Keywords: Data Analysis, Data Processing, registration
We propose a deformable groupwise registration method using a locally low-rank (LLR) dissimilarity to estimate myocardial strain from cine MRI images. The proposed method eliminates the drift effect commonly observed in the optical flow and sequentially pairwise registration, facilitating more accurate strain estimation in the diastolic phase. Compared to the globally low-rank dissimilarity, LLR dissimilarity shows slightly better tracking accuracy by imposing the low-rank property in local image regions rather than the whole image. Experiments on a large public cine MRI dataset demonstrates the accuracy of the proposed method on tracking and strain estimation.
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