Motion artifacts in MRI: A complex problem with many partial solutions

M Zaitsev, J Maclaren, M Herbst - Journal of Magnetic …, 2015 - Wiley Online Library
Subject motion during magnetic resonance imaging (MRI) has been problematic since its
introduction as a clinical imaging modality. While sensitivity to particle motion or blood flow …

[HTML][HTML] What's new and what's next in diffusion MRI preprocessing

CMW Tax, M Bastiani, J Veraart, E Garyfallidis… - NeuroImage, 2022 - Elsevier
Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure
and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the …

[HTML][HTML] An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging

JLR Andersson, SN Sotiropoulos - Neuroimage, 2016 - Elsevier
In this paper we describe a method for retrospective estimation and correction of eddy
current (EC)-induced distortions and subject movement in diffusion imaging. In addition a …

Deep learning for undersampled MRI reconstruction

CM Hyun, HP Kim, SM Lee, S Lee… - Physics in Medicine & …, 2018 - iopscience.iop.org
This paper presents a deep learning method for faster magnetic resonance imaging (MRI)
by reducing k-space data with sub-Nyquist sampling strategies and provides a rationale for …

[BOOK][B] Fundamentals of computerized tomography: image reconstruction from projections

GT Herman - 2009 - books.google.com
This revised and updated second edition–now with two new chapters-is the only book to
give a comprehensive overview of computer algorithms for image reconstruction. It covers …

Recurrent variational network: a deep learning inverse problem solver applied to the task of accelerated MRI reconstruction

G Yiasemis, JJ Sonke, C Sánchez… - Proceedings of the …, 2022 - openaccess.thecvf.com
Abstract Magnetic Resonance Imaging can produce detailed images of the anatomy and
physiology of the human body that can assist doctors in diagnosing and treating pathologies …

Calibrationless parallel imaging reconstruction based on structured low‐rank matrix completion

PJ Shin, PEZ Larson, MA Ohliger… - Magnetic resonance …, 2014 - Wiley Online Library
Purpose A calibrationless parallel imaging reconstruction method, termed simultaneous
autocalibrating and k‐space estimation (SAKE), is presented. It is a data‐driven, coil‐by‐coil …

A survey on the magnetic resonance image denoising methods

J Mohan, V Krishnaveni, Y Guo - Biomedical signal processing and control, 2014 - Elsevier
Over the past several years, although the resolution, signal-to-noise ratio and acquisition
speed of magnetic resonance imaging (MRI) technology have been increased, MR images …

Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI

DK Jones, DC Alexander, R Bowtell, M Cercignani… - NeuroImage, 2018 - Elsevier
The key component of a microstructural diffusion MRI 'super-scanner'is a dedicated high-
strength gradient system that enables stronger diffusion weightings per unit time compared …

B-spline parameterized joint optimization of reconstruction and k-space trajectories (bjork) for accelerated 2d mri

G Wang, T Luo, JF Nielsen, DC Noll… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Optimizing k-space sampling trajectories is a promising yet challenging topic for fast
magnetic resonance imaging (MRI). This work proposes to optimize a reconstruction method …