Kevin J. Parker

12.7k total citations
347 papers, 9.2k citations indexed

About

Kevin J. Parker is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Mechanics of Materials. According to data from OpenAlex, Kevin J. Parker has authored 347 papers receiving a total of 9.2k indexed citations (citations by other indexed papers that have themselves been cited), including 213 papers in Radiology, Nuclear Medicine and Imaging, 186 papers in Biomedical Engineering and 95 papers in Mechanics of Materials. Recurrent topics in Kevin J. Parker's work include Ultrasound Imaging and Elastography (180 papers), Photoacoustic and Ultrasonic Imaging (90 papers) and Ultrasonics and Acoustic Wave Propagation (87 papers). Kevin J. Parker is often cited by papers focused on Ultrasound Imaging and Elastography (180 papers), Photoacoustic and Ultrasonic Imaging (90 papers) and Ultrasonics and Acoustic Wave Propagation (87 papers). Kevin J. Parker collaborates with scholars based in United States, Peru and Sudan. Kevin J. Parker's co-authors include Deborah J. Rubens, R.M. Lerner, Stephen F. Levinson, Kenneth Hoyt, Robert M. Lerner, Benjamín Castañeda, Marvin M. Doyley, Juvenal Ormachea, Lan Gao and J. Ophir and has published in prestigious journals such as Nature Medicine, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Kevin J. Parker

331 papers receiving 8.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kevin J. Parker United States 51 6.1k 5.8k 2.4k 870 665 347 9.2k
Michael F. Insana United States 41 5.5k 0.9× 4.6k 0.8× 2.5k 1.1× 523 0.6× 597 0.9× 251 7.3k
Timothy J. Hall United States 45 6.1k 1.0× 5.6k 1.0× 2.3k 0.9× 343 0.4× 543 0.8× 273 8.8k
Brian S. Garra United States 36 5.2k 0.9× 4.2k 0.7× 1.6k 0.7× 447 0.5× 346 0.5× 162 8.2k
Armando Manduca United States 56 9.5k 1.6× 7.5k 1.3× 2.0k 0.8× 956 1.1× 664 1.0× 278 14.1k
William D. O’Brien United States 43 3.6k 0.6× 4.6k 0.8× 1.8k 0.8× 314 0.4× 426 0.6× 358 8.6k
Tomy Varghese United States 46 5.6k 0.9× 4.9k 0.8× 2.2k 0.9× 321 0.4× 556 0.8× 254 7.3k
J. Ophir United States 56 11.2k 1.8× 9.8k 1.7× 4.6k 1.9× 640 0.7× 1.3k 1.9× 188 13.6k
Gregg E. Trahey United States 57 9.8k 1.6× 8.3k 1.4× 4.6k 1.9× 574 0.7× 1.1k 1.6× 349 11.7k
J. Brian Fowlkes United States 61 5.2k 0.8× 9.6k 1.7× 1.4k 0.6× 286 0.3× 591 0.9× 354 12.7k
Jeffrey C. Bamber United Kingdom 48 4.4k 0.7× 4.1k 0.7× 1.1k 0.5× 475 0.5× 354 0.5× 229 7.8k

Countries citing papers authored by Kevin J. Parker

Since Specialization
Citations

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

Fields of papers citing papers by Kevin J. Parker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin J. Parker. 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 Kevin J. Parker. The network helps show where Kevin J. Parker may publish in the future.

Co-authorship network of co-authors of Kevin J. Parker

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin J. Parker. A scholar is included among the top collaborators of Kevin J. Parker 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 Kevin J. Parker. Kevin J. Parker 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.
Hysi, Eno, Jihye Baek, Xiaolin He, et al.. (2025). A first-in-human study of quantitative ultrasound to assess transplant kidney fibrosis. Nature Medicine. 31(3). 970–978. 5 indexed citations
2.
Marini, Thomas J., et al.. (2024). Developing an enhanced UNet-based architecture for breast tumor segmentation in ultrasound images. 28–28. 2 indexed citations
3.
Baek, Jihye, Ahmed El Kaffas, Aya Kamaya, Kenneth Hoyt, & Kevin J. Parker. (2024). Multiparametric quantification and visualization of liver fat using ultrasound. SHILAP Revista de lepidopterología. 2(1). 100045–100045. 2 indexed citations
4.
Rolland, Jannick P., et al.. (2024). Integrated Difference Autocorrelation: A Novel Approach to Estimate Shear Wave Speed in the Presence of Compression Waves. IEEE Transactions on Biomedical Engineering. 72(2). 586–594. 1 indexed citations
5.
Ormachea, Juvenal, et al.. (2023). Reverberant magnetic resonance elastographic imaging using a single mechanical driver. Physics in Medicine and Biology. 68(5). 55015–55015. 8 indexed citations
6.
7.
Ormachea, Juvenal & Kevin J. Parker. (2022). A Preliminary Study of Liver Fat Quantification Using Reported Ultrasound Speed of Sound and Attenuation Parameters. Ultrasound in Medicine & Biology. 48(4). 675–684. 13 indexed citations
8.
Zvietcovich, Fernando, et al.. (2022). Performance of Shear Wave Speed Measurements by Using Reverberant Optical Coherence Elastography. Chiang Mai Journal of Science. 49(1). 81–92. 2 indexed citations
9.
Ormachea, Juvenal, et al.. (2022). Comprehensive experimental assessments of rheological models’ performance in elastography of soft tissues. Acta Biomaterialia. 146. 259–273. 26 indexed citations
10.
Baek, Jihye, et al.. (2021). Clusters of Ultrasound Scattering Parameters for the Classification of Steatotic and Normal Livers. Ultrasound in Medicine & Biology. 47(10). 3014–3027. 31 indexed citations
11.
O’Connell, Avice M., Tommaso Vincenzo Bartolotta, Alessia Angela Maria Orlando, et al.. (2021). Diagnostic Performance of an Artificial Intelligence System in Breast Ultrasound. Journal of Ultrasound in Medicine. 41(1). 97–105. 34 indexed citations
12.
Baek, Jihye, et al.. (2020). Scattering Signatures of Normal versus Abnormal Livers with Support Vector Machine Classification. Ultrasound in Medicine & Biology. 46(12). 3379–3392. 28 indexed citations
13.
Ormachea, Juvenal, Kevin J. Parker, & R. Graham Barr. (2019). An initial study of complete 2D shear wave dispersion images using a reverberant shear wave field. Physics in Medicine and Biology. 64(14). 145009–145009. 32 indexed citations
14.
Rolland, Jannick P., Humberto Mestre, Michael Giannetto, et al.. (2019). A preliminary study on using reverberant shear wave fields in optical coherence elastography to examine mice brain ex vivo. 48–48. 4 indexed citations
15.
Parker, Kevin J.. (2019). Shapes and distributions of soft tissue scatterers. Physics in Medicine and Biology. 64(17). 175022–175022. 17 indexed citations
16.
Parker, Kevin J., Thomas L. Szabo, & Sverre Holm. (2019). Towards a consensus on rheological models for elastography in soft tissues. Physics in Medicine and Biology. 64(21). 215012–215012. 59 indexed citations
17.
Zvietcovich, Fernando, Natalie Baddour, Jannick P. Rolland, & Kevin J. Parker. (2018). Shear wave propagation in viscoelastic media: validation of an approximate forward model. Physics in Medicine and Biology. 64(2). 25008–25008. 14 indexed citations
18.
Partin, Alexander, Zaegyoo Hah, Christopher T. Barry, Deborah J. Rubens, & Kevin J. Parker. (2013). Elasticity Estimates from Images of Crawling Waves Generated by Miniature Surface Sources. Ultrasound in Medicine & Biology. 40(4). 685–694. 27 indexed citations
19.
Hah, Zaegyoo, et al.. (2011). Integration of Crawling Waves in an Ultrasound Imaging System. Part 1: System and Design Considerations. Ultrasound in Medicine & Biology. 38(2). 296–311. 21 indexed citations
20.
Yu, Qing, et al.. (1998). A New Metric for Color Halftone Visibility.. PICS. 226–230. 3 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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