Biomedical image sequence analysis with application to automatic quantitative assessment of facial paralysis

Shu He, John J. Soraghan, Brian F. O'Reilly

Research output: Contribution to journalArticle

18 Citations (Scopus)
18 Downloads (Pure)

Abstract

Facial paralysis is a condition causing decreased movement on one side of the face. A quantitative, objective, and reliable assessment system would be an invaluable tool for clinicians treating patients with this condition. This paper presents an approach based on the automatic analysis of patient video data. Facial feature localization and facial movement detection methods are discussed. An algorithm is presented to process the optical flow data to obtain the motion features in the relevant facial regions. Three classification methods are applied to provide quantitative evaluations of regional facial nerve function and the overall facial nerve function based on the House-Brackmann scale. Experiments show the radial basis function (RBF) neural network to have superior performance.
Original languageEnglish
Article number81282
Number of pages11
JournalEURASIP Journal on Image and Video Processing
Volume2007
DOIs
Publication statusPublished - 2 Dec 2007

Keywords

  • facial paralysis
  • movement
  • assessment system
  • video data
  • biomedical imaging
  • localization
  • facial nerve function
  • radial basis function

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