Pingkun Yan

9.7k total citations · 3 hit papers
180 papers, 6.4k citations indexed

About

Pingkun Yan is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Pingkun Yan has authored 180 papers receiving a total of 6.4k indexed citations (citations by other indexed papers that have themselves been cited), including 100 papers in Computer Vision and Pattern Recognition, 52 papers in Radiology, Nuclear Medicine and Imaging and 35 papers in Biomedical Engineering. Recurrent topics in Pingkun Yan's work include Medical Image Segmentation Techniques (41 papers), Advanced Neural Network Applications (31 papers) and Radiomics and Machine Learning in Medical Imaging (25 papers). Pingkun Yan is often cited by papers focused on Medical Image Segmentation Techniques (41 papers), Advanced Neural Network Applications (31 papers) and Radiomics and Machine Learning in Medical Imaging (25 papers). Pingkun Yan collaborates with scholars based in United States, China and Canada. Pingkun Yan's co-authors include Xuelong Li, Yuan Yuan, Ge Wang, Barış Türkbey, Xiaoqiang Lu, Mannudeep K. Kalra, Hengyong Yu, Mubarak Shah, Xianbin Cao and Qingsong Yang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Pingkun Yan

168 papers receiving 6.2k 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.

Low-Dose CT Image Denoising Using a Generative Adversarial Network With Wasserstein Distance and Perceptual Loss

2018 1.1k citations Qingsong Yang, Pingkun Yan et al. IEEE Transactions on Medical Imaging profile →
Magnetic Resonance Imaging/Ultrasound Fusion Guided Prostate Biopsy Improves Cancer Detection Following Transrectal Ultrasound Biopsy and Correlates With Multiparametric Magnetic Resonance Imaging

2011 351 citations Peter A. Pinto, Jochen Kruecker et al. profile →
Development of metaverse for intelligent healthcare

2022 219 citations Ge Wang, Chuang Niu et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Pingkun Yan United States	40	3.1k	2.1k	1.4k	1000	974	180	6.4k
Mads Nielsen Denmark	32	4.2k 1.4×	1.5k 0.7×	822 0.6×	700 0.7×	2.2k 2.2×	186	8.2k
Bart M. ter Haar Romeny Netherlands	39	4.7k 1.5×	2.8k 1.4×	1.2k 0.8×	606 0.6×	880 0.9×	195	8.9k
Andreas Maier Germany	40	1.5k 0.5×	2.7k 1.3×	2.2k 1.6×	913 0.9×	1.5k 1.5×	613	8.1k
Dmitry B. Goldgof United States	46	3.3k 1.1×	4.1k 2.0×	1.4k 1.0×	1.6k 1.6×	2.4k 2.5×	275	9.5k
Nikos Paragios France	46	6.2k 2.0×	3.1k 1.5×	1.3k 0.9×	906 0.9×	1.4k 1.4×	198	10.5k
Marius Staring Netherlands	28	2.6k 0.8×	3.4k 1.7×	1.5k 1.1×	967 1.0×	566 0.6×	109	6.7k
Punam K. Saha United States	41	2.3k 0.7×	1.8k 0.9×	886 0.6×	522 0.5×	403 0.4×	207	5.8k
Le Lü United States	39	3.0k 1.0×	4.0k 2.0×	1.5k 1.0×	1.2k 1.2×	3.3k 3.4×	188	9.8k
Rangaraj M. Rangayyan Canada	52	3.7k 1.2×	2.8k 1.3×	1.9k 1.3×	1.1k 1.1×	3.7k 3.8×	329	9.0k
Qian Wang China	42	2.4k 0.8×	3.2k 1.5×	1.2k 0.8×	561 0.6×	1.4k 1.4×	308	7.0k

Countries citing papers authored by Pingkun Yan

Since Specialization

Citations

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

Fields of papers citing papers by Pingkun Yan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pingkun Yan

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Niu, Chuang, Qing Lyu, Christopher D. Carothers, et al.. (2025). Medical multimodal multitask foundation model for lung cancer screening. Nature Communications. 16(1). 1523–1523. 9 indexed citations

Xu, Xuanang, et al.. (2025). Chest X-Ray Foundation Model With Global and Local Representations Integration. IEEE Transactions on Medical Imaging. 44(12). 4787–4799.

Yan, Pingkun, et al.. (2024). Integrating AI in college education: Positive yet mixed experiences with ChatGPT. SHILAP Revista de lepidopterología. 2(4). 100113–100113. 4 indexed citations

Fang, Xi, Daeseung Kim, Xuanang Xu, et al.. (2024). Correspondence attention for facial appearance simulation. Medical Image Analysis. 93. 103094–103094. 6 indexed citations

Yan, Pingkun, Quanzheng Li, Haixing Dai, et al.. (2024). Artificial General Intelligence for Medical Imaging Analysis. UNC Libraries.

Li, Xiang, Lin Zhao, Lu Zhang, et al.. (2024). Artificial General Intelligence for Medical Imaging Analysis. IEEE Reviews in Biomedical Engineering. 18. 113–129. 15 indexed citations

Kim, Daeseung, Xuanang Xu, Xi Fang, et al.. (2024). Learning soft tissue deformation from incremental simulations. Medical Physics. 52(3). 1914–1925.

Chao, Hanqing, et al.. (2024). Unbiasing fairness evaluation of radiology AI model. SHILAP Revista de lepidopterología. 2(3). 100084–100084.

Xu, Xuanang, Han Deng, Tianshu Kuang, et al.. (2023). Machine Learning Effectively Diagnoses Mandibular Deformity Using Three-Dimensional Landmarks. Journal of Oral and Maxillofacial Surgery. 82(2). 181–190. 1 indexed citations

10.

Li, Ming, et al.. (2023). Computer vision-based bronchoscope tracking and navigation tool. 27. 68–68.

11.

Zhang, Jiajin, Hanqing Chao, Amit Dhurandhar, et al.. (2023). When Neural Networks Fail to Generalize? A Model Sensitivity Perspective. Proceedings of the AAAI Conference on Artificial Intelligence. 37(9). 11219–11227. 2 indexed citations

12.

Xu, Xuanang, Sheng Xu, Barış Türkbey, et al.. (2023). Distance map supervised landmark localization for MR-TRUS registration. 123–123. 1 indexed citations

13.

Chao, Hanqing, et al.. (2022). Ultrasound Volume Reconstruction From Freehand Scans Without Tracking. IEEE Transactions on Biomedical Engineering. 70(3). 970–979. 12 indexed citations

14.

Xu, Xuanang, Sheng Xu, Hanqing Chao, et al.. (2022). Ultrasound Frame-to-Volume Registration via Deep Learning for Interventional Guidance. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 70(9). 1016–1025. 6 indexed citations

15.

Chao, Hanqing, Xi Fang, Jiajin Zhang, et al.. (2021). Integrative analysis for COVID-19 patient outcome prediction. UNICA IRIS Institutional Research Information System (University of Cagliari). 46 indexed citations

16.

Fan, Fenglei, Dayang Wang, Qikui Zhu, et al.. (2021). On a Sparse Shortcut Topology of Artificial Neural Networks. IEEE Transactions on Artificial Intelligence. 3(4). 595–608. 10 indexed citations

17.

Peng, Zhao, Xi Fang, Pingkun Yan, et al.. (2019). A Method of Rapid Quantification of Patient-Specific Organ Dose for CT Using Coupled Deep Multi-Organ Segmentation Algorithms and GPU-accelerated Monte Carlo Dose Computing Code. arXiv (Cornell University). 1 indexed citations

18.

Yang, Qingsong, Pingkun Yan, Yanbo Zhang, et al.. (2018). Low-Dose CT Image Denoising Using a Generative Adversarial Network With Wasserstein Distance and Perceptual Loss. IEEE Transactions on Medical Imaging. 37(6). 1348–1357. 1071 indexed citations breakdown →

19.

Hong, Cheng William, Hayet Amalou, Pingkun Yan, et al.. (2014). Prostate Biopsy for the Interventional Radiologist. Journal of Vascular and Interventional Radiology. 25(5). 675–684. 10 indexed citations

20.

Yuan, Yuan, et al.. (2011). Segmenting Images by Combining Selected Atlases on Manifold. Lecture notes in computer science. 14(Pt 3). 272–279. 31 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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