Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/125272
Author(s): Catarina Castro
Carlos Alberto Conceição António
Luísa Costa Sousa
Title: Carotid ultrasound image analysis using artificial neural networks
Issue Date: 2019
Abstract: 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.
Subject: Engenharia, Matemática, Ciências da Saúde, Ciências da engenharia e tecnologias, Matemática, Ciências médicas e da saúde
Engineering, Mathematics, Health sciences, Engineering and technology, Mathematics, Medical and Health sciences
Scientific areas: Ciências da engenharia e tecnologias
Engineering and technology
Ciências exactas e naturais::Matemática
Natural sciences::Mathematics
Ciências médicas e da saúde
Medical and Health sciences
URI: https://hdl.handle.net/10216/125272
Source: M2D2019-8th International Conference on Mechanics and Materials Design
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: restrictedAccess
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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