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

Abstract—The robust identification and measurement of the intima media thickness (IMT) has a high clinical relevance because it represents one of the most precise predictors used in the assessment of potential future cardiovascular events. To facilitate the analysis of arterial wall thickening in serial clinical investigations, in this paper we have developed a novel fully automatic algorithm for the segmentation, measurement, and tracking of the intima media complex (IMC) in B-mode ultrasound video sequences. The proposed algorithm entails a two-stage image analysis process that initially addresses the segmentation of the IMC in the first frame of the ultrasound video sequence using a model-based approach; in the second step, a novel customized tracking procedure is applied to robustly detect the IMC in the subsequent frames. For the video tracking procedure, we introduce a spatially coherent algorithm called adaptive normalized correlation that prevents the tracking process from converging to wrong arterial interfaces. This represents the main contribution of this paper and was developed to deal with inconsistencies in the appearance of the IMC over the cardiac cycle. The quantitative evaluation has been carried out on 40 ultrasound video sequences of the common carotid artery (CCA) by comparing the results returned by the developed algorithm with respect to ground truth data that has been manually annotated by clinical experts. The measured IMTmean ± standard deviation recorded by the proposed algorithm is 0.60 mm ± 0.10, with a mean coefficient of variation (CV) of 2.05%, whereas the corresponding result obtained for the manually annotated ground truth data is 0.60 mm ± 0.11 with a mean CV equal to 5.60%. The numerical results reported in this paper indicate that the proposed algorithm is able to correctly segment and track the IMC in ultrasound CCA video sequences, and we were encouraged by the stability of our technique when applied to data captured under different imaging conditions. Future clinical studies will focus on the evaluation of patients that are affected by advanced cardiovascular conditions such as focal thickening and arterial plaques

Automatic segmentation of the lumen of the carotid artery in ultrasound B-mode images

A new algorithm is proposed for the segmentation of the lumen and bifurcation boundaries of the carotid artery in B-mode ultrasound images. It uses the hipoechogenic characteristics of the lumen for the identification of the carotid boundaries and the echogenic characteristics for the identification of the bifurcation boundaries. The image to be segmented is processed with the application of an anisotropic diffusion filter for speckle removal and morphologic operators are employed in the detection of the artery. The obtained information is then used in the definition of two initial contours, one corresponding to the lumen and the other to the bifurcation boundaries, for the posterior application of the Chan-vese level set segmentation model. A set of longitudinal B-mode images of the common carotid artery (CCA) was acquired with a GE Healthcare Vivid-e ultrasound system (GE Healthcare, United Kingdom). All the acquired images include a part of the CCA and of the bifurcation that separates the CCA into the internal and external carotid arteries. In order to achieve the uppermost robustness in the imaging acquisition process, i.e., images with high contrast and low speckle noise, the scanner was adjusted differently for each acquisition and according to the medical exam. The obtained results prove that we were able to successfully apply a carotid segmentation technique based on cervical ultrasonography. The main advantage of the new segmentation method relies on the automatic identification of the carotid lumen, overcoming the limitations of the traditional methods

An automatic 2D CAD algorithm for the segmentation of the IMT in ultrasound carotid artery images

Common carotid intima-media thickness (IMT) is a reliable measure of early atherosclerosis - its accurate measurement can be used in the process of evaluating the presence and tracking the progression of disease. The aim of this study is to introduce a novel unsupervised Computer Aided Detection (CAD) algorithm that is able to identify and measure the IMT in 2D ultrasound carotid images. The developed technique relies on a suite of image processing algorithms that embeds a statistical model to identify the two interfaces that form the IMT without any user intervention. The proposed image segmentation scheme is based on a spatially continuous vascular model and consists of several steps including data preprocessing, edge filtering, model selection, edge reconstruction and data refinement. To conduct a quantitative evaluation each image was manually segmented by clinical experts and performance metrics between the segmentation results obtained by the proposed method and the ground truth data were calculated. The experimental results show that the proposed CAD system is robust in accurately estimating the IMT in ultrasound carotid data

Classification approach for diagnosis of arteriosclerosis using B-mode ultrasound carotid images

Tese de mestrado. Engenharia Biomédica. Faculdade de Engenharia. Universidade do Porto. 201

Image segmentation and reconstruction of 3D surfaces from carotid ultrasound images

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200

Automatic location of atherosclerotic plaques by ultrasounds

Dissertação de Mestrado em Engenharia Biomédica apresentada à Faculdade de Ciências e Tecnologia da Universidade de Coimbra.As doenças cardiovasculares são uma das mais importantes causas de morte em todo o mundo. Em particular, a aterosclerose é uma doença difícil de diagnosticar em fases iniciais e há uma necessidade urgente de novas técnicas para diagnosticar pacientes em risco baseadas na medição espessura do complexo intima-media. Este trabalho procura desenvolver um novo sistema de segmentação para a detecção da espessura do complexo intima-media em artérias carótida. Todas as images foram pré-processadas de forma a remover o efeito do ruído espectral, e a região de interesse é automaticamente selecionada usando thresholding e connected-component analysis. O sistema baseia-se na derivada de primeira ordem da função Gaussiana como detector das estruturas desejadas – interfaces lumen-intima e media-adventitia, cuja distância entre eles corresponde à espessura do complexo intima-media. Os valores obtido foram comparados com medições realizadas por um especialista. Em média, a diferença entre medições não se mostrou significante mas o seu desvio-padrão associado pode impedir a aplicação em situação médica. Palavras-chave: Ultrasons, Artéria Carótida, Aterosclerose, Segmentação, Intima, Media, Adventitia

Estimation of a Coronary Vessel Wall Deformation with High-Frequency Ultrasound Elastography

Elastography, which is based on applying pressure and estimating the resulting deformation, involves the forward problem to obtain the strain distributions and inverse problem to construct the elastic distributions consistent with the obtained strains on observation points. This thesis focuses on the former problem whose solution is used as an input to the latter problem. The aim is to provide the inverse problem community with accurate strain estimates of a coronary artery vessel wall. In doing so, a new ultrasonic image-based elastography approach is developed. Because the accuracy and quality of the estimated strain fields depend on the resolution level of the ultrasound image and to date best resolution levels obtained in the literature are not enough to clearly see all boundaries of the artery, one of the main goals is to acquire high-resolution coronary vessel wall ultrasound images at different pressures. For this purpose, first an experimental setup is designed to collect radio frequency (RF) signals, and then image formation algorithm is developed to obtain ultrasound images from the collected signals. To segment the noisy ultrasound images formed, a geodesic active contour-based segmentation algorithm with a novel stopping function that includes local phase of the image is developed. Then, region-based information is added to make the segmentation more robust to noise. Finally, elliptical deformable template is applied so that a priori information regarding the shape of the arteries could be taken into account, resulting in more stable and accurate results. The use of this template also implicitly provides boundary point correspondences from which high-resolution, size-independent, non-rigid and local strain fields of the coronary vessel wall are obtained.Ph.D.Committee Chair: Benkeser, Paul; Committee Member: Koblasz, Arthur; Committee Member: Skrinjar, Oskar; Committee Member: Vidakovic, Brani; Committee Member: Yezzi, Anthon