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  • Open Access

    ARTICLE

    Computer Aided Coronary Atherosclerosis Plaque Detection and Classification

    S. Deivanayagi1,*, P. S. Periasamy2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 639-653, 2022, DOI:10.32604/iasc.2022.025632 - 15 April 2022

    Abstract Coronary artery disease (CAD) remains a major reason for increased mortality over the globe, comprising myocardial infarction and ischemic cardiomyopathy. The CAD is highly linked to coronary stenosis owing to the encumbrance of atherosclerotic plaques. Particularly, diversified atherosclerotic plaques are highly responsible for major cardiac adverse events over the calcified and non-calcified plaques. There, the recognition and classification of atherosclerotic plaques play a vital role to prevent and intervene in CAD. The process of detecting various class labels of the atherosclerotic plaques is significant to identify the disease at the earlier stages. Since several automated… More >

  • Open Access

    ABSTRACT

    Associations between Carotid Bifurcation Geometry and Atherosclerotic Plaque Vulnerability: A Chinese Atherosclerosis Risk Evaluation II Study

    Peirong Jiang1, Zhensen Chen2, Daniel S. Hippe2, Hiroko Watase3, Bin Sun1, Ruolan Lin1, Zheting Yang1, Yunjing Xue1,*, Xihai Zhao4,*, Chun Yuan2,4

    Molecular & Cellular Biomechanics, Vol.16, Suppl.2, pp. 34-35, 2019, DOI:10.32604/mcb.2019.07394

    Abstract This article has no abstract. More >

  • Open Access

    ABSTRACT

    Convolution Neural Networks and Support Vector Machines for Automatic Segmentation of Intracoronary Optical Coherence Tomography

    Caining Zhang1, Huaguang Li2, Xiaoya Guo3, David Molony4, Xiaopeng Guo2, Habib Samady4, Don P. Giddens4,5, Lambros Athanasiou6, Rencan Nie2,*, Jinde Cao3,*, Dalin Tang1,*,7

    Molecular & Cellular Biomechanics, Vol.16, Suppl.2, pp. 31-31, 2019, DOI:10.32604/mcb.2019.06983

    Abstract Cardiovascular diseases are closely associated with deteriorating atherosclerotic plaques. Optical coherence tomography (OCT) is a recently developed intravascular imaging technique with high resolution approximately 10 microns and could provide accurate quantification of coronary plaque morphology. However, tissue segmentation of OCT images in clinic is still mainly performed manually by physicians which is time consuming and subjective. To overcome these limitations, two automatic segmentation methods for intracoronary OCT image based on support vector machine (SVM) and convolutional neural network (CNN) were performed to identify the plaque region and characterize plaque components. In vivo IVUS and OCT… More >

  • Open Access

    ABSTRACT

    Using 3D Thin-Layer Model with in Vivo Patient-Specific Vessel Material Properties to Assesse Carotid Atherosclerotic Plaque Vulnerability

    Qingyu Wang1, Dalin Tang1,2,*, Gador Canton3, Zheyang Wu2, Thomas S. Hatsukami4, Kristen L Billiar5, Chun Yuan6

    Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 81-82, 2019, DOI:10.32604/mcb.2019.05748

    Abstract This article has no abstract. More >

  • Open Access

    ABSTRACT

    Automatic Segmentation Methods Based on Machine Learning for Intracoronary Optical Coherence Tomography Image

    Caining Zhang1, Xiaoya Guo2, Dalin Tang1,3,*, David Molony4, Chun Yang3, Habib Samady4, Jie Zheng5, Gary S. Mintz6, Akiko Maehara6, Mitsuaki Matsumura6, Don P. Giddens4,7

    Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 79-80, 2019, DOI:10.32604/mcb.2019.05747

    Abstract Cardiovascular diseases are closely associated with sudden rupture of atherosclerotic plaques. Previous image modalities such as magnetic resonance imaging (MRI) and intravascular ultrasound (IVUS) were unable to identify vulnerable plaques due to their limited resolution. Optical coherence tomography (OCT) is an advanced intravascular imaging technique developed in recent years which has high resolution approximately 10 microns and could provide more accurate morphology of coronary plaque. In particular, it is now possible to identify plaques with fibrous cap thickness <65 μm, an accepted threshold value for vulnerable plaques. However, the current segmentation of OCT images are… More >

  • Open Access

    ABSTRACT

    Characterization of Coronary Atherosclerotic Plaque Composition Based on Convolutional Neural Network (CNN)

    Yifan Yin1, Chunliu He1, Biao Xu2, Zhiyong Li1,*

    Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 57-57, 2019, DOI:10.32604/mcb.2019.05732

    Abstract The tissue composition and morphological structure of atherosclerotic plaques determine its stability or vulnerability. Intravascular optical coherence tomography (IVOCT) has rapidly become the method of choice for assessing the pathology of the coronary arterial wall in vivo due to its superior resolution. However, in clinical practice, the analysis of plaque composition of OCT images mainly relies on the interpretation of images by well-trained experts, which is a time-consuming, labor-intensive procedure and it is also subjective. The purpose of this study is to use the Convolutional neural network (CNN) method to automatically extract the best feature… More >

  • Open Access

    ABSTRACT

    Neovascularization and Intraplaque Hemorrhage in Atherosclerotic Plaque Destabilization-A Mathematical Model

    Muyi Guo1, Yan Cai1, Zhiyong Li1,2,*

    Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 49-49, 2019, DOI:10.32604/mcb.2019.05727

    Abstract Observational studies have identified angiogenesis from the adventitial vasa vasorum and intraplaque hemorrhage (IPH) as critical factors in atherosclerotic plaque progression and destabilization. Here we propose a mathematical model incorporating intraplaque neovascularization and hemodynamic calculation for the quantitative evaluation of atherosclerotic plaque hemorrhage. An angiogenic microvasculature based on histology of a patient’s carotid plaque is generated by two-dimensional nine-point model of endothelial cell migration. Three key cells (endothelial cells, smooth muscle cells and macrophages) and three key chemicals (vascular endothelial growth factors, extracellular matrix and matrix metalloproteinase) are involved in the intraplaque angiogenesis model, and… More >

  • Open Access

    ABSTRACT

    Atherosclerotic Plaque Rupture Prediction: Imaging-Based Computational Simulation and Multiphysical Modelling

    Zhiyong Li1,2,*

    Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 29-30, 2019, DOI:10.32604/mcb.2019.06308

    Abstract In this article, we summarize our previous work in imaging-based computational modelling and simulation of the interaction between blood flow and atherosclerotic plaque. We also discussed our recent developments in multiphysical modelling of plaque progression and destabilization. Significance and translation of the modelling study to clinical practice are discussed in order to better assess plaque vulnerability and accurately predict a possible rupture. More >

  • Open Access

    ABSTRACT

    The Role of Shear Stress in Atherosclerotic Plaque Progression, Destabilization and Rupture

    J. J. Wentzel1,*

    Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 7-8, 2019, DOI:10.32604/mcb.2019.05696

    Abstract The pathophysiology of atherosclerosis is complex and multifactorial, involving systemic risk factors and biomechanical stimuli. Atherosclerotic plaques predominantly form in regions that are exposed to low shear stress of the blood at the vessel wall, whereas regions of moderate and high shear stress are generally protected. For more than 20 years, my research group performs studies to investigate the role of shear stress in atherosclerotic plaque formation and rupture in coronary and carotid arteries of patients and laboratory animals. For that reason, new technology was developed to 3D reconstruct arteries based on fusion of multiple… More >

  • Open Access

    ARTICLE

    Convolution Neural Networks and Support Vector Machines for Automatic Segmentation of Intracoronary Optical Coherence Tomography

    Caining Zhang1, Huaguang Li2, Xiaoya Guo3, David Molony4, Xiaopeng Guo2, Habib Samady4, Don P. Giddens4,5, Lambros Athanasiou6, Rencan Nie2,*, Jinde Cao3,*, Dalin Tang1,*,7

    Molecular & Cellular Biomechanics, Vol.16, No.2, pp. 153-161, 2019, DOI:10.32604/mcb.2019.06873

    Abstract Cardiovascular diseases are closely associated with deteriorating atherosclerotic plaques. Optical coherence tomography (OCT) is a recently developed intravascular imaging technique with high resolution approximately 10 microns and could provide accurate quantification of coronary plaque morphology. However, tissue segmentation of OCT images in clinic is still mainly performed manually by physicians which is time consuming and subjective. To overcome these limitations, two automatic segmentation methods for intracoronary OCT image based on support vector machine (SVM) and convolutional neural network (CNN) were performed to identify the plaque region and characterize plaque components. In vivo IVUS and OCT coronary… More >

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