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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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Journal ArticleDOI

Rapid automated liver quantitative susceptibility mapping.

TL;DR: This work investigates the feasibility of automated quantitative susceptibility mapping (QSM) to measure the liver iron concentration (LIC) and finds it feasible to guide iron‐chelating therapy for patients with transfusional iron overload.
Posted ContentDOI

QSM Reconstruction Challenge 2.0–Part 1: A Realistic in silico Head Phantom for MRI data simulation and evaluation of susceptibility mapping procedures

TL;DR: A whole-head tissue property model is created by segmenting and post-processing high-resolution, multi-parametric MRI data acquired from a healthy volunteer to create a realistic in-silico head phantom for the second QSM Reconstruction Challenge and for future evaluations of processing algorithms for Quantitative Susceptibility Mapping.
Journal ArticleDOI

Phase unwrapping with graph cuts optimization and dual decomposition acceleration for 3D high-resolution MRI data.

TL;DR: Dual decomposition acceleration is introduced to speed up a three‐dimensional graph cut–based phase unwrapping algorithm.
Journal ArticleDOI

MRI tools for assessment of microstructure and nephron function of the kidney

TL;DR: This study reviews the novel tools to examine kidney microstructure and local function and demonstrates the application of these methods in renal pathophysiology.
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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