Zexuan Ji

3.3k total citations · 1 hit paper
100 papers, 2.1k citations indexed

About

Zexuan Ji is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Media Technology. According to data from OpenAlex, Zexuan Ji has authored 100 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Computer Vision and Pattern Recognition, 25 papers in Radiology, Nuclear Medicine and Imaging and 18 papers in Media Technology. Recurrent topics in Zexuan Ji's work include Medical Image Segmentation Techniques (39 papers), Image Retrieval and Classification Techniques (28 papers) and Retinal Imaging and Analysis (23 papers). Zexuan Ji is often cited by papers focused on Medical Image Segmentation Techniques (39 papers), Image Retrieval and Classification Techniques (28 papers) and Retinal Imaging and Analysis (23 papers). Zexuan Ji collaborates with scholars based in China, United States and Australia. Zexuan Ji's co-authors include Quansen Sun, Qiang Chen, Xia De-shen, Sijie Niu, Yong Xia, Songtao Yuan, Daniel L. Rubin, Qiang Chen, Dagan Feng and Qiang Chen and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Zexuan Ji

94 papers receiving 2.0k 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.

OCTA-500: A retinal dataset for optical coherence tomography angiography study

2024 56 citations Mingchao Li, Zexuan Ji et al. profile →

Peers

Zexuan Ji

CVPR

RNMI

MT

AI

OPHTH

Gouenou Coatrieux France

Abd Rahman Ramli Malaysia

Étienne Decencière France

Shadrokh Samavi Iran

Rushi Lan China

Aurélio Campilho Portugal

Ekta Walia India

Dazhe Zhao China

Rui Huang China

Sanjay Agrawal India

Gouenou Coatrieux France

Zexuan Ji

2.5k ×2.0

CVPR

629 ×1.0

RNMI

337 ×0.8

MT

493 ×1.3

AI

63 ×0.2

OPHTH

Citations per year, relative to Zexuan Ji Zexuan Ji (= 1×) peers Gouenou Coatrieux

Countries citing papers authored by Zexuan Ji

Since Specialization

Citations

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

Fields of papers citing papers by Zexuan Ji

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zexuan Ji

This figure shows the co-authorship network connecting the top 25 collaborators of Zexuan Ji. A scholar is included among the top collaborators of Zexuan Ji 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 Zexuan Ji. Zexuan Ji 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

1.

Ji, Zexuan, Yuxuan Ye, & Xiao Ma. (2025). BDFormer: Boundary-aware dual-decoder transformer for skin lesion segmentation. Artificial Intelligence in Medicine. 162. 103079–103079. 8 indexed citations

2.

Ji, Zexuan, et al.. (2025). Grouped multi-scale vision transformer for medical image segmentation. Scientific Reports. 15(1). 11122–11122.

3.

Ji, Zexuan, et al.. (2024). Shared Hybrid Attention Transformer network for colon polyp segmentation. Neurocomputing. 616. 128901–128901. 5 indexed citations

4.

Ji, Zexuan, et al.. (2024). Progressive Group Convolution Fusion network for colon polyp segmentation. Biomedical Signal Processing and Control. 96. 106586–106586. 4 indexed citations

5.

Li, Guannan, Zexuan Ji, & Quansen Sun. (2024). Deep Multi-Instance Conv-Transformer Frameworks for Landmark-Based Brain MRI Classification. Electronics. 13(5). 980–980. 6 indexed citations

6.

Ji, Zexuan, et al.. (2024). Sparse Coding Inspired LSTM and Self-Attention Integration for Medical Image Segmentation. IEEE Transactions on Image Processing. 33. 6098–6113. 2 indexed citations

7.

Ji, Zexuan, Xiao Ma, Theodore Leng, Daniel L. Rubin, & Qiang Chen. (2024). Mirrored X-Net: Joint classification and contrastive learning for weakly supervised GA segmentation in SD-OCT. Pattern Recognition. 153. 110507–110507. 3 indexed citations

8.

Zhang, Zetian, et al.. (2024). SAVE: Encoding spatial interactions for vision transformers. Image and Vision Computing. 152. 105312–105312. 2 indexed citations

9.

Ji, Zexuan, et al.. (2023). Immune Checkpoint Inhibitor-Related Chronic Pneumonitis: A Case Report and Literature Review. Immunotherapy. 15(14). 1117–1123. 2 indexed citations

10.

Wang, Xiaoling, Zexuan Ji, Xiao Ma, et al.. (2021). Automated Grading of Diabetic Retinopathy with Ultra-Widefield Fluorescein Angiography and Deep Learning. Journal of Diabetes Research. 2021. 1–9. 14 indexed citations

11.

Ji, Zexuan, et al.. (2021). Joint Optimization of CycleGAN and CNN Classifier for Detection and Localization of Retinal Pathologies on Color Fundus Photographs. IEEE Journal of Biomedical and Health Informatics. 26(1). 115–126. 22 indexed citations

12.

Ji, Zexuan, et al.. (2020). Complex-Valued Spatial-Scattering Separated Attention Network for Polsar Image Classification. 1723–1726. 11 indexed citations

13.

Wang, Tao, et al.. (2020). Interactive Image Segmentation Based on Label Pair Diffusion. IEEE Transactions on Industrial Informatics. 17(1). 135–146. 5 indexed citations

14.

Niu, Sijie, Zexuan Ji, Menglin Wu, et al.. (2019). Double-branched and area-constraint fully convolutional networks for automated serous retinal detachment segmentation in SD-OCT images. Computer Methods and Programs in Biomedicine. 176. 69–80. 41 indexed citations

15.

Wang, Tao, et al.. (2018). Perceptual Gradient Similarity Deviation for Full Reference Image Quality Assessment. Cmc-computers Materials & Continua. 56(3). 501–515. 8 indexed citations

16.

Ji, Zexuan, Yong Xia, & Yuhui Zheng. (2017). Robust generative asymmetric GMM for brain MR image segmentation. Computer Methods and Programs in Biomedicine. 151. 123–138. 11 indexed citations

17.

Fu, Peng, Quansen Sun, & Zexuan Ji. (2015). Noise Estimation from Remote Sensing Images by Fractal Theory and Adaptive Image Block Division. SHILAP Revista de lepidopterología. 2 indexed citations

18.

Luo, Nan, Quansen Sun, Qiang Chen, Zexuan Ji, & Xia De-shen. (2015). A Novel Tracking Algorithm via Feature Points Matching. PLoS ONE. 10(1). e0116315–e0116315. 3 indexed citations

19.

Sun, Quansen, et al.. (2013). An Improved Image Denoising Algorithm based on Shearlet. International Journal of Signal Processing Image Processing and Pattern Recognition. 6(4). 475–484. 2 indexed citations

20.

Ji, Zexuan, Quansen Sun, & Xia De-shen. (2011). A modified possibilistic fuzzy c-means clustering algorithm for bias field estimation and segmentation of brain MR image. Computerized Medical Imaging and Graphics. 35(5). 383–397. 124 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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