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 Experiment Video

Updated: Jun 23, 2026

Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities
07:13

Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities

Published on: October 27, 2023

Reducing between scanner differences in multi-center PET studies.

Aniket Joshi1, Robert A Koeppe, Jeffrey A Fessler

  • 1Division of Nuclear Medicine, Department of Radiology, University of Michigan, 3480 Kresge III 0552, Ann Arbor, MI, USA.

Neuroimage
|May 22, 2009
PubMed
Summary
This summary is machine-generated.

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

Identification of patients receiving amyloid-targeting therapies in observational studies using amyloid PET trajectories: Insights from LEADS.

Alzheimer's & dementia (Amsterdam, Netherlands)·2026
Same author

A vendor-neutral functional MRI acquisition protocol for multi-site studies.

Aperture neuro·2026
Same author

Tau topography subtypes account for clinical heterogeneity and longitudinal trajectories in early-onset Alzheimer's disease.

Brain communications·2026
Same author

Kappa opioid receptor availability correlates with depressive symptom burden in chronic migraine: a preliminary investigation.

The journal of headache and pain·2026
Same author

Phantom- and simulation-based validation of combined diffusion relaxometry in ex vivo ADRD white matter.

bioRxiv : the preprint server for biology·2026
Same author

Smooth optimization using global and local low-rank regularizers.

SIAM journal on imaging sciences·2026
Same journal

Spatial frequency channels implement a mental ruler in spatial vision.

NeuroImage·2026
Same journal

Exploring the Link Between Intravoxel Incoherent Motion Measured Brain Diffusivity During Wakefulness and Sleep Macrostructure in the Elderly.

NeuroImage·2026
Same journal

Closed-loop adaptation of transcranial magnetic stimulation intensity with electroencephalography feedback.

NeuroImage·2026
Same journal

Volumetric postmortem MRI of the medial temporal lobe in Alzheimer's disease and related disorders: methodological advances and implications for in vivo biomarker development.

NeuroImage·2026
Same journal

Neural responses to equity and inequity when receiving vicarious rewards for self and charity during adolescence.

NeuroImage·2026
Same journal

Cognitive Strategy-based neuromodulation optimizes neural communication to improve working memory.

NeuroImage·2026
See all related articles

This study developed methods to reduce scanner variability in Alzheimer's Disease Neuroimaging Initiative (ADNI) [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) scans. Phantom data showed significant variability reduction, but clinical data requires further refinement.

Area of Science:

  • Neuroimaging
  • Medical Physics
  • Alzheimer's Disease Research

Background:

  • Alzheimer's Disease Neuroimaging Initiative (ADNI) uses [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) across multiple centers.
  • Inter-scanner variability in FDG-PET data arises from differences in scanner resolution, reconstruction, and corrections.

Purpose of the Study:

  • To reduce systematic inter-scanner differences in FDG-PET scans from 50 participating PET centers.
  • To improve data harmonization for multi-center Alzheimer's disease studies.

Main Methods:

  • Developed two correction steps: high-frequency (common resolution smoothing) and low-frequency (affine correction factors).
  • Validated corrections using 3-D Hoffman brain phantom scans and applied them to 95 normal control subject scans.

More Related Videos

Multianimal Magnetic Resonance Imaging for Tumor Measurements in Pancreatic Cancer Mouse Models
09:18

Multianimal Magnetic Resonance Imaging for Tumor Measurements in Pancreatic Cancer Mouse Models

Published on: February 3, 2026

Related Experiment Videos

Last Updated: Jun 23, 2026

Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities
07:13

Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities

Published on: October 27, 2023

Multianimal Magnetic Resonance Imaging for Tumor Measurements in Pancreatic Cancer Mouse Models
09:18

Multianimal Magnetic Resonance Imaging for Tumor Measurements in Pancreatic Cancer Mouse Models

Published on: February 3, 2026

Main Results:

  • High-frequency correction reduced phantom data variability by 20%-50%.
  • Low-frequency correction further reduced phantom data variability by 20%-25%.
  • High-frequency correction showed similar results in clinical scans, but low-frequency correction did not yield further improvements.

Conclusions:

  • The developed high-frequency correction effectively reduces inter-scanner variability in FDG-PET data.
  • Further refinement of the low-frequency correction method is necessary for clinical application in ADNI studies.