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

Unwrapping Cochlear implants by spiral CT

G Wang1, M W Vannier, M W Skinner

  • 1Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO 63110 USA. gwang@linda.wustl.edu

IEEE Transactions on Bio-Medical Engineering
|September 1, 1996
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

Erratum: Evaluation of kurtosis-corrected sound exposure level as a metric for predicting onset of hearing threshold shifts in harbor porpoises (Phocoena phocoena) [J. Acoust. Soc. Am. 152, 295-301 (2022)].

The Journal of the Acoustical Society of America·2022
Same author

Evaluation of kurtosis-corrected sound exposure level as a metric for predicting onset of hearing threshold shifts in harbor porpoises (Phocoena phocoena).

The Journal of the Acoustical Society of America·2022
Same author

Great Ears: Low-Frequency Sensitivity Correlates in Land and Marine Leviathans.

Advances in experimental medicine and biology·2015
Same author

Deadly diving? Physiological and behavioural management of decompression stress in diving mammals.

Proceedings. Biological sciences·2011
Same author

The ears of butterflyfishes (Chaetodontidae): 'hearing generalists' on noisy coral reefs?

Journal of fish biology·2010
Same author

Image reconstruction and image quality evaluation for a 16-slice CT scanner.

Medical physics·2003

This study presents a new method using computed tomography (CT) to precisely measure cochlear implant electrode array length and position. This technique improves programming for better speech recognition in patients with profound hearing loss.

Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Otolaryngology

Background:

  • Profound sensorineural hearing loss often necessitates cochlear implants when hearing aids are ineffective.
  • Accurate electrode placement is crucial for optimizing speech processor programming and maximizing speech recognition.
  • Current methods for determining electrode position can be improved for better patient outcomes.

Purpose of the Study:

  • To develop and validate an approach for measuring the implanted length and position of cochlear electrode arrays.
  • To enable precise unwrapping and visualization of the electrode array from volumetric CT scans.
  • To enhance speech processor programming by providing accurate electrode array geometry.

Main Methods:

  • Utilized volumetric spiral computed tomography (CT) imaging of the Nucleus electrode array.

Related Experiment Videos

  • Developed two algorithms (one K-L transform-based, one non-K-L transform-based) to track and measure curvilinear structures.
  • Digitally synthesized and reconstructed electrode arrays in isotropic voxel grids for analysis.

    • Main Results:

    • Both algorithms accurately measured the lengths of curvilinear structures in numerical and in vitro studies.
    • The electrode array image was successfully unwrapped into a linear representation using the determined local directions.
    • The unwrapping approach provided accurate longitudinal and cross-sectional measurements, improving visualization.

    Conclusions:

    • The described CT-based unwrapping method accurately measures cochlear implant electrode array dimensions.
    • This technique facilitates precise estimation of individual electrode positions after implantation.
    • Improved electrode position knowledge can lead to optimized speech processor programming and enhanced speech recognition.