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

Topology correction using fast marching methods and its application to brain segmentation.

Pierre-Louis Bazin1, Dzung L Pham

  • 1Johns Hopkins University, Baltimore, USA.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|May 12, 2006
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

Multiecho Fat-Water Spiral MR Elastography With Distributed Encoding for Simultaneously Imaging Brain and Skull Displacement.

Magnetic resonance in medicine·2026
Same author

Intrinsic cortical geometry is associated with individual differences in local functional organization.

Research square·2026
Same author

A novel spatiotemporal decomposition and identification of sparse equations for human brain deformation.

Scientific reports·2026
Same author

ECLARE: efficient cross-planar learning for anisotropic resolution enhancement.

Journal of medical imaging (Bellingham, Wash.)·2026
Same author

Microstructural profiles of the human superficial white matter and their associations to cortical geometry and connectivity.

PLoS biology·2026
Same author

Leptomeningeal enhancement in multiple sclerosis demonstrates posterior predilection and T<sub>1</sub> alterations in the adjacent cortex.

Multiple sclerosis journal - experimental, translational and clinical·2026
Same journal

LiftReg: Limited Angle 2D/3D Deformable Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Inverse Consistency by Construction for Multistep Deep Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Can Crowdsourced Annotations Improve AI-based Congestion Scoring For Bedside Lung Ultrasound?

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Equivariant Filters for Efficient Tracking in 3D Imaging.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Lobar Lung Density Embeddings with a Transformer encoder (LobTe) to predict emphysema progression in COPD.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

uniGradICON: A Foundation Model for Medical Image Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
See all related articles

This study introduces a novel method for correcting object topology in medical images. The technique works directly within the image domain, preserving more of the original data than prior surface-based approaches.

Area of Science:

  • Medical image analysis
  • Computational topology
  • Image segmentation

Background:

  • Accurate topological representation is crucial for medical image analysis.
  • Existing methods for topology correction often alter the original segmented surface, leading to data loss.
  • There is a need for topology correction methods that preserve the integrity of the original medical image data.

Purpose of the Study:

  • To present a new method for correcting the topology of segmented objects in medical images.
  • To develop a technique that operates directly in the image domain, avoiding surface alterations.
  • To introduce a topology propagation algorithm that enforces desired topologies efficiently.

Main Methods:

  • Analysis of topological changes and critical points in implicit surfaces.

Related Experiment Videos

  • Development of a topology propagation algorithm using fast marching techniques.
  • Direct manipulation within the image domain to correct object topology.
  • Main Results:

    • The proposed method successfully corrects the topology of segmented objects.
    • The technique operates directly on isosurfaces within the image domain.
    • This approach results in fewer alterations to the original image volume compared to previous methods.

    Conclusions:

    • The novel topology correction method offers an effective solution for medical image analysis.
    • Working in the image domain preserves more of the original data integrity.
    • The fast marching-based algorithm provides an efficient way to enforce desired topologies.