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Notice of retraction
Vol. 34, No. 8(3), S&M3042

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Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
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Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials, Volume 36, Number 5(3) (2024)
Copyright(C) MYU K.K.
pp. 2159-2168
S&M3659 Research Paper of Special Issue
https://doi.org/10.18494/SAM4894
Published: May 31, 2024

Facial Paralysis Diagnosis and Treatment Assessment Computational Model [PDF]

Tiancai Lan, Jun Chen, Jing Huang, Weiliang Ma, and Cheng-Fu Yang

(Received January 3, 2024; Accepted May 2, 2024)

Keywords: asymmetry, computational model, facial paralysis diagnosis and treatment, medical imaging, computer-aided diagnosis

In this study, we introduce an asymmetry calculation model for evaluating the effectiveness of facial paralysis diagnosis and treatment, implemented through a Python and OpenCV algorithm. The algorithm is based on actual images from cases of facial paralysis treatments, and numerical experiments for image comparison and subsequent detailed statistical analysis are conducted. The research findings indicate that the calculated numerical indices provided by this model can relatively accurately assess the effectiveness of facial paralysis diagnosis and treatment on a graded scale. Consequently, in this study, we propose to combine overall facial and specific facial region motion disparity features for a comprehensive facial paralysis grading evaluation. This innovative approach provides a robust tool for the accurate assessment of facial paralysis treatment outcomes, offering significant support for clinical practices and treatment optimization.

Corresponding author: Jun Chen and Cheng-Fu Yang


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Cite this article
Tiancai Lan, Jun Chen, Jing Huang, Weiliang Ma, and Cheng-Fu Yang, Facial Paralysis Diagnosis and Treatment Assessment Computational Model, Sens. Mater., Vol. 36, No. 5, 2024, p. 2159-2168.



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