Zekuan Yu

1.4k total citations
63 papers, 918 citations indexed

About

Zekuan Yu is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Zekuan Yu has authored 63 papers receiving a total of 918 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Radiology, Nuclear Medicine and Imaging, 27 papers in Computer Vision and Pattern Recognition and 12 papers in Artificial Intelligence. Recurrent topics in Zekuan Yu's work include Radiomics and Machine Learning in Medical Imaging (12 papers), Retinal Imaging and Analysis (11 papers) and Advanced Neural Network Applications (10 papers). Zekuan Yu is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (12 papers), Retinal Imaging and Analysis (11 papers) and Advanced Neural Network Applications (10 papers). Zekuan Yu collaborates with scholars based in China, United States and Germany. Zekuan Yu's co-authors include Caixia Kou, Shujin Zhu, Yanye Lu, Yinan Guo, Qiushi Ren, Zhi‐Ri Tang, Jie Liu, Daoying Geng, Qing Xiang and Wei Li and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Zekuan Yu

53 papers receiving 899 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zekuan Yu China	19	460	282	248	137	116	63	918
Il Dong Yun South Korea	19	255 0.6×	542 1.9×	197 0.8×	81 0.6×	114 1.0×	77	1.0k
Qiangguo Jin China	10	703 1.5×	663 2.4×	355 1.4×	262 1.9×	113 1.0×	32	1.3k
Yuqian Zhao China	20	296 0.6×	664 2.4×	264 1.1×	56 0.4×	162 1.4×	99	1.2k
He Ma China	20	756 1.6×	270 1.0×	460 1.9×	103 0.8×	142 1.2×	72	1.2k
Pan Su China	13	287 0.6×	171 0.6×	178 0.7×	145 1.1×	69 0.6×	29	620
N. Sri Madhava Raja India	16	543 1.2×	488 1.7×	464 1.9×	33 0.2×	139 1.2×	46	1.3k
Romuere Silva Brazil	19	399 0.9×	591 2.1×	526 2.1×	54 0.4×	65 0.6×	67	1.1k
Yongzhao Du China	21	215 0.5×	495 1.8×	368 1.5×	24 0.2×	180 1.6×	67	1.1k
Deepak Ranjan Nayak India	26	760 1.7×	723 2.6×	908 3.7×	76 0.6×	122 1.1×	74	2.0k

Countries citing papers authored by Zekuan Yu

Since Specialization

Citations

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

Fields of papers citing papers by Zekuan Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zekuan Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Zekuan Yu. A scholar is included among the top collaborators of Zekuan Yu 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 Zekuan Yu. Zekuan Yu 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, Hongbo, et al.. (2025). L-SSHNN: A Larger search space of Semi-Supervised Hybrid NAS Network for echocardiography segmentation. Expert Systems with Applications. 276. 127084–127084.

Yu, Zekuan, Wei Fu, Lei Zhang, et al.. (2025). Beta-amyloid deposition increases in the brain with the progression of silicosis: a [18F] AV45 PET study in mice. Environmental Research. 279(Pt 2). 121898–121898.

Fang, Xianjin, et al.. (2024). CDSG-SAM: A cross-domain self-generating prompt few-shot brain tumor segmentation pipeline based on SAM. Biomedical Signal Processing and Control. 100. 106936–106936. 4 indexed citations

Wang, Yiqun, Xin Li, Na Li, et al.. (2024). Automated Enhanced Handheld Fundus Photography via Unpaired Learning. IEEE Transactions on Instrumentation and Measurement. 74. 1–12.

Fang, Xianjin, et al.. (2024). SDR2Tr‐GAN: A Novel Medical Image Fusion Pipeline Based on GAN With SDR2 Module and Transformer Optimization Strategy. International Journal of Imaging Systems and Technology. 34(6).

Liu, Jie, et al.. (2024). USCT: Uncertainty-regularized symmetric consistency learning for semi-supervised teeth segmentation in CBCT. Biomedical Signal Processing and Control. 91. 106032–106032. 4 indexed citations

Li, Xiang, et al.. (2023). TransU²-Net: An Effective Medical Image Segmentation Framework Based on Transformer and U²-Net. IEEE Journal of Translational Engineering in Health and Medicine. 11. 441–450. 20 indexed citations

Yu, Zekuan, Meijia Li, Jiacheng Yang, et al.. (2023). A Benchmark Dual-Modality Dental Imaging Dataset and a Novel Cognitively Inspired Pipeline for High-Resolution Dental Point Cloud Synthesis. Cognitive Computation. 15(6). 1922–1933. 5 indexed citations

Tang, Zhi‐Ri, Hau−San Wong, & Zekuan Yu. (2023). Privacy-Preserving Federated Learning With Domain Adaptation for Multi-Disease Ocular Disease Recognition. IEEE Journal of Biomedical and Health Informatics. 28(6). 3219–3227. 13 indexed citations

10.

Guo, Yinan, et al.. (2023). A dynamic constrained multiobjective evolutionary algorithm based on decision variable classification. Swarm and Evolutionary Computation. 83. 101420–101420. 10 indexed citations

11.

Yu, Zekuan, et al.. (2023). SegCoFusion: An Integrative Multimodal Volumetric Segmentation Cooperating With Fusion Pipeline to Enhance Lesion Awareness. IEEE Journal of Biomedical and Health Informatics. 27(12). 5860–5871. 4 indexed citations

12.

Liu, Mengting, Xiaojie Li, Jie Liu, Weifan Liu, & Zekuan Yu. (2023). TUCNet: A channel and spatial attention-based graph convolutional network for teeth upsampling and completion. Computers in Biology and Medicine. 166. 107519–107519. 5 indexed citations

13.

Wong, Hau−San, et al.. (2023). Ocular Disease Recognition via Differential Privacy and Unsupervised Domain Regularizer. IEEE Signal Processing Letters. 31. 136–140. 1 indexed citations

14.

Liu, Xiao, Chong Yao, Rui Xiang, et al.. (2023). BTMF-GAN: A multi-modal MRI fusion generative adversarial network for brain tumors. Computers in Biology and Medicine. 157. 106769–106769. 13 indexed citations

15.

Zhu, Shujin, et al.. (2022). CycleADC-Net: A crack segmentation method based on multi-scale feature fusion. Measurement. 204. 112107–112107. 37 indexed citations

16.

Guo, Yinan, et al.. (2021). Evolutionary Dual-Ensemble Class Imbalance Learning for Human Activity Recognition. IEEE Transactions on Emerging Topics in Computational Intelligence. 6(4). 728–739. 42 indexed citations

17.

Wang, Junjie, et al.. (2021). Coarse-to-fine multiplanar D-SEA UNet for automatic 3D carotid segmentation in CTA images. International Journal of Computer Assisted Radiology and Surgery. 16(10). 1727–1736. 7 indexed citations

18.

Yu, Zekuan, Tao Tang, Xiao Liu, et al.. (2021). Machine learning algorithm improves accuracy of ortho-K lens fitting in vision shaping treatment. Contact Lens and Anterior Eye. 45(3). 101474–101474. 22 indexed citations

19.

Pan, Lei, et al.. (2020). Normalized wall index, intraplaque hemorrhage and ulceration of carotid plaques correlate with the severity of ischemic stroke. Atherosclerosis. 315. 138–144. 18 indexed citations

20.

Kou, Caixia, et al.. (2020). An Enhanced Residual U-Net for Microaneurysms and Exudates Segmentation in Fundus Images. IEEE Access. 8. 185514–185525. 38 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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