This paper aims at developing an ultrasound-based diagnostic measure quantifying plaque
activity and the likelihood of asymptomatic lesions to produce neurological symptoms. Based
on echogenicity the methodology has been successfully applied on longitudinal ultrasound
images of the carotid artery bifurcation. Transverse ultrasound images incorporate noise,
artifacts, shadowing and reverberation. Nevertheless, transverse images are a resource not yet
fully explored. The comparison of sequential transverse images minimizes the intrinsic scale
variability between operators and ultrasound devices. Based on pixel level tissue classification, the use of an artificial neural network analysis appled to transverse images allows identifying vulnerable or unstable echolucent plaques.
Type (Professor's evaluation):
Proceedings of the 8th International Conference on Mechanics and Materials Design, M2D2019, Bologna, 4-6 setembro 2019, paper ref: 109, pp.231-234, Ed. J.F. Silva Gomes Shaker A. Meguid e Dario Croccolo, Società Editrice Esculapio s.r.l.
No. of pages: