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

Geodesic estimation for large deformation anatomical shape averaging and interpolation.

Brian Avants1, James C Gee

  • 1University of Pennsylvania, Philadelphia, PA 19104, USA. avants@grasp.cis.upenn.edu

Neuroimage
|October 27, 2004
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

Adaptive Riemannian optimization for multi-scale diffeomorphic matching.

Nature communications·2026
Same author

Clinicoanatomic localization of iron-rich gliosis in aphasic presentations of globular glial tauopathy.

Brain communications·2026
Same author

Realistic PET image synthesis from MRI for automated inference of brain atrophy and Alzheimer's.

iScience·2026
Same author

Deep Computational Anatomy via Latent-Aligned Multiview Normalizing Flows.

bioRxiv : the preprint server for biology·2026
Same author

Contusions bias cortical thickness estimates after traumatic brain injury: A TRACK-TBI study.

NeuroImage. Clinical·2026
Same author

Text-Image Co-Alignment for Weakly Supervised Polyp Segmentation.

IEEE transactions on medical imaging·2026
Same journal

Brain-Inspired Large Model Mindreading.

NeuroImage·2026
Same journal

Light on Broken Networks: Resting-State fNIRS as a Tool for Connectivity Mapping.

NeuroImage·2026
Same journal

Criticism-Evoked Rumination Is Linked to Dynamic adjustments of the Left Superficial Amygdala in Adolescents.

NeuroImage·2026
Same journal

GeNED.ar cohort: Neuroimaging Resource for Aging Studies in an Admixed Population from Argentina.

NeuroImage·2026
Same journal

DTI-ALPS index correlates with poor neuromodulation outcomes of bilateral STN-DBS in Parkinson's disease patients: a prospective cohort study.

NeuroImage·2026
Same journal

Decoding neuronal criticality firing patterns for large brain based EEG models.

NeuroImage·2026
See all related articles

This study introduces a novel variational method for anatomical averaging using image registration. It generates optimal large deformation atlases, improving average representations of complex anatomical variations.

Area of Science:

  • Medical Image Analysis
  • Computational Anatomy
  • Biomedical Engineering

Background:

  • Traditional anatomical averaging methods often fail with large deformations or complex anatomical variations.
  • Linear averaging is not suitable for viscous or elastic frameworks, necessitating advanced techniques.
  • Existing methods may lack inherent inverse consistency and tools for shape interpolation.

Purpose of the Study:

  • To develop and promote variational methods for anatomical averaging within the image registration space.
  • To create optimal large deformation atlases that account for the underlying shape manifold.
  • To provide an inherently inverse-consistent image registration and geodesic shape interpolation tool.

Main Methods:

  • Utilizing variational methods within the image registration problem space.

Related Experiment Videos

  • Employing a large deformation viscous framework with average forces driving an ordinary differential equation.
  • Estimating geodesics to move images towards a mean shape configuration for atlas construction.

    • Main Results:

    • The developed model generates optimal large deformation atlases, superior to Euclidean anatomical averages.
    • The approach provides inherent inverse consistency in image registration.
    • A tool for constant arc length geodesic shape interpolation is obtained.
    • Improved average representations of highly variable anatomy from distinct populations are achieved.

    Conclusions:

    • Variational methods operating within the image registration space offer a powerful approach for anatomical averaging.
    • The proposed algorithm effectively constructs optimal large deformation atlases, especially for complex anatomical data.
    • This method enhances the accuracy of anatomical averaging and provides valuable supplementary tools for image analysis.