model-Driven Multi-Modal Deep Learning Scheme for Automatic Prediction of TP53 Mutation in Pancreatic Cancer. IEEE Transactions on Medical Imaging. 40(2). 735–747. 32 indexed citations
15.
Yu, Yixing, Xiaozhu Lin, Kemin Chen, et al.. (2013). Values of spectral CT imaging in differential diagnosis of hepatocellular carcinoma and focal nodular hyperplasia. Zhonghua fangshexian yixue zazhi. 47(2). 121–126. 1 indexed citations
16.
Yu, Yang, Naying He, Kang Sun, et al.. (2013). Differentiating hepatocellular carcinoma from angiomyolipoma of the liver with CT spectral imaging: A preliminary study. Clinical Radiology. 68(9). e491–e497. 25 indexed citations
17.
Lin, Xiaozhu, Kemin Chen, Zhiyuan Wu, & Jing Zhang. (2011). Spectral CT imaging in differential diagnosis of pancreatic serous oligocystic adenoma and mucinous cystic neoplasms. Zhonghua fangshexian yixue zazhi. 45(8). 713–717. 2 indexed citations
18.
Xu, Xiao, et al.. (2010). Prospective study comparing two iodine concentrations for multidetector computed tomography of the pancreas. La radiologia medica. 115(6). 898–905. 6 indexed citations
19.
Liu, Yu, et al.. (2009). Intraductal papillary mucinous neoplasms of the pancreas: Correlation of helical CT features with pathologic findings. European Journal of Radiology. 76(2). 222–227. 9 indexed citations
20.
Lin, Xiaozhu, et al.. (2006). A proof of image Euler Number formula. Science in China Series F Information Sciences. 49(3). 364–371. 6 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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