AI-based reconstruction for fast MRI—A systematic review and meta-analysis

Y Chen, CB Schönlieb, P Liò, T Leiner… - Proceedings of the …, 2022 - ieeexplore.ieee.org
Compressed sensing (CS) has been playing a key role in accelerating the magnetic
resonance imaging (MRI) acquisition process. With the resurgence of artificial intelligence …

Deep learning for fast MR imaging: A review for learning reconstruction from incomplete k-space data

S Wang, T ** pipeline tool for phase images
KS Chan, JP Marques - bioRxiv, 2020 - biorxiv.org
Quantitative susceptibility map** (QSM) is a physics-driven computational technique that
has a high sensitivity in quantifying iron deposition based on MRI phase images …

A review and experimental evaluation of deep learning methods for MRI reconstruction

A Pal, Y Rathi - The journal of machine learning for biomedical …, 2022 - pmc.ncbi.nlm.nih.gov
Following the success of deep learning in a wide range of applications, neural network-
based machine-learning techniques have received significant interest for accelerating …

Overview of quantitative susceptibility map** using deep learning: Current status, challenges and opportunities

W Jung, S Bollmann, J Lee - NMR in Biomedicine, 2022 - Wiley Online Library
Quantitative susceptibility map** (QSM) has gained broad interest in the field by extracting
bulk tissue magnetic susceptibility, predominantly determined by myelin, iron and calcium …

QSM reconstruction challenge 2.0: design and report of results

QSM Challenge 2.0 Organization … - Magnetic …, 2021 - Wiley Online Library
Purpose The aim of the second quantitative susceptibility map** (QSM) reconstruction
challenge (Oct 2019, Seoul, Korea) was to test the accuracy of QSM dipole inversion …

[HTML][HTML] Exploring linearity of deep neural network trained QSM: QSMnet+

W Jung, J Yoon, S Ji, JY Choi, JM Kim, Y Nam, EY Kim… - Neuroimage, 2020 - Elsevier
Recently, deep neural network-powered quantitative susceptibility map** (QSM), QSMnet,
successfully performed ill-conditioned dipole inversion in QSM and generated high-quality …