Translation of 1D Inverse Fourier Transform of K-space to an Image Based on Deep Learning for Accelerating Magnetic Resonance Imaging. - Taejoon Eo; Hyungseob Shin; Taeseong Kim; Yohan Jun; Dosik Hwang (MICCAI (1), 2018)

State-of-the-Art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge. - Matthew J. Muckley; Bruno Riemenschneider; Alireza Radmanesh; Sunwoo Kim; Geunu Jeong; Jingyu Ko; Yohan Jun; Hyungseob Shin; Dosik Hwang; Mahmoud Mostapha; Simon Arberet; Dominik Nickel; et al. (CoRR, 2020)

Accelerating Cartesian MRI by domain-transform manifold learning in phase-encoding direction. - Taejoon Eo; Hyungseob Shin; Yohan Jun; Taeseong Kim; Dosik Hwang (Medical Image Anal., 2020)

Joint Deep Model-Based MR Image and Coil Sensitivity Reconstruction Network (Joint-ICNet) for Fast MRI. - Yohan Jun; Hyungseob Shin; Taejoon Eo; Dosik Hwang (CVPR, 2021)

Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge. - Patricia M. Johnson; Geunu Jeong; Kerstin Hammernik; Jo Schlemper; Chen Qin; Jinming Duan 001; Daniel Rueckert; Jingu Lee; Nicola Pezzotti; Elwin de Weerdt; Sahar Yousefi; Mohamed S. Elmahdy; et al. (MLMIR@MICCAI, 2021)

Self-Training Based Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma and Cochlea Segmentation. - Hyungseob Shin; Hyeongyu Kim; Sewon Kim; Yohan Jun; Taejoon Eo; Dosik Hwang (CoRR, 2021)

Deep model-based magnetic resonance parameter mapping network (DOPAMINE) for fast T1 mapping using variable flip angle method. - Yohan Jun; Hyungseob Shin; Taejoon Eo; Taeseong Kim; Dosik Hwang (Medical Image Anal., 2021)

Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction. - Matthew J. Muckley; Bruno Riemenschneider; Alireza Radmanesh; Sunwoo Kim; Geunu Jeong; Jingyu Ko; Yohan Jun; Hyungseob Shin; Dosik Hwang; Mahmoud Mostapha; Simon Arberet; Dominik Nickel; et al. (IEEE Trans. Medical Imaging, 2021)

CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwnannoma and Cochlea Segmentation. - Reuben Dorent; Aaron Kujawa; Marina Ivory; Spyridon Bakas; Nicola Rieke; Samuel Joutard; Ben Glocker; Jorge Cardoso 002; Marc Modat; Kayhan Batmanghelich; Arseniy Belkov; Maria G. Baldeon Calisto; et al. (CoRR, 2022)

COSMOS: Cross-Modality Unsupervised Domain Adaptation for 3D Medical Image Segmentation based on Target-aware Domain Translation and Iterative Self-Training. - Hyungseob Shin; Hyeongyu Kim; Sewon Kim; Yohan Jun; Taejoon Eo; Dosik Hwang (CoRR, 2022)

SDC-UDA: Volumetric Unsupervised Domain Adaptation Framework for Slice-Direction Continuous Cross-Modality Medical Image Segmentation. - Hyungseob Shin; Hyeongyu Kim; Sewon Kim; Yohan Jun; Taejoon Eo; Dosik Hwang (CVPR, 2023)

CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation. - Reuben Dorent; Aaron Kujawa; Marina Ivory; Spyridon Bakas; Nicola Rieke; Samuel Joutard; Ben Glocker; M. Jorge Cardoso; Marc Modat; Kayhan Batmanghelich; Arseniy Belkov; Maria G. Baldeon Calisto; et al. (Medical Image Anal., 2023)

Interpretable multimodal transformer for prediction of molecular subtypes and grades in adult-type diffuse gliomas. - Yunsu Byeon; Yae Won Park; Soohyun Lee; Doohyun Park; Hyungseob Shin; Kyunghwa Han; Jong Hee Chang; Se Hoon Kim; Seung-Koo Lee; Sungsoo Ahn; Dosik Hwang (npj Digit. Medicine, 2025)