Xiaomeng Shi

481 total citations · 1 hit paper
20 papers, 318 citations indexed

About

Xiaomeng Shi is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Global and Planetary Change. According to data from OpenAlex, Xiaomeng Shi has authored 20 papers receiving a total of 318 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 12 papers in Biomedical Engineering and 4 papers in Global and Planetary Change. Recurrent topics in Xiaomeng Shi's work include Advanced X-ray and CT Imaging (12 papers), Radiation Dose and Imaging (10 papers) and Medical Imaging Techniques and Applications (6 papers). Xiaomeng Shi is often cited by papers focused on Advanced X-ray and CT Imaging (12 papers), Radiation Dose and Imaging (10 papers) and Medical Imaging Techniques and Applications (6 papers). Xiaomeng Shi collaborates with scholars based in China, United Kingdom and Germany. Xiaomeng Shi's co-authors include Jianying Li, Xueqian Xie, Rozemarijn Vliegenthart, Shuai Zhang, Geertruida H. de Bock, Beibei Jiang, Weiwu Yao, Jingyu Zhong, Yong Chen and Wei Lu and has published in prestigious journals such as Nature Communications, Remote Sensing of Environment and Radiology.

In The Last Decade

Xiaomeng Shi

20 papers receiving 310 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep Learning Reconstruction Shows Better Lung Nodule Detection for Ultra–Low-Dose Chest CT

2022 118 citations Beibei Jiang, Xiaomeng Shi et al. Radiology profile →

Peers

Xiaomeng Shi

RNMI

PRM

Yutaro Mori Japan

Roman Wesołowski United Kingdom

Cynthia Araujo Canada

Venkataramanan Krishnaswamy United States

Hyun Keol Kim United States

Yacheng Ren China

Parinaz Mehnati Iran

Annika M. K. Nilsson Sweden

M Rodriguez United States

Yutaro Mori Japan

Xiaomeng Shi

63 ×0.3

RNMI

26 ×0.2

60 ×0.8

PRM

46 ×1.3

12 ×0.5

Citations per year, relative to Xiaomeng Shi Xiaomeng Shi (= 1×) peers Yutaro Mori

Countries citing papers authored by Xiaomeng Shi

Since Specialization

Citations

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

Fields of papers citing papers by Xiaomeng Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaomeng Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaomeng Shi. A scholar is included among the top collaborators of Xiaomeng Shi 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 Xiaomeng Shi. Xiaomeng Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Wang, Zhongzhi, et al.. (2025). Renewable energy investment under carbon trading mechanism: the impact of green financing and carbon emission quota. Environment Development and Sustainability. 3 indexed citations

Zhong, Jingyu, Lingling Wang, Chao Yan, et al.. (2024). Deep learning image reconstruction generates thinner slice iodine maps with improved image quality to increase diagnostic acceptance and lesion conspicuity: a prospective study on abdominal dual-energy CT. BMC Medical Imaging. 24(1). 159–159. 6 indexed citations

Zhong, Jingyu, Zhiyuan Wu, Yong Chen, et al.. (2024). Impacts of Adaptive Statistical Iterative Reconstruction-V and Deep Learning Image Reconstruction Algorithms on Robustness of CT Radiomics Features: Opportunity for Minimizing Radiomics Variability Among Scans of Different Dose Levels. Journal of Imaging Informatics in Medicine. 37(1). 123–133. 5 indexed citations

Zhong, Jingyu, Y. Hu, Yue Xing, et al.. (2024). Deep learning image reconstruction for low-kiloelectron volt virtual monoenergetic images in abdominal dual-energy CT: medium strength provides higher lesion conspicuity. Acta Radiologica. 65(9). 1133–1146. 2 indexed citations

Zhu, Hong, et al.. (2024). The impact of deep learning image reconstruction of spectral CTU virtual non contrast images for patients with renal stones. European Journal of Radiology Open. 13. 100599–100599. 1 indexed citations

Fan, Aili, Dong Liu, Hongwei Jin, et al.. (2024). Biosynthesis of Epipyrone A Reveals a Highly Specific Membrane-Bound Fungal C-Glycosyltransferase for Pyrone Galactosylation. Organic Letters. 26(6). 1160–1165. 4 indexed citations

Li, Yi, et al.. (2023). Detection of dawn sea fog/low stratus using geostationary satellite imagery. Remote Sensing of Environment. 294. 113622–113622. 9 indexed citations

Wang, Yong, Jingming Zhang, Boyang Han, et al.. (2023). Noncanonical amino acids as doubly bio-orthogonal handles for one-pot preparation of protein multiconjugates. Nature Communications. 14(1). 974–974. 42 indexed citations

Zhong, Jingyu, Lingyun Wang, Hailin Shen, et al.. (2023). Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers. European Radiology. 33(8). 5331–5343. 10 indexed citations

10.

Shi, Xiaomeng, et al.. (2023). Applicability comparison of three classical remote sensing retrieval methods for nighttime sea fog in Shandong offshore. 113. 31–31. 1 indexed citations

11.

Zhong, Jingyu, Zilai Pan, Yong Chen, et al.. (2023). Robustness of radiomics features of virtual unenhanced and virtual monoenergetic images in dual-energy CT among different imaging platforms and potential role of CT number variability. Insights into Imaging. 14(1). 79–79. 9 indexed citations

12.

Zhong, Jingyu, Hailin Shen, Yong Chen, et al.. (2023). Evaluation of Image Quality and Detectability of Deep Learning Image Reconstruction (DLIR) Algorithm in Single- and Dual-energy CT. Journal of Digital Imaging. 36(4). 1390–1407. 14 indexed citations

13.

Chen, Yong, Jingyu Zhong, Lan Wang, et al.. (2022). Robustness of CT radiomics features: consistency within and between single-energy CT and dual-energy CT. European Radiology. 32(8). 5480–5490. 28 indexed citations

14.

Chen, Yong, Jingyu Zhong, Lan Wang, et al.. (2022). Multivendor Comparison of Quantification Accuracy of Iodine Concentration and Attenuation Measurements by Dual-Energy CT: A Phantom Study. American Journal of Roentgenology. 219(5). 827–839. 16 indexed citations

15.

Zhong, Jingyu, Yong Chen, Jianying Li, et al.. (2022). Deep learning image reconstruction algorithm reduces image noise while alters radiomics features in dual-energy CT in comparison with conventional iterative reconstruction algorithms: a phantom study. European Radiology. 33(2). 812–824. 24 indexed citations

16.

Jiang, Beibei, Xiaomeng Shi, Shuai Zhang, et al.. (2022). Deep Learning Reconstruction Shows Better Lung Nodule Detection for Ultra–Low-Dose Chest CT. Radiology. 303(1). 202–212. 118 indexed citations breakdown →

17.

Meng, Qianqian, et al.. (2022). Prediction of proton beam range in phantom with metals based on monochromatic energy CT images. Journal of Radiation Research. 63(6). 828–837. 1 indexed citations

18.

Wang, Shengkai, Yi Li, Suping Zhang, Xiaomeng Shi, & Xianyao Chen. (2020). The Microphysical Properties of a Sea-Fog Event along the West Coast of the Yellow Sea in Spring. Atmosphere. 11(4). 413–413. 5 indexed citations

19.

Li, Yi, Boris Thies, Suping Zhang, Xiaomeng Shi, & Jörg Bendix. (2015). Optical Thickness and Effective Radius Retrievals of Low Stratus and Fog from MTSAT Daytime Data as a Prerequisite for Yellow Sea Fog Detection. Remote Sensing. 8(1). 8–8. 18 indexed citations

20.

Shi, Xiaomeng, et al.. (2015). Impact of autumn SST in the Japan Sea on winter rainfall and air temperature in Northeast China. Journal of Ocean University of China. 14(4). 604–611. 2 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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