23 citations · 48 across the 7 of their papers we have counts for
8 papers
Vessel segmentation for X-separation
Taechang Kim, Sooyeon Ji, Kyeongseon Min +5
-separation is an advanced quantitative susceptibility mapping (QSM) method that is designed to generate paramagnetic () and diamagnetic () susceptibility m…
χ-sepnet: Deep neural network for magnetic susceptibility source separation
Minjun Kim, Sooyeon Ji, Jiye Kim +8
Magnetic susceptibility source separation (-separation), an advanced quantitative susceptibility mapping (QSM) method, enables the separate estimation of para- and diamagnetic s…
In-vivo high-resolution χ-separation at 7T
Jiye Kim, Minjun Kim, Sooyeon Ji +7
A recently introduced quantitative susceptibility mapping (QSM) technique, -separation, offers the capability to separate paramagnetic () and diamagnetic ($χ_{\…
So You Want to Image Myelin Using MRI: Magnetic Susceptibility Source Separation for Myelin Imaging
Jongho Lee, Sooyeon Ji, Se-Hong Oh
In MRI, researchers have long endeavored to effectively visualize myelin distribution in the brain, a pursuit with significant implications for both scientific research and clinica…
Self-supervised training of deep denoisers in multi-coil MRI considering noise correlations
Juhyung Park, Dongwon Park, Sooyeon Ji +3
Deep learning-based denoising methods have shown powerful results for improving the signal-to-noise ratio of magnetic resonance (MR) images, mostly by leveraging supervised learnin…
DeepResp: Deep learning solution for respiration-induced B0 fluctuation artifacts in multi-slice GRE
Hongjun An, Hyeong-Geol Shin, Sooyoen Ji +5
Respiration-induced B fluctuation corrupts MRI images by inducing phase errors in k-space. A few approaches such as navigator have been proposed to correct for the artifacts at…
Deep Reinforcement Learning Designed Shinnar-Le Roux RF Pulse using Root-Flipping: DeepRF_SLR
Dongmyung Shin, Sooyeon Ji, Doohee Lee +3
A novel approach of applying deep reinforcement learning to an RF pulse design is introduced. This method, which is referred to as DeepRF_SLR, is designed to minimize the peak ampl…
Exploring linearity of deep neural network trained QSM: QSMnet+
Woojin Jung, Jaeyeon Yoon, Joon Yul Choi +4
Recently, deep neural network-powered quantitative susceptibility mapping (QSM), QSMnet, successfully performed ill conditioned dipole inversion in QSM and generated high-quality s…