SSL-QALAS: Self-Supervised Learning for rapid multiparameter estimation in quantitative MRI using 3D-QALAS.

ABSTRACT:

Purpose

To develop and evaluate a method for rapid estimation of multiparametric T₁ , T₂ , proton density, and inversion efficiency maps from 3D-quantification using an interleaved Look-Locker acquisition sequence with T₂ preparation pulse (3D-QALAS) measurements using self-supervised learning (SSL) without the need for an external dictionary.

Methods

An SSL-based QALAS mapping method (SSL-QALAS) was developed for rapid and dictionary-free estimation of multiparametric maps from 3D-QALAS measurements. The accuracy of the reconstructed quantitative maps using dictionary matching and SSL-QALAS was evaluated by comparing the estimated T₁ and T₂ values with those obtained from the reference methods on an International Societ

SUBMITTER: Jun Y 

PROVIDER: S-EPMC10527557 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature