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

We 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 ≈10−6) than the previously used MGVR 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.