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

Estimating distributed anatomical connectivity using fast marching methods and diffusion tensor imaging.

Geoffrey J M Parker1, Claudia A M Wheeler-Kingshott, Gareth J Barker

  • 1Division of Imaging Science and Biomedical Engineering, University of Manchester, UK. geoff.parker@man.ac.uk

IEEE Transactions on Medical Imaging
|June 20, 2002
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

Bullying victimization and brain development: a longitudinal structural magnetic resonance imaging study from adolescence to early adulthood.

Translational psychiatry·2026
Same author

Digital Twin Brain simulation and manipulation of a functional brain network underlying mental illness.

bioRxiv : the preprint server for biology·2026
Same author

Characterising a stress-sensitive default mode network (DMN) deficit in major psychiatric disorders.

Communications biology·2026
Same author

Bullying Victimization and Brain Development: A Longitudinal Structural Magnetic Resonance Imaging Study from Adolescence to Early Adulthood.

bioRxiv : the preprint server for biology·2026
Same author

The Sex-Dependent Relationship Between Amygdala Activation and Depressive Symptoms With Problematic Drinking.

Biological psychiatry·2026
Same author

Charting the velocity of brain growth and development.

ArXiv·2026
Same journal

Physiology-guided Self-supervised Learning for Simultaneous Dual-Tracer PET Separation.

IEEE transactions on medical imaging·2026
Same journal

Informed-Exploration Reinforcement Learning for Automated Virtual Coronary Intervention Planning.

IEEE transactions on medical imaging·2026
Same journal

4D Reconstruction of Fetal Left Ventricle from Echocardiography via 2.5D Radial Segmentation and Graph-Fourier Reconstruction.

IEEE transactions on medical imaging·2026
Same journal

Generalised Medical Phrase Grounding.

IEEE transactions on medical imaging·2026
Same journal

EndoLRMGS: Combining Large Reconstruction Modelling and Gaussian Splatting for Complete Endoscopic Scene Reconstruction.

IEEE transactions on medical imaging·2026
Same journal

A Neural-Analytical Fusion Scatter Correction Method for Multi-Source CT Using Equivalent High-Order Scatter.

IEEE transactions on medical imaging·2026
See all related articles

This study introduces a novel method using magnetic resonance diffusion tensor imaging to map brain connections. The technique successfully identifies major white matter tracts and their branching patterns in the brain.

Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Anatomy

Background:

  • Understanding brain connectivity is crucial for neuroscience.
  • Magnetic Resonance Diffusion Tensor Imaging (DTI) provides insights into white matter structure.
  • Current methods for mapping brain pathways can be limited.

Purpose of the Study:

  • To present a new method for determining anatomical connection paths between brain regions.
  • To utilize level set theory and fast marching methods for advanced brain mapping.
  • To demonstrate the method's capability in elucidating white matter tracts and connectivity.

Main Methods:

  • Employing magnetic resonance diffusion tensor information.
  • Applying level set theory with fast marching methods.

Related Experiment Videos

  • Generating three-dimensional time of arrival maps to identify connection paths.

    • Main Results:

    • Successfully elucidated major white matter tracts in the normal brain.
    • Demonstrated the ability to identify multiple connections and tract branching.
    • Generated maps of connectivity between various brain regions.
    • Described four distinct methods for quantifying the degree of connectivity.

    Conclusions:

    • The presented method offers a robust approach for mapping brain anatomical connections.
    • This technique effectively visualizes complex white matter pathways and connectivity patterns.
    • The findings contribute to a deeper understanding of brain structural organization and function.