A Deep Learning Framework for Design and Analysis of Surgical Bioprosthetic Heart Valves.

ABSTRACT: Bioprosthetic heart valves (BHVs) are commonly used as heart valve replacements but they are prone to fatigue failure; estimating their remaining life directly from medical images is difficult. Analyzing the valve performance can provide better guidance for personalized valve design. However, such analyses are often computationally intensive. In this work, we introduce the concept of deep learning (DL) based finite element analysis (DLFEA) to learn the deformation biomechanics of bioprosthetic aortic valves directly from simulations. The proposed DL framework can eliminate the time-consuming biomechanics simulations, while predicting valve deformations with the same fidelity. We present statistical results that demonstrate the high performance of the DLFEA framework and the applicability o

SUBMITTER: Balu A 

PROVIDER: S-EPMC6898064 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature