Zhengyi Yang

822 total citations
33 papers, 581 citations indexed

About

Zhengyi Yang is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Zhengyi Yang has authored 33 papers receiving a total of 581 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Biomedical Engineering and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Zhengyi Yang's work include Medical Imaging and Analysis (10 papers), Advanced MRI Techniques and Applications (9 papers) and Advanced Neuroimaging Techniques and Applications (7 papers). Zhengyi Yang is often cited by papers focused on Medical Imaging and Analysis (10 papers), Advanced MRI Techniques and Applications (9 papers) and Advanced Neuroimaging Techniques and Applications (7 papers). Zhengyi Yang collaborates with scholars based in Australia, China and Hong Kong. Zhengyi Yang's co-authors include David C. Reutens, Nyoman D. Kurniawan, Farshid Sepehrband, Graham J. Galloway, Jeremy F.P. Ullmann, Kristi A. Clark, Kay Richards, Steven Petrou, James F. Griffith and Ping‐Chung Leung and has published in prestigious journals such as NeuroImage, Endocrine Reviews and Neurology.

In The Last Decade

Zhengyi Yang

31 papers receiving 574 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhengyi Yang Australia 12 325 133 62 59 55 33 581
Nathaniel D. Kelm United States 12 463 1.4× 84 0.6× 92 1.5× 29 0.5× 63 1.1× 17 656
Masami Goto Japan 16 477 1.5× 272 2.0× 19 0.3× 64 1.1× 45 0.8× 61 881
Maurizio Bergamino United States 17 450 1.4× 157 1.2× 37 0.6× 31 0.5× 51 0.9× 52 791
Andrew A. Chen United States 15 197 0.6× 143 1.1× 31 0.5× 74 1.3× 51 0.9× 33 684
Tanguy Duval Canada 15 674 2.1× 133 1.0× 145 2.3× 52 0.9× 135 2.5× 23 884
Maria Marcella Laganà Italy 19 435 1.3× 205 1.5× 24 0.4× 56 0.9× 195 3.5× 69 949
Mohamed Tachrount United Kingdom 13 316 1.0× 131 1.0× 46 0.7× 26 0.4× 108 2.0× 24 691
Christoph Leuze United States 13 659 2.0× 309 2.3× 40 0.6× 69 1.2× 55 1.0× 45 1.0k
Vasudeva G. Iyer United States 15 200 0.6× 77 0.6× 18 0.3× 29 0.5× 89 1.6× 70 691
Yasuhiro Nakata Japan 22 439 1.4× 245 1.8× 21 0.3× 23 0.4× 48 0.9× 83 1.3k

Countries citing papers authored by Zhengyi Yang

Since Specialization
Citations

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

Fields of papers citing papers by Zhengyi Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhengyi Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Zhengyi Yang. A scholar is included among the top collaborators of Zhengyi Yang 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 Zhengyi Yang. Zhengyi Yang 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.
Ai, Bo, Peipei Wang, Zhengyi Yang, Yuxin Tian, & Dandan Liu. (2022). Spatiotemporal dynamics analysis of aquaculture zones and its impact on green tide disaster in Haizhou Bay, China. Marine Environmental Research. 183. 105825–105825. 16 indexed citations
2.
Yang, Zhengyi. (2018). Rural Logistics Demand Forecast Based on Gray Neural Network Model. 1 indexed citations
3.
Neubert, Aleš, Zhengyi Yang, Craig Engstrom, et al.. (2016). Automatic segmentation of the glenohumeral cartilages from magnetic resonance images. Medical Physics. 43(10). 5370–5379. 7 indexed citations
4.
Yang, Zhengyi, Jeiran Choupan, David C. Reutens, & Julia Hocking. (2015). Lateralization of temporal lobe epilepsy based on resting-state functional magnetic resonance imaging and machine learning. QUT ePrints (Queensland University of Technology). 1 indexed citations
5.
Sepehrband, Farshid, Kristi A. Clark, Jeremy F.P. Ullmann, et al.. (2015). Brain tissue compartment density estimated using diffusion‐weighted MRI yields tissue parameters consistent with histology. Human Brain Mapping. 36(9). 3687–3702. 111 indexed citations
6.
Yang, Zhengyi, Jürgen Fripp, Shekhar S. Chandra, et al.. (2015). Automatic bone segmentation and bone-cartilage interface extraction for the shoulder joint from magnetic resonance images. Physics in Medicine and Biology. 60(4). 1441–1459. 17 indexed citations
7.
Reutens, David C., et al.. (2014). Modified human contrast sensitivity function based phase mask for susceptibility-weighted imaging. NeuroImage Clinical. 4. 765–778. 2 indexed citations
8.
Kurniawan, Nyoman D., Kay Richards, Zhengyi Yang, et al.. (2013). Visualization of mouse barrel cortex using ex-vivo track density imaging. NeuroImage. 87. 465–475. 20 indexed citations
9.
Yang, Shan, Zhengyi Yang, Kai Zhong, et al.. (2013). Integration of ultra-high field MRI and histology for connectome based research of brain disorders. Frontiers in Neuroanatomy. 7. 31–31. 23 indexed citations
10.
Cowin, Gary, et al.. (2012). Effect of a 12-month lifestyle behavioral modification intervention on fat compartmentation in overweight and obese prepubertal children. Endocrine Reviews. 33(3). 1 indexed citations
11.
Ullmann, Jeremy F.P., Marianne Keller, Charles Watson, et al.. (2012). Segmentation of the C57BL/6J mouse cerebellum in magnetic resonance images. NeuroImage. 62(3). 1408–1414. 27 indexed citations
12.
Yang, Zhengyi, Kay Richards, Nyoman D. Kurniawan, Steven Petrou, & David C. Reutens. (2012). MRI-guided volume reconstruction of mouse brain from histological sections. Journal of Neuroscience Methods. 211(2). 210–217. 29 indexed citations
13.
Yang, Zhengyi, Viktor Vegh, & David C. Reutens. (2012). A fast multi-resolution differential evolution method for multimodal image registration. 11. 804–809. 3 indexed citations
14.
15.
Calamante, Fernando, Jacques‐Donald Tournier, Nyoman D. Kurniawan, et al.. (2011). Super-resolution track-density imaging studies of mouse brain: Comparison to histology. NeuroImage. 59(1). 286–296. 88 indexed citations
16.
Richards, Kay, Charles Watson, Rachel F. Buckley, et al.. (2011). Segmentation of the mouse hippocampal formation in magnetic resonance images. NeuroImage. 58(3). 732–740. 73 indexed citations
17.
Yang, Zhengyi, James F. Griffith, Ping‐Chung Leung, & Raymond Lee. (2009). Effect of Osteoporosis on Morphology and Mobility of the Lumbar Spine. Spine. 34(3). E115–E121. 37 indexed citations
18.
Yang, Zhengyi, et al.. (2008). A new method for determining lumbar spine motion using Bayesian belief network. Medical & Biological Engineering & Computing. 46(4). 333–340. 10 indexed citations
19.
Wang, Biao & Zhengyi Yang. (2008). A detailed study on the use of polynomial functions for modeling geometric distortion in magnetic resonance imaging. Medical Physics. 35(3). 908–916. 5 indexed citations
20.
Yang, Zhengyi, et al.. (2005). The Accuracy of Surface Measurement for Motion Analysis of Osteoporotic Thoracolumbar Spine. PubMed. 2005. 6871–6874. 8 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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