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

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

A mind-brain-body dataset of MRI, EEG, cognition, emotion, and peripheral physiology in young and old adults

A Babayan, M Erbey, D Kumral, JD Reinelt, AMF Reiter… - Scientific data, 2019 - nature.com
We present a publicly available dataset of 227 healthy participants comprising a young (N=
153, 25.1±3.1 years, range 20–35 years, 45 female) and an elderly group (N= 74, 67.6±4.7 …

Higher-order total variation approaches and generalisations

K Bredies, M Holler - Inverse Problems, 2020 - iopscience.iop.org
Over the last decades, the total variation (TV) has evolved to be one of the most broadly-
used regularisation functionals for inverse problems, in particular for imaging applications …

Quantitative susceptibility mapping using deep neural network: QSMnet

J Yoon, E Gong, I Chatnuntawech, B Bilgic, J Lee… - Neuroimage, 2018 - Elsevier
Deep neural networks have demonstrated promising potential for the field of medical image
reconstruction, successfully generating high quality images for CT, PET and MRI. In this …

Quantitative susceptibility mapping: report from the 2016 reconstruction challenge

C Langkammer, F Schweser, K Shmueli… - Magnetic resonance …, 2018 - Wiley Online Library
Purpose The aim of the 2016 quantitative susceptibility mapping (QSM) reconstruction
challenge was to test the ability of various QSM algorithms to recover the underlying …

DeepQSM-using deep learning to solve the dipole inversion for quantitative susceptibility mapping

S Bollmann, KGB Rasmussen, M Kristensen… - Neuroimage, 2019 - Elsevier
Quantitative susceptibility mapping (QSM) is based on magnetic resonance imaging (MRI)
phase measurements and has gained broad interest because it yields relevant information …

[HTML][HTML] SEPIA—Susceptibility mapping pipeline tool for phase images

KS Chan, JP Marques - Neuroimage, 2021 - Elsevier
Quantitative susceptibility mapping (QSM) is a physics-driven computational technique that
has a high sensitivity in quantifying iron deposition based on MRI phase images …

[HTML][HTML] A robust multi-scale approach to quantitative susceptibility mapping

J Acosta-Cabronero, C Milovic, H Mattern, C Tejos… - Neuroimage, 2018 - Elsevier
Abstract Quantitative Susceptibility Mapping (QSM), best known as a surrogate for tissue
iron content, is becoming a highly relevant MRI contrast for monitoring cellular and vascular …

Nonlinear dipole inversion (NDI) enables robust quantitative susceptibility mapping (QSM)

D Polak, I Chatnuntawech, J Yoon, SS Iyer… - NMR in …, 2020 - Wiley Online Library
High‐quality Quantitative Susceptibility Mapping (QSM) with Nonlinear Dipole Inversion
(NDI) is developed with pre‐determined regularization while matching the image quality of …

Learning-based single-step quantitative susceptibility mapping reconstruction without brain extraction

H Wei, S Cao, Y Zhang, X Guan, F Yan, KW Yeom… - NeuroImage, 2019 - Elsevier
Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic
susceptibility from MRI gradient-echo phase signal and typically requires several processing …