Jongho Lee

4.8k total citations · 1 hit paper
107 papers, 3.2k citations indexed

About

Jongho Lee is a scholar working on Radiology, Nuclear Medicine and Imaging, Cellular and Molecular Neuroscience and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Jongho Lee has authored 107 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Cellular and Molecular Neuroscience and 14 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Jongho Lee's work include Advanced MRI Techniques and Applications (56 papers), Advanced Neuroimaging Techniques and Applications (42 papers) and Advanced NMR Techniques and Applications (13 papers). Jongho Lee is often cited by papers focused on Advanced MRI Techniques and Applications (56 papers), Advanced Neuroimaging Techniques and Applications (42 papers) and Advanced NMR Techniques and Applications (13 papers). Jongho Lee collaborates with scholars based in South Korea, United States and Puerto Rico. Jongho Lee's co-authors include Jeff H. Duyn, Peter van Gelderen, Yoonho Nam, Masaki Fukunaga, Afonso C. Silva, Karin Shmueli, Hellmut Merkle, Eung Yeop Kim, Se‐Hong Oh and Jacco A. de Zwart and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Journal of Applied Physics.

In The Last Decade

Jongho Lee

103 papers receiving 3.2k citations

Hit Papers

Recommended implementation of quantitative susceptibility... 2024 2026 2025 2024 10 20 30 40 50

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jongho Lee South Korea 32 2.3k 520 382 333 327 107 3.2k
Alan H. Wilman Canada 36 2.3k 1.0× 670 1.3× 416 1.1× 275 0.8× 341 1.0× 118 3.7k
Alexander Rauscher Canada 36 2.5k 1.1× 472 0.9× 632 1.7× 176 0.5× 238 0.7× 131 3.8k
Andreas Deistung Germany 28 3.0k 1.3× 768 1.5× 915 2.4× 319 1.0× 184 0.6× 74 4.1k
Brian J. Soher United States 37 2.7k 1.2× 547 1.1× 275 0.7× 332 1.0× 765 2.3× 85 4.1k
Karin Shmueli United Kingdom 20 2.2k 1.0× 1.1k 2.2× 318 0.8× 152 0.5× 216 0.7× 65 3.0k
Gunnar Krueger Switzerland 27 2.2k 1.0× 1.1k 2.1× 317 0.8× 224 0.7× 260 0.8× 65 3.6k
Mary A. McLean United Kingdom 34 2.2k 0.9× 391 0.8× 264 0.7× 585 1.8× 558 1.7× 102 3.5k
Boris Keil United States 34 2.1k 0.9× 858 1.6× 657 1.7× 268 0.8× 268 0.8× 99 3.5k
Tobias Kober Switzerland 30 2.5k 1.1× 903 1.7× 334 0.9× 200 0.6× 208 0.6× 152 3.7k
Frank Träber Germany 41 2.6k 1.2× 485 0.9× 637 1.7× 452 1.4× 214 0.7× 133 4.6k

Countries citing papers authored by Jongho Lee

Since Specialization
Citations

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

Fields of papers citing papers by Jongho Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jongho Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Jongho Lee. A scholar is included among the top collaborators of Jongho Lee 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 Jongho Lee. Jongho Lee 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.
Jang, Jinhee, et al.. (2025). χ‐sepnet: Deep Neural Network for Magnetic Susceptibility Source Separation. Human Brain Mapping. 46(2). e70136–e70136. 4 indexed citations
2.
Shin, Hyeong‐Geol, Woojun Kim, Hyunsoo Lee, et al.. (2025). Association of iron deposition in MS lesion with remyelination capacity using susceptibility source separation MRI. NeuroImage Clinical. 45. 103748–103748. 1 indexed citations
3.
Lee, Jongho, et al.. (2024). So You Want to Image Myelin Using MRI: Magnetic Susceptibility Source Separation for Myelin Imaging. Magnetic Resonance in Medical Sciences. 23(3). 291–306. 10 indexed citations
4.
Jang, Jinhee, et al.. (2024). Comparison between R2′‐based and R2*‐based χ‐separation methods: A clinical evaluation in individuals with multiple sclerosis. NMR in Biomedicine. 37(9). e5167–e5167. 6 indexed citations
5.
Lee, Jongho & Hyun Kim. (2024). DCT-ViT: High-Frequency Pruned Vision Transformer With Discrete Cosine Transform. IEEE Access. 12. 80386–80396. 4 indexed citations
6.
Bilgic̦, Berkin, Mauro Costagli, Kwok‐Shing Chan, et al.. (2024). Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro‐magnetic tissue properties study group. Magnetic Resonance in Medicine. 91(5). 1834–1862. 58 indexed citations breakdown →
7.
Lee, Subin, et al.. (2023). Relationship Between Cortical Iron and Diabetes Mellitus in Older Adults With Cognitive Complaints: A Quantitative Susceptibility Map Study. Investigative Magnetic Resonance Imaging. 27(2). 84–84. 2 indexed citations
8.
Lee, Subin, et al.. (2023). Depth-wise profiles of iron and myelin in the cortex and white matter using χ-separation: A preliminary study. NeuroImage. 273. 120058–120058. 13 indexed citations
9.
Park, Dongwon, Minjun Kim, Hyungjin Kim, Jongho Lee, & Se Young Chun. (2023). Domain adaptation from posteroanterior to anteroposterior X-ray radiograph classification via deep neural converter with label recycling. 32. 1–4. 1 indexed citations
10.
11.
Kim, Woojun, et al.. (2022). χ-Separation Imaging for Diagnosis of Multiple Sclerosis versus Neuromyelitis Optica Spectrum Disorder. Radiology. 307(1). e220941–e220941. 27 indexed citations
12.
Shin, Dong-Myung, et al.. (2020). Deep Reinforcement Learning Designed Shinnar-Le Roux RF Pulse Using Root-Flipping: DeepRFSLR. IEEE Transactions on Medical Imaging. 39(12). 4391–4400. 8 indexed citations
14.
Sung, Young Hee, Jongho Lee, Yoonho Nam, et al.. (2018). Initial diagnostic workup of parkinsonism: Dopamine transporter positron emission tomography versus susceptibility map-weighted imaging at 3T. Parkinsonism & Related Disorders. 62. 171–178. 15 indexed citations
15.
Yoon, Jaeyeon, Enhao Gong, Itthi Chatnuntawech, et al.. (2018). Quantitative susceptibility mapping using deep neural network: QSMnet. NeuroImage. 179. 199–206. 116 indexed citations
16.
Jung, Woojin, Jingu Lee, Hyeong‐Geol Shin, et al.. (2017). Whole brain g-ratio mapping using myelin water imaging (MWI) and neurite orientation dispersion and density imaging (NODDI). NeuroImage. 182. 379–388. 34 indexed citations
17.
Lee, Jongho, Juan M. Santos, Steven Conolly, et al.. (2006). Respiration‐induced B0field fluctuation compensation in balanced SSFP: Real‐time approach for transition‐band SSFP fMRI. Magnetic Resonance in Medicine. 55(5). 1197–1201. 39 indexed citations
18.
Lee, Jongho, et al.. (2003). The Effect of Isoflavone Supplement on Plasma Lipids & Antioxidant Status in Hypercholesterolemic Postmenopausal Women. The Korean Journal of Nutrition. 36(6). 603–612. 7 indexed citations
19.
You, Cheol‐Hwan, et al.. (2003). Classifications of cloud types using weather radar. 대기. 13(1). 498–501.
20.
Lee, Jongho, et al.. (2003). Impact of Laser in Situ Keratomileusis (LASIK) Treatment on Quality of Life in Myopia Patients. Journal of the Korean Ophthalmological Society. 44(11). 2591–2606. 2 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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