Jong Chul Ye
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- Medical Imaging Techniques and Applications 58
- Advanced MRI Techniques and Applications 53
- Optical Imaging and Spectroscopy Techniques 23
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- Image and Signal Denoising Methods 32
- Advanced Image Processing Techniques 23
- Biophysics top 0.5%
- Structural Biology top 2%
- Biomedical Engineering top 0.5%
- Photoacoustic and Ultrasonic Imaging 45
- Advanced X-ray and CT Imaging 30
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- Sparse and Compressive Sensing Techniques 67
- Journals
- IEEE Transactions on Medical Imaging (17 papers)Optics Express (9 papers)Medical Image Analysis (8 papers)
- Partner nations
- South KoreaUnited StatesSwitzerland
In The Last Decade
Jong Chul Ye
244 papers receiving 8.7k citations
Hit Papers
Peers
Comparison fields: 5 of 182
- Radiology, Nuclear Medicine and Imaging 4.7k
- Computer Vision and Pattern Recognition 2.3k
- Biophysics 538
- Structural Biology 104
- Biomedical Engineering 3.1k
Countries citing papers authored by Jong Chul Ye
This map shows the geographic impact of Jong Chul Ye'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 Jong Chul Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jong Chul Ye more than expected).
Fields of papers citing papers by Jong Chul Ye
This network shows the impact of papers produced by Jong Chul Ye. 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 Jong Chul Ye. The network helps show where Jong Chul Ye may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jong Chul Ye, 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 | 2025 | 0 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 29 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 14 | |
| 7 | 2023 | 5 | |
| 8 | 2023 | 5 | |
| 9 | 2023 | 1 | |
| 10 | 2022 | 9 | |
| 11 | 2021 | 39 | |
| 12 | Federated Split Task-Agnostic Vision Transformer for COVID-19 CXR Diagnosis | 2021 | 20 |
| 13 | 2020 | 12 | |
| 14 | 2020 | 59 | |
| 15 | 2020 | 40 | |
| 16 | Multiphase Level-Set Loss for Semi-Supervised and Unsupervised Segmentation with Deep Learning | 2019 | 3 |
| 17 | Wavelet Domain Residual Network (WavResNet) for Low-Dose X-ray CT Reconstruction | 2017 | 3 |
| 18 | Wavelet Residual Network for Low-Dose CT via Deep Convolutional Framelets. | 2017 | 6 |
| 19 | Geometric GAN | 2017 | 44 |
| 20 | Inpainting based metal reduction in dental X-ray computed tomography | 2012 | 2 |
About Jong Chul Ye
Jong Chul Ye is a scholar working on Radiology, Nuclear Medicine and Imaging, Biophysics and Computer Vision and Pattern Recognition, having authored 260 papers that have together received 9.0k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (67 papers), Medical Imaging Techniques and Applications (58 papers), Advanced MRI Techniques and Applications (53 papers), Photoacoustic and Ultrasonic Imaging (45 papers), Image and Signal Denoising Methods (32 papers), Advanced X-ray and CT Imaging (30 papers), Advanced Image Processing Techniques (23 papers) and Optical Imaging and Spectroscopy Techniques (23 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (4.7k citations), Computer Vision and Pattern Recognition (2.3k citations) and Biophysics (538 citations). Jong Chul Ye has collaborated with scholars based in South Korea, United States and Switzerland. Frequent co-authors include Yoseob Han, Sungho Tak, Hong Jung, Kyong Hwan Jin, Hyungjin Chung, Eung Yeop Kim, Jaejun Yoo, Ge Wang, Bruno De Man and Eun‐Hee Kang. Their work appears in journals such as IEEE Transactions on Medical Imaging, Optics Express, Medical Image Analysis, IEEE Signal Processing Magazine and Magnetic Resonance in Medicine.
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.