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

Positron Emission Tomography01:29

Positron Emission Tomography

Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body being...
Imaging Studies II: Positron Emission Tomography and Scintigraphy01:25

Imaging Studies II: Positron Emission Tomography and Scintigraphy

Positron Emission Tomography (PET) is a medical imaging technique that provides crucial insights into the body's physiological functions at a molecular level. It is an indispensable resource for diagnosing, staging, and monitoring various illnesses, notably cancer, neurological disorders, and cardiovascular conditions.
Fundamental Principles of PET

You might also read

Related Articles

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

Sort by
Same author

Open-Geometry PET: Quantifying the Trade-off Between Time-of-Flight Resolution and Angular Coverage.

Physics in medicine and biology·2026
Same author

An Open Multi-Center Whole-Body FDG PET/CT Foundation Model for Tumor Segmentation.

ArXiv·2026
Same author

Influence of an AQP4 haplotype and sleep duration on early Alzheimer's disease.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2026
Same author

Direct Cardiac T1 Mapping with Subspace Modeling and Free-breathing Data Acquisition.

IEEE transactions on bio-medical engineering·2026
Same author

Scan-wise generalized PET denoising with contrastive adversarial learning.

Physics in medicine and biology·2026
Same author

Individualized Treatment Effect Inference of Head and Neck Cancer with Multimodal Data.

APSIPA Transactions on Signal and Information Processing·2026

Related Experiment Video

Updated: May 24, 2026

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451
05:17

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451

Published on: April 18, 2025

Parametric imaging with Bayesian priors: a validation study with (11)C-Altropane PET.

Yu-Hua Dean Fang1, Georges El Fakhri, John A Becker

  • 1Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA.

Neuroimage
|March 20, 2012
PubMed
Summary

Bayesian estimation enhances signal-to-noise ratio in parametric imaging, improving detection of localized changes. This method requires a modest sample size and reduces bias, making it valuable for neuroimaging studies.

More Related Videos

Multi-Tracer Studies of Brain Oxygen and Glucose Metabolism Using a Time-of-Flight Positron Emission Tomography-Computed Tomography Scanner
08:36

Multi-Tracer Studies of Brain Oxygen and Glucose Metabolism Using a Time-of-Flight Positron Emission Tomography-Computed Tomography Scanner

Published on: June 7, 2024

Related Experiment Videos

Last Updated: May 24, 2026

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451
05:17

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451

Published on: April 18, 2025

Multi-Tracer Studies of Brain Oxygen and Glucose Metabolism Using a Time-of-Flight Positron Emission Tomography-Computed Tomography Scanner
08:36

Multi-Tracer Studies of Brain Oxygen and Glucose Metabolism Using a Time-of-Flight Positron Emission Tomography-Computed Tomography Scanner

Published on: June 7, 2024

Area of Science:

  • Neuroimaging
  • Medical Physics
  • Statistical Modeling

Background:

  • Parametric imaging is crucial in neuroimaging for quantitative analysis.
  • Bayesian estimation offers potential for improving signal-to-noise ratio (SNR) in parametric images.
  • Limited empirical data exists on Bayesian estimation's assumptions and performance in this context.

Purpose of the Study:

  • To empirically evaluate the assumptions and performance of Bayesian estimation for parametric imaging.
  • To assess the impact of Bayesian estimation on signal-to-noise ratio and bias.
  • To determine the optimal sample size for Bayesian estimation in neuroimaging.

Main Methods:

  • Utilized data from 54 subjects previously studied with (11)C-Altropane.
  • Applied normality tests to assess data and parametric distribution assumptions.
  • Conducted simulation studies to evaluate detection of localized differences using statistical parametric mapping (SPM).

Main Results:

  • Normality assumptions were met in over 80% of voxels.
  • Bayesian estimation reduced the standard deviation of binding potential by 30-50% without significant bias.
  • A modest sample size (as few as 10 subjects) is sufficient for a priori information, with minimal impact from subject selection.

Conclusions:

  • Bayesian estimation effectively improves SNR in parametric images.
  • This method enhances the reliability of detecting localized changes in neuroimaging cohorts.
  • Bayesian estimation allows for more sensitive analyses or reduced sample sizes in neuroimaging research.