Seasonally‐induced alterations of some facial signs in Caucasian women and their changes induced by a daily application of a photo‐protective product

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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. a des valeurs comparables de celles des experts, voire même de meilleure reproductibilit e dans certains cas. CONCLUSION: Ce syst eme de scorage automatique, encore en d eveloppement, semble offrir une nouvelle approche dans la description quantitative de signes du visage, ind ependante de l'oeil humain, dans de nombreuses applications, comme la personnalisation, a vis ee cosm etique ou dermatologique, dans le suivi de certaines strat egies m edicales de l'antivieillissement cutan e.

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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

Jiang¹,

Kezele²,

Levinshtein³

et al. 2019

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“…), (v) urban pollution, (vi) solar exposures, (vii) lifestyles, (viii) mood, etc. . However, almost all of these quoted papers focused on women, as major consumers of cosmetic products or aesthetical needs.…”

Section: Introductionmentioning

confidence: 99%

A new procedure, free from human assessment, that automatically grades some facial skin signs in men from selfie pictures. Application to changes induced by a severe aerial chronic urban pollution

Zhang¹,

Jiang²,

Kezele³

et al. 2020

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Objective These were two folds: at first, to develop an automatic grading system specifically dedicated to some facial signs of men, similar to the one previously validated on women of different ethnic ancestry and second, to assess its potential in detecting and grading the possible impacts of a severe aerial urban pollution on some facial signs of Chinese men. Methods In both studies, selfie images were obtained from differently aged men. Nine facial signs were automatically graded through a specific A.I‐based algorithm and clinically assessed by a panel of experts and dermatologists. Selfie pictures were taken from individual smartphones of variable optical properties. The first study, designed for developing an automatic grading system, involved three comparable cohorts of men from three different regional ancestries (African, Asian, Caucasian, 110 each) the selfie images of which were acquired under four different lighting conditions. As a second use case study, the facial signs of two cohorts of Chinese men (101 and 100, each), differently aged, regularly exposed to very different aerial urban pollution conditions (UP) were analysed by the same algorithm, selfies being taken under only one lighting condition. Results ‐The new automatic grading system of facial signs suits well to men, showing comparable results than that the one dedicated to women and provides data in close agreement with experts’ assessments. ‐In both cases (expert’s or automatic methodology), the accuracy of the scores appeared ethnic‐dependent. ‐The applied case confirmed previous results obtained clinically, that is, that many facial signs were found of an increased severity among men exposed to a severe urban pollution, as compared to those living in a less polluted city. ‐In both studies, statistical agreements between the automatic grading system and expert’s assessments were reached. In some facial signs, the automatic grading system seems offering a slightly better accuracy than the assessments made by the experts. Conclusion Apart from some minor limitations, this A.I‐based automatic grading system, free from human intervention, performed as well as the one previously developed in women, in close agreement with expert’s assessments. In epidemiological studies, this system offers an easy, fast, affordable and confidential approach in the detection and quantification of male facial signs.

“…These lead to a progressive alteration of some facial traits, being structural (wrinkles, ptosis etc.) or pigmentary, the changes of which are now well documented and clinically evaluated [5][6][7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

An automatic procedure that grades some facial skin structural signs: agreements and validation with clinical assessments made by dermatologists

Flament

Hofmann

Roó

et al. 2019

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Objective To confirm the robustness and validity of an automatic scoring system, algorithm‐based, that grades the severity of nine facial signs through “selfies” smartphones pictures taken by European Caucasian women through dermatological assessments. Methods 157 Caucasian women from three countries (France, Germany, Spain), of different ages (20–75 years), took one “selfie” image by the frontal camera of their smartphones whereas local dermatologists photographed them with the back camera of the same smartphone. The same nine facial signs of these subjects were initially graded by these local dermatologists, using referential Skin Aging Atlases. All 314 “selfies” images were then further automatically analyzed by the algorithm. The severity of facial signs (wrinkles, pigmentation, ptosis, skin folds etc.) were statistically compared to the assessments made by the three dermatologists, taken as ground truth. Results Highly significant coefficients of correlation (P < 0.001) were found in the three cohorts between the grades provided by the system and those from dermatologists in live. The back camera – of a better resolution than the frontal one – seems affording slightly more significant correlations. However, although significantly correlated, the signs of vascular disorders and cheek skin pores present some disparities that are likely linked to the technical diversity of smartphones or self‐shootings, leading to lower coefficients of correlations. Conclusion This automatic scoring system offers a promising approach in the harmonization of Dermatological assessments of skin facial signs and their changes with age or the follow up of anti‐aging treatments.