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In 2005, our group have performed the first-ever use of augmented reality (AR) in medical diagnosis and medical treatment of varicose veins. AR has been used in leg vein treatment to search feeder veins bellow resilient telangiectasias. AR in combination with duplex ultrasound (DU) to evaluate refluxing saphenous veins, improved diagnostic accuracy and identified two situations where semiotics was uncapable to detect or misleading: the presence of invisible feeder veins under telangiectasias and asymptomatic saphenous reflux under varicose veins. This ambiguity implied the need for a diagnostic decision tree before starting varicose vein treatment. A 9-cell table was conceived to comprehend such a decision tree comprising 2 main questions: Question 1: On the horizontal rows: what are the types of varicose veins (with or without reflux on saphenous veins and/or perforant veins), if any? Question 2: On the vertical columns: which kind of telangiectasias does the patient have (with or without feeder veins connected), if any? A thorough DU evaluation answers question 1 and determines if there is axial reflux or not. AR answers question 2 determining if there are feeder veins or not. This proposed classification is intended to guide leg vein treatment and is not intended to replace any other scores, such as the Comprehensive Classification System for Chronic Venous Disorders (CEAP) or the Venous Clinical Severity Score (VCSS). This is a simple classification system that can be used for medical decision, health economics outcomes research and for outcome evaluation following aesthetic vein treatment.