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用于化妆品和皮肤护理研究的皮肤荧光摄影技术现状:从分子光谱到人工智能图像分析

State-of-the-Art in Skin Fluorescent Photography for Cosmetic and Skincare Research: From Molecular Spectra to AI Image Analysis.

作者信息

Chekanov Konstantin, Danko Daniil, Tlyachev Timur, Kiselev Konstantin, Hagens Ralf, Georgievskaya Anastasia

机构信息

Haut.AI OÜ, Telliskivi 60a/8, 10412 Tallinn, Harjumaa, Estonia.

Beiersdorf AG, Beiersdorfstraße 1-9, 22529 Hamburg, Germany.

出版信息

Life (Basel). 2024 Oct 6;14(10):1271. doi: 10.3390/life14101271.

Abstract

Autofluorescence is a remarkable property of human skin. It can be excited by UV and observed in the dark using special detection systems. The method of fluorescence photography (FP) is an effective non-invasive tool for skin assessment. It involves image capturing by a camera the emission of light quanta from fluorophore molecules in the skin. It serves as a useful tool for cosmetic and skincare research, especially for the detection of pathological skin states, like acne, psoriasis, etc. To the best of our knowledge, there is currently no comprehensive review that fully describes the application and physical principles of FP over the past five years. The current review covers various aspects of the skin FP method from its biophysical basis and the main fluorescent molecules of the skin to its potential applications and the principles of FP recording and analysis. We pay particular attention to recently reported works on the automatic analysis of FP based on artificial intelligence (AI). Thus, we argue that FP is a rapidly evolving technology with a wide range of potential applications. We propose potential directions of the development of this method, including new AI algorithms for the analysis and expanding the range of applications.

摘要

自体荧光是人体皮肤的一种显著特性。它可被紫外线激发,并使用特殊检测系统在黑暗中观察到。荧光摄影(FP)方法是一种用于皮肤评估的有效非侵入性工具。它涉及通过相机捕捉皮肤中荧光团分子发射的光量子。它是化妆品和护肤品研究的有用工具,尤其用于检测痤疮、牛皮癣等病理性皮肤状态。据我们所知,目前尚无全面综述充分描述过去五年中FP的应用和物理原理。本综述涵盖了皮肤FP方法的各个方面,从其生物物理基础和皮肤的主要荧光分子到其潜在应用以及FP记录与分析的原理。我们特别关注最近报道的基于人工智能(AI)的FP自动分析的研究成果。因此,我们认为FP是一项快速发展的技术,具有广泛的潜在应用。我们提出了该方法的潜在发展方向,包括用于分析的新AI算法以及扩大应用范围。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8187/11509763/8913cbabeb6d/life-14-01271-g001.jpg

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