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Search Results (29)
  • Open Access

    ARTICLE

    Segmentation of the Left Ventricle in Cardiac MRI Using Random Walk Techniques

    Osama S. Faragallah1,*, Ghada Abdel-Aziz2, Hala S. El-sayed3, Gamal G. N. Geweid4,5

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 575-588, 2021, DOI:10.32604/iasc.2021.019023 - 11 August 2021

    Abstract As a regular tool for assessing and diagnosing cardiovascular disease (CVD), medical professionals and health care centers, are highly dependent on cardiac imaging. The purpose of dividing the cardiac images is to paint the inner and outer walls of the heart to divide all or part of the limb’s boundaries. In order to enhance cardiologist in the process of cardiac segmentation, new and accurate methods are needed to divide the selected object, which is the left ventricle (LV). Segmentation techniques aim to provide a fast segmentation process and improve the reliability of the process. In… More >

  • Open Access

    ARTICLE

    Data and Machine Learning Fusion Architecture for Cardiovascular Disease Prediction

    Munir Ahmad1, Majed Alfayad2, Shabib Aftab1,3, Muhammad Adnan Khan4,*, Areej Fatima5, Bilal Shoaib6, Mohammad Sh. Daoud7, Nouh Sabri Elmitwally2,8

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2717-2731, 2021, DOI:10.32604/cmc.2021.019013 - 21 July 2021

    Abstract Heart disease, which is also known as cardiovascular disease, includes various conditions that affect the heart and has been considered a major cause of death over the past decades. Accurate and timely detection of heart disease is the single key factor for appropriate investigation, treatment, and prescription of medication. Emerging technologies such as fog, cloud, and mobile computing provide substantial support for the diagnosis and prediction of fatal diseases such as diabetes, cancer, and cardiovascular disease. Cloud computing provides a cost-efficient infrastructure for data processing, storage, and retrieval, with much of the extant research recommending More >

  • Open Access

    REVIEW

    Mechano-Sensing and shear stress-shielding by endothelial primary cilia: structure, composition, and function

    HUAN YIN1, LIZHEN WANG1, YUBO FAN1, BINGMEI M. FU1,2,*

    BIOCELL, Vol.45, No.5, pp. 1187-1199, 2021, DOI:10.32604/biocell.2021.016650 - 12 July 2021

    Abstract Primary cilium is an antenna-like and non-motile structure protruding from the apical surface of most mammalian cells including endothelial cells lining the inner side of all the blood vessels in our body. Although it has been over a century since primary cilia were discovered, the investigation about their mechano-sensing and other roles in maintaining normal functions of cardiovascular system has just started in recent years. This focused review aims to give an update about the current literature for the role of endothelial primary cilia in blood flow mechano-sensing and shear stress-shielding. To do this, we… More >

  • Open Access

    ARTICLE

    Multifactorial Disease Detection Using Regressive Multi-Array Deep Neural Classifier

    D. Venugopal1, T. Jayasankar2,*, N. Krishnaraj3, S. Venkatraman4, N. B. Prakash5, G. R. Hemalakshmi5

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 27-38, 2021, DOI:10.32604/iasc.2021.015205 - 17 March 2021

    Abstract Comprehensive evaluation of common complex diseases associated with common gene mutations is currently a hot area of human genome research into causative new developments. A multi-fractal analysis of the genome is performed by placing the entire DNA sequence into smaller fragments and using the chaotic game representation and systematic methods to calculate the general dimensional spectrum of each fragment. This is a time consuming process as it uses floating point to represent large data sets and requires processing time. The proposed Regressive Multi-Array Deep Neural Classifier (RMDNC) system is implemented to reduce the computation time,… More >

  • Open Access

    ARTICLE

    Smart CardioWatch System for Patients with Cardiovascular Diseases Who Live Alone

    Raisa Nazir Ahmed Kazi1,*, Manjur Kolhar2, Faiza Rizwan2

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1237-1250, 2021, DOI:10.32604/cmc.2020.012707 - 26 November 2020

    Abstract The widespread use of smartwatches has increased their specific and complementary activities in the health sector for patient’s prognosis. In this study, we propose a framework referred to as smart forecasting CardioWatch (SCW) to measure the heart-rate variation (HRV) for patients with myocardial infarction (MI) who live alone or are outside their homes. In this study, HRV is used as a vital alarming sign for patients with MI. The performance of the proposed framework is measured using machine learning and deep learning techniques, namely, support vector machine, logistic regression, and decision-tree classification techniques. The results More >

  • Open Access

    ABSTRACT

    On the Image-Based Non-Invasive Diagnosis of Cardiovascular Diseases

    Peng Wu1,*, Qi Gao2, Runjie Wei3, Hongping Wang3, Lizhong Wang3

    Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 27-28, 2019, DOI:10.32604/mcb.2019.05711

    Abstract Cardiovascular diseases are the leading cause of human deaths worldwide. Traditional diagnostic tools of cardiovascular diseases are either based on 2D static medical images, or invasive, bringing troubles to both patients and doctors. Our team is committed to the development of image-based non-invasive diagnostic system for cardiovascular diseases. We have made progress mainly in the following areas: 1) 4D flow technology for heart and large blood vessels. According to MRI 4D Flow data, three-dimensional velocity fields within blood vessels were constructed. Divergence-fee smoothing (DFS) was proposed to eliminate the high frequency noise in the hemodynamic… More >

  • Open Access

    ABSTRACT

    Multi-Modality Image-Based Modeling Approach for Cardiovascular Disease: Simulation, Assessment, Prediction, and Virtual Surgery

    Dalin Tang1,2,*

    Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 11-11, 2019, DOI:10.32604/mcb.2019.05170

    Abstract Medical imaging and image-based modeling have made considerable progress in recent years in cardiovascular research, such as identifying atherosclerotic plaque morphological and mechanical risk factors which may be used in developing improved patient screening strategies, and performing virtual heart surgery seeking optimal surgical procedures for best post-surgical outcome. We will report recent progress in using multi-modality image-based models to predict vulnerable plaque progression and vulnerability change. In particular, we will report our recent results using IVUS+OCT data to obtain more accurate stress/strain calculations. Inflammation and cap erosion will affect cap material properties. If OCT image… More >

  • Open Access

    ARTICLE

    Preparing adolescents with heart problems for transition to adult care, 2009–2010 National Survey of Children with Special Health Care Needs

    Karrie F. Downing1,2, Matthew E. Oster1,3, Sherry L. Farr1

    Congenital Heart Disease, Vol.12, No.4, pp. 497-506, 2017, DOI:10.1111/chd.12476

    Abstract Objective: A substantial percentage of children with congenital heart disease (CHD) fail to transfer to adult care, resulting in increased risk of morbidity and mortality. Transition planning discussions with a provider may increase rates of transfer, yet little is known about frequency and content of these discussions. We assessed prevalence and predictors of transition-related discussions between providers and parents of children with special healthcare needs (CSHCN) and heart problems, including CHD.
    Design: Using parent-reported data on 12- to 17-year-olds from the 2009–2010 National Survey of CSHCN, we calculated adjusted prevalence ratios (aPR) for associations between demographic factors… More >

  • Open Access

    ABSTRACT

    Image-Based Computational Modeling for Cardiovascular Diseases with Potential Clinical Applications

    Dalin Tang1, Chun Yang2, Pedro N. del Nido3, Tal Geva3, Chun Yuan4, Tom Hatsukami5, Fei Liu4, Jie Zheng6, Pamela K. Woodard6

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.1, No.1, pp. 1-6, 2007, DOI:10.3970/icces.2007.001.001

    Abstract Image-based computational models for blood flow in the heart and diseased arteries have been developed for disease assessment and potential clinical applications. Models with fluid-structure interactions for human right ventricle (RV) remodeling surgery design, carotid and coronary atherosclerotic plaques and abdominal aortic aneurysm (AAA) were presented. Organ morphology, material properties, governing equations, proper initial and boundary conditions, controlling factors and research focuses for each model were discussed. More >

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