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    LinFlo-Net: A Two-Stage Deep Learning Method to Generate Simulation Ready Meshes of the Heart 

    Source: Journal of Biomechanical Engineering:;2024:;volume( 146 ):;issue: 007:;page 71005-1
    Author(s): Narayanan, Arjun; Kong, Fanwei; Shadden, Shawn
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: We present a deep learning model to automatically generate computer models of the human heart from patient imaging data with an emphasis on its capability to generate thin-walled cardiac structures. Our method works by ...
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    Automating Model Generation for Image-Based Cardiac Flow Simulation 

    Source: Journal of Biomechanical Engineering:;2020:;volume( 142 ):;issue: 011:;page 0111011-1
    Author(s): Kong, Fanwei; Shadden, Shawn C.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Computational fluid dynamics (CFD) modeling of left ventricle (LV) flow combined with patient medical imaging data has shown great potential in obtaining patient-specific hemodynamics information for functional assessment ...
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