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Nonlinear formulation of the magnetic field to source relationship for robust quantitative susceptibility mapping.

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TLDR
This nonlinear QSM method reduced salt and pepper noise or checkerboard pattern in high susceptibility regions in healthy subjects and markedly reduced artifacts in patients with intracerebral hemorrhages.
Abstract
Quantitative susceptibility mapping (QSM) opens the door for measuring tissue magnetic susceptibility properties that may be important biomarkers, and QSM is becoming an increasingly active area of scientific and clinical investigations. In practical applications, there are sources of errors for QSM including noise, phase unwrapping failures, and signal model inaccuracy. To improve the robustness of QSM quality, we propose a nonlinear data fidelity term for frequency map estimation and dipole inversion to reduce noise and effects of phase unwrapping failures, and a method for model error reduction through iterative tuning. Compared with the previous phase based linear QSM method, this nonlinear QSM method reduced salt and pepper noise or checkerboard pattern in high susceptibility regions in healthy subjects and markedly reduced artifacts in patients with intracerebral hemorrhages.

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Investigating the oxygenation of brain arteriovenous malformations using quantitative susceptibility mapping.

TL;DR: This is the first study to show, non-invasively, that AVM draining veins have a significantly larger SvO2 than healthy veins, which is a finding congruent with arteriovenous shunting.
Journal ArticleDOI

The choice of embedding media affects image quality, tissue R(2)*, and susceptibility behaviors in post‐mortem brain MR microscopy at 7.0T

TL;DR: The quality and precision of post‐mortem MRI microscopy may vary depending on the embedding medium used, and the impact of widely used media on image quality, contrast of high spatial resolution gradient‐echo, and effective transverse relaxation rate are evaluated.
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Background field removal technique using regularization enabled sophisticated harmonic artifact reduction for phase data with varying kernel sizes.

TL;DR: The proposed REV-SHARP is a new method combined with variable spherical kernel size and Tikhonov regularization that might make it possible to be more accurate backgroud field removal and help to achive better accuracy of QSM.
Journal ArticleDOI

Changes in brain iron concentration after exposure to high-altitude hypoxia measured by quantitative susceptibility mapping

TL;DR: The magnetic susceptibility value can serve as a quantitative marker of brain iron, and variations of regional susceptibility reported herein indicate that HA hypoxia can result in significant iron deposition in most deep gray matter regions.
Journal ArticleDOI

Multi-centre, multi-vendor reproducibility of 7T QSM and R2* in the human brain: results from the UK7T study

TL;DR: The harmonized UK7T protocol and pipeline delivers on average a 3-fold improvement in the coefficient of reproducibility for QSM and R2* at 7T compared to previous reports of multi-site reproducible at 3T, suggesting that it is reasonable to pool data across sites using the harmonised protocol.
References
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Book

Classical Electrodynamics

Journal ArticleDOI

Fast robust automated brain extraction

TL;DR: An automated method for segmenting magnetic resonance head images into brain and non‐brain has been developed and described and examples of results and the results of extensive quantitative testing against “gold‐standard” hand segmentations, and two other popular automated methods.
Book

Numerical Methods for Least Squares Problems

Åke Björck
TL;DR: Theorems and statistical properties of least squares solutions are explained and basic numerical methods for solving least squares problems are described.
Journal ArticleDOI

The rician distribution of noisy mri data

TL;DR: The image intensity in magnetic resonance magnitude images in the presence of noise is shown to be governed by a Rician distribution and low signal intensities (SNR < 2) are therefore biased due to the noise.
Journal ArticleDOI

Satellite radar interferometry: Two-dimensional phase unwrapping

TL;DR: In this paper, an approach to 'unwrapping' the 2 pi ambiguities in the two-dimensional data set is presented, where it is found that noise and geometrical radar layover corrupt measurements locally, and these local errors can propagate to form global phase errors that affect the entire image.
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