Guangming Ni

1.0k total citations · 1 hit paper
55 papers, 658 citations indexed

About

Guangming Ni is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Biophysics. According to data from OpenAlex, Guangming Ni has authored 55 papers receiving a total of 658 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Biomedical Engineering, 17 papers in Radiology, Nuclear Medicine and Imaging and 17 papers in Biophysics. Recurrent topics in Guangming Ni's work include Optical Coherence Tomography Applications (23 papers), Photoacoustic and Ultrasonic Imaging (11 papers) and Image Processing Techniques and Applications (11 papers). Guangming Ni is often cited by papers focused on Optical Coherence Tomography Applications (23 papers), Photoacoustic and Ultrasonic Imaging (11 papers) and Image Processing Techniques and Applications (11 papers). Guangming Ni collaborates with scholars based in China, Singapore and United States. Guangming Ni's co-authors include Chao Zhou, Aaron H. Wasserman, Kristen Ball, Jinyun Zou, Yonatan R. Lewis‐Israeli, Mitchell A. Gabalski, Aitor Aguirre, Wen Li, Juanxiu Liu and Brett Volmert and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Scientific Reports.

In The Last Decade

Guangming Ni

52 papers receiving 643 citations

Hit Papers

Self-assembling human heart organoids for the modeling of... 2021 2026 2022 2024 2021 50 100 150 200 250
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.

  1. Self-assembling human heart organoids for the modeling of cardiac development and congenital heart disease
    2021 295 citations Yonatan R. Lewis‐Israeli, Aaron H. Wasserman et al. Nature Communications profile →

Peers

Guangming Ni
Guanglei Xiong United States
Lingfeng Yu China
Zhen Qiu United States
Cameron M. Lee United States
Wen‐Chuan Kuo Taiwan
Anant Agrawal United States
Qili Zhao China
Oscar Carrasco‐Zevallos United States
Nicolas Jaccard United Kingdom
Hyeon‐Cheol Park United States
Guanglei Xiong United States
Guangming Ni
Citations per year, relative to Guangming Ni Guangming Ni (= 1×) peers Guanglei Xiong

Countries citing papers authored by Guangming Ni

Since Specialization
Citations

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

Fields of papers citing papers by Guangming Ni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guangming Ni

This figure shows the co-authorship network connecting the top 25 collaborators of Guangming Ni. A scholar is included among the top collaborators of Guangming Ni 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 Guangming Ni. Guangming Ni 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.
Ni, Guangming, Kai Cao, Xiangfeng Zeng, et al.. (2025). Advanced 3D retinal lesion segmentation using channel-spatial attention-guided multi-scale feature aggregation. Biomedical Optics Express. 16(5). 2093–2093. 1 indexed citations
2.
Zeng, Xiaojuan, et al.. (2025). High-responsiveness and -precision 3D NIR visual-assisted eye-pupil tracking robot for free-style ophthalmic OCT imaging. Optics Express. 33(4). 7321–7321. 2 indexed citations
3.
Huang, Hao, Xiaojuan Zeng, Ke Cao, et al.. (2025). 3D Distance-Color-Coded Assessment of PCI Stent Apposition via Deep-Learning-Based Three-Dimensional Multi-Object Segmentation. IEEE Transactions on Medical Imaging. 44(11). 4717–4731. 1 indexed citations
4.
Gan, Y.S., Lang Qin, Sung‐Nan Pei, et al.. (2025). 3D Neighbor2Neighbor-based unsupervised deep learning for noise reduction in OCT imaging: insights from multiple clinical datasets. Optics Express. 33(21). 43476–43476.
5.
He, Jin, et al.. (2024). Non-invasive quantitative blood cell counting using optical coherence tomography. Optics & Laser Technology. 179. 111313–111313. 1 indexed citations
6.
Ge, Xin, Si Chen, Guangming Ni, et al.. (2024). Deblurring, artifact-free optical coherence tomography with deconvolution-random phase modulation. SHILAP Revista de lepidopterología. 3(1). 230020–230020. 10 indexed citations
7.
Zheng, Fei, Meixuan Li, Jie Zhong, et al.. (2024). Unsupervised OCT image despeckling with ground-truth- and repeated-scanning-free features. Optics Express. 32(7). 11934–11934.
8.
Li, Meixuan, Fei Zheng, Rong Wang, et al.. (2024). High-accuracy 3D segmentation of wet age-related macular degeneration via multi-scale and cross-channel feature extraction and channel attention. Biomedical Optics Express. 15(2). 1115–1115. 5 indexed citations
9.
10.
Cao, Kai, Yi Liu, Xiangfeng Zeng, et al.. (2024). Semi-supervised 3D retinal fluid segmentation via correlation mutual learning with global reasoning attention. Biomedical Optics Express. 15(12). 6905–6905. 1 indexed citations
11.
Ge, Xin, Jin He, Si Chen, et al.. (2023). FMMAS-OCT: Aberration correction for high-resolution cellular imaging. Optics and Lasers in Engineering. 174. 107964–107964. 1 indexed citations
12.
Wang, Rong, et al.. (2023). SNR-Net OCT: brighten and denoise low-light optical coherence tomography images via deep learning. Optics Express. 31(13). 20696–20696. 5 indexed citations
13.
Li, Meixuan, et al.. (2023). MAS-Net OCT: a deep-learning-based speckle-free multiple aperture synthetic optical coherence tomography. Biomedical Optics Express. 14(6). 2591–2591. 4 indexed citations
14.
Ni, Guangming, et al.. (2022). Three‐dimensional morphological revealing of human placental villi with common obstetric complications via optical coherence tomography. Bioengineering & Translational Medicine. 8(1). e10372–e10372. 10 indexed citations
15.
Ni, Guangming, Xiaohui Du, Jing Zhang, et al.. (2021). Single A-Line Method for Fast Sample-Structure-Nondependent Dispersion Compensation of FD-OCT. IEEE Photonics Technology Letters. 33(24). 1455–1458. 4 indexed citations
16.
Liu, Juanxiu, Chen Gui, Lin Liu, et al.. (2021). Automatic Semicircular Canal Segmentation of CT Volumes Using Improved 3D U‐Net with Attention Mechanism. Computational Intelligence and Neuroscience. 2021(1). 9654059–9654059. 14 indexed citations
17.
Du, Xiaohui, Xiangzhou Wang, Guangming Ni, et al.. (2021). SDoF-Net: Super Depth of Field Network for Cell Detection in Leucorrhea Micrograph. IEEE Journal of Biomedical and Health Informatics. 26(3). 1229–1238. 5 indexed citations
18.
Lewis‐Israeli, Yonatan R., Aaron H. Wasserman, Mitchell A. Gabalski, et al.. (2021). Self-assembling human heart organoids for the modeling of cardiac development and congenital heart disease. Nature Communications. 12(1). 5142–5142. 295 indexed citations breakdown →
19.
Peng, Di, et al.. (2020). An SBS-Based Optoelectronic Oscillator for High-Speed and High-Sensitivity Temperature Sensing. IEEE Photonics Technology Letters. 32(16). 995–998. 4 indexed citations
20.

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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