ArticleDiagnostics (Basel, Switzerland)2021
Facial Paralysis Detection in Infrared Thermal Images Using Asymmetry Analysis of Temperature and Texture Features.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 18 citations in OpenAlex.
- An evaluation of various parts of face to identify facial paralysis using temporal convolutional neural network model.Scientific reports · 2026Article
- Telerehabilitation for peripheral facial palsy: A scoping review.Journal of telemedicine and telecare · 2026Article
- Artificial Intelligence Framework for Automated Facial Asymmetry Detection Using Key-Point Analysis and Neural Networks.Journal of imaging informatics in medicine · 2026Article
- Warm acupuncture combined with precise meridian sinew needling for refractory peripheral facial paralysis: a propensity score-matched retrospective study on clinical efficacy and infrared thermal imaging.Frontiers in medicine · 2026Article
- Deep learning-based automatic facial symmetry scoring in peripheral facial palsy.Scientific reports · 2025Article
- Type 1 and Type 2 Diabetes Measurement Using Human Face Skin Region.Journal of diabetes research · 2023Article
- The Facial Skin Blood Flow Change of Stroke Patients with Facial Paralysis after Peripheral Magnetic Stimulation: A Pilot Study.Brain sciences · 2022Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Facial temperature distribution in healthy people shows contralateral symmetry, which is generally disrupted by facial paralysis. This study aims to develop a quantitative thermal asymmetry analysis method for early diagnosis of facial paralysis in infrared thermal images. First, to improve the reliability of thermal image analysis, the facial regions of interest (ROIs) were segmented using corner and edge detection. A new temperature feature was then defined using the maximum and minimum temperature, and it was combined with the texture feature to represent temperature distribution of facial ROIs. Finally, Minkowski distance was used to measure feature symmetry of bilateral ROIs. The feature symmetry vectors were input into support vector machine to evaluate the degree of facial thermal symmetry. The results showed that there were significant differences in thermal symmetry between patients with facial paralysis and healthy people. The accuracy of the proposed method for early diagnosis of facial paralysis was 0.933, and the area under the ROC curve was 0.947. In conclusion, temperature and texture features can effectively quantify thermal asymmetry caused by facial paralysis, and the application of machine learning in early detection of facial paralysis in thermal images is feasible.
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