Literature DB >> 16119241

Automated correction of spin-history related motion artefacts in fMRI: simulated and phantom data.

Lucian Muresan1, Remco Renken, Jos B T M Roerdink, Hendrikus Duifhuis.   

Abstract

This paper concerns the problem of correcting spin-history artefacts in fMRI data. We focus on the influence of through-plane motion on the history of magnetization. A change in object position will disrupt the tissue's steady-state magnetization. The disruption will propagate to the next few acquired volumes until a new steady state is reached. In this paper we present a simulation of spin-history effects, experimental data, and an automatic two-step algorithm for detecting and correcting spin-history artefacts. The algorithm determines the steady-state distribution of all voxels in a given slice and indicates which voxels need a spin-history correction. The spin-history correction is meant to be applied before standard realignment procedures. To obtain experimental data a special phantom and an MRI compatible motion system were designed. The effect of motion on spin-history is presented for data obtained using this phantom inside a 1.5-T MRI scanner. We show that the presented algorithm is capable of detecting the occurrence of a displacement, and it determines which voxels need a spin-history correction. The results of the phantom study show good agreement with the simulations.

Mesh:

Year:  2005        PMID: 16119241     DOI: 10.1109/TBME.2005.851484

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  17 in total

1.  Comparison of fMRI statistical software packages and strategies for analysis of images containing random and stimulus-correlated motion.

Authors:  Victoria L Morgan; Benoit M Dawant; Yong Li; David R Pickens
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2.  Transients may occur in functional magnetic resonance imaging without physiological basis.

Authors:  Ville Renvall; Riitta Hari
Journal:  Proc Natl Acad Sci U S A       Date:  2009-11-16       Impact factor: 11.205

Review 3.  Noise and non-neuronal contributions to the BOLD signal: applications to and insights from animal studies.

Authors:  Shella D Keilholz; Wen-Ju Pan; Jacob Billings; Maysam Nezafati; Sadia Shakil
Journal:  Neuroimage       Date:  2016-12-22       Impact factor: 6.556

4.  Minimizing noise in pediatric task-based functional MRI; Adolescents with developmental disabilities and typical development.

Authors:  Catherine Fassbender; Prerona Mukherjee; Julie B Schweitzer
Journal:  Neuroimage       Date:  2017-01-24       Impact factor: 6.556

Review 5.  Prospective motion correction in functional MRI.

Authors:  Maxim Zaitsev; Burak Akin; Pierre LeVan; Benjamin R Knowles
Journal:  Neuroimage       Date:  2016-11-11       Impact factor: 6.556

6.  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

7.  Development of 2dTCA for the detection of irregular, transient BOLD activity.

Authors:  Victoria L Morgan; Yong Li; Bassel Abou-Khalil; John C Gore
Journal:  Hum Brain Mapp       Date:  2008-01       Impact factor: 5.038

8.  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

Review 9.  Methods for cleaning the BOLD fMRI signal.

Authors:  César Caballero-Gaudes; Richard C Reynolds
Journal:  Neuroimage       Date:  2016-12-09       Impact factor: 6.556

Review 10.  Resting-state fMRI confounds and cleanup.

Authors:  Kevin Murphy; Rasmus M Birn; Peter A Bandettini
Journal:  Neuroimage       Date:  2013-04-06       Impact factor: 6.556

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