Mun Bae Lee

571 total citations · 1 hit paper
14 papers, 513 citations indexed

About

Mun Bae Lee is a scholar working on Radiology, Nuclear Medicine and Imaging, Electrical and Electronic Engineering and Cognitive Neuroscience. According to data from OpenAlex, Mun Bae Lee has authored 14 papers receiving a total of 513 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Radiology, Nuclear Medicine and Imaging, 7 papers in Electrical and Electronic Engineering and 5 papers in Cognitive Neuroscience. Recurrent topics in Mun Bae Lee's work include Advanced MRI Techniques and Applications (11 papers), Electrical and Bioimpedance Tomography (7 papers) and Advanced Neuroimaging Techniques and Applications (5 papers). Mun Bae Lee is often cited by papers focused on Advanced MRI Techniques and Applications (11 papers), Electrical and Bioimpedance Tomography (7 papers) and Advanced Neuroimaging Techniques and Applications (5 papers). Mun Bae Lee collaborates with scholars based in South Korea and United States. Mun Bae Lee's co-authors include Oh In Kwon, Hyung Joong Kim, Eung Je Woo, Saurav Z. K. Sajib, Geon‐Ho Jahng, Chang‐Woo Ryu, Hak Young Rhee, Yeon Hyang Kim, Soonchan Park and Hae-Woong Kwon and has published in prestigious journals such as PLoS ONE, NeuroImage and Scientific Reports.

In The Last Decade

Mun Bae Lee

13 papers receiving 509 citations

Hit Papers

align trajectories

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.

Extracellular Total Electrolyte Concentration Imaging for Electrical Brain Stimulation (EBS)

2018 461 citations Saurav Z. K. Sajib, Mun Bae Lee et al. Scientific Reports profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mun Bae Lee South Korea	6	145	109	77	69	69	14	513
Lars Dähne Italy	11	234 1.6×	70 0.6×	188 2.4×	126 1.8×	31 0.4×	15	845
Young-Zoon Yoon South Korea	11	439 3.0×	139 1.3×	135 1.8×	72 1.0×	41 0.6×	13	761
Ei YAMAMOTO Japan	22	220 1.5×	130 1.2×	94 1.2×	63 0.9×	64 0.9×	77	1.2k
Martin Bencsik United Kingdom	15	160 1.1×	66 0.6×	104 1.4×	53 0.8×	130 1.9×	48	710
Diana J. Lewis United States	10	102 0.7×	40 0.4×	69 0.9×	183 2.7×	33 0.5×	23	388
Binjie Zhang China	16	137 0.9×	49 0.4×	118 1.5×	93 1.3×	26 0.4×	44	792
Kuntao Chen China	11	118 0.8×	78 0.7×	94 1.2×	25 0.4×	37 0.5×	22	411
Ziqiao Sun China	9	377 2.6×	137 1.3×	75 1.0×	152 2.2×	19 0.3×	14	605
Rebecca Wu Canada	14	234 1.6×	206 1.9×	83 1.1×	149 2.2×	37 0.5×	30	973
Inhee Cho South Korea	9	398 2.7×	182 1.7×	134 1.7×	118 1.7×	18 0.3×	14	929

Countries citing papers authored by Mun Bae Lee

Since Specialization

Citations

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

Fields of papers citing papers by Mun Bae Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mun Bae Lee

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

All Works

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14 of 14 papers shown

Kwon, Hae-Woong, Mun Bae Lee, Hak Young Rhee, et al.. (2025). Exploring the relationship between larmor-frequency electrical conductivity, diffusivity, and tissue volume in the aging brain. Quantitative Imaging in Medicine and Surgery. 15(5). 4669–4688. 1 indexed citations

Kim, Hyug‐Gi, et al.. (2024). Functional MRI study with conductivity signal changes during visual stimulation. Journal of Neuroscience Methods. 412. 110288–110288. 2 indexed citations

Lee, Mun Bae, Hak Young Rhee, Soonchan Park, et al.. (2024). Increased extra-neurite conductivity of brain in patients with Alzheimer's disease: A pilot study. Psychiatry Research Neuroimaging. 340. 111807–111807. 1 indexed citations

Jahng, Geon‐Ho, Mun Bae Lee, & Oh In Kwon. (2024). Principle, Development, and Application of Electrical Conductivity Mapping Using Magnetic Resonance Imaging. 35(4). 73–88.

Kwon, Oh In, Mun Bae Lee, & Geon‐Ho Jahng. (2023). High frequency conductivity decomposition by solving physically constraint underdetermined inverse problem in human brain. Scientific Reports. 13(1). 3273–3273. 1 indexed citations

Park, Soonchan, Mun Bae Lee, Hak Young Rhee, et al.. (2022). Application of High-Frequency Conductivity Map Using MRI to Evaluate It in the Brain of Alzheimer's Disease Patients. Frontiers in Neurology. 13. 872878–872878. 6 indexed citations

Lee, Mun Bae, Hyung Joong Kim, & Oh In Kwon. (2021). Decomposition of high-frequency electrical conductivity into extracellular and intracellular compartments based on two-compartment model using low-to-high multi-b diffusion MRI. BioMedical Engineering OnLine. 20(1). 29–29. 6 indexed citations

Lee, Mun Bae, Geon‐Ho Jahng, Hyung Joong Kim, & Oh In Kwon. (2021). High-frequency conductivity at Larmor-frequency in human brain using moving local window multilayer perceptron neural network. PLoS ONE. 16(5). e0251417–e0251417. 3 indexed citations

Lee, Mun Bae, Geon‐Ho Jahng, Hyung Joong Kim, Eung Je Woo, & Oh In Kwon. (2020). Extracellular electrical conductivity property imaging by decomposition of high-frequency conductivity at Larmor-frequency using multi-b-value diffusion-weighted imaging. PLoS ONE. 15(4). e0230903–e0230903. 8 indexed citations

10.

Jahng, Geon‐Ho, Mun Bae Lee, Hyung Joong Kim, Eung Je Woo, & Oh In Kwon. (2020). Low-frequency dominant electrical conductivity imaging of in vivo human brain using high-frequency conductivity at Larmor-frequency and spherical mean diffusivity without external injection current. NeuroImage. 225. 117466–117466. 15 indexed citations

11.

Sajib, Saurav Z. K., Mun Bae Lee, Hyung Joong Kim, Eung Je Woo, & Oh In Kwon. (2018). Extracellular Total Electrolyte Concentration Imaging for Electrical Brain Stimulation (EBS). Scientific Reports. 8(1). 290–290. 461 indexed citations breakdown →

12.

Lee, Mun Bae, Yeon Hyang Kim, Geon‐Ho Jahng, & Oh In Kwon. (2018). Angular resolution enhancement technique for diffusion-weighted imaging (DWI) using predicted diffusion gradient directions. NeuroImage. 183. 836–846. 5 indexed citations

13.

Lee, Mun Bae, Hyung Joong Kim, Eung Je Woo, & Oh In Kwon. (2018). Anisotropic conductivity tensor imaging for transcranial direct current stimulation (tDCS) using magnetic resonance diffusion tensor imaging (MR-DTI). PLoS ONE. 13(5). e0197063–e0197063. 3 indexed citations

14.

Lee, Mun Bae, Woo Chul Jeong, Saurav Z. K. Sajib, Hyung Joong Kim, & Oh In Kwon. (2015). Magnetic flux density measurement through phase decomposition using non‐interleaved scan in MREIT. Electronics Letters. 51(12). 890–892. 1 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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