Kejuan Yue

739 total citations · 1 hit paper
17 papers, 400 citations indexed

About

Kejuan Yue is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Kejuan Yue has authored 17 papers receiving a total of 400 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Ophthalmology and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Kejuan Yue's work include Retinal Imaging and Analysis (12 papers), Glaucoma and retinal disorders (7 papers) and Digital Imaging for Blood Diseases (5 papers). Kejuan Yue is often cited by papers focused on Retinal Imaging and Analysis (12 papers), Glaucoma and retinal disorders (7 papers) and Digital Imaging for Blood Diseases (5 papers). Kejuan Yue collaborates with scholars based in China, Finland and United States. Kejuan Yue's co-authors include Zailiang Chen, Qing Liu, Beiji Zou, Guoying Zhao, Chaoyu Chen, Dong Ni, Xindi Hu, Yuhao Huang, Xin Yang and Xinrui Zhou and has published in prestigious journals such as Scientific Reports, Journal of Investigative Dermatology and Medical Image Analysis.

In The Last Decade

Kejuan Yue

17 papers receiving 385 citations

Hit Papers

align trajectories sort by overperformance

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.

Segment anything model for medical images?

2023 215 citations Yuhao Huang, Xin Yang et al. Medical Image Analysis profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kejuan Yue China	7	241	203	120	87	38	17	400
Soochahn Lee South Korea	10	293 1.2×	255 1.3×	153 1.3×	69 0.8×	24 0.6×	30	477
Khin Yadanar Win Thailand	11	223 0.9×	174 0.9×	107 0.9×	120 1.4×	61 1.6×	16	354
Maria Inês Meyer Belgium	5	220 0.9×	177 0.9×	72 0.6×	88 1.0×	25 0.7×	5	368
Yanda Meng United Kingdom	11	227 0.9×	230 1.1×	71 0.6×	252 2.9×	22 0.6×	28	504
Yangqin Feng Singapore	12	258 1.1×	165 0.8×	68 0.6×	232 2.7×	47 1.2×	20	444
Andres Diaz‐Pinto United Kingdom	8	503 2.1×	306 1.5×	330 2.8×	81 0.9×	21 0.6×	14	637
Zaiwang Gu China	7	329 1.4×	199 1.0×	202 1.7×	91 1.0×	17 0.4×	13	415
Pierre-Henri Conze France	14	304 1.3×	277 1.4×	64 0.5×	199 2.3×	68 1.8×	47	616
Swamidoss Issac Niwas India	14	279 1.2×	212 1.0×	202 1.7×	140 1.6×	33 0.9×	19	499
Sebastian Otálora Switzerland	14	345 1.4×	200 1.0×	123 1.0×	293 3.4×	21 0.6×	18	514

Countries citing papers authored by Kejuan Yue

Since Specialization

Citations

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

Fields of papers citing papers by Kejuan Yue

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kejuan Yue

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

All Works

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17 of 17 papers shown

Yue, Kejuan, et al.. (2025). Unsupervised domain adaptation teacher–student network for retinal vessel segmentation via full-resolution refined model. Scientific Reports. 15(1). 2038–2038. 2 indexed citations

Zou, Beiji, et al.. (2024). PFFNet: A pyramid feature fusion network for microaneurysm segmentation in fundus images. IET Image Processing. 18(14). 4653–4665. 1 indexed citations

Zou, Beiji, et al.. (2024). A novel approach for intelligent diagnosis and grading of diabetic retinopathy. Computers in Biology and Medicine. 172. 108246–108246. 27 indexed citations

Wang, Zheng, Xinyu Tan, Yang Xue, et al.. (2024). Smart diabetic foot ulcer scoring system. Scientific Reports. 14(1). 11588–11588. 1 indexed citations

Zou, Beiji, et al.. (2024). A novel approach for automatic classification of macular degeneration OCT images. Scientific Reports. 14(1). 19285–19285. 4 indexed citations

Wang, Zheng, et al.. (2024). Computer-Aided Assessment of Repigmentation Rates in Vitiligo Patients: Implications for Treatment Efficacy - A Retrospective Study. Journal of Investigative Dermatology. 145(1). 56–64.e5. 1 indexed citations

Chen, Chaoyu, Xin Yang, Yuhao Huang, et al.. (2023). FetusMapV2: Enhanced fetal pose estimation in 3D ultrasound. Medical Image Analysis. 91. 103013–103013. 3 indexed citations

Huang, Yuhao, Xin Yang, Lian Liu, et al.. (2023). Segment anything model for medical images?. Medical Image Analysis. 92. 103061–103061. 215 indexed citations breakdown →

Zou, Beiji, et al.. (2020). Deep Learning and Its Application in Diabetic Retinopathy Screening. Chinese Journal of Electronics. 29(6). 992–1000. 4 indexed citations

10.

Zou, Beiji, Qing Liu, Kejuan Yue, et al.. (2019). Saliency‐Based Segmentation of Optic Disc in Retinal Images. Chinese Journal of Electronics. 28(1). 71–75. 15 indexed citations

11.

Yue, Kejuan, Beiji Zou, Zailiang Chen, & Qing Liu. (2019). Retinal vessel segmentation using dense U-net with multiscale inputs. Journal of Medical Imaging. 6(3). 1–1. 22 indexed citations

12.

Yue, Kejuan, Beiji Zou, Zailiang Chen, & Qing Liu. (2018). Improved multi‐scale line detection method for retinal blood vessel segmentation. IET Image Processing. 12(8). 1450–1457. 22 indexed citations

13.

Chen, Zailiang, Hao Wei, Hailan Shen, et al.. (2018). Intraretinal layer segmentation and parameter measurement in optic nerve head region through energy function of spatial-gradient continuity constraint. Journal of Central South University. 25(8). 1938–1947. 3 indexed citations

14.

Yue, Kejuan, et al.. (2017). Prediction of Drug‐Drug Interactions Based on Multi‐layer Feature Selection and Data Balance. Chinese Journal of Electronics. 26(3). 585–590. 3 indexed citations

15.

Liu, Qing, Beiji Zou, Jie Chen, et al.. (2016). A location-to-segmentation strategy for automatic exudate segmentation in colour retinal fundus images. Computerized Medical Imaging and Graphics. 55. 78–86. 69 indexed citations

16.

Liu, Qing, Beiji Zou, Jie Chen, et al.. (2016). Retinal Vessel Segmentation from Simple to Difficult. University of Oulu Repository (University of Oulu). 57–64. 6 indexed citations

17.

Xiao, Li, et al.. (2015). A Novel LASSO-based feature weighting selection method for microarray data classification. 5 .–5 .. 2 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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