Beschreibung:
Reduced Order Models for the Biomechanics of Living Organs, a new volume in the Biomechanics of Living Organisms series, provides a comprehensive overview of the state-of-the-art in biomechanical computations using reduced order models, along with a deeper understanding of the associated reduction algorithms that will face students, researchers, clinicians and industrial partners in the future. The book gathers perspectives from key opinion scientists who describe and detail their approaches, methodologies and findings. It is the first to synthesize complementary advances in Biomechanical modelling of living organs using reduced order techniques in the design of medical devices and clinical interventions, including surgical procedures.
Part 1: Backgrounds and Fundamentals of Reduced Order Models 1. An introduction to Model Order Reduction Techniques 2. Linear and nonlinear dimensionality reduction of biomechanical models 3. Shape parameterizations for reduced order modeling in biophysics 4. Data-driven modelling and artificial intelligence 5. Deep Learning for Real-Time Computational Biomechanics 6. An introduction to Pod-Greedy-Galerkin reduced basis method 7. Machine learning and biophysical models: how to benefit each other?