Fully automated segmentation and tracking of the intima media thickness in ultrasound video sequences of the common carotid artery

Automatic Measurement of the Carotid Blood Flow for Wearable Sensors: A Pilot Study

The assessment of the velocity of blood flowing in the carotid, in modern clinical practice, represents an important exam performed both in emergency situations and as part of scheduled screenings. It is typically performed by an expert sonographer who operates a complex and costly clinical echograph. Unfortunately, in developing countries, in rural areas, and even in crowded modern cities, the access to this exam can be limited by the lack of suitable personnel and ultrasound equipment. The recent availability of low-cost, handheld devices has contributed to solving part of the problem, but a wide access to the exam is still hampered by the lack of expert sonographers. In this work, an automated procedure is presented with the hope that, in the near future, it can be integrated into a low-cost, handheld instrument that is also suitable for self-measurement, for example, as can be done today with the finger oximeter. The operator should only place the probe on the neck, transversally with respect to the common tract of the carotid. The system, in real-time, automatically locates the vessel lumen, places the sample volume, and performs an angle-corrected velocity measurement of the common carotid artery peak velocity. In this study, the method was implemented for testing on the ULA-OP 256 scanner. Experiments on flow phantoms and volunteers show a performance in sample volume placement similar to that achieved by expert operators, and an accuracy and repeatability of 3.2% and 4.5%, respectively.

Carotid Ultrasound Boundary Study (CUBS): An Open Multicenter Analysis of Computerized Intima-Media Thickness Measurement Systems and Their Clinical Impact

Common carotid intima-media thickness (CIMT) is a commonly used marker for atherosclerosis and is often computed in carotid ultrasound images. An analysis of different computerized techniques for CIMT measurement and their clinical impacts on the same patient data set is lacking. Here we compared and assessed five computerized CIMT algorithms against three expert analysts' manual measurements on a data set of 1088 patients from two centers. Inter- and intra-observer variability was assessed, and the computerized CIMT values were compared with those manually obtained. The CIMT measurements were used to assess the correlation with clinical parameters, cardiovascular event prediction through a generalized linear model and the Kaplan-Meier hazard ratio. CIMT measurements obtained with a skilled analyst's segmentation and the computerized segmentation were comparable in statistical analyses, suggesting they can be used interchangeably for CIMT quantification and clinical outcome investigation. To facilitate future studies, the entire data set used is made publicly available for the community at http://dx.doi.org/10.17632/fpv535fss7.1.

A Review on Joint Carotid Intima-Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework

Cardiovascular diseases (CVDs) are the top ten leading causes of death worldwide. Atherosclerosis disease in the arteries is the main cause of the CVD, leading to myocardial infarction and stroke. The two primary image-based phenotypes used for monitoring the atherosclerosis burden is carotid intima-media thickness (cIMT) and plaque area (PA). Earlier segmentation and measurement methods were based on ad hoc conventional and semi-automated digital imaging solutions, which are unreliable, tedious, slow, and not robust. This study reviews the modern and automated methods such as artificial intelligence (AI)-based. Machine learning (ML) and deep learning (DL) can provide automated techniques in the detection and measurement of cIMT and PA from carotid vascular images. Both ML and DL techniques are examples of supervised learning, i.e., learn from "ground truth" images and transformation of test images that are not part of the training. This review summarizes (1) the evolution and impact of the fast-changing AI technology on cIMT/PA measurement, (2) the mathematical representations of ML/DL methods, and (3) segmentation approaches for cIMT/PA regions in carotid scans based for (a) region-of-interest detection and (b) lumen-intima and media-adventitia interface detection using ML/DL frameworks. AI-based methods for cIMT/PA segmentation have emerged for CVD/stroke risk monitoring and may expand to the recommended parameters for atherosclerosis assessment by carotid ultrasound.

Estimating Arterial Wall Deformations from Automatic Key-Point Detection and Matching

Assessing arterial-wall motion and deformations may reveal pathologic alterations in biomechanical properties of the parietal tissues and, thus, contribute to the detection of vascular disease onset. Ultrasound image sequences allow the observation of this motion and many methods have been developed to estimate temporal changes in artery diameter and wall thickness and to track 2-D displacements of selected points. Some methods enable the assessment of shearing or stretching within the wall, but none of them can estimate all these deformations simultaneously. The method herein proposed was devised to simultaneously estimate translation, compression, stretching and shearing of the arterial wall in ultrasound B-mode image sequences representing the carotid artery longitudinal section. Salient blob-like patterns, called key points, are automatically detected in each frame and matched between successive frames. A robust estimator based on an affine transformation model is then used to assess frame-to-frame motion explaining at best the key-point matches and to reject outliers. Realistic simulated image sequences were used to evaluate the accuracy and robustness of the method against ground truth. The method was also visually assessed on clinical image sequences, for which true deformations are unknown.

Fully Automated Integrated Segmentation of Carotid Artery Ultrasound Images Using DBSCAN and Affinity Propagation

Purpose

B-mode ultrasound images are used in identifying the presence of fat deposit if any in carotid artery. The intima media, lumen, bifurcation boundary is detected by the echogenic characteristics embedded in the carotid artery.

Methods

A fully automatic self-learning based segmentation is proposed by extracting the edges by a modified affinity propagation, which are given as inputs to the Density Based Spatial Clustering of Applications with Noise (DBSCAN) for super pixel segmentation. The segmented results are analyzed with Gradient Vector Flow (GVF) snake model and Particle Swarm Optimization (PSO) clustering based segmentation using various performance measures.

Results

The proposed parameter free, fully automatic segmentation method combining Affinity propagation and DBSCAN are evaluated for a database of 361 images and gives reinforced results in the longitudinal B-mode ultrasound images. The proposed approach gives an improved accuracy of 12% increase when compared with the manual segmentation and 15% compared with segmentation by affinity propagation and DBSCAN when performed individually. The average Root Mean Square Error (RMSE) is 110 ± 44 µm.

Conclusion

Extracted edge points are used for clustering in a fully automated carotid artery segmentation approach.

Fully Automatic Measurement of Intima-Media Thickness in Ultrasound Images of the Common Carotid Artery Based on Improved Otsu's Method and Adaptive Wind Driven Optimization

The intima media thickness (IMT) of the common carotid artery (CCA) can be used to predict the risk of atherosclerosis. Many image segmentation techniques have been used for IMT measurement. However, severe noise in the ultrasound image can lead to erroneous segmentation results. To improve the robustness to noise, a fully automatic method, based on an improved Otsu's method and an adaptive wind-driven optimization technique, is proposed for estimating the IMT (denoted as "improved Otsu-AWDO"). First, an advanced despeckling filter, i.e., " Nagare's filter" is used to address the speckle noise in the carotid ultrasound images. Next, an improved fuzzy contrast method (IFC) is used to enhance the region of the intima media complex (IMC) in the blurred filtered images. Then, a new method is used for automatic extraction of the region of interest (ROI). Finally, the lumen intima interface and media adventitia interface are segmented from the IMC using improved Otsu-AWDO. Then, 156 B-mode longitudinal carotid ultrasound images of six different datasets are used to evaluate the performance of the automatic measurements. The results indicate that the absolute error of proposed method is only 10.1 ± 9.6 (mean ± std in μm). Moreover, the proposed method has a correlation coefficient as high as 0.9922, and a bias as low as 0.0007. From comparison with previous methods, we can conclude that the proposed method has strong robustness and can provide accurate IMT estimations.

Vascular deformation in human atherosclerotic carotid artery evaluated by 2D analysis of ultrasonography

OBJECTIVES

Common carotid artery (CCA) remodelling in the atherosclerosis process is an inherent necessary element that decreases the progress of significant lumen compromise. The present study used a semi-automated method to assess relationships of intima-media thickness (IMT), lumen diameter (LD) and inter-adventitial diameter (IAD) using ultrasound B-mode images of atherosclerotic carotid artery.

METHODS

In the cross-sectional study, 120 male subjects (age range: 40-60 years) were classified into four research groups namely control, mild, moderate, and severe stenosis. The maximum near and far wall IMT, mean of both walls' IMT and IAD, and also LD of the left CCA were extracted for all participants. Pearson correlation coefficient was utilized to investigate relationships of IMT, LD, and IAD.

RESULTS

Results revealed that the maximum far and near wall IMT, mean of both walls' IMT and IAD in the CCA were significantly different in stenosis patients and the control group (p< 0.001). However, there were no significant differences among the four studied groups in terms of LD of CCA (p = 0.65). There was a stronger correlation between mean of both walls' IMT and IAD in comparison with mean far wall IMT and IAD (p < 0.001).

CONCLUSIONS

Results indicated that changes of IAD in the left CCA were associated with carotid deformation, and thus it can be considered as a predictor of atherosclerosis process.

Carotid artery ultrasound image analysis: A review of the literature

Stroke is one of the prominent causes of death in the recent days. The existence of susceptible plaque in the carotid artery can be used in ascertaining the possibilities of cardiovascular diseases and long-term disabilities. The imaging modality used for early screening of the disease is B-mode ultrasound image of the person in the artery area. The objective of this article is to give a widespread review of the imaging modes and methods used for studying the carotid artery for identifying stroke, atherosclerosis and related cardiovascular diseases. We encompass the review in methods used for artery wall tracking, intima-media, and lumen segmentation which will help in finding the extent of the disease. Due to the characteristics of the imaging modality used, the images have speckle noise which worsens the image quality. Adaptive homomorphic filtering with wavelet and contourlet transforms, Levy Shrink, gamma distribution were used for image denoising. Learning-based neural network approaches for denoising give better edge preservation. Domain knowledge-based segmentation approaches have proved to provide more accurate intima-media thickness measurements. There is a requirement of useful fully automatic segmentation approaches, 3D, 4D systems, and plaque motion analysis. Taking into consideration the image priors like geometry, imaging physics, intensity and temporal data, image analysis has to be performed. Encouragingly more research has focused on content-specific segmentation and classification techniques. With the evaluation of machine learning algorithms, classifying the image as with or without a fat deposit has gained better accuracy and sensitivity. Machine learning-based approaches like self-organizing map, k-nearest neighborhood and support vector machine achieve promising accuracy and sensitivity in classification. The literature reveals that there is more scope in identifying a patient-specific model in a fully automatic manner.

Biomechanical characteristics of isolated carotid atherosclerotic plaques assessed by ultrasonography

BACKGROUND

The aim of this study was to assess the biomechanical characteristics of carotid atherosclerotic plaques using intima-media thickness (IMT) automatic tracking combined with acoustic densitometry (AD) imaging, and to elucidate the relationship between biomechanical characteristics and inflammatory activity of corresponding plaques evaluated by 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT).

METHODS

Sixty-one patients with isolated carotid atherosclerotic plaques underwent conventional carotid ultrasonography, IMT automatic tracking, and acoustic densitometry (AD) imaging. Following these assessments, patients received an 18F-FDG PET/CT scan within 24 hours. We quantified biomechanical and AD parameters including IMT strain rate (SR), IMT time strain rate (TR), and corrected average image intensity value (AIIc%) on the upstream, fibrous cap top, and downstream regions of the plaque and compared them to the reference area(normal intima adjacent to the upstream of the assessed plaque). Target background ratio (TBR) was acquired by 18F-FDG PET/CT for evaluating the inflammatory activity of corresponding plaques. We further divided all participants into an inflammatory group (TBR≥1.25) and non-inflammatory group (TBR<1.25) measures of SR/TR and AIIc% in the two groups were compared and analyzed.

RESULTS

SR/TR were significantly lower in the plaque group when compared to reference area. SR/TR at the cap top area (CTA) and downstream area (DA) of the plaques were lower than those in the reference area (P<0.05) while there was no statistically significant difference in SR or TR of the upstream area (UA) between the plaque and reference area. SR/TR were significantly greater for UA than CTA and DA (P<0.05 for both). AIIc% was significantly lower for UA and CTA than that for DA (P<0.05). The SR/TR of plaque regions were negatively correlated with corresponding AIIc% (r=-0.74, r=-0.75, P<0.05). TR in the inflammatory group was significantly lower than in the non-inflammatory group (P<0.05), while SR and AIIc% showed no statistically significant difference. TR demonstrated a significant negative correlation with TBR (r=-0.83, P<0.05). Receiver operating characteristic curve (ROC) analysis showed that the area under the curve (AUC) of TR was 0.87. Furthermore, TR less than 75.06‰ demonstrated a sensitivity of 88.0% and a specificity of 80.6% for the identification of inflammatory plaques.

CONCLUSIONS

IMT automatic tracking, combined with AD imaging, can be applied to identify the anisotropic biomechanical features of carotid plaques. This novel imaging modality may be used to provide an early assessment of the biomechanical characteristics of carotid plaques. Additionally, the TR parameter was associated with plaque inflammation reaction, possibly providing a new indicator for the early identification of plaque vulnerability.

A dynamic ultrasound simulation of a pulsating three-layered CCA for validation of two-dimensional wall motion and blood velocity estimation algorithms

PURPOSE

A dynamic ultrasound simulation model for the common carotid artery (CCA) with three arterial layers for validation of two-dimensional wall motion and blood velocity estimation algorithms is proposed in the present study. This model describes layers with not only characteristics of echo distributions conforming to clinical ones but also varying thicknesses, axial, and radial displacements with pulsatile blood pressure during a cardiac cycle.

METHODS

The modeling process is as follows: first, a geometrical model according with the clinical structure size of a CCA is built based on the preset layer thicknesses and the diameter of lumen. Second, a three-dimensional scatterer model is constructed by a mapping with a Hilbert space-filling curve from the one-dimensional scatterer distribution with the position and amplitude following Gamma and Gaussian distributions, respectively. The characteristics of three layers and blood are depicted by smoothly adjusting the scatterer density, the scale, and shape parameters of the Gamma distribution as well as the mean and standard deviation of the Gaussian distribution. To obtain the values of parameters of scatterer distributions, including the shape parameter, density, and intensity, for arterial layers and blood, the envelope signals simulated from different configurations of scatterer distribution are compared with those from different kinds of tissue of CCAs in vivo through a statistic analysis. Finally, the dynamic scatterer model is realized based on the blood pressure, elasticity modulus of intima-media (IM) and adventitia, varying IM thickness, axial displacement of IM as well as blood flow velocity at central axis during a cardiac cycle. Then, the corresponding radiofrequency (RF) signals, envelope signals, and B-mode images of the pulsatile CCA are generated in a dynamic scanning mode using Field II platform.

RESULTS

The three arterial layers, blood, and surrounding tissue in simulated B-mode ultrasound images are clearly legible. The results based on a statistical analysis for the envelope signals from 30 simulations indicate that the echo characteristics of blood, intima, media, and adventitia are in accordant with clinical ones. The maximum relative errors between the preset geometrical sizes and the measured ones from the simulated images for the diameter of the lumen and the thicknesses of the intima, media, and adventitia are 0.13%, 3.89%, 1.35%, and 0.06%, respectively. For the dynamic parameters, the variation in IM thickness, the radial displacements of lumen and adventitia as well as the axial displacement of IM and blood flow velocity are measured with the mean relative errors of 68.03%, 9.27%, 2.10%, 4.93%, and 17.34%, respectively.

CONCLUSION

The simulated results present static sizes and dynamical variations according with preset values; echo distributions conforming to clinical versions. Therefore, the presented simulation model could be useful as a data source to evaluate the performance of studies on measurements of ultrasound-based tissue structures and dynamic parameters for the CCA layers.

A Review on Atherosclerotic Biology, Wall Stiffness, Physics of Elasticity, and Its Ultrasound-Based Measurement

Functional and structural changes in the common carotid artery are biomarkers for cardiovascular risk. Current methods for measuring functional changes include pulse wave velocity, compliance, distensibility, strain, stress, stiffness, and elasticity derived from arterial waveforms. The review is focused on the ultrasound-based carotid artery elasticity and stiffness measurements covering the physics of elasticity and linking it to biological evolution of arterial stiffness. The paper also presents evolution of plaque with a focus on the pathophysiologic cascade leading to arterial hardening. Using the concept of strain, and image-based elasticity, the paper then reviews the lumen diameter and carotid intima-media thickness measurements in combined temporal and spatial domains. Finally, the review presents the factors which influence the understanding of atherosclerotic disease formation and cardiovascular risk including arterial stiffness, tissue morphological characteristics, and image-based elasticity measurement.

Appraisal of different ultrasonography indices in patients with carotid artery atherosclerosis

In this study a semi-automated image-processing based method was designed in which the parameters such as intima-media thickness (IMT), resistive index (RI), pulsatility index (PI), dicrotic notch index (DNI), and mean wavelet entropy (MWE) were evaluated in B-mode and Doppler ultrasound in patients presenting with carotid artery atherosclerosis. In a cross-sectional design, 144 men were divided into four groups of control, mild, moderate and severe stenosis subjects. In all individuals, far wall IMT, RI, PI, DNI, and MWE of the left common carotid artery (CCA) were extracted using the proposed method. Our findings showed that the maximum far wall IMT, RI, PI, DNI in the CCA were significantly different in the patients with mild, moderate, and severe stenosis compared to control group (p-value < 0.05), however, there were no significant differences in MWE among the four groups (p-value > 0.05). The proposed method can help physicians to better identify patients at risk of cardiovascular diseases.

A Fully-Automatic Method to Segment the Carotid Artery Layers in Ultrasound Imaging: Application to Quantify the Compression-Decompression Pattern of the Intima-Media Complex During the Cardiac Cycle

The aim of this study was to introduce and evaluate a contour segmentation method to extract the interfaces of the intima-media complex in carotid B-mode ultrasound images. The method was applied to assess the temporal variation of intima-media thickness during the cardiac cycle. The main methodological contribution of the proposed approach is the introduction of an augmented dimension to process 2-D images in a 3-D space. The third dimension, which is added to the two spatial dimensions of the image, corresponds to the tentative local thickness of the intima-media complex. The method is based on a dynamic programming scheme that runs in a 3-D space generated with a shape-adapted filter bank. The optimal solution corresponds to a single medial axis representation that fully describes the two anatomical interfaces of the arterial wall. The method is fully automatic and does not require any input from the user. The method was trained on 60 subjects and validated on 184 other subjects from six different cohorts and four different medical centers. The arterial wall was successfully segmented in all analyzed images (average pixel size = 57 ± 20 mm), with average segmentation errors of 47 ± 70 mm for the lumen-intima interface, 55 ± 68 mm for the media-adventitia interface and 66 ± 90 mm for the intima-media thickness. The amplitude of the temporal variations in IMT during the cardiac cycle was significantly higher in the diseased population than in healthy volunteers (106 ± 48 vs. 86 ± 34 mm, p = 0.001). The introduced framework is a promising approach to investigate an emerging functional parameter of the arterial wall by assessing the cyclic compression-decompression pattern of the tissues.

Ultrasound intima-media thickness measurement of the carotid artery using ant colony optimization combined with a curvelet-based orientation-selective filter

PURPOSE

Automatic measurement of the intima-media thickness (IMT) from ultrasound carotid images is an important task in clinical diagnosis. Many computer-based techniques for IMT measurement have been proposed to overcome the limits of manual segmentation. However, the robustness of the algorithms would be influenced by the inherent speckle noise of ultrasound image. This paper proposed a curvelet guided ant colony optimization (CGACO) strategy that could achieve satisfied accuracy for IMT measurement with improved robustness to noise.

METHODS

The curvelet-based orientation-selective (CBOS) filter was first introduced for speckle removal and edge enhancement. Different from conventional methods, CBOS filter processes the curvelet coefficients by orientations rather than by magnitude. Then, a specially designed two-leg ant colony optimization technique, combined with Otsu thresholding and Sobel edge detector, was proposed as a novel segmentation method to extract the media-adventitia (MA) and the lumen-intima (LI) boundaries. Finally, a coupled snake model was employed to further smooth the contours of MA and LI.

RESULTS

In addition to 224 carotid artery images acquired from 34 participants, simulated speckled images with nine levels of noise were also included in the database. The mean absolute distance errors of CGACO for LI interface tracings, MA interface tracings, and IMT measurements were 0.030 ± 0.027, 0.039 ± 0.036, and 0.041 ± 0.036 mm, respectively. Besides, CGACO had a correlation coefficient as high as 0.992 and a bias as low as -0.008. All these measures were comparable to or better than a previous technique and the manual segmentation. On the other hand, CGACO had the highest success rate of 98.7% in the segmentation of real data. It also maintained a much higher success rate in the segmentation of simulated images with different levels of speckle noise.

CONCLUSIONS

The proposed technique showed accurate IMT measurement results. Furthermore, benefiting from the CBOS filter, the robustness to noise of the algorithm was substantially improved. Therefore, CGACO could provide a reliable way to segment the carotid artery from ultrasound images and could be used in clinical practice of IMT measurement, particularly in early atherosclerotic stages.

Automatic Lumen Detection on Longitudinal Ultrasound B-Mode Images of the Carotid Using Phase Symmetry

This article describes a method that improves the performance of previous approaches for the automatic detection of the common carotid artery (CCA) lumen centerline on longitudinal B-mode ultrasound images. We propose to detect several lumen centerline candidates using local symmetry analysis based on local phase information of dark structures at an appropriate scale. These candidates are analyzed with selection mechanisms that use symmetry, contrast or intensity features in combination with position-based heuristics. Several experimental results are provided to evaluate the robustness and performance of the proposed method in comparison with previous approaches. These results lead to the conclusion that our proposal is robust to noise, lumen artifacts, contrast variations and that is able to deal with the presence of CCA-like structures, significantly improving the performance of our previous approach, from 87.5% ± 0.7% of correct detections to 98.3% ± 0.3% in a set of 200 images.

Automatic Measurement of End-Diastolic Arterial Lumen Diameter in ARTSENS

Over past few years, we are developing a system for facilitating large scale screening of patients for cardiovascular risk—arterial stiffness evaluation for noninvasive screening (ARTSENS). ARTSENS is an image-free device that uses a single element ultrasound transducer to obtain noninvasive measurements of arterial stiffness (AS) in a fully automated manner. AS is directly proportional to end-diastolic lumen diameter (Dd). Multilayered structure of the arterial walls and indistinct characteristics of intima-lumen interface (ILI) makes it quite difficult to accurately estimate Dd in A-mode radio-frequency (RF) frames obtained from ARTSENS. In this paper, we propose a few methods based on fitting simple mathematical models to the echoes from arterial walls, followed by a novel method to fuse the information from curve fitting error and distension curve to arrive at an accurate measure of Dd. To bring down the curve fitting time and facilitate processing on low-end processors, a novel approach using the autocorrelation of echoes from opposite walls of the artery has been discussed. The methods were analyzed for their comparative accuracy against reference Dd obtained from 85 human volunteers using Hitachi-Aloka eTRACKING system. Dd from all reported methods show strong and statistically significant positive correlation with eTRACKING and mean error of less than 7% could be achieved. As expected, Dd from all methods show significant positive correlation with age.

Simultaneous extraction of carotid artery intima-media interfaces in ultrasound images: assessment of wall thickness temporal variation during the cardiac cycle

OBJECTIVES

The aim of this work is to present and evaluate a novel segmentation method for localizing the contours of the intima-media complex in the carotid artery wall through longitudinal ultrasound B-mode imaging. The method is used to investigate the association between atherosclerosis risk factors and the cyclic variation of the intima-media thickness during the heart beat.

METHODS

The framework introduced is based on two main features. The first is a simultaneous extraction of both the lumen-intima and the media-adventitia interfaces, using the combination of an original shape-adapted filter bank and a specific dynamic programming scheme. The second is an innovative spatial transformation that eases the extraction of skewed and curved contours, and exploits the result from the previous image as a priori information, when processing the current image. The intima-media thickness is automatically derived from the estimated contours for each time step during the cardiac cycle. Our method was evaluated in vivo on 57 healthy volunteers and 25 patients at high cardiovascular risk. Reference contours were generated for each subject by averaging the tracings performed by three experienced observers.

RESULTS

Segmentation errors were 29 ± 27 μm for the lumen-intima interface, 42 ± 38 μm for the media-adventitia interface, and 22 ± 16 μm for the intima-media thickness. This uncertainty was similar to inter- and intra-observer variability. Furthermore, the amplitude of the temporal variation in thickness of the intima-media layers during the cardiac cycle was significantly higher in at-risk patients compared to healthy volunteers (79 ± 36 vs. 64 ± 26 μm, p = 0.032). Conclusion: The method proposed may provide a relevant diagnostic aid for atherosclerosis screening in clinical studies.

Carotid artery segmentation in ultrasound images and measurement of intima-media thickness

Background. The segmentation of the common carotid artery (CCA) wall is imperative for the determination of the intima-media thickness (IMT) on B-mode ultrasound (US) images. The IMT is considered an important indicator in the evaluation of the risk for the development of atherosclerosis. In this paper, authors have discussed the relevance of measurements in clinical practices and the challenges that one has to face while approaching the segmentation of carotid artery on ultrasound images. The paper presents an overall review of commonly used methods for the CCA segmentation and IMT measurement along with the different performance metrics that have been proposed and used for performance validation. Summary and future directions are given in the conclusion.