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

Large deformation inverse consistent elastic image registration.

Jianchun He1, Gary E Christensen

  • 1Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242, USA. jianchun-he@uiowa.edu

Information Processing in Medical Imaging : Proceedings of the ... Conference
|September 4, 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

Genetic Spectrum of Hemoglobinopathies in Reproductive-Age Individuals from a Hospital-Based Cohort in Guangdong, China: A 7-Year Retrospective Analysis.

Biomedicines·2026
Same author

High-Resolution Three-Dimensional Hybrid MRI + Low Dose CT Vocal Tract Modeling: A Cadaveric Pilot Study.

Journal of voice : official journal of the Voice Foundation·2025
Same author

Structural and functional characteristics of healthy and injured porcine lungs during deflation: a quantitative CT imaging analysis.

Journal of applied physiology (Bethesda, Md. : 1985)·2025
Same author

Comparative study of third-generation sequencing-based CASMA-trio and STR linkage analysis for identifying SMN1 2 + 0 carriers.

Scientific reports·2025
Same author

4DCT image artifact detection using deep learning.

Medical physics·2024
Same author

Prior knowledge-guided vision-transformer-based unsupervised domain adaptation for intubation prediction in lung disease at one week.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2024
Same journal

Enhancing Alzheimer's Diagnosis: Leveraging Anatomical Landmarks in Graph Convolutional Neural Networks on Tetrahedral Meshes.

Information processing in medical imaging : proceedings of the ... conference·2026
Same journal

Cycle-Consistent Zero-Shot Through-Plane Super-Resolution for Anisotropic Head MRI.

Information processing in medical imaging : proceedings of the ... conference·2026
Same journal

Brightness-Invariant Tracking Estimation in Tagged MRI.

Information processing in medical imaging : proceedings of the ... conference·2025
Same journal

Multi-View and Multi-Scale Alignment for Contrastive Language-Image Pre-training in Mammography.

Information processing in medical imaging : proceedings of the ... conference·2025
Same journal

Using Multiple Instance Learning to Build Multimodal Representations.

Information processing in medical imaging : proceedings of the ... conference·2025
Same journal

mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds.

Information processing in medical imaging : proceedings of the ... conference·2024
See all related articles

This novel image registration algorithm accurately aligns medical images with significant nonlinear deformations. It significantly reduces inverse consistency errors, improving registration accuracy for brain imaging applications.

Area of Science:

  • Medical Imaging
  • Computational Anatomy
  • Image Processing

Background:

  • Accurate medical image registration is crucial for analyzing anatomical changes.
  • Existing algorithms struggle with locally large nonlinear deformations, limiting their clinical utility.
  • Minimizing inverse consistency error is a key challenge in robust image registration.

Purpose of the Study:

  • To develop a new image registration algorithm capable of handling large nonlinear deformations.
  • To concurrently estimate forward and reverse transformations while minimizing inverse consistency error.
  • To validate the algorithm's performance on 2D and 3D Magnetic Resonance (MR) brain images.

Main Methods:

  • The algorithm concatenates a series of small deformation transformations to model large deformations.

Related Experiment Videos

  • A linear elastic continuum mechanical model is used for regularization of incremental transformations.
  • Concurrent estimation of forward and reverse transformations minimizes inverse consistency error.

    • Main Results:

    • Demonstrated performance on ten 2D and twelve 3D MR brain image registration experiments.
    • Achieved significant reductions in inverse consistency error compared to viscous fluid registration.
    • Average reduction of 50x in 2D and 30x in 3D for inverse consistency error.

    Conclusions:

    • The proposed algorithm effectively registers images with locally large nonlinear deformations.
    • It offers superior performance in reducing inverse consistency error for brain MR images.
    • This method holds promise for improved medical image analysis and clinical applications.