Neural Network Vessel Lumen Regression for Automated Lumen Cross-Section Segmentation in Cardiovascular Image-Based Modeling.

Journal: Cardiovascular engineering and technology
PMID: 33179176

Abstract

PURPOSE: We accelerate a pathline-based cardiovascular model building method by training machine learning models to directly predict vessel lumen surface points from computed tomography (CT) and magnetic resonance (MR) medical image data.

Authors

  • Gabriel Maher
    Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA. gdmaher@stanford.edu.
  • David Parker
    Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, New York, United States of America.
  • Nathan Wilson
    Open Source Medical Software Corporation, Los Angeles, CA, USA.
  • Alison Marsden
    Pediatric Cardiology, Bioengineering, Stanford University, Stanford, CA, USA.

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