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Quantitative cardiac magnetic resonance imaging (MRI) is an increasinglyimportant diagnostic tool for cardiovascular diseases. Yet, co-registration ofall baseline images within the quantitative MRI sequence is essential for theaccuracy and precision of quantitative maps. However, co-registering allbaseline images from a quantitative cardiac MRI sequence remains a nontrivialtask because of the simultaneous changes in intensity and contrast, incombination with cardiac and respiratory motion. To address the challenge, wepropose a novel motion correction framework based on robust principle componentanalysis (rPCA) that decomposes quantitative cardiac MRI into low-rank andsparse components, and we integrate the groupwise CNN-based registrationbackbone within the rPCA framework. The low-rank component of rPCA correspondsto the quantitative mapping (i.e. limited degree of freedom in variation),while the sparse component corresponds to the residual motion, making it easierto formulate and solve the groupwise registration problem. We evaluated ourproposed method on cardiac T1 mapping by the modified Look-Locker inversionrecovery (MOLLI) sequence, both before and after the Gadolinium contrast agentadministration. Our experiments showed that our method effectively improvedregistration performance over baseline methods without introducing rPCA, andreduced quantitative mapping error in both in-domain (pre-contrast MOLLI) andout-of-domain (post-contrast MOLLI) inference. The proposed rPCA framework isgeneric and can be integrated with other registration backbones.

Contrast-Agnostic Groupwise Registration by Robust PCA for Quantitative Cardiac MRI