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

Three-dimensional modeling by combining artificial with real data.

I Gargantini1, H H Atkinson, G F Schrack

  • 1Department of Computer Science, University of Western Ontario, London, Canada.

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society
|November 1, 1990
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

Executive function, memory, and gait speed decline in well-functioning older adults.

The journals of gerontology. Series A, Biological sciences and medical sciences·2010
Same author

An algorithm for encoding and decoding the 3-D Hilbert order.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·1997
Same journal

Continual test-time adaptation via weight averaging of feature augmentations in cross-domain medical image segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

A lightweight network for segmenting tree-like structures in medical images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

RGCNN-nnUNet: Recurrent group equivariant nnU-Net for robust brain tissue segmentation on stroke NCCT.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

Self-supervised isotropic reconstruction for abnormality detection in anisotropic MRI.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

WDBDM: Wavelet-based dual-branch diffusion model for low-dose CT and PET denoising.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

ScribSAM: A robust scribble-supervised framework for spatiotemporal segmentation of breast lesions in ultrasound videos.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
See all related articles

This study introduces a hybrid filling technique to merge 3D imaging data from Computed Tomography scans and custom models for enhanced bone grafting simulations. The method addresses data conflicts for improved graphics modeling.

Area of Science:

  • Computer graphics
  • Medical imaging
  • Biomedical engineering

Background:

  • Combining Volume Representation (e.g., CT scans) and Boundary Representation (e.g., polygon vertices) data is challenging for custom 3D models.
  • Existing methods struggle with data conflicts arising from subsampling or digitization errors in graphics simulations.

Purpose of the Study:

  • To propose a novel hybrid filling technique for integrating disparate 3D data representations.
  • To address and resolve data conflicts in graphics simulation for applications like bone grafting.
  • To demonstrate the technique's efficacy through a designed graphics experiment.

Main Methods:

  • Developed a hybrid filling technique to process and combine Volume Representation and Boundary Representation data.
  • Implemented a method to handle conflicting adjacency information caused by data acquisition errors.

Related Experiment Videos

  • Designed a graphics experiment showcasing the integration of partially defined objects.

    • Main Results:

    • The hybrid technique successfully merges data from different representations, overcoming common simulation issues.
    • Conflicting adjacency information due to errors was effectively processed and resolved.
    • The experiment validated the method's capability in handling mixed-representation models.

    Conclusions:

    • The proposed hybrid filling technique offers a robust solution for integrating diverse 3D data in graphics simulations.
    • This approach enhances the accuracy and feasibility of creating custom-designed models, particularly for medical applications like bone grafting.
    • Further development can improve the simulation of complex anatomical structures and surgical procedures.