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: Jul 12, 2026

Three-Dimensional Shape Modeling and Analysis of Brain Structures
05:33

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

A 3D Brain Geometry Toolkit for Multisite Neuroimaging Analysis.

Yanghee Im, Melody J Y Kang, Boris A Gutman

    Biorxiv : the Preprint Server for Biology
    |July 10, 2026
    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

    A Surface-based deep learning approach for cortical shape analysis.

    bioRxiv : the preprint server for biology·2024
    Same author

    Childhood Disadvantage Moderates Late Midlife Default Mode Network Cortical Microstructure and Visual Memory Association.

    The journals of gerontology. Series A, Biological sciences and medical sciences·2023
    Same author

    Heritability Estimation of Cognitive Phenotypes in the ABCD Study<sup>®</sup> Using Mixed Models.

    Behavior genetics·2023
    Same author

    Task fMRI paradigms may capture more behaviorally relevant information than resting-state functional connectivity.

    NeuroImage·2023
    Same author

    Identification of novel genomic risk loci shared between common epilepsies and psychiatric disorders.

    Brain : a journal of neurology·2023
    Same author

    A Multicompartmental Diffusion Model for Improved Assessment of Whole-Body Diffusion-weighted Imaging Data and Evaluation of Prostate Cancer Bone Metastases.

    Radiology. Imaging cancer·2023

    This study introduces a 3D brain geometry analysis toolkit for large-scale neuroimaging. Surface-based shape analysis improves diagnostic and treatment prediction for brain disorders compared to traditional volume metrics.

    Area of Science:

    • Neuroimaging
    • Computational Neuroscience
    • Brain Geometry Analysis

    Background:

    • Traditional volumetric analysis lacks spatial precision for brain alterations.
    • Large-scale initiatives require robust methods for analyzing multisite neuroimaging data.
    • Developing advanced tools is crucial for identifying reliable brain markers for disorders.

    Purpose of the Study:

    • To present a toolkit for 3D brain geometry analysis tailored for large-scale neuroimaging studies.
    • To address challenges in multisite data integration, confound correction, and statistical modeling.
    • To enhance the discovery of illness-related brain markers using surface-based models.

    Main Methods:

    • Developed a scalable framework for multisite data integration and site-specific confound correction.

    More Related Videos

    A Neural Implant Design Toolbox for Nonhuman Primates
    06:33

    A Neural Implant Design Toolbox for Nonhuman Primates

    Published on: February 9, 2024

    Modeling the Functional Network for Spatial Navigation in the Human Brain
    05:55

    Modeling the Functional Network for Spatial Navigation in the Human Brain

    Published on: October 13, 2023

    Related Experiment Videos

    Last Updated: Jul 12, 2026

    Three-Dimensional Shape Modeling and Analysis of Brain Structures
    05:33

    Three-Dimensional Shape Modeling and Analysis of Brain Structures

    Published on: November 14, 2019

    A Neural Implant Design Toolbox for Nonhuman Primates
    06:33

    A Neural Implant Design Toolbox for Nonhuman Primates

    Published on: February 9, 2024

    Modeling the Functional Network for Spatial Navigation in the Human Brain
    05:55

    Modeling the Functional Network for Spatial Navigation in the Human Brain

    Published on: October 13, 2023

  • Implemented accelerated statistical modeling using the Fast and Efficient Mixed-Effects Algorithm (FEMA).
  • Utilized interpretable machine learning and interactive visualization for results analysis.

    • Main Results:

    • Subcortical shape measures, when combined across sites, captured complex differences between diagnostic groups (bipolar disorder).
    • The FEMA algorithm accelerated statistical modeling by 16-fold.
    • Machine learning models demonstrated superior predictive performance using shape features over traditional volumes.

    Conclusions:

    • Surface-based brain geometry analysis offers greater spatial precision than traditional volumetrics.
    • The developed toolkit effectively integrates multisite data and accelerates analysis for large-scale studies.
    • Shape features show promise for improved diagnostic and treatment prediction in neurological and psychiatric disorders.