VESSEL DETECTION IN CAROTID ULTRASOUND IMAGES USING ARTIFICIAL NEURAL NETWORKS

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2018

Autores

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

Ata de Conferência Internacional

Título: Proceedings of the 6th International Conference Integrity, Reliability and Failure

Páginas: 1169-1172

Proceedings IRF2018: 6th International Conference I ntegrity-Reliability-Failure

Lisbon, Portugal, 22-26 July 2018

Indexação

ISI Proceedings

ISI Web of Knowledge - 1 Citação

Classificação Científica

CORDIS: Ciências da Saúde > Ciências Médicas ; Ciências Tecnológicas > Engenharia

FOS: Ciências médicas e da saúde ; Ciências da engenharia e tecnologias

Outras Informações

ID Authenticus: P-00Q-XFK

Abstract (EN): Carotid Doppler ultrasound and imaging are focused on the visualization, identification and measurement of vessels and blood flow providing critical diagnostic information on symptomatic or asymptomatic stenotic or embolic accidents. Ultrasound imaging is a complicated interplay between physical principles and signal processing methods. In this work the development of a new algorithm for vessel identification and image segmentation in ultrasound images is reported. A fully automatic technique based on pixel intensity distribution alleviates the laborious and time consuming manual measurement and classification of the carotid artery.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Notas: IRF2018 ¿ 6th International Conference on Integrity, Reliability and Failure, Lisbon-Portugal, 22-26 July, 2018, Ed. J.F. Silva Gomes e Shaker A. Meguid, Edições INEGI/FEUP, Symp-10: Biomechanics of Cardiovascular and Orthopaedic Desease, Book of abstracts: pp. 473-474, ref: 7293, CD-ROM: pp. 1169-1172, 2018.

Nº de páginas: 4