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 Videos

Consensus inference in neuroimaging.

L K Hansen1, F A Nielsen, S C Strother

  • 1Informatics and Mathematical Modelling, Technical University of Denmark, DK-2800 Lyngby, Denmark.

Neuroimage
|May 16, 2001
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

Dimethyl Fumarate, But Not Rituximab, Reduces Serum GFAP Levels and PIRMA in Relapsing-Remitting MS.

Annals of clinical and translational neurology·2026
Same author

Clinical symptoms and surgical outcome of colloid cysts of the third ventricle: A multicenter retrospective study.

Brain & spine·2025
Same author

Definition of Local Spatial Densities in Hadrons.

Physical review letters·2022
Same author

Chitin-calcium alginate composite fibers for wound care dressings spun from ionic liquid solution.

Journal of materials chemistry. B·2020
Same author

Design, synthesis and in vitro evaluation of β-glucuronidase-sensitive prodrug of 5-aminolevulinic acid for photodiagnosis of breast cancer cells.

Bioorganic chemistry·2018
Same author

Two subgroups of antipsychotic-naive, first-episode schizophrenia patients identified with a Gaussian mixture model on cognition and electrophysiology.

Translational psychiatry·2017
Same journal

Lifespan Trajectories of the Brain's Functional Complexity Characterized by Multiscale Sample Entropy.

NeuroImage·2026
Same journal

Pleasant fragrance modulates dyadic social sharing of positive emotion: Sharer-centered socioemotional enhancement effect and its neural couplings.

NeuroImage·2026
Same journal

Altered Functional Hierarchical and Sequential Organization in Individuals with Schizophrenia during Auditory Processing.

NeuroImage·2026
Same journal

Mechanical Deformation Explains Distinct Neuroimaging Patterns and Etiologies in Brain Trauma.

NeuroImage·2026
Same journal

Ventral striatum temporal interference brain stimulation enhances the reward-positivity event-related potential and reduces anxiety.

NeuroImage·2026
Same journal

NeuroHarm‑Kit: An Open‑Source Toolbox for Benchmarking Deep‑Learning Harmonization of Multi‑Site T1‑Weighted MRI.

NeuroImage·2026
See all related articles

Model averaging in neuroimaging improves results by directly comparing and averaging summary images after histogram equalization. This technique enhances the receiver operating characteristic (ROC) curve performance in fMRI studies.

Area of Science:

  • Neuroimaging
  • Medical Image Analysis
  • Statistical Modeling

Background:

  • Neuroimaging studies often generate complex model summary images.
  • Direct comparison and averaging of these images can be challenging due to variations.
  • Enhancing the reliability and performance of neuroimaging analyses is crucial.

Purpose of the Study:

  • To introduce and validate a novel model averaging technique for neuroimaging.
  • To demonstrate the utility of histogram equalization for image comparison.
  • To improve the performance of statistical models in neuroimaging analyses.

Main Methods:

  • Development of a model averaging procedure for neuroimaging data.
  • Application of histogram equalization to normalize image intensity distributions.

Related Experiment Videos

  • Evaluation of the method using a simulation study and a functional MRI (fMRI) dataset.

    • Main Results:

    • Model summary images can be directly compared and averaged after histogram equalization.
    • The averaging procedure significantly enhances the receiver operating characteristic (ROC) curve in simulations.
    • The method was successfully applied to an fMRI study of the motor cortex, showing improved performance.

    Conclusions:

    • Model averaging, combined with histogram equalization, is an effective technique for neuroimaging.
    • This approach enhances the diagnostic performance of neuroimaging models.
    • The method offers a valuable tool for analyzing fMRI data and other neuroimaging modalities.