Carotid ultrasound image analysis using artificial neural networks

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Catarina Castro (Author) FEUP; Carlos Alberto Conceição António (Author) FEUP; Luísa Costa Sousa (Author) FEUP

Conference proceedings International

Title: M2D2019-8th International Conference on Mechanics and Materials Design

Pages: 131-134

Scientific classification

CORDIS: Technological sciences > Engineering ; Physical sciences > Mathematics ; Health sciences

FOS: Engineering and technology ; Natural sciences > Mathematics ; Medical and Health sciences

Other information

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

Notes: 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: 4