Utilizing deep learning for dermal matrix quality assessment on in vivo line‐field confocal optical coherence tomography images

Line‐field confocal optical coherence tomography (LC‐OCT) is an imaging technique providing non‐invasive “optical biopsies” with an isotropic spatial resolution of ∼1  μm and deep penetration until the dermis. Analysis of obtained images is classically performed by experts, thus requiring long and fastidious training and giving operator‐dependent results. In this study, the objective was to develop a new automated method to score the quality of the dermal matrix precisely, quickly, and directly from in vivo LC‐OCT images. Once validated, this new automated method was applied to assess photo‐aging‐related changes in the quality of the dermal matrix.

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