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

Genus zero surface conformal mapping and its application to brain surface mapping.

Xianfeng Gu1, Yalin Wang, Tony F Chan

  • 1Department of Computer and Information Science and Engineering, University of Florida, FL 32611, USA. gu@cise.ufl.edu

IEEE Transactions on Medical Imaging
|September 2, 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

SKULL-STRIPPING WITH DEFORMABLE ORGANISMS.

Proceedings. IEEE International Symposium on Biomedical Imaging·2014
Same author

Genome-wide interaction analysis reveals replicated epistatic effects on brain structure.

Neurobiology of aging·2014
Same author

Brain connectivity and novel network measures for Alzheimer's disease classification.

Neurobiology of aging·2014
Same author

Empowering imaging biomarkers of Alzheimer's disease.

Neurobiology of aging·2014
Same author

Seemingly unrelated regression empowers detection of network failure in dementia.

Neurobiology of aging·2014
Same author

Physical activity, body mass index, and brain atrophy in Alzheimer's disease.

Neurobiology of aging·2014
Same journal

LLM-enhanced Neuron Segmentation and Reconstruction in Complex Mouse Brain Images.

IEEE transactions on medical imaging·2026
Same journal

Matrixed-Spectrum Decomposition Accelerated Linear Boltzmann Transport Equation Solver for Fast Scatter Correction in Multi-Spectral CT.

IEEE transactions on medical imaging·2026
Same journal

The Ritz Adjoint Method for MRI Pulse Design.

IEEE transactions on medical imaging·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
See all related articles

We present a novel conformal mapping method for brain surface analysis. This technique ensures stable and robust cortical surface matching using magnetic resonance imaging (MRI) data.

Area of Science:

  • Computational geometry
  • Neuroimaging analysis
  • Differential geometry

Background:

  • Conformal parameterization is crucial for analyzing surface geometry.
  • Existing methods face challenges in stability and robustness for complex biological surfaces like the brain.
  • The cohomology of holomorphic one-forms offers a theoretical foundation for global conformal mappings.

Purpose of the Study:

  • To develop a general and robust method for global conformal parameterization of surfaces.
  • To apply this method to the problem of cortical surface matching using magnetic resonance imaging (MRI) data.
  • To ensure uniqueness and stability of the conformal map for brain surface analysis.

Main Methods:

  • Utilized the structure of the cohomology group of holomorphic one-forms for surface parameterization.

Related Experiment Videos

  • Developed an algorithm to minimize harmonic energy for unique mapping between genus zero manifolds.
  • Represented brain surfaces using mesh structures and incorporated additional constraints for map uniqueness.
  • Validated the method using magnetic resonance imaging (MRI) data.

    • Main Results:

    • The conformal mapping algorithm demonstrated preservation of angular relationships on brain surfaces.
    • Mappings were found to be stable across MRIs acquired at different times.
    • The method proved robust to variations in data triangulation and resolution.
    • Empirical tests confirmed the stability and extensibility of the algorithm.

    Conclusions:

    • The developed general method for global conformal parameterization is effective for cortical surface matching.
    • The algorithm provides stable, robust, and unique mappings for brain surface analysis.
    • This approach offers advantages in stability and extensibility compared to existing brain surface conformal mapping algorithms.