Stratum corneum nanotexture feature detection using deep-learning and spatial analysis: a non-invasive tool for skin barrier assessment
Non classé | Scientific PublicationsStratum corneum nanotexture feature detection using deep-learning and spatial analysis: a non-invasive tool for skin barrier assessment
GigaScience, 1-10, September 2024
Building on prior work, this study improves atopic dermatitis severity assessment by refining Loretta’s AFM and AI metrics—and introducing a new one. Using over 1,000 labeled skin cell images, our AI detects CNOs with 91% accuracy. The new Effective Corneocyte Topographical Index (ECTI) adds spatial analysis to map CNO distribution, boosting reliability. The research shows Loretta’s method is even more effective at distinguishing atopic dermatitis severity levels, making it a powerful, noninvasive tool for skin health evaluation.
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