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  • Open Access


    Comparison of Aortic Flow Patterns in Patients with and without Aortic Valve Disease: Hemodynamic Simulation Based on PC-MRI and CTA Data

    Lijian Xu1,2, Lekang Yin3, Fuyou Liang1,2,*

    Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 71-72, 2019, DOI:10.32604/mcb.2019.05741

    Abstract Recent studies have revealed that aortic valve diseases are associated with the increased incidence of the aortopathy development. However, the influence of aortic valve diseases on aortic hemodynamics remains unclear. The purpose of this study was therefore to investigate the hemodynamic differences in patients with and without aortic valve disease through patient-specific simulations performed on two aorta models (BAV with severe stenosis vs. normal tricuspid aortic valve (TAV)). Realistic geometries and boundary conditions were obtained from computed tomography angiography (CTA) and phase-contrast magnetic resonance imaging (PC-MRI) measurements, respectively. In addition, 4D-MRI were performed to validate the numerical methods used to… More >

  • Open Access


    Automated Segmentation of Atherosclerotic Plaque Using Bayes Classifier for Multi-Contrast In Vivo and Ex Vivo MR Images

    Xueying Huang1, Chun Yang2, Jie Zheng3, Pamela K. Woodard3, Dalin Tang1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.1, No.1, pp. 29-34, 2007, DOI:10.3970/icces.2007.001.029

    Abstract Atherosclerotic plaques may rupture without warning and cause acute cardiovascular syndromes such as heart attack and stroke. Accurate identification of plaque components will improve the accuracy and reliability of computational models. In this article, we present a segmentation method using a cluster analysis technique to quantify and classify plaque components from magnetic resonance images (MRI). 3D in vivo and ex vivo multi-contrast (T1-, proton density-, and T2-weighted) MR Images were acquired from a patient of cardiovascular disease. Normal distribution Bayes classifier was performed on ex vivo and in vivo MR Images respectively. The resulting segmentation obtained from cluster analysis showed… More >

  • Open Access


    Comparison of Hemodynamic Endpoints between Normal Subject and Tetralogy Patient Using Womersley Velocity Profile and MR Based Flow Measurements

    Ashish Das, William M. Gottliebson†,‡, Madhura Karve, Rupak Banerjee∗,§,¶

    Molecular & Cellular Biomechanics, Vol.8, No.1, pp. 21-42, 2011, DOI:10.3970/mcb.2011.008.021

    Abstract Right ventricular (RV) enlargement and pulmonary valve insufficiency (PI) are well-known, unavoidable long term sequelae encountered by patients who undergo tetralogy of Fallot (TOF) surgery. Despite their lifelong need for cardiac surveillance and occasional re-intervention, there is a paucity of numerical data characterizing blood flows in their pulmonary arteries (PA). Specifically, although PA regurgitation is well-known to be ubiquitously present in adult repaired TOF (rTOF) patients yet, there have been only limited numerical studies to fully characterize this process. The few studies available have utilized idealized, simplistic geometric models or overly simplistic boundary conditions that fail to account for flow… More >

  • Open Access


    A Novel Reversible Data Hiding Scheme Based on Lesion Extraction and with Contrast Enhancement for Medical Images

    Xingxing Xiao1, Yang1,*, Rui Li2, Weiming Zhang3

    CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 101-115, 2019, DOI:10.32604/cmc.2019.05293

    Abstract The medical industry develops rapidly as science and technology advance. People benefit from medical resource sharing, but suffer from privacy leaks at the same time. In order to protect patients’ privacy and improve quality of medical images, a novel reversible data hiding (RDH) scheme based on lesion extraction and with contrast enhancement is proposed. Furthermore, the proposed scheme can enhance the contrast of medial image's lesion area directly and embed high-capacity privacy data reversibly. Different from previous segmentation methods, this scheme first adopts distance regularized level set evolution (DRLSE) to extract lesion and targets at the lesion area accurately for… More >

  • Open Access


    A Novel Method for Solving Ill-conditioned Systems of Linear Equations with Extreme Physical Property Contrasts

    Cheng-Yu Ku1

    CMES-Computer Modeling in Engineering & Sciences, Vol.96, No.6, pp. 409-434, 2013, DOI:10.3970/cmes.2013.096.409

    Abstract This paper proposes a novel method, named the dynamical Jacobianinverse free method (DJIFM), with the incorporation of a two-sided equilibrium algorithm for solving ill-conditioned systems of linear equations with extreme physical property contrasts. The DJIFM is based on the construction of a scalar homotopy function for transforming the vector function of linear or nonlinear algebraic equations into a time-dependent scalar function by introducing a fictitious time-like variable. The DJIFM demonstrated great numerical stability for solving linear or nonlinear algebraic equations, particularly for systems involving ill-conditioned Jacobian or poor initial values that cause convergence problems. With the incorporation of a newly… More >

  • Open Access


    A Computational Method Based on Augmented Lagrangians and Fast Fourier Transforms for Composites with High Contrast

    J.C. Michel1, H. Moulinec, P. Suquet

    CMES-Computer Modeling in Engineering & Sciences, Vol.1, No.2, pp. 79-88, 2000, DOI:10.3970/cmes.2000.001.239

    Abstract An iterative numerical method based on Fast Fourier Transforms has been proposed by \cite{MOU98} to investigate the effective properties of periodic composites. This iterative method is based on the exact expression of the Green function for a linear elastic, homogeneous reference material. When dealing with linear phases, the number of iterations required to reach convergence is proportional to the contrast between the phases properties, and convergence is therefore not ensured in the case of composites with infinite contrast (those containing voids or rigid inclusions or highly nonlinear materials). It is proposed in this study to overcome this difficulty by using… More >

  • Open Access


    Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine

    B. V. Santhosh Krishna1, *, T. Gnanasekaran2

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 855-869, 2019, DOI:10.32604/cmc.2019.07585

    Abstract An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction… More >

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