Publication

•  Kang, J., Bak, D., Shin, N. Y., Kim, H. G., & Nam, Y. (2026). Improved BG‐PVS Quantification in Infant Brain MRI Using Anatomy‐Informed Pseudo‐Labels for Joint BG and PVS Segmentation. Journal of Magnetic Resonance Imaging. link

•  Park, G. E., Kim, S. H., Nam, Y., Kang, J., Park, M., & Kang, B. J. (2024). 3D Breast Cancer Segmentation in DCE‐MRI Using Deep Learning with Weak Annotation. Journal of Magnetic Resonance Imaging. link

•  Kim, H., Jang, J., Kang, J., Jang, S., Nam, Y., Choi, Y., ... & Kim, B. S. (2022). Clinical implications of focal mineral deposition in the globus pallidus on CT and quantitative susceptibility mapping of MRI. Korean Journal of Radiology, 23(7), 742. link

•  Nam, Y., Choi, Y., Kang, J., Seo, M., Heo, S. J., & Lee, M. K. (2022). Diagnosis of nasal bone fractures on plain radiographs via convolutional neural networks. Scientific Reports, 12(1), 21510. link

•  Kim, W., Shin, H. G., Lee, H., Park, D., Kang, J., Nam, Y., ... & Jang, J. (2022). χ-Separation Imaging for Diagnosis of Multiple Sclerosis versus Neuromyelitis Optica Spectrum Disorder. Radiology, 220941. link

•  Kang, J., & Nam, Y. (2022). Applications of Artificial Intelligence in MR Image Acquisition and Reconstruction. Journal of the Korean Society of Radiology, 83(6), 1229-1239. link

•  Lee, J. H., Kang, J., Oh, S. H., & Ye, D. H. (2022). Multi-Domain Neumann Network with Sensitivity Maps for Parallel MRI Reconstruction. Sensors, 22(10), 3943. link

•  Kang, J., Kim, H., Kim, E., Kim, E., Lee, H., Shin, N. Y., & Nam, Y. (2021). Convolutional Neural Network-Based Automatic Segmentation of Substantia Nigra on Nigrosome and Neuromelanin Sensitive MR Images. Investigative Magnetic Resonance Imaging, 25(3), 156-163. link

•  Nam, Y., Park, G. E., Kang, J., & Kim, S. H. (2020). Fully Automatic Assessment of Background Parenchymal Enhancement on Breast MRI Using Machine‐Learning Models. Journal of Magnetic Resonance Imaging. Link / GitHub