A new procedure, free from human assessment that automatically grades some facial skin structural signs. Comparison with assessments by experts, using referential atlases of skin ageing

Objective To develop an automatic system that grades the severity of facial signs through ‘selfies’ pictures taken by women of different ages and ethnics. Methods 1140 women from three ethnics (African‐American, Asian, Caucasian), of different ages (18–80 years old), took ‘selfies’ by high resolution smartphones cameras under different conditions of lighting or facial expressions. A dedicated software, was developed, based on a Convolutional Neural Network (CNN) that integrates training data from referential Skin Aging Atlases. The latter allows to an immediate quantification of the severity of nine facial signs according to the ethnicity declared by the subject. These automatic grading were confronted to those assessed by 12 trained experts and dermatologists either on ‘selfies’ pictures or in live conditions on a smaller cohort of women. Results The system appears weakly influenced by lighting conditions or facial expressions (coefficients of variations ranging 10–13% for most signs) and leads to global agreements with experts’ assessments, even showing a better reproducibility on some facial signs. Conclusion This automatic scoring system, still in development, seems offering a new quantitative approach in the quantified description of facial signs, independent from human vision, in many applications, being individual, cosmetic oriented or dermatological with regard to the follow‐up of medical anti‐ageing corrective strategies. Resumé Objectif De développer un système automatique qui quantifie la sévérité de certains signes du visage à partir de photographies de type ‘selfies’ pris par des femmes d'origine ethnique et d’âge différents. Méthodes 1140 femmes de trois ethnies différentes (Afro‐Américaines, Asiatiques, Caucasiennes), d’âges différents (18–80 ans) ont pris des selfies sous différentes conditions d’éclairage et d'expressions faciales. Un logiciel dédié a été développé, basé sur un réseau de convolution neuronal et intégrant les données d'annotations utilisant les Atlas de Vieillissement Cutané. Ce système quantifie immédiatement la sévérité de 9 signes faciaux selon l'ethnie déclarée par le sujet. Ces scores ont été confrontés à ceux de 12 experts et dermatologistes soit à partir des ‘selfies’ ou en conditions réelles sur un groupe plus restreint de femmes. Résultats Le système apparaît faiblement influencé par les conditions d’éclairage et les expressions faciales (coefficients de variation de l'ordre de 10–13%) et conduit à des valeurs comp