This project proposes an alternate method to DIN/ISO parameters for analyzing the effects of intrinsic and extrinsic aging on skin morphology. This method improves the efficacy of assessing aging by evaluating the surface and subsurface of the skin. The volumetric data obtained using OCT was processed using a machine learning approach to obtain DEJ segmentation, which was further segmented to obtain the morphological information of the micro-plateaus. The results showed that the flattening of DEJ due to aging is accompanied by changes in the size and shape of micro-plateaus in the DEJ.
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