Keywords: Motion Correction, Motion Correction, multi-parametric mapping
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.
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