Research Interests

My primary research interests focus on developing methods for mapping the electro-magnetic properties in magnetic resonance imaging (MRI) using machine learning and deep learning techniques, based on finite-difference time-domain simulations. Specifically, I am interested in quantifying electrical properties tomography (EPT) and in developing coil combination methods to apply EPT algorithms to various anatomical regions. Additionally, I am keen to explore functional MRI and motion correction.

•     [2020, 2023, and 2024] ISMRM Trainee (Educational) Stipend Awards from the International Society for Magnetic Resonance in Medicine (ISMRM).

•     [2024] 3rd Place Award from the International Society for Magnetic Resonance in Medicine Electro-Magnetic Tissue Properties (EMTP) Study Group (ISMRM 2024). Paper Title: A Joint 2.5D Physics-coupled Deep learning based Polynomial Fitting Approach for MR Electrical Properties Tomography.

•     [2024] ISMRM Annual Meeting Program Committee’s Selection from the International Society for Magnetic Resonance in Medicine (ISMRM 2024). Paper Title: The first MR Electrical Properties Tomography (MR-EPT) reconstruction challenge: preliminary results of simulated data. [Hands-On Committee]

•     [2023] 2023 ISMRM Research Exchange Program Grant: Research grant together with Prof. Stefano Mandija  from the International Society for Magnetic Resonance (ISMRM 2023), 5,000 USD. Project proposal title: Deep Learning based Electrical Properties Tomography as Biomarker in Radiotherapy.

•     [2023] 3rd Place Award from the International Society for Magnetic Resonance in Medicine Electro-Magnetic Tissue Properties (EMTP) Study Group (ISMRM 2023). Paper Title: A Deep learning informed Polynomial Fitting Approach for Electrical Properties Tomography.

•     [2023] ISMRM Merit Award Summa Cum Laude from the International Society for Magnetic Resonance in Medicine (ISMRM 2023). Paper Title: A Deep learning informed Polynomial Fitting Approach for Electrical Properties Tomography.

•     [2023] ISMRM Annual Meeting Program Committee’s Selection from the International Society for Magnetic Resonance in Medicine (ISMRM 2023). Paper Title: A Deep learning informed Polynomial Fitting Approach for Electrical Properties Tomography.

•     [2022] 2nd Place Award from the International Society for Magnetic Resonance in Medicine Electro-Magnetic Tissue Properties (EMTP) Study Group (ISMRM 2022). Paper Title: Feasibility study for conductivity reconstructions from spin-echo images using artificial neural network with simulation data in 3T MR system.

•     [2022] ISMRM Merit Award Magna Cum Laude from the International Society for Magnetic Resonance in Medicine (ISMRM 2022). Paper Title: Feasibility study for conductivity reconstructions from spin-echo images using artificial neural network with simulation data in 3T MR system.

•     [2022] 2022-1 Yonsei University Merit Academic Paper Award (No. 2022-68) from Yonsei University. Paper Title: Improving Phase-based Conductivity Reconstruction by Means of Deep Learning based Denoising of B1+ Phase Data for 3T MRI.

•     [2020] ISMRM Merit Award Magna Cum Laude from the International Society for Magnetic Resonance in Medicine (ISMRM 2022). Paper Title: Improving Phase-based Conductivity Reconstructions by Means of Deep Learning-based Denoising of B1+ Phase Data.

1.        Kyu-Jin Jung, Thierry G. Meerbothe, Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Stefano Mandija, and Dong-Hyun Kim, “A Joint 2.5D Physics-coupled Deep learning based Polynomial Fitting Approach for MR Electrical Properties Tomography,” IEEE Transactions on Medical Imaging, (2024), Under Review.

2.      Kyu-Jin Jung, Stefano Mandija, Chuanjiang Cui, Jun-Hyeong Kim, Mohammed A. Al-masni, Thierry G. Meerbothe, Mina Park, Cornelis A.T. van den Berg, and Dong-hyun Kim, “Data-driven Electrical Conductivity Brain Imaging using 3T MRI,” Human Brain Mapping, 44(15), 4986-5001 (2023).

3.  Kyu-Jin Jung, Stefano Mandija, Jun-Hyeong Kim, Kanghyun Ryu, Soozy Jung, Chuanjiang Cui, Soo-Yeon Kim, Mina Park, Cornelis A. T. van den Berg, and Dong-hyun Kim, “Improving Phase-based Conductivity Reconstruction by Means of Deep Learning based Denoising of B1+ Phase Data for 3T MRI,” Magnetic Resonance in Medicine, 86(4), 2084-2094 (2021).

4.      Kyu-Jin Jung, and Jin-Kyu Byun, “The Human Exposure Assessment of Magnetic Field From an Induction Cooktop Using Coupling Factor Based on Measurement Data,” Journal of Magnetics, 23(3), 473-479 (2018).

5.  Kyu-Jin Jung, Jae-Hoon Shim, Min-Soo Choi, and Jin-Kyu Byun, “Non-Uniform Magnetic Field Exposure Assessment Using Coupling Factors Based on 3-D Anatomical Human Model,” IEEE Transactions on Magnetics, 54(3), 1-4 (2018).

1.    Kyu-Jin Jung, Chuanjiang Cui, SooHyoung Lee, Ji-Won Chun, and Dong-Hyun Kim. Investigation of functional MRI using phase-based EPT: Comparison with simulations. Organization for Human Brain Mapping (OHBM) 2024, Seoul, Korea (2024).

2.      Kyu-Jin Jung, Thierry G. Meerbothe,  Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Dong-Hyun Kim, and Stefano Mandija. A Joint 2.5D Physics-coupled Deep learning based Polynomial Fitting Approach for MR Electrical Properties Tomography. 2024 ISMRM & ISMRT Annual Meeting & Exhibition, Singapore (2024). [ISMRM EMTP Study Group 3rd place Award]

3.      Stefano Mandija, Alessandro Arduino, Cornelis A.T. van den Berg, Patrick Fuchs, Ilias Giannakopoulos, Yusuf Ziya Ider, Kyu-Jin Jung, Ulrich Kastcher, Dong-Hyun Kim, Riccardo Lattanzi, Thierry G. Meerbothe, Khin-Khin Tha, Luca Zilberti. The first MR Electrical Properties Tomography (MR-EPT) reconstruction challenge: preliminary results of simulated data. 2024 ISMRM & ISMRT Annual Meeting & Exhibition, Singapore (2024). [Hands-On Committee] [Highlights : Committee’s Selection; Additional Exposure with Traditional Poster]

4.     Kyu-Jin Jung, Thierry G. Meerbothe,  Chuanjiang Cui, Mina Park, Jaeuk Yi, Cornelis A.T. van den Berg, Dong-Hyun Kim, and Stefano Mandija. A Deep learning informed Polynomial Fitting Approach for Electrical Properties Tomography. 2023 ISMRM & ISMRT Annual Meeting & Exhibition, Toronto, Canada (2023). [Oral presentation] [Summa Cum Laude Award] [Highlights : Committee’s Selection; Additional Exposure with Traditional Poster] [ISMRM EMTP Study Group 3rd place Award]

5.  Kyu-Jin Jung, Chuanjiang Cui, Jae-Hun Lee, Jun-Hyeong Kim, Kyoung-Jin Park, SooHyoung Lee, SunYoung Jung, and Dong-Hyun Kim. Investigation of electrical conductivity changes during functional activity of the brain via phase-based MR-EPT: Preliminary observation. 2023 ISMRM & ISMRT Annual Meeting & Exhibition, Toronto, Canada (2023). [Oral presentation]

6.    Kyu-Jin Jung, Stefano Mandija, Jun-Hyeong Kim, Chuanjiang Cui, Sanghyeok Choi, Jaeuk Yi, Mina Park, Cornelis A.T. van den Berg, and Dong-Hyun Kim. Feasibility study for conductivity reconstructions from spin-echo images using artificial neural network with simulation data in 3T MR system. Joint Annual Meeting ISMRM-ESMRMB & SMRT 31st Annual Meeting, London, England, UK (2022). [Oral presentation] [Magna Cum Laude Award] [ISMRM EMTP Study Group 2nd place Award]

7.    Kyu-Jin Jung, Stefano Mandija, Jun-Hyeong Kim, Kanghyun Ryu, Soozy Jung, Mina Park, Mohammed A. Al-masni, Cornelis A.T. van den Berg, and Dong-Hyun Kim. Improving Phase-based Conductivity Reconstructions by Means of Deep Learning-based Denoising of B1+ Phase Data. 28th International Society for Magnetic Resonance in Medicine, Online (2020). [Oral presentation] [Magna Cum Laude Award]