Literature DB >> 8316069

MRI simulation using the k-space formalism.

J S Petersson1, J O Christoffersson, K Golman.   

Abstract

An MRI simulation method, together with a corresponding computer program, using the k-space formalism has been developed. It uses a FFT algorithm to generate the ideal NMR signal from a user defined object. The k-space trajectory given by a pulse sequence is calculated. And it is used to select elements from the ideal NMR signal. This selection of elements mimic the sampling of the signal in an actual MRI experiment. During the sampling procedure changes in signal amplitude due to relaxation and excitation are introduced as well as signal phase changes due to movement or flow. Artifacts due to stimulated echoes and transversal magnetization that propagate through several repetition periods are also handled. The usefulness of the method is demonstrated by calculations using standard spin-echo sequence as well as modifications introduced in order to generate angiographical images and flow phase images. Further more a fast pulse sequence, echo planar imaging (EPI), is also simulated. The method is faster than previously presented ones. It is capable of generating images (128 x 128 matrix), including more than eight different T1 and T2 combinations, in less than 3 min on a standard 386/387 type IBM compatible PC.

Mesh:

Year:  1993        PMID: 8316069     DOI: 10.1016/0730-725x(93)90475-s

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  7 in total

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

Authors:  Ning Xu; J Michael Fitzpatrick; Yong Li; Benoit M Dawant; David R Pickens; Victoria L Morgan
Journal:  Magn Reson Imaging       Date:  2007-06-21       Impact factor: 2.546

2.  Distributed large-scale simulation of magnetic resonance imaging.

Authors:  A R Brenner; J Kürsch; T G Noll
Journal:  MAGMA       Date:  1997-06       Impact factor: 2.310

3.  A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN).

Authors:  Christopher W Roy; Tom Hilbert; Tobias Kober; Matthias Stuber; Hélène Lajous; Priscille de Dumast; Sébastien Tourbier; Yasser Alemán-Gómez; Jérôme Yerly; Thomas Yu; Hamza Kebiri; Kelly Payette; Jean-Baptiste Ledoux; Reto Meuli; Patric Hagmann; Andras Jakab; Vincent Dunet; Mériam Koob; Meritxell Bach Cuadra
Journal:  Sci Rep       Date:  2022-05-23       Impact factor: 4.996

4.  Simulation of High-Resolution Magnetic Resonance Images on the IBM Blue Gene/L Supercomputer Using SIMRI.

Authors:  K G Baum; G Menezes; M Helguera
Journal:  Int J Biomed Imaging       Date:  2011-04-10

5.  Computer simulation of magnetic resonance angiography imaging: model description and validation.

Authors:  Artur Klepaczko; Piotr Szczypiński; Grzegorz Dwojakowski; Michał Strzelecki; Andrzej Materka
Journal:  PLoS One       Date:  2014-04-16       Impact factor: 3.240

6.  High performance MRI simulations of motion on multi-GPU systems.

Authors:  Christos G Xanthis; Ioannis E Venetis; Anthony H Aletras
Journal:  J Cardiovasc Magn Reson       Date:  2014-07-04       Impact factor: 5.364

7.  Parallel simulations for QUAntifying RElaxation magnetic resonance constants (SQUAREMR): an example towards accurate MOLLI T1 measurements.

Authors:  Christos G Xanthis; Sebastian Bidhult; George Kantasis; Einar Heiberg; Håkan Arheden; Anthony H Aletras
Journal:  J Cardiovasc Magn Reson       Date:  2015-11-26       Impact factor: 5.364

  7 in total

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