J. Elefteriades

This study uses finite element analysis on CT images to analyze biomechanical stress changes in aortic dissection across pre-dissection, post-dissection, and post-repair states, revealing increased wall stress and stress concentration regions.

This paper integrates deep neural networks with finite element methods to improve biomechanical analysis of the human aorta, reducing errors and computational time.

PyTorch-FEA improves computational efficiency and accuracy in biomechanical analysis of human aorta using autograd and deep learning.