Literature DB >> 16841304

Development of a functional magnetic resonance imaging simulator for modeling realistic rigid-body motion artifacts.

Ivana Drobnjak1, David Gavaghan, Endre Süli, Joe Pitt-Francis, Mark Jenkinson.   

Abstract

Functional magnetic resonance imaging (FMRI) is a noninvasive method of imaging brain function in vivo. However, images produced in FMRI experiments are imperfect and contain several artifacts that contaminate the data. These artifacts include rigid-body motion effects, B0-field inhomogeneities, chemical shift, and eddy currents. To investigate these artifacts, with the eventual aim of minimizing or removing them completely, a computational model of the FMR image acquisition process was built that can simulate all of the above-mentioned artifacts. This paper gives an overview of the development of the FMRI simulator. The simulator uses the Bloch equations together with a geometric definition of the object (brain) and a varying T2* model for the BOLD activations. Furthermore, it simulates rigid-body motion of the object by solving Bloch equations for given motion parameters that are defined for an object moving continuously in time, including during the read-out period, which is a novel approach in the area of MRI computer simulations. With this approach it is possible, in a controlled and precise way, to simulate the full effects of various rigid-body motion artifacts in FMRI data (e.g. spin-history effects, B0-motion interaction, and within-scan motion blurring) and therefore formulate and test algorithms for their reduction. Copyright 2006 Wiley-Liss, Inc.

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Year:  2006        PMID: 16841304     DOI: 10.1002/mrm.20939

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  20 in total

1.  Computer-generated fMRI phantoms with motion-distortion interaction.

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2.  Transients may occur in functional magnetic resonance imaging without physiological basis.

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4.  A Web-Based Educational Magnetic Resonance Simulator: Design, Implementation and Testing.

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Journal:  J Med Syst       Date:  2019-12-02       Impact factor: 4.460

5.  An empirical investigation of motion effects in eMRI of interictal epileptiform spikes.

Authors:  Padmavathi Sundaram; Robert V Mulkern; William M Wells; Christina Triantafyllou; Tobias Loddenkemper; Ellen J Bubrick; Darren B Orbach
Journal:  Magn Reson Imaging       Date:  2011-05-08       Impact factor: 2.546

6.  Prospective active marker motion correction improves statistical power in BOLD fMRI.

Authors:  Jordan Muraskin; Melvyn B Ooi; Robin I Goldman; Sascha Krueger; William J Thomas; Paul Sajda; Truman R Brown
Journal:  Neuroimage       Date:  2012-12-05       Impact factor: 6.556

7.  SimPACE: generating simulated motion corrupted BOLD data with synthetic-navigated acquisition for the development and evaluation of SLOMOCO: a new, highly effective slicewise motion correction.

Authors:  Erik B Beall; Mark J Lowe
Journal:  Neuroimage       Date:  2014-06-24       Impact factor: 6.556

8.  Bootstrap generation and evaluation of an fMRI simulation database.

Authors:  Pierre Bellec; Vincent Perlbarg; Alan C Evans
Journal:  Magn Reson Imaging       Date:  2009-06-30       Impact factor: 2.546

9.  Accurate and robust brain image alignment using boundary-based registration.

Authors:  Douglas N Greve; Bruce Fischl
Journal:  Neuroimage       Date:  2009-06-30       Impact factor: 6.556

10.  SimTB, a simulation toolbox for fMRI data under a model of spatiotemporal separability.

Authors:  Erik B Erhardt; Elena A Allen; Yonghua Wei; Tom Eichele; Vince D Calhoun
Journal:  Neuroimage       Date:  2011-12-08       Impact factor: 6.556

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