Towards the Development of a Thyroid Ultrasound Biometric Scheme Based on Tissue Echo-morphological Features

This paper proposes a biometric system based on features extracted from the thyroid tissue accessed through 2D ultrasound. Tissue echo-morphology, which accounts for the intensity (echogenicity), texture and structure has started to be used as a relevant parameter in a clinical setting. In this paper, features related to texture, morphology and tissue reflectivity are extracted from the ultrasound images and the most discriminant ones are selected as an input for a prototype biometric identification system. Several classifiers were tested, with the best results being achieved by a combination of classifiers (k-Nearest Neighbors, MAP and entropy distance). Using leave-one-out cross-validation method the identification rate was up to 94%. Features related to texture and echogenicity were tested individually with high identification rates up to 78% and 70%, respectively. This suggests that the acoustic impedance (reflectivity or echogenicity) of the tissue as well as texture are feasible parameters to discriminate between distinct subjects. This paper shows the effectiveness of the proposed classification, which can be used not only as a new biometric modality but also as a diagnostic tool.