Deep-Learning-Based Preprocessing for Quantitative Myocardial Perfusion MRI.

ABSTRACT:

Background

Quantitative myocardial perfusion cardiac MRI can provide a fast and robust assessment of myocardial perfusion status for the noninvasive diagnosis of myocardial ischemia while being more objective than visual assessment. However, it currently has limited use in clinical practice due to the challenging postprocessing required, particularly the segmentation.

Purpose

To evaluate the efficacy of an automated deep learning (DL) pipeline for image processing prior to quantitative analysis.

Study type

Retrospective.

Population

In all, 175 (350 MRI scans; 1050 image series) clinical patients under both rest and stress conditions (135/10/30 training/validation/test).

Field strength/sequence

3.0T/2D multislice saturation recovery T₁ -weighte

SUBMITTER: Scannell CM 

PROVIDER: S-EPMC7317373 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature