Zhennan Yan

1.3k total citations
37 papers, 616 citations indexed

About

Zhennan Yan is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Zhennan Yan has authored 37 papers receiving a total of 616 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 18 papers in Radiology, Nuclear Medicine and Imaging and 8 papers in Biomedical Engineering. Recurrent topics in Zhennan Yan's work include Medical Image Segmentation Techniques (14 papers), Advanced Neural Network Applications (8 papers) and Radiomics and Machine Learning in Medical Imaging (7 papers). Zhennan Yan is often cited by papers focused on Medical Image Segmentation Techniques (14 papers), Advanced Neural Network Applications (8 papers) and Radiomics and Machine Learning in Medical Imaging (7 papers). Zhennan Yan collaborates with scholars based in United States, China and Netherlands. Zhennan Yan's co-authors include Shaoting Zhang, Dimitris Metaxas, Dimitris Metaxas, Yiqiang Zhan, Zhigang Peng, Xiang Sean Zhou, Yoshihisa Shinagawa, Shu Liao, Kang Li and Liang Zhao and has published in prestigious journals such as Nature Communications, IEEE Transactions on Medical Imaging and Frontiers in Psychology.

In The Last Decade

Zhennan Yan

35 papers receiving 604 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhennan Yan United States 13 281 228 205 131 49 37 616
Avi Ben-Cohen Israel 8 262 0.9× 209 0.9× 100 0.5× 118 0.9× 23 0.5× 10 594
Phillip Chlap Australia 10 359 1.3× 198 0.9× 182 0.9× 117 0.9× 22 0.4× 30 792
Tahir Mahmood South Korea 13 342 1.2× 232 1.0× 192 0.9× 77 0.6× 14 0.3× 30 620
Norliza Mohd Noor Malaysia 13 245 0.9× 142 0.6× 171 0.8× 71 0.5× 18 0.4× 115 646
Pierre-Henri Conze France 14 304 1.1× 199 0.9× 277 1.4× 87 0.7× 17 0.3× 47 616
Mahboubeh Jannesari Germany 3 245 0.9× 234 1.0× 108 0.5× 79 0.6× 13 0.3× 7 510
Xuanang Xu United States 13 312 1.1× 240 1.1× 237 1.2× 150 1.1× 31 0.6× 33 657
Kim Eun Hee Germany 5 201 0.7× 180 0.8× 82 0.4× 77 0.6× 15 0.3× 25 496

Countries citing papers authored by Zhennan Yan

Since Specialization
Citations

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

Fields of papers citing papers by Zhennan Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhennan Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Zhennan Yan. A scholar is included among the top collaborators of Zhennan 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 Zhennan Yan. Zhennan Yan 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.
Yan, Zhennan, et al.. (2025). Consumer willingness to pay for green express packaging in e-commerce: an eye-tracking experiment analysis. Frontiers in Psychology. 16. 1615315–1615315.
2.
Zhu, Huiyuan, Guangyu Tao, Yifeng Jiang, et al.. (2024). Automatic detection of pulmonary embolism on computed tomography pulmonary angiogram scan using a three-dimensional convolutional neural network. European Journal of Radiology. 177. 111586–111586. 4 indexed citations
3.
Xia, Qing, Zhennan Yan, Zhiqiang Hu, et al.. (2023). AVDNet: Joint coronary artery and vein segmentation with topological consistency. Medical Image Analysis. 91. 102999–102999. 10 indexed citations
4.
Yan, Zhennan, Mu Zhou, Hui Qu, et al.. (2023). Mining multi-center heterogeneous medical data with distributed synthetic learning. Nature Communications. 14(1). 5510–5510. 16 indexed citations
5.
Wang, Yiwei, Wenjun Xia, Zhennan Yan, et al.. (2023). Root canal treatment planning by automatic tooth and root canal segmentation in dental CBCT with deep multi-task feature learning. Medical Image Analysis. 85. 102750–102750. 37 indexed citations
6.
Qu, Hui, et al.. (2022). Modality Bank: Learn multi-modality images across data centers without sharing medical data. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2022. 4758–4763. 2 indexed citations
7.
Qu, Yang, Xiaomin Li, Zhennan Yan, et al.. (2021). Surgical planning of pelvic tumor using multi-view CNN with relation-context representation learning. Medical Image Analysis. 69. 101954–101954. 27 indexed citations
8.
Xia, Qing, Zhiqiang Hu, Zhennan Yan, et al.. (2021). Few-Shot Learning by a Cascaded Framework With Shape-Constrained Pseudo Label Assessment for Whole Heart Segmentation. IEEE Transactions on Medical Imaging. 40(10). 2629–2641. 37 indexed citations
9.
Qu, Hui, Mu Zhou, Zhennan Yan, et al.. (2021). Genetic mutation and biological pathway prediction based on whole slide images in breast carcinoma using deep learning. npj Precision Oncology. 5(1). 87–87. 69 indexed citations
10.
Li, Zhongyu, et al.. (2019). Fully Automatic Segmentation Of Short-Axis Cardiac MRI Using Modified Deep Layer Aggregation. 793–797. 5 indexed citations
11.
Shan, Juan, et al.. (2016). A novel and robust automatic seed point selection method for breast ultrasound images. 11. 1–5. 5 indexed citations
12.
Yan, Zhennan, Yiqiang Zhan, Zhigang Peng, et al.. (2015). Bodypart Recognition Using Multi-stage Deep Learning. Lecture notes in computer science. 24. 449–461. 29 indexed citations
13.
Yan, Zhennan, Shaoting Zhang, Boubakeur Belaroussi, et al.. (2014). Atlas-based liver segmentation and hepatic fat-fraction assessment for clinical trials. Computerized Medical Imaging and Graphics. 41. 80–92. 20 indexed citations
14.
Yan, Zhennan, et al.. (2014). Accurate Whole-Brain Segmentation for Alzheimer’s Disease Combining an Adaptive Statistical Atlas and Multi-atlas. Lecture notes in computer science. 8331. 65–73. 3 indexed citations
15.
Zhou, Jinghao, Baoshe Zhang, K Prado, et al.. (2014). Efficient deformable model with sparse shape composition prior on compromised right lung segmentation in CT. 764–768. 1 indexed citations
16.
Xiang, Yu, Shaoting Zhang, Zhennan Yan, et al.. (2014). Is Interactional Dissynchrony a Clue to Deception? Insights From Automated Analysis of Nonverbal Visual Cues. IEEE Transactions on Cybernetics. 45(3). 492–506. 24 indexed citations
17.
Yan, Zhennan, Shaoting Zhang, Xiaofeng Liu, Dimitris Metaxas, & Albert Montillo. (2013). Accurate segmentation of brain images into 34 structures combining a non-stationary adaptive statistical atlas and a multi-atlas with applications to Alzheimer'S disease. PubMed. 30. 1202–1205. 11 indexed citations
18.
Yan, Zhennan, et al.. (2007). Soft Tissue Deformation Simulation in Virtual Surgery using Nonlinear Finite Element Method. Conference proceedings. 2007. 3642–3645. 11 indexed citations
19.
Gu, Lixu, et al.. (2007). Virtual Surgery Deformable Modelling Employing GPU Based Computation. 221–227. 7 indexed citations
20.
Yan, Zhennan, et al.. (2003). Anatomical-map system for CT interpretation. 246–250.

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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