Bin Dong

6.2k total citations · 1 hit paper
121 papers, 2.9k citations indexed

About

Bin Dong is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Bin Dong has authored 121 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Computer Vision and Pattern Recognition, 35 papers in Computational Mechanics and 35 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Bin Dong's work include Image and Signal Denoising Methods (25 papers), Medical Imaging Techniques and Applications (19 papers) and Medical Image Segmentation Techniques (18 papers). Bin Dong is often cited by papers focused on Image and Signal Denoising Methods (25 papers), Medical Imaging Techniques and Applications (19 papers) and Medical Image Segmentation Techniques (18 papers). Bin Dong collaborates with scholars based in China, United States and Singapore. Bin Dong's co-authors include Zuowei Shen, Yiping Lu, Stanley Osher, Jian‐Feng Cai, Steve Jiang, Xun Jia, Yu Mao, Wotao Yin, Gang Wu and Haochen Wang and has published in prestigious journals such as Nature Communications, PLoS ONE and Journal of Computational Physics.

In The Last Decade

Bin Dong

112 papers receiving 2.7k citations

Hit Papers

PDE-Net 2.0: Learning PDEs from data with a numeric-symbo... 2019 2026 2021 2023 2019 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bin Dong China 28 958 775 705 540 356 121 2.9k
Peter Maaß Germany 32 551 0.6× 584 0.8× 332 0.5× 578 1.1× 163 0.5× 123 3.1k
Yunmei Chen United States 29 1.2k 1.2× 775 1.0× 601 0.9× 266 0.5× 77 0.2× 144 4.1k
Jean‐Christophe Pesquet France 34 1.8k 1.8× 1.8k 2.4× 394 0.6× 582 1.1× 93 0.3× 207 4.2k
Rick Chartrand United States 20 1.3k 1.4× 2.5k 3.3× 693 1.0× 1.2k 2.2× 102 0.3× 44 4.0k
Changfeng Gui United States 24 2.1k 2.2× 270 0.3× 538 0.8× 324 0.6× 169 0.5× 85 5.1k
Misha E. Kilmer United States 26 1.7k 1.8× 1.9k 2.5× 1.3k 1.9× 1.2k 2.2× 137 0.4× 65 5.0k
Jérôme Idier France 29 656 0.7× 680 0.9× 389 0.6× 434 0.8× 56 0.2× 144 3.2k
Xue‐Cheng Tai Norway 38 3.5k 3.7× 2.4k 3.1× 480 0.7× 557 1.0× 161 0.5× 202 6.3k
Charles K. Chui United States 30 4.3k 4.5× 825 1.1× 420 0.6× 215 0.4× 502 1.4× 111 6.5k
Mike E. Davies United Kingdom 35 2.3k 2.4× 3.9k 5.1× 489 0.7× 1.8k 3.4× 215 0.6× 181 7.2k

Countries citing papers authored by Bin Dong

Since Specialization
Citations

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

Fields of papers citing papers by Bin Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bin Dong

This figure shows the co-authorship network connecting the top 25 collaborators of Bin Dong. A scholar is included among the top collaborators of Bin Dong 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 Bin Dong. Bin Dong 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.
Zhang, Haimiao, et al.. (2024). A comparative study of deep learning and iterative algorithms for joint channel estimation and signal detection in OFDM systems. Signal Processing. 223. 109554–109554. 3 indexed citations
3.
Li, Yonghong, et al.. (2024). Investigation of Asymmetric Flow of a Slender Body with Low-Aspect Ratio Fins Having Large Deflection Angles. Aerospace. 11(10). 835–835. 2 indexed citations
4.
Chen, Zifan, Yang Chen, Yu Sun, et al.. (2024). Predicting gastric cancer response to anti-HER2 therapy or anti-HER2 combined immunotherapy based on multi-modal data. Signal Transduction and Targeted Therapy. 9(1). 222–222. 37 indexed citations
5.
Chen, Zifan, Jie Zhao, Jiazheng Li, et al.. (2024). MSI-UNet: A Flexible UNet-Based Multi-Scale Interactive Framework for 3D Gastric Tumor Segmentation on CT Scans. 1–5. 1 indexed citations
6.
Lou, Cunguang, Yaxin Wang, Lei Huang, et al.. (2023). Quartz tuning fork (QTF) coating enhanced Mid-Infrared laser Induced-Thermoacoustic spectroscopy (LITES) for human exhaled methane detection. Infrared Physics & Technology. 133. 104824–104824. 19 indexed citations
7.
Meng, He, Zifan Chen, Xiangyu Gao, et al.. (2023). Associations of subcutaneous fat area and Systemic Immune-inflammation Index with survival in patients with advanced gastric cancer receiving dual PD-1 and HER2 blockade. Journal for ImmunoTherapy of Cancer. 11(6). e007054–e007054. 27 indexed citations
8.
Wang, Yan, Bing Liu, Qingjie Min, et al.. (2023). Spatial transcriptomics delineates molecular features and cellular plasticity in lung adenocarcinoma progression. Cell Discovery. 9(1). 96–96. 34 indexed citations
9.
Huang, Xiang, et al.. (2023). Meta-Auto-Decoder: a Meta-Learning-Based Reduced Order Model for Solving Parametric Partial Differential Equations. Communications on Applied Mathematics and Computation. 6(2). 1096–1130. 1 indexed citations
10.
Sun, Fenggang, et al.. (2023). Deep Learning-Based Pine Nematode Trees’ Identification Using Multispectral and Visible UAV Imagery. Drones. 7(3). 183–183. 25 indexed citations
11.
Dong, Bin, et al.. (2022). Introduction to Data Science. 1 indexed citations
12.
Dong, Bin, et al.. (2021). Agglomeration of particles by a converging ultrasound field and their quantitative assessments. Ultrasonics Sonochemistry. 75. 105590–105590. 17 indexed citations
13.
Shen, Chenyang, Dan Nguyen, Zhiguo Zhou, et al.. (2020). An introduction to deep learning in medical physics: advantages, potential, and challenges. Physics in Medicine and Biology. 65(5). 05TR01–05TR01. 106 indexed citations
14.
Chen, Geng, Bin Dong, Yong Zhang, et al.. (2018). Angular Upsampling in Infant Diffusion MRI Using Neighborhood Matching in x-q Space. Frontiers in Neuroinformatics. 12. 57–57. 7 indexed citations
15.
Cai, Jian‐Feng, Bin Dong, & Zuowei Shen. (2015). Image restoration: A wavelet frame based model for piecewise smooth functions and beyond. Applied and Computational Harmonic Analysis. 41(1). 94–138. 51 indexed citations
16.
Dong, Bin, et al.. (2012). Optimal surface marker locations for tumor motion estimation in lung cancer radiotherapy. Physics in Medicine and Biology. 57(24). 8201–8215. 16 indexed citations
17.
Jia, Xun, Yifei Lou, Bin Dong, Zhen Tian, & Steve Jiang. (2010). 4D Computed Tomography Reconstruction from Few-Projection Data via Temporal Non-local Regularization. Lecture notes in computer science. 13(Pt 1). 143–150. 38 indexed citations
18.
Dong, Bin, Nira Dyn, & Kai Hormann. (2009). Properties of dual pseudo-splines. Applied and Computational Harmonic Analysis. 29(1). 104–110. 11 indexed citations
19.
Dong, Bin & Zuowei Shen. (2006). Pseudo-splines, wavelets and framelets. Applied and Computational Harmonic Analysis. 22(1). 78–104. 76 indexed citations
20.
Dong, Bin & Zuowei Shen. (2006). Construction of biorthogonal wavelets from pseudo-splines. Journal of Approximation Theory. 138(2). 211–231. 17 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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