Jonathan M. Chia

510 total citations
16 papers, 422 citations indexed

About

Jonathan M. Chia is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Physiology. According to data from OpenAlex, Jonathan M. Chia has authored 16 papers receiving a total of 422 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 7 papers in Cardiology and Cardiovascular Medicine and 6 papers in Physiology. Recurrent topics in Jonathan M. Chia's work include Cardiovascular Disease and Adiposity (6 papers), Advanced MRI Techniques and Applications (6 papers) and Advanced Neuroimaging Techniques and Applications (4 papers). Jonathan M. Chia is often cited by papers focused on Cardiovascular Disease and Adiposity (6 papers), Advanced MRI Techniques and Applications (6 papers) and Advanced Neuroimaging Techniques and Applications (4 papers). Jonathan M. Chia collaborates with scholars based in United States, Finland and Netherlands. Jonathan M. Chia's co-authors include Peng Hu, Thomas G. Perkins, Vicente Gilsanz, Larry Yin, Skorn Ponrartana, Zhiyue Wang, Leigh Ramos‐Platt, Nancy Rollins, Qi Peng and Paul T. Weatherall and has published in prestigious journals such as Magnetic Resonance in Medicine, American Journal of Roentgenology and Medical Physics.

In The Last Decade

Jonathan M. Chia

15 papers receiving 420 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jonathan M. Chia United States	10	211	160	159	62	60	16	422
Sofia Calado Portugal	12	86 0.4×	18 0.1×	26 0.2×	114 1.8×	26 0.4×	20	390
Oliver Chaudry Germany	13	179 0.8×	109 0.7×	47 0.3×	53 0.9×	17 0.3×	21	426
J. P. Finn United States	11	27 0.1×	405 2.5×	46 0.3×	66 1.1×	82 1.4×	16	626
Kimberly A. Ward United States	11	128 0.6×	20 0.1×	53 0.3×	12 0.2×	123 2.0×	13	422
Samantha E. Schoeneman United States	9	31 0.1×	69 0.4×	42 0.3×	93 1.5×	9 0.1×	12	335
Holly S. Norman United States	15	60 0.3×	16 0.1×	249 1.6×	38 0.6×	39 0.7×	24	666
Katsunori Tsuji Japan	11	99 0.5×	8 0.1×	90 0.6×	18 0.3×	30 0.5×	32	349
Christina Zompola Greece	14	78 0.4×	26 0.2×	142 0.9×	270 4.4×	8 0.1×	47	589
Georgia Keramida United Kingdom	11	34 0.2×	222 1.4×	29 0.2×	132 2.1×	7 0.1×	33	433
Paula F. Moon-Massat United States	13	87 0.4×	26 0.2×	12 0.1×	28 0.5×	242 4.0×	34	478

Countries citing papers authored by Jonathan M. Chia

Since Specialization

Citations

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

Fields of papers citing papers by Jonathan M. Chia

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan M. Chia. 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 Jonathan M. Chia. The network helps show where Jonathan M. Chia may publish in the future.

Co-authorship network of co-authors of Jonathan M. Chia

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan M. Chia. A scholar is included among the top collaborators of Jonathan M. Chia 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 Jonathan M. Chia. Jonathan M. Chia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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16 of 16 papers shown

1.

Keller, Sarah, et al.. (2018). Improvement of Reliability of Diffusion Tensor Metrics in Thigh Skeletal Muscles. European Journal of Radiology. 102. 55–60. 6 indexed citations

2.

Chia, Jonathan M., et al.. (2017). Improved fat-suppression homogeneity with mDIXON turbo spin echo (TSE) in pediatric spine imaging at 3.0 T. Acta Radiologica. 58(11). 1386–1394. 14 indexed citations

3.

Chia, Jonathan M., et al.. (2017). Ultra‐short echo time images quantify high liver iron. Magnetic Resonance in Medicine. 79(3). 1579–1585. 36 indexed citations

4.

Hu, Peng, et al.. (2016). Non-gadolinium dynamic angiography of the neurovasculature using arterial spin labeling MRI: preliminary experience in children. Magnetic Resonance Materials in Physics Biology and Medicine. 30(2). 107–112. 5 indexed citations

5.

Hu, Peng, et al.. (2016). Assessment of cerebral blood perfusion reserve with acetazolamide using 3D spiral ASL MRI: Preliminary experience in pediatric patients. Magnetic Resonance Imaging. 35. 132–140. 17 indexed citations

6.

Wang, Zhiyue, et al.. (2016). Correlation between diffusion kurtosis and NODDI metrics in neonates and young children. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9788. 97881F–97881F.

7.

Wang, Zhiyue, et al.. (2014). Signal‐to‐noise assessment for diffusion tensor imaging with single data set and validation using a difference image method with data from a multicenter study. Medical Physics. 41(9). 92302–92302. 4 indexed citations

8.

Ponrartana, Skorn, Leigh Ramos‐Platt, Peng Hu, et al.. (2014). Effectiveness of diffusion tensor imaging in assessing disease severity in Duchenne muscular dystrophy: preliminary study. Pediatric Radiology. 45(4). 582–589. 63 indexed citations

9.

Wren, Tishya A.L., et al.. (2013). Heterogeneity of muscle fat infiltration in children with spina bifida. Research in Developmental Disabilities. 35(1). 215–222. 5 indexed citations

10.

Hu, Peng, Tai-Wei Wu, Larry Yin, et al.. (2013). MRI detection of brown adipose tissue with low fat content in newborns with hypothermia. Magnetic Resonance Imaging. 32(2). 107–117. 34 indexed citations

11.

Hu, Peng, et al.. (2013). Comparison of brown and white adipose tissues in infants and children with chemical‐shift‐encoded water‐fat MRI. Journal of Magnetic Resonance Imaging. 38(4). 885–896. 76 indexed citations

12.

Hu, Peng, et al.. (2013). Comparison of brown and white adipose tissues in infants and children with chemical‐shift‐encoded water‐fat MRI. Journal of Magnetic Resonance Imaging. 38(4). 2 indexed citations

13.

Hu, Peng, Thomas G. Perkins, Jonathan M. Chia, & Vicente Gilsanz. (2012). Characterization of Human Brown Adipose Tissue by Chemical-Shift Water-Fat MRI. American Journal of Roentgenology. 200(1). 177–183. 94 indexed citations

14.

Wang, Zhiyue, et al.. (2011). A quality assurance protocol for diffusion tensor imaging using the head phantom from American College of Radiology. Medical Physics. 38(7). 4415–4421. 27 indexed citations

15.

Peng, Qi, Roderick McColl, Yao Ding, et al.. (2007). Automated method for accurate abdominal fat quantification on water‐saturated magnetic resonance images. Journal of Magnetic Resonance Imaging. 26(3). 738–746. 22 indexed citations

16.

Peng, Qi, Roderick McColl, Jihong Wang, Jonathan M. Chia, & Paul T. Weatherall. (2005). Water‐saturated three‐dimensional balanced steady‐state free precession for fast abdominal fat quantification. Journal of Magnetic Resonance Imaging. 21(3). 263–271. 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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