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Related Concept Videos

Planar Rigid-Body Motion01:22

Planar Rigid-Body Motion

Understanding the movement of a rigid body in planar motion involves recognizing that every particle within this body is traversing a path that maintains a consistent distance from a specific plane. This concept is fundamental in the study of physics and mechanical engineering, and it allows us to comprehend better how objects move in space.
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Motion Of A Charged Particle In A Magnetic Field01:22

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Related Experiment Video

Updated: May 21, 2026

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

Phase informed model for motion and susceptibility.

Chloe Hutton1, Jesper Andersson, Ralf Deichmann

  • 1Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, United Kingdom.

Human Brain Mapping
|June 28, 2012
PubMed
Summary
This summary is machine-generated.

A new method, phase informed model for motion and susceptibility (PIMMS), corrects geometric distortions in echo-planar imaging (EPI) caused by head motion. PIMMS improves functional MRI (fMRI) data quality by reducing motion-related artifacts and false negatives.

Keywords:
EPIdistortion correctiondynamic field mappinghead motionphase imagesusceptibility artifact

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Area of Science:

  • Neuroimaging
  • Magnetic Resonance Imaging (MRI)
  • Biophysics

Background:

  • Magnetic susceptibility variations in the head cause geometric distortions in echo-planar images (EPI), primarily affecting the phase-encode direction.
  • These distortions are influenced by head orientation in the magnetic field and change with head movement during MRI scans.
  • Existing methods like rigid body realignment may not fully address motion-induced susceptibility artifacts in functional MRI (fMRI).

Purpose of the Study:

  • To introduce and validate a novel method, the phase informed model for motion and susceptibility (PIMMS), for estimating and correcting geometric distortions related to head motion in EPI.
  • To demonstrate the efficacy of PIMMS in improving the quality of fMRI data acquired at 3T.
  • To compare the performance of PIMMS against conventional rigid body realignment techniques.

Main Methods:

  • Developed a phase informed model for motion and susceptibility (PIMMS) that models head motion parameters and scanner hardware characteristics.
  • Fitted the PIMMS model to EPI phase time series data.
  • Utilized the model fit parameters to generate maps for correcting susceptibility artifacts in magnitude images.

Main Results:

  • PIMMS effectively estimates changes in geometric distortion associated with head motion.
  • Compared to conventional rigid body realignment, PIMMS removes residual variance linked to motion-related distortion effects in EPI-based fMRI.
  • PIMMS demonstrated a reduction in false negatives compared to standard realignment methods that include motion parameters in statistical models.

Conclusions:

  • The PIMMS method offers a robust approach to correct for susceptibility-induced geometric distortions in EPI data.
  • PIMMS enhances the accuracy and reliability of fMRI analyses by mitigating motion-related artifacts.
  • This technique is compatible with standard EPI sequences providing accurate phase information.