Joint segmentation and characterization of the dermis in 50 MHz ultrasound 2D and 3D images of the skin

International audienceHighlights• The signal statistics in 50 MHz high frequency ultrasound images of the dermis are studied accurately layer by layer.• An automatic, accurate segmentation method is developed, which is highly resistant to artifacts thanks to the use of elaborate non-linear filters and a multiple loss level-set segmentation algorithm.• Based on fits to a Nakagami law, a score is computed for characterizing skin photo aging.• The joint segmentation and characterization algorithm is designed to be applied to 2D and 3D images.AbstractWe propose a novel joint segmentation and characterization algorithm for the assessment of skin aging using 50 MHz high-frequency ultrasound images. The proposed segmentation method allows a fine determination of the envelope signal's statistics in the dermis as a function of depth. The sequence of statistical estimates obtained is then combined into a single aging score. The segmentation is based on tailored recursive non-linear filters. The epidermis and the dermis are jointly segmented with a non-parametric active contour combining a texture criterion, an epidermis indicator map and the geometric constraint of horizontal continuity. The algorithm is designed to apply to 2D and 3D images as well. We evaluated skin photo-aging on ultrasound images with an experimental study on a cohort of 76 women separated into 2 groups of different ages. Two aging scores are computed from the images: local dermal contrast and skin roughness. We show that these scores are much better at identifying the two groups (p-value) than the previously used indicator (p-value 0.046). Moreover, we find that a combined score more reliably evaluates skin photo-aging, with 84% success, than a scoring of the ultrasound images by 4 experts