Texture Analysis in Ultrasound Images of Carotid Plaque Components of Asymptomatic and Symptomatic Subjects (original) (raw)
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Electrical Engineering & Applied Signal Processing Series, 2005
There are indications that the texture of certain components of atherosclerotic carotid plaques in the common carotid artery (CCA), obtained by high resolution ultrasound imaging, may have additional prognostic implication for the risk of stroke. The objective of this study was to perform texture analysis of the middle component of atherosclerotic carotid plaques in 230 CCA plaque ultrasound images (115 asymptomatic and 115 symptomatic). These were manually delineated by a neurovascular expert after normalization and despeckle filtering using the linear despeckle filter (DsFlsmv). Texture features were extracted from the middle plaque component. We found statistical significant differences for some of the texture features extracted, between asymptomatic and symptomatic subjects. The results showed that it may be possible to identify a group of patients at risk of stroke (asymptomatic versus symptomatic) based on texture features extracted from the middle component of the atherosclerotic carotid plaque in ultrasound images of the CCA.
Selection of parameters for texture analysis for the classification of carotid plaques
IEEE Trans Med Imaging, 2003
Abstract: Texture features extracted from high-resolution ultrasound images of carotid plaques can be used for the identification of patients at risk of stroke. This work explores the selection of the parameters for the computation of the texture features, which will yield the best class separation between symptomatic and asymptomatic subjects. The following texture algorithms were investigated on 230 carotid plaque images (recorded from 115 symptomatic and 115 asymptomatic subjects): Spatial Gray Level Dependence Matrices ( ...
2011
Abstract Carotid plaques have been associated with ipsilateral neurological symptoms. High-resolution ultrasound can provide information not only on the degree of carotid artery stenosis but also on the characteristics of the arterial wall including the size and consistency of atherosclerotic plaques. The aim of this study was to determine cerebrovascular risk stratification based on ultrasonic plaque texture features and clinical features in patients with asymptomatic internal carotid artery (ICA) stenosis.
2003
The extraction of features characterizing the structure of atherosclerotic carotid plaques, obtained by high-resolution ultrasound imaging is important for the correct plaque classification and the estimation of the risk of stroke. In this study morphological features were extracted and compared with the well-known texture features spatial gray level dependence matrices (SGLDM), gray level difference statistics (GLDS) and the first order statistics (FOS) for the classification of 330 carotid plaques.
Texture Analysis for the Classification of Carotid Plaques
1998
Abstract The objective of this work is to develop a computer aided system which will facilitate the automated characterization of carotid plaques recorded from high resolution ultrasound images for the identification of individuals with asymptomatic carotid stenosis at risk of stroke. The system consists of the following four modules:(i) image standardization,(ii) image segmentation,(iii) feature extraction and selection,(iv) plaque classification.
Multi-feature texture analysis for the classification of carotid plaques
1999
Abstract We develop a computer aided system which will facilitate the automated characterisation of carotid plaques recorded from high resolution ultrasound images for the identification of individuals with asymptomatic carotid stenosis at risk of stroke. The plaques were classified into: symptomatic or asymptomatic. Ten different texture feature sets were extracted from the segmented plaque image.
Texture Feature Variability in Ultrasound Video of the Atherosclerotic Carotid Plaque
IEEE journal of translational engineering in health and medicine, 2017
The objective of this paper was to investigate texture feature variability in ultrasound video of the carotid artery during the cardiac cycle in an attempt to define new discriminatory biomarkers of the vulnerable plaque. More specifically, in this paper, 120 longitudinal ultrasound videos, acquired from 40 normal (N) subjects from the common carotid artery and 40 asymptomatic (A) and 40 symptomatic (S) subjects from the proximal internal carotid artery were investigated. The videos were intensity normalized and despeckled, and the intima-media complex (IMC) (from the N subjects) and the atherosclerotic carotid plaques (from the A and S subjects) were segmented from each video, in order to extract the M-mode image, and the texture features associated with cardiac states of systole and diastole. The main results of this paper can be summarized as follows: 1) texture features varied significantly throughout the cardiac cycle with significant differences identified between the cardiac ...
Texture-based classification of atherosclerotic carotid plaques
2003
Abstract There are indications that the morphology of atherosclerotic carotid plaques, obtained by high-resolution ultrasound imaging, has prognostic implications. The objective of this study was to develop a computer-aided system that will facilitate the characterization of carotid plaques for the identification of individuals with asymptomatic carotid stenosis at risk of stroke.
Angiology, 2011
We estimated the value of objective, computerized texture analysis of ultrasonic images in distinguishing carotid plaques associated with neurological ipsilateral symptoms (amaurosis fugax [AmF; n ¼ 30], transient ischemic attack [TIA; n ¼ 52], and stroke [n ¼ 55]) from asymptomatic plaques (n ¼ 51). We performed 3 case-control studies (1/symptom with asymptomatic plaques as control). On logistic regression, AmF was independently associated with severity of stenosis, percentage of pixels with gray levels 0 to 10 (PPCS1; measure of echolucency), and spatial gray level dependence matrices (SGLDM) information measure of correlation (IMC-1; texture); TIAs with PPCS1 (echolucency), SGLDM correlation, and skewness (both texture); and stroke with PPCS1, SGLDM correlation, and percentage of pixels with gray levels 11 to 20 (PPCS2; echolucency). The area under the curve of the regression-derived predicted probability for AmF, TIA, and stroke was 0.92, 0.82, and 0.85, respectively (all P < .001). Texture analysis can identify carotid plaques associated with a neurological event, improving the diagnostic value of echolucency measures. Texture analyses could be applied to natural history studies.