Changmin Ryu
Medical Imaging Artificialย Intelligence Laboratory
Electrical & Electronic Engineering
Yonsei University
Integrated M.S./Ph.D. student
Medical Imaging Artificialย Intelligence Laboratory
Electrical & Electronic Engineering
Yonsei University
Integrated M.S./Ph.D. student
Medical Image Processing
eXplainable AI
Clinical Applications
Multi-Modality data analysis
2025.03 ~ Yonsei University ย Seoul, Korea
Joint M.S./Ph.D., (Electrical & Electronic Engineering)
2019.03 ~ 2025.02 Hankuk University of Foreign Studies ย Yongin-si, Korea
B.S., (Biomedical Engineering)
1. [2025] Changmin Ryu, Na-Young Shin, Sunyoung Jung, and Dong-Hyun Kim*. Attention-Guided Deep Learning Model for Predicting Myelination Age from Multi- contrast Brain MRI of Neonates and Infants. KCR 2025. Oral Presentation.ย
2. [2025] Hyeryn Park, Changmin Ryu, Dong-Hyun Kim, Hyun Seok Choi, and Sung-min Gho*. Infant Brain Age Estimation Using Deep Learning on Myelin-Sensitive T1w/T2w Ratio Images. KCR 2025. Oral Presentation.ย
3. [2025] Changmin Ryu, Sunyoung Jung, Na-Young Shin, and Dong-Hyun Kim*. Attention-guided deep learning model focusing on myelination for predicting brain age using multi contrast MRI. ISMRM 2025. Oral Presentation.ย
4. [2025] Changmin Ryu, Sunyoung Jung, Yoonseok Choi, and Dong-Hyun Kim*. Improving subcortical segmentation in brain MRI using knowledge distillation to enhance robustness against motion artifacts. ISMRM 2025. Digital Poster.ย
5. [2024] Changmin Ryu, Sunyoung Jung, Yoonseok Choi, and Dong-Hyun Kim*. Improving subcortical segmentation in brain MRI using knowledge distillation to enhance robustness against motion artifacts. ICMRI 2024. Printed Poster. Best Trainee Scientific Awards Poster Presentation(Gold).
6. [2024] Changmin Ryu, Joon-Yong Jung, Keum San Chun, Sungwon Lee, Yoonho Nam*. On the feasibility of detecting spinal stenosis using deep learning in radiography. KCR 2024. Oral Presentation.
7. [2024] Hagyeong Yu, Changmin Ryu, Junghwa Kang, Tae Young Lee, Yoonho nam*. Quantitative analysis of MRI-visible perivascular spaces in schizophrenia. OHBM 2024. Printed Poster.
8. [2024] Hagyeong Yu, Changmin Ryu, Junghwa Kang, Tae Young Lee, Yoonho nam*. Quantitative analysis of MRI-visible perivascular spaces in schizophrenia. ISMRM 2024. Printed Poster.
9. [2023] Oh Joon Kwon, Changmin Ryu, Eun a Kwon, Hyun Gi Kim, Yoonho Nam*. Improved basal ganglia segmentation of three dimensional neonatal brain MR images for perivascular space assessment. ICMRI 2023. Oral Presentation.ย
Comming Soon ...
1. [2025] "์์ ์ ๋ ๋์ด ์ถ์ ๋ฐฉ๋ฒ ๋ฐ ์ฅ์น", ๊น๋ํ, ์ ์ฐฝ๋ฏผ, ์ ๋์, ์ถ์๋ฒํธ: 10-2025-0067307, ์ถ์์ผ์: 2025.05.23