StrainNet: Improved Myocardial Strain Analysis of Cine MRI by Deep Learning from DENSE.

ABSTRACT:

Purpose

To develop a three-dimensional (two dimensions + time) convolutional neural network trained with displacement encoding with stimulated echoes (DENSE) data for displacement and strain analysis of cine MRI.

Materials and methods

In this retrospective multicenter study, a deep learning model (StrainNet) was developed to predict intramyocardial displacement from contour motion. Patients with various heart diseases and healthy controls underwent cardiac MRI examinations with DENSE between August 2008 and January 2022. Network training inputs were a time series of myocardial contours from DENSE magnitude images, and ground truth data were DENSE displacement measurements. Model performance was evaluated using pixelwise end-point error (EPE). For testing, StrainNet was appli

SUBMITTER: Wang Y 

PROVIDER: S-EPMC10316292 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature