Literature DB >> 6530920

A computer algorithm for the simulation of any nuclear magnetic resonance (NMR) imaging method.

J Bittoun, J Taquin, M Sauzade.   

Abstract

More than a dozen Nuclear Magnetic Resonance (NMR) imaging methods have been described using different radio-frequency pulse sequences, magnetic field gradient variations, and data processing. In order to have a theoretical understanding in the most general case, we have conceived a computer program for the simulation of NMR imaging techniques. The algorithm uses the solution of the Bloch equations at each point of a simulated object. The direction of every elementary magnetic moment is computed at each instant, and stored in an array giving the global signal to be processed, whatever the pulse and gradient sequence. To test the validity of this program, we have simulated some well-known experimental results. Some applications are presented which contribute to the understanding of image distortions and to techniques such as selective radio-frequency pulse or oscillating gradients. This program can be used to unravel physical and technological causes of image distortions, to have a "microscopic" look at any parameter of an experiment, and to study the contrast given by various NMR imaging techniques as a function of the three NMR parameters, i.e., the hydrogen nuclei density rho and the relaxation times T1 and T2.

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Year:  1984        PMID: 6530920     DOI: 10.1016/0730-725x(84)90065-1

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


  10 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.  Signal decay due to susceptibility-induced intravoxel dephasing on multiple air-filled cylinders: MRI simulations and experiments.

Authors:  François De Guio; Hugues Benoit-Cattin; Armel Davenel
Journal:  MAGMA       Date:  2008-06-25       Impact factor: 2.310

3.  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

4.  Measuring T₂ and T₁, and imaging T₂ without spin echoes.

Authors:  G Wang; A M El-Sharkawy; W A Edelstein; M Schär; P A Bottomley
Journal:  J Magn Reson       Date:  2011-12-07       Impact factor: 2.229

5.  Minimum acquisition methods for simultaneously imaging T(1), T(2), and proton density with B(1) correction and no spin-echoes.

Authors:  Guan Wang; AbdEl-Monem M El-Sharkawy; Paul A Bottomley
Journal:  J Magn Reson       Date:  2014-03-01       Impact factor: 2.229

6.  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

7.  Magnetic resonance parameter mapping using model-guided self-supervised deep learning.

Authors:  Fang Liu; Richard Kijowski; Georges El Fakhri; Li Feng
Journal:  Magn Reson Med       Date:  2021-01-19       Impact factor: 3.737

8.  Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model.

Authors:  Fang Liu; Julia V Velikina; Walter F Block; Richard Kijowski; Alexey A Samsonov
Journal:  IEEE Trans Med Imaging       Date:  2016-10-25       Impact factor: 10.048

Review 9.  Virtual clinical trials in medical imaging: a review.

Authors:  Ehsan Abadi; William P Segars; Benjamin M W Tsui; Paul E Kinahan; Nick Bottenus; Alejandro F Frangi; Andrew Maidment; Joseph Lo; Ehsan Samei
Journal:  J Med Imaging (Bellingham)       Date:  2020-04-11

10.  Numerical simulation of time-resolved 3D phase-contrast magnetic resonance imaging.

Authors:  Thomas Puiseux; Anou Sewonu; Ramiro Moreno; Simon Mendez; Franck Nicoud
Journal:  PLoS One       Date:  2021-03-26       Impact factor: 3.240

  10 in total

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