Objective: Cardiovascular magnetic resonance-feature tracking (CMR-FT) represents a group of methods for myocardial strain estimation from cardiac cine MRI images. Established CMR-FT methods are mainly based on optical flow or pairwise registration. However, these methods suffer from either inaccurate estimation of large motion or drift effect caused by accumulative tracking errors. In this work, we propose a deformable groupwise registration method using a locally low-rank (LLR) dissimilarity metric for CMR-FT. Methods: The proposed method (Groupwise-LLR) tracks the feature points by a groupwise registration-based two-step strategy. Unlike the globally low-rank (GLR) dissimilarity metric, the proposed LLR metric imposes low-rankness on local image patches rather than the whole image. We quantitatively compared Groupwise-LLR with the Farneback optical flow, a pairwise registration method, and a GLR-based groupwise registration method on simulated and in vivo datasets. Results: Results from the simulated dataset showed that Groupwise-LLR achieved more accurate tracking and strain estimation compared with the other methods. Results from the in vivo dataset showed that Groupwise-LLR achieved more accurate tracking and elimination of the drift effect in late-diastole. Inter-observer reproducibility of strain estimates was similar between all studied methods. Conclusion: The proposed method estimates myocardial strains more accurately due to the application of a groupwise registration-based tracking strategy and an LLR-based dissimilarity metric. Significance: The proposed CMR-FT method may facilitate more accurate estimation of myocardial strains, especially in diastole, for clinical assessments of cardiac dysfunction.

翻译：摘要：目的：心血管磁共振特征追踪（CMR-FT）是一类从心脏电影MRI图像估计心肌应变的方法。现有CMR-FT方法主要基于光流或成对配准，但这些方法存在大运动估计不准确或因累积跟踪误差导致的漂移效应问题。本文提出一种采用局部低秩（LLR）相似性度量的可变形组配准CMR-FT方法。方法：所提方法（Groupwise-LLR）通过基于组配准的两步策略跟踪特征点。与全局低秩（GLR）相似性度量不同，LLR度量将低秩性施加于局部图像块而非整幅图像。我们在模拟数据集和活体数据集上将Groupwise-LLR与Farneback光流法、成对配准方法及基于GLR的组配准方法进行了定量比较。结果：模拟数据集结果表明，Groupwise-LLR在跟踪和应变估计精度上优于其他方法。活体数据集结果表明，Groupwise-LLR能够更精确地跟踪心肌运动并消除舒张晚期的漂移效应。所有研究方法在应变估计的观察者间可重复性方面表现相似。结论：所提方法通过采用基于组配准的跟踪策略和LLR相似性度量，实现了更准确的心肌应变估计。意义：本文提出的CMR-FT方法可促进更准确的心肌应变估计（尤其在舒张期），为心脏功能障碍的临床评估提供支持。