Evaluation of Simplified ROI Definition in Facial Thermography for Psychophysiological and Medical Applications

Consistent definition of facial regions of interest (ROIs) is essential for comparable evaluation of temperature dynamics, yet manual ROI annotation remains common. As anatomically faithful annotation is time-consuming and cognitively demanding, this study investigates whether simplified geometric ROIs anchored to facial landmarks can be used without introducing differences in temperature statistics that exceed relevant measurement uncertainty levels. Three novice raters annotated five common facial ROIs across repeated sessions. Temperature metrics (mean, median, and standard deviation) were calculated from all pixels and from the warmest 10% of pixels at three spatial resolutions. Differences between annotation approaches were evaluated with respect to the best achievable and realistic uncertainty levels, 0.3 °C and 1.3 °C, respectively. The simplification reduced annotation time by 42% while maintaining excellent inter- and intra-rater reliability. For most ROIs and metrics, differences remained within the stricter uncertainty level, with larger deviations observed mainly in the anatomically variable periorbital region. Lower spatial resolution increased variability, particularly for small ROIs that fell below the minimum size criterion. These results demonstrate that simplified ROI definitions provide comparable temperature statistics while substantially improving time efficiency, supporting their use in manual and automated facial thermography analysis.