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

Virtual open heart surgery: obtaining models suitable for surgical simulation.

Thomas Sangild Sørensen1, Jean Stawiaski, Jesper Mosegaard

  • 1CAVI, University of Aarhus, Denmark. sangild@cavi.dk

Studies in Health Technology and Informatics
|March 23, 2007
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

Fast 4D cone-beam CT from 60 s acquisitions.

Physics and imaging in radiation oncology·2021
Same author

A Vector Flow Imaging Method for Portable Ultrasound Using Synthetic Aperture Sequential Beamforming.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control·2017
Same author

Fast reconstruction of low dose proton CT by sinogram interpolation.

Physics in medicine and biology·2016
Same author

Overcoming foetal motion using interactive real-time magnetic resonance imaging.

Clinical physiology and functional imaging·2016
Same author

Quantitative Neuroimaging Software for Clinical Assessment of Hippocampal Volumes on MR Imaging.

Journal of Alzheimer's disease : JAD·2015
Same author

A simulation study on proton computed tomography (CT) stopping power accuracy using dual energy CT scans as benchmark.

Acta oncologica (Stockholm, Sweden)·2015

We developed a pre-processing strategy for surgical simulation, including imaging, segmentation, and model reconstruction. This approach is ideal for virtual open heart surgery simulators and GPU-accelerated techniques.

Area of Science:

  • Medical Simulation
  • Computer-Aided Surgery
  • Biomedical Imaging

Background:

  • Surgical simulation requires accurate patient-specific models.
  • Existing GPU-accelerated techniques need effective pre-processing pipelines.
  • Virtual surgery demands robust data preparation.

Purpose of the Study:

  • To present a comprehensive pre-processing strategy for surgical simulation.
  • To detail imaging, segmentation, and model reconstruction steps.
  • To establish prerequisites for a virtual open heart surgery simulator.

Main Methods:

  • Imaging acquisition and processing.
  • Image segmentation techniques for anatomical structures.
  • 3D model reconstruction from segmented data.

Related Experiment Videos

  • Integration with GPU-accelerated simulation frameworks.

    • Main Results:

    • A validated pre-processing pipeline.
    • Demonstrated suitability for virtual open heart surgery.
    • Compatibility with existing simulation technologies.

    Conclusions:

    • The presented strategy effectively prepares data for advanced surgical simulation.
    • This pre-processing is crucial for realistic virtual surgical environments.
    • The methodology supports the development of sophisticated surgical training tools.