Zhenyuan Ning

1.2k total citations
26 papers, 661 citations indexed

About

Zhenyuan Ning is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Zhenyuan Ning has authored 26 papers receiving a total of 661 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 14 papers in Radiology, Nuclear Medicine and Imaging and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Zhenyuan Ning's work include AI in cancer detection (15 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Medical Image Segmentation Techniques (5 papers). Zhenyuan Ning is often cited by papers focused on AI in cancer detection (15 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Medical Image Segmentation Techniques (5 papers). Zhenyuan Ning collaborates with scholars based in China, United States and Japan. Zhenyuan Ning's co-authors include Yu Zhang, Qianjin Feng, Wufan Chen, Qing Xiao, Tao Chen, Yikai Xu, Shuai Han, Shuixing Zhang, Yuting Chen and Yu Zhang and has published in prestigious journals such as Bioinformatics, IEEE Transactions on Pattern Analysis and Machine Intelligence and NeuroImage.

In The Last Decade

Zhenyuan Ning

23 papers receiving 654 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhenyuan Ning China 12 374 289 127 125 112 26 661
Jiawei Sun China 17 410 1.1× 194 0.7× 146 1.1× 163 1.3× 128 1.1× 54 747
Keewon Shin South Korea 9 199 0.5× 122 0.4× 131 1.0× 56 0.4× 45 0.4× 21 455
Si‐Wa Chan Taiwan 15 530 1.4× 369 1.3× 78 0.6× 80 0.6× 296 2.6× 44 879
Michael Wels Germany 15 250 0.7× 66 0.2× 226 1.8× 125 1.0× 92 0.8× 32 513
Lara Harrison Finland 11 294 0.8× 75 0.3× 68 0.5× 34 0.3× 42 0.4× 14 560
Yunyan Zhang Canada 15 258 0.7× 74 0.3× 52 0.4× 47 0.4× 66 0.6× 57 745
Clifford Yang United States 11 377 1.0× 356 1.2× 64 0.5× 87 0.7× 85 0.8× 22 673

Countries citing papers authored by Zhenyuan Ning

Since Specialization
Citations

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

Fields of papers citing papers by Zhenyuan Ning

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhenyuan Ning

This figure shows the co-authorship network connecting the top 25 collaborators of Zhenyuan Ning. A scholar is included among the top collaborators of Zhenyuan Ning 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 Zhenyuan Ning. Zhenyuan Ning 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.
2.
Ning, Zhenyuan, et al.. (2025). DC-Net: Decomposing and coupling saliency map for lesion segmentation in ultrasound images. Engineering Applications of Artificial Intelligence. 148. 110355–110355. 1 indexed citations
3.
Ning, Zhenyuan, et al.. (2025). Interpretable deep fuzzy network-aided detection of central lymph node metastasis status in papillary thyroid carcinoma. International Journal of Computer Assisted Radiology and Surgery. 20(10). 2119–2129.
4.
Feng, Qianjin, et al.. (2024). Cross-view discrepancy-dependency network for volumetric medical image segmentation. Medical Image Analysis. 99. 103329–103329. 4 indexed citations
5.
Xiao, Qing, Guiying Liu, Qianjin Feng, Yu Zhang, & Zhenyuan Ning. (2024). Tensor Coupled Learning of Incomplete Longitudinal Features and Labels for Clinical Score Regression. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(1). 369–386. 2 indexed citations
6.
Feng, Qianjin, et al.. (2024). Semantics and instance interactive learning for labeling and segmentation of vertebrae in CT images. Medical Image Analysis. 99. 103380–103380. 2 indexed citations
7.
Zhong, Tao, Shujun Liang, Zhenyuan Ning, et al.. (2024). nBEST: Deep-learning-based non-human primates Brain Extraction and Segmentation Toolbox across ages, sites and species. NeuroImage. 295. 120652–120652.
8.
Feng, Qianjin, et al.. (2023). Mix-supervised multiset learning for cancer prognosis analysis with high-censoring survival data. Expert Systems with Applications. 239. 122430–122430. 2 indexed citations
9.
Liu, Shangqing, Zhenyuan Ning, Yu Zhang, et al.. (2023). Multi-modal analysis for accurate prediction of preoperative stage and indications of optimal treatment in gastric cancer. La radiologia medica. 128(5). 509–519. 7 indexed citations
10.
Ning, Zhenyuan, et al.. (2022). Mutual-Assistance Learning for Standalone Mono-Modality Survival Analysis of Human Cancers. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(6). 7577–7594. 6 indexed citations
11.
12.
Ning, Zhenyuan, et al.. (2021). Deep cross-view co-regularized representation learning for glioma subtype identification. Medical Image Analysis. 73. 102160–102160. 10 indexed citations
13.
Ning, Zhenyuan, Qing Xiao, Longmei Cai, et al.. (2021). Multi-modal magnetic resonance imaging-based grading analysis for gliomas by integrating radiomics and deep features. Annals of Translational Medicine. 9(4). 298–298. 30 indexed citations
14.
Ning, Zhenyuan, et al.. (2021). Relation-Aware Shared Representation Learning for Cancer Prognosis Analysis With Auxiliary Clinical Variables and Incomplete Multi-Modality Data. IEEE Transactions on Medical Imaging. 41(1). 186–198. 18 indexed citations
15.
Ning, Zhenyuan, et al.. (2021). SMU-Net: Saliency-Guided Morphology-Aware U-Net for Breast Lesion Segmentation in Ultrasound Image. IEEE Transactions on Medical Imaging. 41(2). 476–490. 107 indexed citations
16.
Zhang, Bin, Zhenyuan Ning, Ke Wang, et al.. (2020). Deep learning of lumbar spine X-ray for osteopenia and osteoporosis screening: A multicenter retrospective cohort study. Bone. 140. 115561–115561. 108 indexed citations
17.
Zhong, Tao, Fenqiang Zhao, Zhenyuan Ning, et al.. (2020). DIKA-Nets: Domain-invariant knowledge-guided attention networks for brain skull stripping of early developing macaques. NeuroImage. 227. 117649–117649. 14 indexed citations
18.
Ning, Zhenyuan, et al.. (2020). Integrative analysis of cross-modal features for the prognosis prediction of clear cell renal cell carcinoma. Bioinformatics. 36(9). 2888–2895. 40 indexed citations
19.
Chen, Tao, Zhenyuan Ning, Lili Xu, et al.. (2018). Radiomics nomogram for predicting the malignant potential of gastrointestinal stromal tumours preoperatively. European Radiology. 29(3). 1074–1082. 57 indexed citations
20.
Ning, Zhenyuan, et al.. (2018). Bag of deep features for preoperative prediction of sentinel lymph node metastasis in breast cancer. Physics in Medicine and Biology. 63(24). 245014–245014. 30 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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