Abstract

Motivation: Motion correction (MoCo) for cardiac parametric mapping can be challenging due to the dynamic signal variations. Traditional model-based methods need an analytical model, which is often unavailable for multi-parametric mapping applications. Goal(s): To propose a model-free dictionary matching-based MoCo method for cardiac multi-parametric mapping. Approach: The method alternates between dictionary matching and image registration. In vivo validation was performed in 10 healthy subjects for cardiac joint T1 and T2 mapping with controlled breathing. Results: Compared with non-MoCo, the proposed method significantly reduced inter-image misalignment and improved the quality of the T1 and T2 maps. Impact: The proposed MoCo method can be applied to any quantitative MRI application with a signal dictionary, which includes both single-parametric and multi-parametric mapping.