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  • Research Article
  • Open Access

Biomedical Image Sequence Analysis with Application to Automatic Quantitative Assessment of Facial Paralysis

EURASIP Journal on Image and Video Processing20072007:081282

  • Received: 26 February 2007
  • Accepted: 16 October 2007
  • Published:


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.


  • Radial Basis Function
  • Optical Flow
  • Facial Feature
  • Video Data
  • Motion Feature


Authors’ Affiliations

Department of Electronic and Electrical Engineering, University of Strathclyde, Royal College Building, Glasgow, G1 1XW, UK
Institute of Neurological Sciences, Southern General Hospital, 1345 Govan Road, Glasgow, G51 4TF, UK


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© He et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.