Automatic Time-Resolved Cardiovascular Segmentation of 4D Flow MRI Using Deep Learning.

ABSTRACT:

Background

Segmenting the whole heart over the cardiac cycle in 4D flow MRI is a challenging and time-consuming process, as there is considerable motion and limited contrast between blood and tissue.

Purpose

To develop and evaluate a deep learning-based segmentation method to automatically segment the cardiac chambers and great thoracic vessels from 4D flow MRI.

Study type

Retrospective.

Subjects

A total of 205 subjects, including 40 healthy volunteers and 165 patients with a variety of cardiac disorders were included. Data were randomly divided into training (n = 144), validation (n = 20), and testing (n = 41) sets.

Field strength/sequence

A 3 T/time-resolved velocity encoded 3D gradient echo sequence (4D flow MRI).

Assessment

A 3D neural network

SUBMITTER: Bustamante M 

PROVIDER: S-EPMC10946960 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature