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

Authors:
Shu He;John J. Soraghan;Brian F. O'Reilly
Affiliations:
Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK;Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK;Institute of Neurological Sciences, Southern General Hospital, Glasgow, UK
Venue:
Journal on Image and Video Processing
Year:
2007

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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.