A quantitative technique to analyze and evaluate microstructures of skin hair follicles based on mueller matrix polarimetry

In this study, we propose a quantitative technique to analyze and evaluate microstructures of skin hair follicles based on Mueller Matrix transmission microscopy. We measure the Mueller matrix polar decomposition (MMPD) parameter images to reveal the characteristic linear birefringence distribution induced by hair follicles in mouse skin tissue samples. The results indicate that the Mueller matrix-derived parameters can be used to reveal the location and structural integrity of hair follicles. For accurate hair follicle location identification and quantitative structural evaluations, we use the image segmentation method, sliding window algorithm, and image texture analysis methods together to process the Mueller matrix-derived images. It is demonstrated that the hair follicle regions can be more accurately recognized, and their locations can be precisely identified based on the Mueller matrix-derived texture parameters. Moreover, comparisons between manual size measurement and polarimetric calculation results confirm that the Mueller matrix parameters have good performance for follicle size estimation. The results shown in this study suggest that the technique based on Mueller matrix microscopy can realize automatically hair follicle identification, detection, and quantitative evaluation. It has great potential in skin structure-related studies and clinical dermatological applications.

Abstract licence: CC BY

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