Jun Ki Lee
Impact in
- Cognitive Neuroscience top 5%
- Functional Brain Connectivity Studies
- Neural dynamics and brain function
- Psychiatry and Mental health top 5%
- Epilepsy research and treatment
- Dementia and Cognitive Impairment Research
Papers in
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- Medical Image Segmentation Techniques 2
- Digital Image Processing Techniques 1
- Robotic Path Planning Algorithms 1
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- Advanced Neuroimaging Techniques and Applications 2
- Co-authors
- Alan Charles Evans (2 shared papers)June Sic Kim (2 shared papers)David J. MacDonald (1 shared paper)Yasser Ad-Dab’bagh (1 shared paper)Vivek Kumar Singh (1 shared paper)Jason P. Lerch (1 shared paper)Sun I. Kim (1 shared paper)Jong‐Min Lee (2 shared papers)
- Partner nations
- South KoreaCanadaUnited States
In The Last Decade
Jun Ki Lee
4 papers receiving 924 citations
Jun Ki Lee's Hit Papers
Peers
Comparison fields: 5 of 84
- Cognitive Neuroscience 432
- Psychiatry and Mental health 284
- Radiology, Nuclear Medicine and Imaging 354
- Neurology 33
- Computer Vision and Pattern Recognition 90
Countries citing papers authored by Jun Ki Lee
This map shows the geographic impact of Jun Ki 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 Jun Ki Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Ki Lee more than expected).
Fields of papers citing papers by Jun Ki Lee
This network shows the impact of papers produced by Jun Ki 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 Jun Ki Lee. The network helps show where Jun Ki Lee may publish in the future.
Co-authors
The 20 scholars most cited alongside Jun Ki Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification Hit paper breakdown → | 2005 | 728 |
| 2 | 2007 | 111 | |
| 3 | 2006 | 100 | |
| 4 | 2024 | 1 | |
| 5 | 2026 | 0 |
About Jun Ki Lee
Jun Ki Lee is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Psychiatry and Mental health, Rheumatology and Pediatrics, Perinatology and Child Health, having authored 5 papers that have together received 940 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (2 papers), Advanced Neuroimaging Techniques and Applications (2 papers), Robotics and Sensor-Based Localization (1 paper), Glycogen Storage Diseases and Myoclonus (1 paper), Digital Image Processing Techniques (1 paper), Robotic Path Planning Algorithms (1 paper), Modular Robots and Swarm Intelligence (1 paper) and Functional Brain Connectivity Studies (1 paper). The work is most often cited by research in Cognitive Neuroscience (432 citations), Psychiatry and Mental health (284 citations), Radiology, Nuclear Medicine and Imaging (354 citations), Neurology (33 citations) and Computer Vision and Pattern Recognition (90 citations). Jun Ki Lee has collaborated with scholars based in South Korea, Canada and United States. Frequent co-authors include Alan Charles Evans, June Sic Kim, David J. MacDonald, Yasser Ad-Dab’bagh, Vivek Kumar Singh, Jason P. Lerch, Sun I. Kim, Jong‐Min Lee, In Young Kim and Sun Il Kim. Their work appears in journals such as NeuroImage and IEEE Robotics and Automation Letters.
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.