No 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.

Infrared thermography (IRT), as a noncontact tool for temperature measurement, is widely applied in the study of acupuncture modernization. The aim of this study was to assess the intra- and interrater reliability of infrared image analysis of facial acupoints of subjects with facial paralysis and determine the factors influencing the variability of the measured values. A total of 26 patients with facial paralysis on one side, aged 26 to 53 years, participated voluntarily in the study. Facial infrared thermal images of all participants were analyzed by two trained raters at two different time points at a one-week interval. The intraclass correlation coefficient (ICC) was used to determine the intra- and interrater reliability of IRT measurements. The ICC values varied depending on the analyzed acupoints. The reliability of temperature measurement ranged from moderate to excellent (intrarater, ICC ranged from 0.669 to 0.990; interrater, ICC ranged from 0.661 to 0.987). The reliability of temperature difference measurement ranged from low to excellent (intrarater, ICC ranged from 0.412 to 0.882; interrater, ICC ranged from 0.334 to 0.828). The main influencing factor of reliability is the incomplete consistency in selecting acupoint positions when repeatedly positioning the same acupoint manually. Despite low reliability of temperature difference measurement at some acupoints, some auxiliary measures can be used to reduce the error of manual positioning. Thus, infrared thermal imaging still has the potential to assist in objective and quantitative research on acupuncture.