Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Search for Gluino-Mediated Bottom Squark Production in pp[over ] Collisions at sqrt[s]=1.96 TeV.

Physical review letters·2009
Same author

Search for exclusive Z-boson production and observation of high-mass pp[over ]-->pgammagammap[over ]-->pl;{+}l;{-}p[over ] events in pp[over ] collisions at sqrt[s]=1.96 TeV.

Physical review letters·2009
Same author

First measurement of the tt[over ] differential cross section dsigma/dM_{tt[over ]} in pp[over ] collisions at sqrt[s]=1.96 TeV.

Physical review letters·2009
Same author

Genotoxicity of silver nanoparticles in Allium cepa.

The Science of the total environment·2009
Same author

Search for top-quark production via flavor-changing neutral currents in W+1 jet events at CDF.

Physical review letters·2009
Same author

Measurement of the top-quark mass with dilepton events selected using neuroevolution at CDF.

Physical review letters·2009

Related Experiment Video

Updated: Mar 21, 2026

Profiling Maternal Behavior Responses During Whole-Brain Imaging
07:12

Profiling Maternal Behavior Responses During Whole-Brain Imaging

Published on: January 24, 2025

1.5K

Improved frame-based estimation of head motion in PET brain imaging.

J M Mukherjee1, C Lindsay1, A Mukherjee2

  • 1Department of Radiology, University of Massachusetts Medical School, Worcester, Massachusetts 01655.

Medical Physics
|May 6, 2016
PubMed
Summary

This study presents a new method to accurately estimate and compensate for head motion during PET brain imaging using short 5-second frames. This technique improves image quality and quantitation by reducing intraframe motion artifacts.

More Related Videos

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

43.8K
Author Spotlight: Comparative Imaging of Neural Activity in Awake and Freely Moving States
06:25

Author Spotlight: Comparative Imaging of Neural Activity in Awake and Freely Moving States

Published on: January 19, 2024

1.7K

Related Experiment Videos

Last Updated: Mar 21, 2026

Profiling Maternal Behavior Responses During Whole-Brain Imaging
07:12

Profiling Maternal Behavior Responses During Whole-Brain Imaging

Published on: January 24, 2025

1.5K
Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

43.8K
Author Spotlight: Comparative Imaging of Neural Activity in Awake and Freely Moving States
06:25

Author Spotlight: Comparative Imaging of Neural Activity in Awake and Freely Moving States

Published on: January 19, 2024

1.7K

Area of Science:

  • Medical Imaging
  • Nuclear Medicine
  • Neuroscience

Background:

  • Head motion during Positron Emission Tomography (PET) brain imaging significantly degrades image quality and quantitation.
  • Existing head restraints are unreliable, necessitating advanced motion compensation strategies.
  • Data-driven motion estimation and external tracking are explored as alternatives.

Purpose of the Study:

  • To introduce a novel data-driven motion estimation method for PET brain imaging.
  • To reduce image quality degradation caused by intraframe motion.
  • To improve quantitation in PET brain studies through motion compensation.

Main Methods:

  • PET list mode data divided into 5-second frames, reconstructed without attenuation correction.
  • 3D multiresolution registration algorithm used for interframe motion estimation and compensation.
  • Simulated head motion introduced to PET data to validate the method.

Main Results:

  • The method accurately compensates for gradual and step-like motions with 5-second frames (0.2 mm average spatial accuracy).
  • Complex six-degree-of-freedom motion estimated with 0.3 mm average accuracy.
  • Preprocessing of 5-second images is crucial for successful registration; method is robust to CT-PET timing variations.

Conclusions:

  • Motion can be effectively estimated for short 5-second frames in FDG PET brain imaging.
  • Utilizing non-attenuation corrected frames enhances robustness against motion-induced errors.
  • Longer frame times (60 seconds) lead to significant accuracy degradation (approx. 2 mm).