Late gadolinium enhancement cardiovascular magnetic resonance with generative artificial intelligence.

ABSTRACT:

Background

Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging enables imaging of scar/fibrosis and is a cornerstone of most CMR imaging protocols. CMR imaging can benefit from image acceleration; however, image acceleration in LGE remains challenging due to its limited signal-to-noise ratio. In this study, we sought to evaluate a rapid two-dimensional (2D) LGE imaging protocol using a generative artificial intelligence (AI) algorithm with inline reconstruction.

Methods

A generative AI-based image enhancement was used to improve the sharpness of 2D LGE images acquired with low spatial resolution in the phase-encode direction. The generative AI model is an image enhancement technique built on the enhanced super-resolution generative adversarial n

SUBMITTER: Demirel OB 

PROVIDER: S-EPMC11761327 | biostudies-literature | 2025 Summer

REPOSITORIES: biostudies-literature