VESSEL DETECTION IN CAROTID ULTRASOUND IMAGES USING ARTIFICIAL NEURAL NETWORKS

• Type: Article in International Conference Proceedings Book
• Date: 2018

Authors

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

Conference proceedings International

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

Pages: 1169-1172

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

Lisbon, Portugal, 22-26 July 2018

Indexing

ISI Proceedings

ISI Web of Knowledge - 1 Citation

Scientific classification

CORDIS: Health sciences > Medical sciences ; Technological sciences > Engineering

FOS: Medical and Health sciences ; Engineering and technology

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific

Notes: 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. of pages: 4