Strain Estimation

Strain estimation focuses on accurately measuring deformation in various materials and biological tissues, aiming to improve diagnostics and material characterization. Current research emphasizes developing robust and efficient methods, employing techniques like deep learning (including physics-informed neural networks and variational autoencoders), advanced image processing (e.g., digital image correlation and MRI tagging), and novel sensor technologies (such as fiber Bragg gratings). These advancements are improving the accuracy and speed of strain quantification across diverse applications, from structural health monitoring and robotic surgery to medical imaging and the diagnosis of conditions like heart failure and diabetic foot ulcers.