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
- Robotic Path Planning Algorithms 1
- Digital Image Processing Techniques 1
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- Advanced Neuroimaging Techniques and Applications 2
- Co-authors
- June Sic Kim (2 shared papers)Alan C. Evans (2 shared papers)Jason P. Lerch (1 shared paper)Vivek Kumar Singh (1 shared paper)Yasser Ad-Dab’bagh (1 shared paper)Sun I. Kim (1 shared paper)David MacDonald (1 shared paper)Jong‐Min Lee (2 shared papers)
- Journals
- NeuroImage (3 papers)
- Partner nations
- South KoreaCanada
In The Last Decade
Jun Ki Lee
4 papers receiving 870 citations
Jun Ki Lee's Hit Papers
Peers
Comparison fields: 5 of 87
- Cognitive Neuroscience 479
- Psychiatry and Mental health 328
- Radiology, Nuclear Medicine and Imaging 400
- Pediatrics, Perinatology and Child Health 92
- Neurology 71
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 17 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 | 680 |
| 2 | 2007 | 107 | |
| 3 | 2006 | 92 | |
| 4 | 2024 | 1 |
About Jun Ki Lee
Jun Ki Lee is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Pediatrics, Perinatology and Child Health, Cognitive Neuroscience and Rheumatology, having authored 4 papers that have together received 880 indexed citations. Recurring topics across this work include Advanced Neuroimaging Techniques and Applications (2 papers), Medical Image Segmentation Techniques (2 papers), Pharmacological Effects and Toxicity Studies (1 paper), Modular Robots and Swarm Intelligence (1 paper), Robotics and Sensor-Based Localization (1 paper), Epilepsy research and treatment (1 paper), Robotic Path Planning Algorithms (1 paper) and Digital Image Processing Techniques (1 paper). The work is most often cited by research in Cognitive Neuroscience (479 citations), Psychiatry and Mental health (328 citations), Radiology, Nuclear Medicine and Imaging (400 citations), Pediatrics, Perinatology and Child Health (92 citations) and Neurology (71 citations). Jun Ki Lee has collaborated with scholars based in South Korea and Canada. Frequent co-authors include June Sic Kim, Alan C. Evans, Jason P. Lerch, Vivek Kumar Singh, Yasser Ad-Dab’bagh, Sun I. Kim, David MacDonald, Jong‐Min Lee, Joong Koo Kang and Sang‐Ahm Lee. Their work appears in journals such as NeuroImage.
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.