MR Engineering

P-ME-02 2023_FA-029

Assessment of Image Quality in Virtual Fat-Suppressed T2-Weighted Images Generated by Pix2pix Architecture with Varying Training Data Volume

Teresa Ichiki / Gunma Prefectural College of Health Sciences(Japan)

Corresponding author : Teresa Ichiki / r202006@gchs.ac.jp

P-ME-03 2023_KA-042

Reproducibility issue in network training of deep learning MR reconstruction

Chungseok Oh / Seoul National University(Korea)

Corresponding author : Jongho Lee / jonghoyi@snu.ac.kr

P-ME-04 2023_KA-047

Simultaneous multislice pulse optimization using DeepRF

Jiye Kim / Seoul National University(Korea)

Corresponding author : Jongho Lee / jonghoyi@snu.ac.kr

P-ME-05 2023_FA-036

Phantom dedicated for Quantitative Susceptibility Mapping of MRI

Moeno Koma / Gunma Prefectural Collage of Health Sciences(Japan)

Corresponding author : Moeno Koma / r202013@gchs.ac.jp

P-ME-06 2023_KA-142

A comparative study of T2-weighted and susceptibility-weighted imaging for brain damages in a photothrombotic ischemic stroke animal model

Sung Suk Oh / Daegu-Gyeongbuk Medical Innovation Foundation (K-MEDI hub)(Korea)

Corresponding author : Jong-Ryul Choi / jongryul32@kmedihub.re.kr