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 |
Files in This Item:
File | Description | Size | Format | |
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374214.pdf Restricted Access | Artigo completo | 209.57 kB | Adobe PDF | Request a copy from the Author(s) |
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