Validation of a deep learning-based software for automated analysis of T2 mapping in cardiac magnetic resonance imaging.

ABSTRACT:

Background

The reliability and diagnostic performance of deep learning (DL)-based automated T2 measurements on T2 map of 3.0-T cardiac magnetic resonance imaging (MRI) using multi-institutional datasets have not been investigated. We aimed to evaluate the performance of a DL-based software for measuring automated T2 values from 3.0-T cardiac MRI obtained at two centers.

Methods

Eighty-three subjects were retrospectively enrolled from two centers (42 healthy subjects and 41 patients with myocarditis) to validate a commercial DL-based software that was trained to segment the left ventricular myocardium and measure T2 values on T2 mapping sequences. Manual reference T2 values by two experienced radiologists and those calculated by the DL-based software were obtained. The segmen

SUBMITTER: Kim H 

PROVIDER: S-EPMC10585511 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature