Jinsuh Kim

2.0k total citations · 1 hit paper
21 papers, 1.6k citations indexed

About

Jinsuh Kim is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology and Genetics. According to data from OpenAlex, Jinsuh Kim has authored 21 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Neurology and 3 papers in Genetics. Recurrent topics in Jinsuh Kim's work include Advanced MRI Techniques and Applications (9 papers), MRI in cancer diagnosis (7 papers) and Advanced Neuroimaging Techniques and Applications (7 papers). Jinsuh Kim is often cited by papers focused on Advanced MRI Techniques and Applications (9 papers), MRI in cancer diagnosis (7 papers) and Advanced Neuroimaging Techniques and Applications (7 papers). Jinsuh Kim collaborates with scholars based in United States, China and Austria. Jinsuh Kim's co-authors include Godfrey D. Pearlson, Hangyi Jiang, Peter C.M. van Zijl, Susumu Mori, Inam Kureshi, Michael C. Stevens, Suzanne T. Witt, David W. Lovejoy, Phillip Zhe Sun and Yin Wu and has published in prestigious journals such as NeuroImage, Magnetic Resonance in Medicine and Archives of Physical Medicine and Rehabilitation.

In The Last Decade

Jinsuh Kim

19 papers receiving 1.6k citations

Hit Papers

DtiStudio: Resource program for diffusion tensor computat... 2006 2026 2012 2019 2006 250 500 750
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. DtiStudio: Resource program for diffusion tensor computation and fiber bundle tracking
    2006 857 citations Hangyi Jiang, Peter C.M. van Zijl et al. Computer Methods and Programs in Biomedicine profile →

Peers

Jinsuh Kim
Henk Mutsaerts Netherlands
Deqiang Qiu United States
Maria Vittoria Spampinato United States
Ken Sakaie United States
John Woo United States
Itamar Ronen Netherlands
Alina Jurcoane Germany
Shannon Kolind Canada
Akifumi Hagiwara Japan
Francesca B. Pizzini Italy
Henk Mutsaerts Netherlands
Jinsuh Kim
Citations per year, relative to Jinsuh Kim Jinsuh Kim (= 1×) peers Henk Mutsaerts

Countries citing papers authored by Jinsuh Kim

Since Specialization
Citations

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

Fields of papers citing papers by Jinsuh Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jinsuh Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Jinsuh Kim. A scholar is included among the top collaborators of Jinsuh Kim 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 Jinsuh Kim. Jinsuh Kim 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.
Bouaynaya, Nidhal, Fanny Morón, Jinsuh Kim, et al.. (2024). Robust AI-Driven Segmentation of Glioblastoma T1c and FLAIR MRI Series and the Low Variability of the MRIMath© Smart Manual Contouring Platform. Diagnostics. 14(11). 1066–1066.
2.
Raman, Fabio, Sejong Bae, Jinsuh Kim, et al.. (2023). Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas. Cancers. 15(13). 3274–3274. 8 indexed citations
3.
4.
5.
Hu, Ranliang, et al.. (2022). Fast diffusion kurtosis imaging in acute ischemic stroke shows mean kurtosis‐diffusivity mismatch. Journal of Neuroimaging. 32(5). 941–946. 1 indexed citations
6.
Nabors, Burt, et al.. (2022). Undesired impact of iron supplement on MRI assessment of post-treatment glioblastoma. CNS Oncology. 11(4). CNS90–CNS90. 3 indexed citations
7.
Salehani, Arsalaan, et al.. (2022). The effect of procedural end-tidal CO2 on infarct expansion during anterior circulation thrombectomy. Interventional Neuroradiology. 30(5). 689–693. 2 indexed citations
8.
Langkammer, Christian, Ferdinand Schweser, Karin Shmueli, et al.. (2017). Quantitative susceptibility mapping: Report from the 2016 reconstruction challenge. Magnetic Resonance in Medicine. 79(3). 1661–1673. 139 indexed citations
9.
Wu, Yin, Jinsuh Kim, Suk‐Tak Chan, et al.. (2016). Comparison of image sensitivity between conventional tensor‐based and fast diffusion kurtosis imaging protocols in a rodent model of acute ischemic stroke. NMR in Biomedicine. 29(5). 625–630. 15 indexed citations
10.
Kim, Jinsuh, Yin Wu, Yingkun Guo, Hairong Zheng, & Phillip Zhe Sun. (2015). A review of optimization and quantification techniques for chemical exchange saturation transfer MRI toward sensitive in vivo imaging. Contrast Media & Molecular Imaging. 10(3). 163–178. 94 indexed citations
11.
Kim, Jinsuh, et al.. (2014). Neuropsychological Performance, Brain Imaging, and Driving Violations in Multiple Sclerosis. Archives of Physical Medicine and Rehabilitation. 95(10). 1818–1823. 15 indexed citations
12.
Kim, Jinsuh, et al.. (2014). Epithelioid hemangioma of the spine: Two cases. Radiology Case Reports. 9(4). 984–984. 8 indexed citations
13.
Stevens, Michael C., et al.. (2012). Multiple resting state network functional connectivity abnormalities in mild traumatic brain injury. Brain Imaging and Behavior. 6(2). 293–318. 162 indexed citations
14.
Kim, Jinsuh, Enrique C. Leira, R. Charles Callison, et al.. (2010). Toward fully automated processing of dynamic susceptibility contrast perfusion MRI for acute ischemic cerebral stroke. Computer Methods and Programs in Biomedicine. 98(2). 204–213. 30 indexed citations
15.
Wu, Andrew S., Bao H., Jinsuh Kim, & Daniel L. Rubin. (2009). Evaluation of Negation and Uncertainty Detection and its Impact on Precision and Recall in Search. Journal of Digital Imaging. 24(2). 234–242. 13 indexed citations
16.
Moritani, Toshio, Jinsuh Kim, Yutaka Satō, Daniel J. Bonthius, & Wendy R. K. Smoker. (2008). Abnormal hypermyelination in a neonate with Sturge‐Weber syndrome demonstrated on diffusion‐tensor imaging. Journal of Magnetic Resonance Imaging. 27(3). 617–620. 19 indexed citations
17.
Lee, Jee Eun, Moo K. Chung, Mariana Lazar, et al.. (2008). A study of diffusion tensor imaging by tissue-specific, smoothing-compensated voxel-based analysis. NeuroImage. 44(3). 870–883. 84 indexed citations
18.
Magnotta, Vincent A., Jinsuh Kim, Timothy R. Koscik, et al.. (2008). Diffusion Tensor Imaging in Preclinical Huntington’s Disease. Brain Imaging and Behavior. 3(1). 77–84. 38 indexed citations
19.
Calhoun, Vince D., et al.. (2007). Diffusion tensor imaging in schizophrenia: Relationship to symptoms. Schizophrenia Research. 98(1-3). 157–162. 109 indexed citations
20.
Jiang, Hangyi, Peter C.M. van Zijl, Jinsuh Kim, Godfrey D. Pearlson, & Susumu Mori. (2006). DtiStudio: Resource program for diffusion tensor computation and fiber bundle tracking. Computer Methods and Programs in Biomedicine. 81(2). 106–116. 857 indexed citations breakdown →

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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