Theme 4. Computational Systems, Modeling and Simulation in Medicine, Multiscale Modeling & Synthetic Biology
In Silico Clinical Trials for Cardiovascular Disease
Nenad Filipovic Bogdan Milicevic Tijana Šušteršič Nikola Radovanovic
All presenters are from:
University of Kragujevac, Serbia, and Bioengineering Research and Development Center (BioIRC), Kragujevac, Serbia
This session will cover four topics of:
In Silico Drug Testing for Cardiomyopathy Disease;
The Recurrent Neural Networks for Muscle stress Prediction in Finite Element Analysis Deep Learning based Segmentation and Classification of Herniated Disc in Magnetic Resonance Images; and Automatic Detection and Semantic Segmentation of Atherosclerotic Carotid Plaque using Machine Learning
SOFA: An Open-Source Solution for Physics Simulation
Hugo Talbot, SOFA Consortium, France
SOFA is an open-source framework for interactive physics simulation, with an emphasis on soft body dynamics. Further to 15 years of research and development, the framework is made up of a stable core providing state-of-the-art models and numerical methods. Its LGPL v2.1 open-source license (permissive and non-contaminating) and its plugin architecture foster the development of prototypes and products under any commercial license. Today, SOFA benefits from a large international community made up of research centers and companies.
Engineering simulation software has become invaluable within many industries. The role of simulation in all medical curricula to safely learn and rehearse surgical procedures significantly increased in the last decade. Research centers and companies rely on SOFA to build realistic simulations for surgical training and planning with haptic, VR/AR technologies. Physics simulation with SOFA has applications beyond healthcare. For device manufacturing, SOFA can be a strategic approach to shorten the design cycle and to reduce its costs, by predicting and optimizing the interaction between the product and its physical environment. In robotics, teams within the community aim at revolutionizing how to control and design robots using simulation.