10,162 research outputs found
Correction of artifacts in diffusion-weighted MR images
V semestrálnom projekte je popísaný princíp nukleárnej magnetickej rezonancie, ďalej je rozobraná difúzia v NMR a metódy jej merania. Ďalšia časť rozoberá vznik a korekciu artefaktov v NMR a v poslednej časti je urobený experiment filtrácie rôzne skreslených obrazov artefaktami.The semester project is described by nuclear magnetic resonance, is discussed further in diffusion MRI and its method of measurement. The next section discusses the creation and correction of artifacts in MRI, and in the last part of the experiment made ??various filtering image distortion artifacts.
Accelerated Cardiac Diffusion Tensor Imaging Using Joint Low-Rank and Sparsity Constraints
Objective: The purpose of this manuscript is to accelerate cardiac diffusion
tensor imaging (CDTI) by integrating low-rankness and compressed sensing.
Methods: Diffusion-weighted images exhibit both transform sparsity and
low-rankness. These properties can jointly be exploited to accelerate CDTI,
especially when a phase map is applied to correct for the phase inconsistency
across diffusion directions, thereby enhancing low-rankness. The proposed
method is evaluated both ex vivo and in vivo, and is compared to methods using
either a low-rank or sparsity constraint alone. Results: Compared to using a
low-rank or sparsity constraint alone, the proposed method preserves more
accurate helix angle features, the transmural continuum across the myocardium
wall, and mean diffusivity at higher acceleration, while yielding significantly
lower bias and higher intraclass correlation coefficient. Conclusion:
Low-rankness and compressed sensing together facilitate acceleration for both
ex vivo and in vivo CDTI, improving reconstruction accuracy compared to
employing either constraint alone. Significance: Compared to previous methods
for accelerating CDTI, the proposed method has the potential to reach higher
acceleration while preserving myofiber architecture features which may allow
more spatial coverage, higher spatial resolution and shorter temporal footprint
in the future.Comment: 11 pages, 16 figures, published on IEEE Transactions on Biomedical
Engineerin
Diffusion Imaging in the Rat Cervical Spinal Cord
Magnetic resonance imaging (MRI) is the state of the art approach for assessing the status of the spinal cord noninvasively, and can be used as a diagnostic and prognostic tool in cases of disease or injury. Diffusion weighted imaging (DWI), is sensitive to the thermal motion of water molecules and allows for inferences of tissue microstructure. This report describes a protocol to acquire and analyze DWI of the rat cervical spinal cord on a small-bore animal system. It demonstrates an imaging setup for the live anesthetized animal and recommends a DWI acquisition protocol for high-quality imaging, which includes stabilization of the cord and control of respiratory motion. Measurements with diffusion weighting along different directions and magnitudes (b-values) are used. Finally, several mathematical models of the resulting signal are used to derive maps of the diffusion processes within the spinal cord tissue that provide insight into the normal cord and can be used to monitor injury or disease processes noninvasively.
The video component of this article can be found at http://www.jove.com/video/52390/ Introduction Magneti
Deep learning-based parameter mapping for joint relaxation and diffusion tensor MR Fingerprinting
Magnetic Resonance Fingerprinting (MRF) enables the simultaneous
quantification of multiple properties of biological tissues. It relies on a
pseudo-random acquisition and the matching of acquired signal evolutions to a
precomputed dictionary. However, the dictionary is not scalable to
higher-parametric spaces, limiting MRF to the simultaneous mapping of only a
small number of parameters (proton density, T1 and T2 in general). Inspired by
diffusion-weighted SSFP imaging, we present a proof-of-concept of a novel MRF
sequence with embedded diffusion-encoding gradients along all three axes to
efficiently encode orientational diffusion and T1 and T2 relaxation. We take
advantage of a convolutional neural network (CNN) to reconstruct multiple
quantitative maps from this single, highly undersampled acquisition. We bypass
expensive dictionary matching by learning the implicit physical relationships
between the spatiotemporal MRF data and the T1, T2 and diffusion tensor
parameters. The predicted parameter maps and the derived scalar diffusion
metrics agree well with state-of-the-art reference protocols. Orientational
diffusion information is captured as seen from the estimated primary diffusion
directions. In addition to this, the joint acquisition and reconstruction
framework proves capable of preserving tissue abnormalities in multiple
sclerosis lesions
The effect of realistic geometries on the susceptibility-weighted MR signal in white matter
Purpose: To investigate the effect of realistic microstructural geometry on
the susceptibility-weighted magnetic resonance (MR) signal in white matter
(WM), with application to demyelination.
Methods: Previous work has modeled susceptibility-weighted signals under the
assumption that axons are cylindrical. In this work, we explore the
implications of this assumption by considering the effect of more realistic
geometries. A three-compartment WM model incorporating relevant properties
based on literature was used to predict the MR signal. Myelinated axons were
modeled with several cross-sectional geometries of increasing realism: nested
circles, warped/elliptical circles and measured axonal geometries from electron
micrographs. Signal simulations from the different microstructural geometries
were compared to measured signals from a Cuprizone mouse model with varying
degrees of demyelination.
Results: Results from simulation suggest that axonal geometry affects the MR
signal. Predictions with realistic models were significantly different compared
to circular models under the same microstructural tissue properties, for
simulations with and without diffusion.
Conclusion: The geometry of axons affects the MR signal significantly.
Literature estimates of myelin susceptibility, which are based on fitting
biophysical models to the MR signal, are likely to be biased by the assumed
geometry, as will any derived microstructural properties.Comment: Accepted March 4 2017, in publication at Magnetic Resonance in
Medicin
Feasibility of diffusion and probabilistic white matter analysis in patients implanted with a deep brain stimulator.
Deep brain stimulation (DBS) for Parkinson\u27s disease (PD) is an established advanced therapy that produces therapeutic effects through high frequency stimulation. Although this therapeutic option leads to improved clinical outcomes, the mechanisms of the underlying efficacy of this treatment are not well understood. Therefore, investigation of DBS and its postoperative effects on brain architecture is of great interest. Diffusion weighted imaging (DWI) is an advanced imaging technique, which has the ability to estimate the structure of white matter fibers; however, clinical application of DWI after DBS implantation is challenging due to the strong susceptibility artifacts caused by implanted devices. This study aims to evaluate the feasibility of generating meaningful white matter reconstructions after DBS implantation; and to subsequently quantify the degree to which these tracts are affected by post-operative device-related artifacts. DWI was safely performed before and after implanting electrodes for DBS in 9 PD patients. Differences within each subject between pre- and post-implantation FA, MD, and RD values for 123 regions of interest (ROIs) were calculated. While differences were noted globally, they were larger in regions directly affected by the artifact. White matter tracts were generated from each ROI with probabilistic tractography, revealing significant differences in the reconstruction of several white matter structures after DBS. Tracts pertinent to PD, such as regions of the substantia nigra and nigrostriatal tracts, were largely unaffected. The aim of this study was to demonstrate the feasibility and clinical applicability of acquiring and processing DWI post-operatively in PD patients after DBS implantation. The presence of global differences provides an impetus for acquiring DWI shortly after implantation to establish a new baseline against which longitudinal changes in brain connectivity in DBS patients can be compared. Understanding that post-operative fiber tracking in patients is feasible on a clinically-relevant scale has significant implications for increasing our current understanding of the pathophysiology of movement disorders, and may provide insights into better defining the pathophysiology and therapeutic effects of DBS
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