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Biological Fluid Dynamics: Data-driven Hemodynamics

ORAL · H14 · ID: 22754





Presentations

  • Inferring the left atrial appendage (LAA) hemodynamics from 4D CT contrast dynamics: reduced order models (ROMs) and physics informed neural networks (PINNs).

    ORAL

    Presenters

    • Bahetihazi Maidu

      UC San Diego, University of California, San Diego

    Authors

    • Bahetihazi Maidu

      UC San Diego, University of California, San Diego

    • Alejandro Gonzalo

      UC San Diego & University of Washington, University of California San Diego

    • Lorenzo Rossini

      UC San Diego

    • Davis Vigneault

      UC San Diego, Department of Radiology, Stanford University, Stanford, CA, 94305, USA

    • Pablo Martinez-Legazpi

      Universidad Nacional de Educación a Distancia, Gregorio Marañon Hospital, Spain, Dpt. Física Matemática y Fluidos. UNED

    • Javier Bermejo

      Hospital G.U. Gregorio Marañón, Gregorio Marañon Hospital, Spain, Hospital General Universitario Gregorio Marañon, Hospital General Universitario Gregorio Marañón, Hospital Gregorio Maranon, Madrid, Spain

    • Oscar Flores

      Univ. Carlos III De Madrid, Univ Carlos III De Madrid, Univ. Carlos III de Madrid

    • Manuel Garcia-Villalba

      Univ Carlos III De Madrid, Univ. Carlos III de Madrid

    • Elliot McVeigh

      UC San Diego, University of California San Diego

    • Andrew M Kahn

      University of California San Diego, UC San Diego, University of California, San Diego

    • Juan Carlos del Alamo

      University of Washington; University of California San Diego, UC San Diego & University of Washington, University of Washington, University of Washington & University of California, San Diego

    View abstract →

  • A Machine Learning Methodology for estimation of vascular characteristics using a single carotid waveform

    ORAL

    Presenters

    • Soha Niroumandi

      Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA, USA, University of Southern California

    Authors

    • Soha Niroumandi

      Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA, USA, University of Southern California

    • Rashid Alavi

      Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA, USA, University of Southern California

    • Niema M Pahlevan

      University of Southern California, Univ of Southern California, Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA, USA

    View abstract →

  • Towards resolving hemodynamic velocities from time-resolved contrast-enhanced magnetic resonance angiography using physics-informed machine learning

    ORAL

    Presenters

    • Roshan M D'Souza

      University of Wisconsin - Milwaukee

    Authors

    • Roshan M D'Souza

      University of Wisconsin - Milwaukee

    • Amirhossein Arzani

      Department of Mechanical Engineering, Northern Arizona University, Northern Arizona University

    • Isaac Perez-Raya

      Rochester Institute of Technology

    • Amin Pashaei

      University of Wisconsin Milwaukee

    View abstract →

  • Data-driven near-wall blood flow and wall shear stress modeling with physics-informed neural networks

    ORAL

    Presenters

    • Amirhossein Arzani

      Department of Mechanical Engineering, Northern Arizona University, Northern Arizona University

    Authors

    • Amirhossein Arzani

      Department of Mechanical Engineering, Northern Arizona University, Northern Arizona University

    • Jian-Xun Wang

      University of Notre Dame

    • Roshan M D'Souza

      University of Wisconsin - Milwaukee

    View abstract →

  • Brain Hemodynamic Predictions from Noninvasive Transcranial Doppler Ultrasound and Angiography Data Using Physics-Informed Neural Networks

    ORAL

    Publication: Sarabian, M., Babaee, B., & Laksari, K. (2020). Brain haemodynamic predictions from non‑invasive Transcranial Doppler Ultrasound data using physics‑informed neural networks. Manuscript submitted

    Presenters

    • Mohammad Sarabian

      University of Arizona

    Authors

    • Mohammad Sarabian

      University of Arizona

    • Hessam Babaee

      University of Pittsburgh

    • Kaveh Laksari

      University of Arizona

    View abstract →

  • Improving the Diagnostic Accuracy of Cardiac Auscultation using Supervised Learning: a Computational Hemoacoustic Study

    ORAL

    Publication: Bailoor S, Seo JH, Schena S and Mittal R. "Detecting Aortic Valve Anomaly from Induced Murmurs: Insights from Computational Hemodynamic Models". Frontiers in Physiology (under review)

    Presenters

    • Shantanu Bailoor

      Johns Hopkins University

    Authors

    • Shantanu Bailoor

      Johns Hopkins University

    • Jung-Hee Seo

      Johns Hopkins University, Johns Hopkins Univ

    • Stefano Schena

      Johns Hopkins Medical Institute

    • Rajat Mittal

      Johns Hopkins University

    View abstract →

  • All-in-one, physics-informed dealiasing method to regularize cardiac 4D flow MRI data.

    ORAL

    Presenters

    • Christian Chazo Paz

      Hospital G.U. Gregorio Marañón; Univ. Carlos III de Madrid

    Authors

    • Christian Chazo Paz

      Hospital G.U. Gregorio Marañón; Univ. Carlos III de Madrid

    • Oscar Flores

      Univ. Carlos III De Madrid, Univ Carlos III De Madrid, Univ. Carlos III de Madrid

    • Pablo Martinez-Legazpi

      Universidad Nacional de Educación a Distancia, Gregorio Marañon Hospital, Spain, Dpt. Física Matemática y Fluidos. UNED

    • Cathleen M Nguyen

      University of Washington; University of California San Diego, University of Washington & University of California, San Diego

    • Cristina Santa Marta

      Universidad Nacional de Educación a Distancia

    • Andrew M Kahn

      University of California San Diego, UC San Diego, University of California, San Diego

    • Javier Bermejo

      Hospital G.U. Gregorio Marañón, Gregorio Marañon Hospital, Spain, Hospital General Universitario Gregorio Marañon, Hospital General Universitario Gregorio Marañón, Hospital Gregorio Maranon, Madrid, Spain

    • Juan Carlos del Alamo

      University of Washington; University of California San Diego, UC San Diego & University of Washington, University of Washington, University of Washington & University of California, San Diego

    View abstract →

  • Super-resolution study of aneurism based on AI PIV - preliminary report

    ORAL

    Presenters

    • Wojciech Majewski

    Authors

    • Wojciech Majewski

    • Wojciech Kaspera

      Medical University of Silesia, Sosnowiec, Poland

    • Marek Ples

      Silesian University of Technology, Gliwice, Poland

    • Marta Sobkowiak-Pilorz

      Silesian University of Technology, Gliwice, Poland

    • Runjie Wei

      Microvec Pte Ltd, Singapore

    • Wojciech Wolański

      Silesian University of Technology, Gliwice, Poland

    View abstract →