Automatic quantification of vocal cord paralysis - an application of fibre-optic endoscopy video processing

Radhika Menon, Lykourgos Petropoulakis, John J. Soraghan, Heba Lakany, Kenneth MacKenzie, Omar Hilmi, Gaetano Di Caterina

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

1 Citation (Scopus)
138 Downloads (Pure)

Abstract

Full movement of the vocal cords is necessary for life sustaining functions. To enable correct diagnosis of reduced vocal cord motion and thereby potentially enhance treatment outcomes, it is proposed to objectively determine the degree of vocal cord paralysis in contrast to the current clinical practice of subjective evaluation. Our study shows that quantitative assessment can be achieved using optical flow based motion estimation of the opening and closing movements of the vocal cords. The novelty of the proposed method lies in the automatic processing of fibre-optic endoscopy videos to derive an objective measure for the degree of paralysis, without the need for high-end data acquisition systems such as high speed cameras or stroboscopy. Initial studies with three video samples yield promising results and encourage further investigation of vocal cord paralysis using this technique.
Original languageEnglish
Title of host publicationProceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies
Subtitle of host publicationBIOIMAGING
Place of PublicationSetúbal, Portugal
Pages108-113
Number of pages6
Volume2
Publication statusPublished - 23 Feb 2017
Event4th International Conference on Bioimaging - Rua Diogo Macedo, Porto, Portugal
Duration: 21 Feb 201723 Feb 2017
http://www.bioimaging.biostec.org/

Conference

Conference4th International Conference on Bioimaging
Abbreviated titleBioimaging 2017
Country/TerritoryPortugal
CityPorto
Period21/02/1723/02/17
Internet address

Keywords

  • motion estimation
  • automatic segmentation
  • computer-assisted diagnosis
  • fibre-optic endoscopy
  • vocal cord motion
  • paralysis
  • video processing
  • optical flow based motion estimation

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