Automated OCTA vessel count algorithm for quantitative analysis of skin disease activity

In dermatological practice, assessment of disease severity in inflammatory skin diseases typically relies on visual-based scoring. Since this method is prone to inter-observer variabilities, there is an unmet need for user-independent biomarkers for quantitative disease scoring and early treatment response detection. This work demonstrates a novel automated vessel count algorithm that aims to detect the pathological vessel elongation in patients with psoriasis and atopic dermatitis. The algorithm utilizes optical coherence tomography angiography images. Preliminary results from patient data demonstrate the capability of the technique to differentiate between healthy and inflamed skin.<p></p>