Reliability of brain volume measures of accelerated 3D T1-weighted images with deep learning-based reconstruction.

ABSTRACT:

Purpose

The time-intensive nature of acquiring 3D T1-weighted MRI and analyzing brain volumetry limits quantitative evaluation of brain atrophy. We explore the feasibility and reliability of deep learning-based accelerated MRI scans for brain volumetry.

Methods

This retrospective study collected 3D T1-weighted data using 3T from 42 participants for the simulated acceleration dataset and 48 for the validation dataset. The simulated acceleration dataset consists of three sets at different simulated acceleration levels (Simul-Accel) corresponding to level 1 (65% undersampling), 2 (70%), and 3 (75%). These images were then subjected to deep learning-based reconstruction (Simul-Accel-DL). Conventional images (Conv) without acceleration and DL were set as the reference. In the val

SUBMITTER: Jung W 

PROVIDER: S-EPMC11802604 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature