Kui Ying

1.2k total citations
36 papers, 890 citations indexed

About

Kui Ying is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Kui Ying has authored 36 papers receiving a total of 890 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Biomedical Engineering and 5 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Kui Ying's work include Advanced MRI Techniques and Applications (17 papers), Photoacoustic and Ultrasonic Imaging (8 papers) and Medical Imaging Techniques and Applications (7 papers). Kui Ying is often cited by papers focused on Advanced MRI Techniques and Applications (17 papers), Photoacoustic and Ultrasonic Imaging (8 papers) and Medical Imaging Techniques and Applications (7 papers). Kui Ying collaborates with scholars based in China, United States and United Kingdom. Kui Ying's co-authors include Jianwen Luo, Jing Bai, Ping He, Ping He, Jing Bai, Bradley D. Clymer, Wenchuan Wu, Petra Schmalbrock, Yaqiang Liu and Shi Wang and has published in prestigious journals such as Blood, Magnetic Resonance in Medicine and IEEE Transactions on Medical Imaging.

In The Last Decade

Kui Ying

36 papers receiving 854 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kui Ying China 12 266 254 98 76 69 36 890
Lianghao Han United Kingdom 17 304 1.1× 285 1.1× 164 1.7× 70 0.9× 121 1.8× 40 1.4k
Gerd Wübbeler Germany 17 322 1.2× 177 0.7× 40 0.4× 95 1.3× 25 0.4× 73 1.0k
H. Olkkonen Finland 21 206 0.8× 109 0.4× 178 1.8× 90 1.2× 17 0.2× 95 1.2k
Yongbum Lee Japan 16 230 0.9× 431 1.7× 366 3.7× 110 1.4× 46 0.7× 136 1.6k
Francesco Leporati Italy 16 198 0.7× 221 0.9× 185 1.9× 97 1.3× 13 0.2× 91 914
Katsuya Kondo Japan 15 153 0.6× 47 0.2× 167 1.7× 72 0.9× 39 0.6× 111 601
Ping Lü China 19 260 1.0× 209 0.8× 292 3.0× 201 2.6× 9 0.1× 128 1.4k
Yunxiang Li China 20 513 1.9× 298 1.2× 200 2.0× 123 1.6× 13 0.2× 85 1.6k
Bryan M. Williams United Kingdom 14 224 0.8× 577 2.3× 354 3.6× 56 0.7× 16 0.2× 63 1.1k

Countries citing papers authored by Kui Ying

Since Specialization
Citations

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

Fields of papers citing papers by Kui Ying

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kui Ying

This figure shows the co-authorship network connecting the top 25 collaborators of Kui Ying. A scholar is included among the top collaborators of Kui Ying 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 Kui Ying. Kui Ying 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.
Ying, Kui, et al.. (2024). Population Distribution in Guizhou’s Mountainous Cities: Evolution of Spatial Pattern and Driving Factors. Land. 13(9). 1469–1469. 2 indexed citations
2.
Li, Ziyu, Berkin Bilgic̦, Hong‐Hsi Lee, et al.. (2024). DIMOND: DIffusion Model OptimizatioN with Deep Learning. Advanced Science. 11(24). e2307965–e2307965. 5 indexed citations
3.
Ying, Kui, et al.. (2023). Intelligent Microwave Staring Correlated Imaging. Electromagnetic waves. 176. 109–128. 4 indexed citations
4.
Zhang, Xian, Junfang Yang, Jingjing Li, et al.. (2021). Factors associated with treatment response to CD19 CAR-T therapy among a large cohort of B cell acute lymphoblastic leukemia. Cancer Immunology Immunotherapy. 71(3). 689–703. 32 indexed citations
5.
Wang, Shi, Lingyun Zhao, Dan Wang, et al.. (2019). Multifunction bismuth gadolinium oxide nanoparticles as radiosensitizer in radiation therapy and imaging. Physics in Medicine and Biology. 64(19). 195007–195007. 39 indexed citations
6.
Xu, Junshen, Esra Abacı Türk, Larry Zhang, et al.. (2019). Fetal Pose Estimation in Volumetric MRI Using a 3D Convolution Neural Network. Lecture notes in computer science. 11767. 403–410. 22 indexed citations
7.
Guo, Rong, Yoann Petibon, Yixin Ma, et al.. (2018). MR-based motion correction for cardiac PET parametric imaging: a simulation study. EJNMMI Physics. 5(1). 3–3. 3 indexed citations
8.
Ma, Chao, Kexin Deng, Shuang Hu, et al.. (2017). A minimum-phase Shinnar-Le Roux spectral-spatial excitation RF pulse for simultaneous water and lipid suppression in 1H-MRSI of body extremities. Magnetic Resonance Imaging. 45. 18–25. 1 indexed citations
9.
Ying, Kui, Ji Wang, Linyan Su, et al.. (2014). Differences in functional activity between boys with pure oppositional defiant disorder and controls during a response inhibition task: a preliminary study. Brain Imaging and Behavior. 8(4). 588–597. 13 indexed citations
10.
Chen, Feiyu, Xinwei Shi, Shuo Chen, et al.. (2014). Accelerated model-based proton resonance frequency shift temperature mapping using echo-based GRAPPA reconstruction. Magnetic Resonance Imaging. 33(2). 240–245. 3 indexed citations
11.
Fang, Sheng, Wenchuan Wu, Kui Ying, & Hua Guo. (2013). A new fast magnetic resonance imaging method based on variabledensity spiral data acquisition and Bregman iterative reconstruction. Acta Physica Sinica. 62(4). 48702–48702. 8 indexed citations
12.
Li, Cheng, et al.. (2010). Model-based PRFS thermometry using fat as the internal reference and the extended Prony algorithm for model fitting. Magnetic Resonance Imaging. 28(3). 418–426. 5 indexed citations
13.
Ying, Kui, et al.. (2010). Coherence regularization for SENSE reconstruction with a nonlocal operator (CORNOL). Magnetic Resonance in Medicine. 64(5). 1413–1425. 12 indexed citations
14.
Li, Cheng, et al.. (2009). An internal reference model–based PRF temperature mapping method with Cramer‐Rao lower bound noise performance analysis. Magnetic Resonance in Medicine. 62(5). 1251–1260. 9 indexed citations
15.
Bai, Jing, et al.. (2008). A two-dimensional CVIB imaging system with a speckle tracking algorithm. Ultrasonics. 48(5). 394–402. 4 indexed citations
16.
Luo, Jianwen, Kui Ying, & Jing Bai. (2006). Elasticity reconstruction for ultrasound elastography using a radial compression: An inverse approach. Ultrasonics. 44. e195–e198. 10 indexed citations
17.
Bai, Jing, Tianxin Gao, Kui Ying, & Nanguang Chen. (2005). Locating inhomogeneities in tissue by using the most probable diffuse path of light. Journal of Biomedical Optics. 10(2). 24024–24024. 14 indexed citations
18.
Luo, Jianwen, Jing Bai, Ping He, & Kui Ying. (2004). Axial strain calculation using a low-pass digital differentiator in ultrasound elastography. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 51(9). 1119–1127. 97 indexed citations
19.
Ying, Kui, Bradley D. Clymer, & Petra Schmalbrock. (1996). Adaptive filtering for high resolution magnetic resonance images. Journal of Magnetic Resonance Imaging. 6(2). 367–377. 6 indexed citations
20.
Schmalbrock, Petra, et al.. (1993). Optimization of submillimeter‐resolution MR imaging methods for the inner ear. Journal of Magnetic Resonance Imaging. 3(3). 451–459. 27 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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