ESB Webinar - Learn How to use SimVascular: the open source pipeline for cardiovascular modeling

When: 11/06/2019 - 11/06/2019
Where: Webinar

The first webinar of the ESB Webinar Series will take place on June 11th 2019 at 17:00 CET. In this webinar an open source software package to simulate and analyze the cardiovascular system will be explored. SimVascular is the only fully open source software package providing a complete pipeline from medical image data segmentation to patient specific blood flow simulation and analysis.

Presentation will be given by Mr. Gabriel Maher. Gabriel is a PhD Student at the Cardiovascular Biomechanics Computation lab at Stanford University, his research is focused on deep learning for cardiovascular medical imaging and he is one of the core developers of the SimVascular project

During the webinar, the speaker will explore together with the developers the features and abilities of the software and the procedure of building and analyzing a complete cardiovascular model.

More specifically, you will learn how to use SimVascular to:

  • Build 3D patient-specific cardiovascular models
  • Run computational blood flow simulations
  • Visualize and analyze simulation data 

and become familiar with the features of the software such as:

  • Image Analysis: volume rendering, image denoising, edge detection
  • Model Construction: level set segmentation, model repair tools
  • Meshing: radius-based and boundary layer meshing, adaptive mesh refinement
  • Simulation: deformable walls, variable mechanical properties, highly parallelized solver
  • Machine learning to accelerate vascular segmentation
  • Python interface
  • Automated pipeline for 1D simulations
  • Enhanced capabilities for 3D segmentation

You will have the chance to ask your questions which will be addressed by the instructors at the end of the webinar. However, it would be great if you could send your question in advance while filling the registration form or by sending to and/or before the start of the webinar.

Click here to register for the webinar.

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