Open AccessAn integrated system for the complete segmentation of the common carotid artery bifurcation in ultrasound images
Author(s) -
Christos P. Loizou,
M. Pantziaris
Publication year - 2015
Publication title -
journal of biomedical engineering and informatics
Language(s) - English
Resource type - Journals
eISSN - 2377-939X
pISSN - 2377-9381
DOI - 10.5430/jbei.v1n1p11
Subject(s) - segmentation , common carotid artery , ultrasound , medicine , stroke (engine) , neurovascular bundle , internal carotid artery , intima media thickness , radiology , carotid bifurcation , carotid arteries , 3d ultrasound , stenosis , artificial intelligence , bifurcation , image segmentation , computer vision , cardiology , computer science , anatomy , mechanical engineering , engineering , physics , nonlinear system , quantum mechanics
The complete segmentation of the common carotid artery (CCA) bifurcation in ultrasound images is important for the evaluation of atherosclerosis disease and the quantification of the risk of stroke. The current research work further evaluates and validates a semi-automated (SA) snake’s based segmentation system suitable for the complete segmentation of the CCA bifurcation in two-dimensional (2D) ultrasound images. The proposed system semi-automatically estimates the intima-media thickness (IMT), the atherosclerotic carotid plaque borders and dimensions, the internal carotid artery (ICA) origin’s stenosis, the carotid diameter (D), as well as other geometric measurements of the atherosclerotic carotid plaque. The system was evaluated on 300 2D longitudinal ultrasound images of the CCA bifurcation with manual (M) segmentations available from a neurovascular expert. No statistical significant differences between all M and SA IMT, plaque and D segmentation measurements were found. In a future study, texture features extracted from the intima-media complex (IMC) may be used to separate subjects in high and low risk groups, which may develop a stroke. However, a larger scale study is required for evaluating the system before its application in the real clinical practice.