Eunju Cha
Impact in
- Structural Biology top 10%
- Advanced Electron Microscopy Techniques and Applications
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- Medical Imaging Techniques and Applications
- Advanced MRI Techniques and Applications
Papers in
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- Advanced Image Processing Techniques 2
- Generative Adversarial Networks and Image Synthesis 2
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- Photoacoustic and Ultrasonic Imaging 2
- Co-authors
- Jong Chul Ye (6 shared papers)Yoseob Han (2 shared papers)Hyungjin Chung (3 shared papers)Jaeduck Jang (2 shared papers)Eunha Lee (2 shared papers)Junho Lee (2 shared papers)Eung Yeop Kim (1 shared paper)Sungwoo Hwang (1 shared paper)
- Journals
- IEEE Transactions on Medical Imaging (1 paper)Image and Vision Computing (1 paper)IEEE Journal of Selected Topics in Signal Processing (1 paper)SIAM Journal on Imaging Sciences (1 paper)Biomedical Signal Processing and Control (1 paper)
- Partner nations
- South KoreaUnited States
In The Last Decade
Eunju Cha
8 papers receiving 301 citations
Peers
Comparison fields: 5 of 56
- Structural Biology 25
- Radiology, Nuclear Medicine and Imaging 147
- Computer Vision and Pattern Recognition 104
- Surfaces, Coatings and Films 22
- Media Technology 24
Countries citing papers authored by Eunju Cha
This map shows the geographic impact of Eunju Cha'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 Eunju Cha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eunju Cha more than expected).
Fields of papers citing papers by Eunju Cha
This network shows the impact of papers produced by Eunju Cha. 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 Eunju Cha. The network helps show where Eunju Cha may publish in the future.
Co-authors
The 23 scholars most cited alongside Eunju Cha, 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 | 2018 | 213 | |
| 2 | 2021 | 39 | |
| 3 | 2022 | 13 | |
| 4 | 2020 | 12 | |
| 5 | 2020 | 10 | |
| 6 | 2022 | 9 | |
| 7 | 2020 | 9 | |
| 8 | 2024 | 1 | |
| 9 | 2025 | 0 | |
| 10 | 2024 | 0 |
About Eunju Cha
Eunju Cha is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Structural Biology, Radiation and Radiology, Nuclear Medicine and Imaging, having authored 10 papers that have together received 306 indexed citations. Recurring topics across this work include Advanced Electron Microscopy Techniques and Applications (3 papers), Advanced X-ray Imaging Techniques (2 papers), Medical Imaging Techniques and Applications (2 papers), Photoacoustic and Ultrasonic Imaging (2 papers), Advanced Image Processing Techniques (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Advanced MRI Techniques and Applications (2 papers) and Cell Image Analysis Techniques (1 paper). The work is most often cited by research in Structural Biology (25 citations), Radiology, Nuclear Medicine and Imaging (147 citations), Computer Vision and Pattern Recognition (104 citations), Surfaces, Coatings and Films (22 citations) and Media Technology (24 citations). Eunju Cha has collaborated with scholars based in South Korea and United States. Frequent co-authors include Jong Chul Ye, Yoseob Han, Hyungjin Chung, Jaeduck Jang, Eunha Lee, Junho Lee, Eung Yeop Kim, Sungwoo Hwang, Tae‐Gon Kim and Myoungho Jeong. Their work appears in journals such as IEEE Transactions on Medical Imaging, Image and Vision Computing, IEEE Journal of Selected Topics in Signal Processing, SIAM Journal on Imaging Sciences and Biomedical Signal Processing and Control.
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.