L'Oréal Research and Innovation, 9 Rue Pierre Dreyfus, 92110, Clichy, France.
Dermatology, Venereology and Allergy Department, Charité Medicine University, Charitéplatz 1, 10115, Berlin, Germany.
Int J Cosmet Sci. 2019 Oct;41(5):472-478. doi: 10.1111/ics.12563. Epub 2019 Sep 4.
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.
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.
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.
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.
确认一种基于算法的自动评分系统的稳健性和有效性,该系统通过欧洲白种女性使用智能手机前置摄像头拍摄的“自拍”照片,对 9 种面部特征的严重程度进行评分,并通过皮肤科评估进行验证。
来自三个国家(法国、德国和西班牙)的 157 名白种女性,年龄不同(20-75 岁),使用智能手机的前置摄像头拍摄一张“自拍”照片,而当地皮肤科医生使用同一部智能手机的后置摄像头为她们拍照。这些受试者的同样的 9 种面部特征最初由当地皮肤科医生使用参考皮肤衰老图谱进行分级。所有 314 张“自拍”图像随后由算法进一步自动分析。面部特征的严重程度(皱纹、色素沉着、上睑下垂、皮肤褶皱等)与三位皮肤科医生的评估结果(作为基准)进行统计学比较。
在三个队列中,系统提供的评分与现场皮肤科医生的评分之间存在高度显著的相关性(P<0.001)。分辨率优于前置摄像头的后置摄像头似乎提供了略微更高的相关性。然而,尽管相关性显著,但血管紊乱和脸颊皮肤毛孔的迹象存在一些差异,这些差异可能与智能手机或自拍的技术多样性有关,导致相关性系数较低。
这种自动评分系统为皮肤科评估面部特征及其随年龄变化或抗老化治疗的随访提供了一种很有前景的方法。