Wanlin Peng

444 total citations
34 papers, 298 citations indexed

About

Wanlin Peng is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Wanlin Peng has authored 34 papers receiving a total of 298 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Cardiology and Cardiovascular Medicine and 8 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Wanlin Peng's work include Advanced MRI Techniques and Applications (10 papers), Cardiac Imaging and Diagnostics (8 papers) and MRI in cancer diagnosis (7 papers). Wanlin Peng is often cited by papers focused on Advanced MRI Techniques and Applications (10 papers), Cardiac Imaging and Diagnostics (8 papers) and MRI in cancer diagnosis (7 papers). Wanlin Peng collaborates with scholars based in China, United States and Germany. Wanlin Peng's co-authors include Chunchao Xia, Zhenlin Li, Yingkun Guo, Jinge Zhang, Zihan Meng, Bowen Ke, Fang Wang, Qixian Chen, Yao Wang and Peng Mi and has published in prestigious journals such as Biomaterials, Scientific Reports and Medicine.

In The Last Decade

Wanlin Peng

30 papers receiving 295 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wanlin Peng China 11 170 84 69 39 38 34 298
Deirdre Cassidy United Kingdom 7 94 0.6× 115 1.4× 100 1.4× 119 3.1× 95 2.5× 13 353
Benjamin King United States 10 116 0.7× 44 0.5× 191 2.8× 98 2.5× 128 3.4× 29 467
Federica Ciolina Italy 9 136 0.8× 141 1.7× 49 0.7× 120 3.1× 70 1.8× 26 362
Pierre‐Olivier Comby France 12 157 0.9× 116 1.4× 29 0.4× 105 2.7× 130 3.4× 36 414
Oshaani Abeyakoon United Kingdom 8 197 1.2× 149 1.8× 40 0.6× 91 2.3× 27 0.7× 14 387
Sylvie Chillon France 9 125 0.7× 27 0.3× 91 1.3× 54 1.4× 88 2.3× 16 278
Julia Wiedemann Germany 9 100 0.6× 21 0.3× 25 0.4× 62 1.6× 105 2.8× 16 297
Aline Criton France 10 276 1.6× 253 3.0× 140 2.0× 86 2.2× 82 2.2× 17 455
Sylvia Kinzel Germany 10 188 1.1× 62 0.7× 110 1.6× 92 2.4× 65 1.7× 14 345
Luisa Di Mare Italy 6 142 0.8× 133 1.6× 40 0.6× 39 1.0× 97 2.6× 7 299

Countries citing papers authored by Wanlin Peng

Since Specialization
Citations

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

Fields of papers citing papers by Wanlin Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wanlin Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Wanlin Peng. A scholar is included among the top collaborators of Wanlin Peng 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 Wanlin Peng. Wanlin Peng 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.
Xia, Chunchao, Jing Tang, Yao Li, et al.. (2025). Evaluation of high-resolution pituitary dynamic contrast-enhanced MRI using deep learning–based compressed sensing and super-resolution reconstruction. European Radiology. 35(10). 5922–5934. 1 indexed citations
2.
Li, Hanyu, Zejun Liang, Rong Fu, et al.. (2025). Deep Learning-Based Segmentation of Gravity-Loaded Human Spine. Journal of Visualized Experiments.
3.
Dong, Xiaoyu, et al.. (2025). Meta-analysis of risk factors for oral frailty in older adults. Geriatric Nursing. 62(Pt A). 7–12.
4.
5.
Peng, Wanlin, et al.. (2023). Accelerated 3D MR neurography of the brachial plexus using deep learning–constrained compressed sensing. European Radiology. 34(2). 842–851. 10 indexed citations
6.
Peng, Wanlin, Hongwei Li, Yingkun Guo, et al.. (2023). Cardiovascular indicators associated with ventricular remodeling in chronic high-altitude disease: a cardiovascular MRI study. European Radiology. 33(9). 6267–6277.
7.
Chen, Dun, Guoyu Li, Jinming Li, et al.. (2023). Mechanical characteristics and damage evolution of granite under freeze–thaw cycles. Frontiers in Energy Research. 10. 6 indexed citations
8.
Peng, Wanlin, Yi Xiao, Wen Zeng, et al.. (2022). Rapid 3D breath-hold MR cholangiopancreatography using deep learning–constrained compressed sensing reconstruction. European Radiology. 33(4). 2500–2509. 15 indexed citations
9.
Xu, Xu, Wen Zeng, Wanlin Peng, et al.. (2021). Deep learning trained algorithm maintains the quality of half-dose contrast-enhanced liver computed tomography images: Comparison with hybrid iterative reconstruction. European Journal of Radiology. 135. 109487–109487. 18 indexed citations
10.
He, Yong, Zhao Qin, Huayan Xu, et al.. (2021). Characterization of infarcted myocardium by T1-mapping and its association with left ventricular remodeling. European Journal of Radiology. 137. 109590–109590. 5 indexed citations
11.
Peng, Wanlin, Tianjing Zhang, Ke Shi, et al.. (2021). Automatic machine learning based on native T1 mapping can identify myocardial fibrosis in patients with hypertrophic cardiomyopathy. European Radiology. 32(2). 1044–1053. 9 indexed citations
12.
Zeng, Wen, Xu Xu, Jinge Zhang, et al.. (2021). [Noise Reduction Effect of Deep-learning-based Image Reconstruction Algorithms in Thin-section Chest CT].. PubMed Central. 52(2). 286–292. 2 indexed citations
13.
Shi, Ke, Min Ma, Chunchao Xia, et al.. (2021). Increased oxygenation is associated with myocardial inflammation and adverse regional remodeling after acute ST-segment elevation myocardial infarction. European Radiology. 31(12). 8956–8966. 3 indexed citations
14.
Xu, Huayan, Wanlin Peng, Zhi‐gang Yang, et al.. (2021). The association of secondary hyperparathyroidism and myocardial damages in hemodialysis end-stage renal disease patients: assessed by cardiovascular magnetic resonance native T1 mapping. Journal of Cardiovascular Magnetic Resonance. 23(1). 23–23. 5 indexed citations
15.
16.
Li, Zhenlin, Jinge Zhang, Chunchao Xia, et al.. (2020). Radiation doses in CT examinations from the West China Hospital, Sichuan University and setting local diagnostic references levels. Annals of Translational Medicine. 8(16). 1010–1010. 12 indexed citations
17.
Diao, Kaiyue, Jinge Zhang, Wanlin Peng, et al.. (2019). Achieving Low Radiation Dose in “One-Stop” Myocardial Computed Tomography Perfusion Imaging in Coronary Artery Disease Using 16-cm Wide Detector CT. Academic Radiology. 27(11). 1531–1539. 2 indexed citations
18.
Wang, Jin, Zhi‐gang Yang, Yan Ren, et al.. (2019). Cardiac magnetic resonance feature tracking for quantifying right ventricular deformation in type 2 diabetes mellitus patients. Scientific Reports. 9(1). 11148–11148. 15 indexed citations
19.
Peng, Wanlin, Zhenlin Li, Huayan Xu, et al.. (2018). Assessment of right ventricular dysfunction in end-stage renal disease patients on maintenance haemodialysis by cardiac magnetic resonance imaging. European Journal of Radiology. 102. 89–94. 13 indexed citations
20.
Peng, Wanlin, Zhenlin Li, Chunchao Xia, et al.. (2017). A CONSORT-compliant prospective randomized controlled trial. Medicine. 96(30). e7324–e7324. 14 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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