53 citations · 348 across the 45 of their papers we have counts for
4 papers · 1 filter
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…
PRIME: Phase Reversed Interleaved Multi-Echo acquisition enables highly accelerated distortion-free diffusion MRI
Yohan Jun, Qiang Liu, Ting Gong +13
Purpose: To develop and evaluate a new pulse sequence for highly accelerated distortion-free diffusion MRI (dMRI) by inserting additional echoes without prolonging TR, when general…
Fast Whole-Brain MR Multi-Parametric Mapping with Scan-Specific Self-Supervised Networks
Amir Heydari, Abbas Ahmadi, Tae Hyung Kim +1
Quantification of tissue parameters using MRI is emerging as a powerful tool in clinical diagnosis and research studies. The need for multiple long scans with different acquisition…
NLCG-Net: A Model-Based Zero-Shot Learning Framework for Undersampled Quantitative MRI Reconstruction
Xinrui Jiang, Yohan Jun, Jaejin Cho +3
Typical quantitative MRI (qMRI) methods estimate parameter maps in a two-step pipeline that first reconstructs images from undersampled k-space data and then performs model fitting…