Fully automatic segmentation of ultrasound common carotid artery images based on machine learning

Neurocomputing

Volumn 151, Issue P1, 2015, Pages 161-167

  Menchón Lara, Rosa María ^a   Sancho Gómez, José Luis ^a  

^a TECHNICAL UNIVERSITY OF CARTAGENA   (Spain)

Author keywords

Atherosclerosis; Auto encoders; Deep learning; Intima media thickness; Pattern recognition; Ultrasound imaging

Indexed keywords

ARTIFICIAL INTELLIGENCE; BLOOD VESSELS; COMPLEX NETWORKS; DIAGNOSIS; DISEASES; LEARNING SYSTEMS; NEURAL NETWORKS; PATHOLOGY; PATTERN RECOGNITION; ULTRASONIC APPLICATIONS; ULTRASONIC IMAGING;

ATHEROSCLEROSIS; AUTO ENCODERS; DEEP LEARNING; INTIMA-MEDIA THICKNESS; ULTRASOUND IMAGING;

IMAGE SEGMENTATION;

ACCURACY; ARTERIAL WALL THICKNESS; ARTICLE; ATHEROSCLEROSIS; AUTOMATED PATTERN RECOGNITION; B SCAN; CALCULATION; CAROTID ARTERY; IMAGE ANALYSIS; IMAGE QUALITY; MACHINE LEARNING; MATHEMATICAL ANALYSIS; ULTRASOUND; ULTRASOUND SCANNER;

EID: 84922693250     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2014.09.066     Document Type: Article

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