Weili Shi

507 total citations
64 papers, 297 citations indexed

About

Weili Shi is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Weili Shi has authored 64 papers receiving a total of 297 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Computer Vision and Pattern Recognition, 20 papers in Radiology, Nuclear Medicine and Imaging and 15 papers in Artificial Intelligence. Recurrent topics in Weili Shi's work include Medical Image Segmentation Techniques (11 papers), AI in cancer detection (11 papers) and Advanced Neural Network Applications (11 papers). Weili Shi is often cited by papers focused on Medical Image Segmentation Techniques (11 papers), AI in cancer detection (11 papers) and Advanced Neural Network Applications (11 papers). Weili Shi collaborates with scholars based in China, Japan and United States. Weili Shi's co-authors include Zhengang Jiang, Yu Miao, Huamin Yang, Yuqin Li, Bai Ji, Zhanfang Chen, Zhihua Li, Sheng Li, Jianhua Liu and Mengying Xiao and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

Weili Shi

53 papers receiving 288 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Weili Shi China 9 132 101 66 55 36 64 297
Mohammad Eslami Iran 9 82 0.6× 130 1.3× 88 1.3× 35 0.6× 17 0.5× 41 365
Jeremiah Neubert United States 7 136 1.0× 134 1.3× 88 1.3× 43 0.8× 35 1.0× 36 410
Xiaoyong Zhang Japan 11 70 0.5× 169 1.7× 128 1.9× 31 0.6× 10 0.3× 59 368
Dongsheng Jiang China 9 233 1.8× 139 1.4× 65 1.0× 76 1.4× 32 0.9× 22 391
Yeejin Lee South Korea 10 192 1.5× 80 0.8× 70 1.1× 39 0.7× 11 0.3× 26 321
Tianbao Zhou China 5 210 1.6× 112 1.1× 130 2.0× 44 0.8× 17 0.5× 9 449
Juan Morales‐Sánchez Spain 10 177 1.3× 188 1.9× 29 0.4× 55 1.0× 17 0.5× 49 381
Shuqian Luo China 12 201 1.5× 289 2.9× 61 0.9× 136 2.5× 12 0.3× 42 499

Countries citing papers authored by Weili Shi

Since Specialization
Citations

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

Fields of papers citing papers by Weili Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weili Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Weili Shi. A scholar is included among the top collaborators of Weili Shi 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 Weili Shi. Weili Shi 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.
Li, Yao, Cheng Wang, Miao Yu, et al.. (2025). Co‐training semi‐supervised medical image segmentation based on pseudo‐label weight balancing. Medical Physics. 52(6). 3854–3876. 1 indexed citations
2.
Yang, Huamin, et al.. (2024). Improved shape-from-template method with perspective space constraints for disappearing features. Complex & Intelligent Systems. 10(4). 5475–5488.
3.
Shi, Weili, et al.. (2024). MS-TCNet: An effective Transformer–CNN combined network using multi-scale feature learning for 3D medical image segmentation. Computers in Biology and Medicine. 170. 108057–108057. 22 indexed citations
4.
Shi, Weili, et al.. (2024). Intra-modality masked image modeling: A self-supervised pre-training method for brain tumor segmentation. Biomedical Signal Processing and Control. 95. 106343–106343. 4 indexed citations
5.
Shi, Weili, et al.. (2024). Automatic pterygopalatine fossa segmentation and localisation based on DenseASPP. International Journal of Medical Robotics and Computer Assisted Surgery. 20(2). e2633–e2633. 2 indexed citations
6.
Jiang, Zhengang, et al.. (2024). GMIM: Self-supervised pre-training for 3D medical image segmentation with adaptive and hierarchical masked image modeling. Computers in Biology and Medicine. 176. 108547–108547. 2 indexed citations
7.
Shi, Weili, et al.. (2024). Binocular camera-based visual localization with optimized keypoint selection and multi-epipolar constraints. Journal of King Saud University - Computer and Information Sciences. 36(10). 102228–102228.
8.
Li, Zhihua, et al.. (2023). COVID19-ResCapsNet: A Novel Residual Capsule Network for COVID-19 Detection from Chest X-Ray Scans Images. IEEE Access. 1–1. 3 indexed citations
9.
Zhang, Min, et al.. (2023). Transformer‐based 2D/3D medical image registration for X‐ray to CT via anatomical features. International Journal of Medical Robotics and Computer Assisted Surgery. 20(1). e2619–e2619. 1 indexed citations
10.
Li, Zhihua, Yanfang Li, Miao Yu, et al.. (2023). A Novel Multi-Scale Channel Attention-Guided Neural Network for Brain Stroke Lesion Segmentation. IEEE Access. 11. 66050–66062. 3 indexed citations
11.
Shi, Weili, et al.. (2023). An Automatic and Robust Visual SLAM Method for Intra-Abdominal Environment Reconstruction. Journal of Advanced Computational Intelligence and Intelligent Informatics. 27(6). 1216–1229. 2 indexed citations
12.
Shi, Weili, et al.. (2022). DAFLNet: Dual Asymmetric Feature Learning Network for COVID-19 Disease Diagnosis in X-Rays. Computational and Mathematical Methods in Medicine. 2022. 1–13. 1 indexed citations
13.
Zhou, Zhongliang, Nathaniel P. Hitt, Benjamin H. Letcher, Weili Shi, & Sheng Li. (2022). Pigmentation-based Visual Learning for Salvelinus fontinalis Individual Re-identification. 2022 IEEE International Conference on Big Data (Big Data). 6850–6852. 2 indexed citations
14.
Li, Zhihua, et al.. (2021). Low-Dose CT Image Denoising with Improving WGAN and Hybrid Loss Function. Computational and Mathematical Methods in Medicine. 2021. 1–14. 35 indexed citations
15.
Shi, Weili, et al.. (2021). A Segmentation Method of Foramen Ovale Based on Multiatlas. Computational and Mathematical Methods in Medicine. 2021. 1–10.
16.
Li, Yuqin, et al.. (2021). A Novel Medical Image Denoising Method Based on Conditional Generative Adversarial Network. Computational and Mathematical Methods in Medicine. 2021. 1–11. 21 indexed citations
17.
Miao, Yu, Weili Shi, Zhengang Jiang, et al.. (2020). Logarithmic Fuzzy Entropy Function for Similarity Measurement in Multimodal Medical Images Registration. Computational and Mathematical Methods in Medicine. 2020. 1–16. 1 indexed citations
18.
Yang, Huamin, et al.. (2017). A Study of Multilevel Banded Graph Cuts for Three-Dimensional Colon Tissue Segmentation. International Journal of Pattern Recognition and Artificial Intelligence. 31(9). 1755012–1755012. 1 indexed citations
19.
Shi, Weili, et al.. (2012). Research on the Key Technology of Image Guided Surgery. PRZEGLĄD ELEKTROTECHNICZNY. 29–33. 2 indexed citations
20.
Shi, Weili, et al.. (2012). Research on the Intercommunication of Healthy Records and Hospital Medical Records. PRZEGLĄD ELEKTROTECHNICZNY. 26–28.

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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