YoVDO

WarpPINN: Cine-MR Image Registration with Physics-Informed Neural Networks

Offered By: DataLearning@ICL via YouTube

Tags

Physics Informed Neural Networks Courses Strain Analysis Courses Automatic Differentiation Courses Cardiomyopathies Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a cutting-edge approach to cardiac image analysis in this 58-minute talk by Francisco Sahli. Delve into the development of WarpPINN, a physics-informed neural network designed for image registration in cine magnetic resonance imaging. Learn how this innovative method quantifies local heart deformations, providing valuable insights for diagnosing cardiomyopathies. Discover how WarpPINN incorporates tissue incompressibility and hyperelastic behavior to generate accurate strain estimations. Examine the use of Fourier feature mappings to overcome neural network limitations and capture discontinuities in strain fields. Evaluate the algorithm's performance on synthetic examples and a benchmark dataset of healthy volunteers. Gain understanding of how WarpPINN outperforms existing methodologies in landmark tracking and delivers physiologically accurate strain measurements in radial and circumferential directions. Consider the potential applications of this technique for improved heart failure diagnosis and general image registration tasks.

Syllabus

Francisco Sahli - WarpPINN: Cine-MR image registration with physics-informed neural networks


Taught by

DataLearning@ICL

Related Courses

Inverse Methods in Heat Transfer
Indian Institute of Technology Madras via Swayam
Laboratory for Interdisciplinary Breakthrough Science - Hybrid
International Centre for Theoretical Sciences via YouTube
Improving the Variational Learning of Physics-Driven Neural Generative Models
Alan Turing Institute via YouTube
HypoSVI- Earthquake Hypocentre Inversion With Stein Variational Inference and Physics Informed Neural Networks
Alan Turing Institute via YouTube
Emulating InterStellar Medium Chemistry with Physics Informed Neural Networks
Alan Turing Institute via YouTube