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Nonrigid Groupwise Registration for Motion Estimation and Compensation in Compressed Sensing Reconstruction of Breath-Hold Cardiac Cine MRI

机译:非刚性成组配准的呼吸保持性心脏磁共振成像压缩感知重建中的运动估计和补偿

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摘要

Purpose: Compressed sensing methods with motion estimation and compensation techniques have been proposed for the reconstruction of accelerated dynamic MRI. However, artifacts that naturally arise in compressed sensing reconstruction procedures hinder the estimation of motion from reconstructed images, especially at high acceleration factors. This work introduces a robust groupwise nonrigid motion estimation technique applied to the compressed sensing reconstruction of dynamic cardiac cine MRI sequences.Theory and Methods: A spatio-temporal regularized, groupwise, nonrigid registration method based on a B-splines deformation model and a least squares metric is used to estimate and to compensate the movement of the heart in breath-hold cine acquisitions and to obtain a quasistatic sequence with highly sparse representation in temporally transformed domains.Results: Short axis in vivo datasets are used for validation, both original multicoil as well as DICOM data. Fully sampled data were retrospectively undersampled with various acceleration factors and reconstructions were compared with the two well-known methods k-t FOCUSS and MASTeR. The proposed method achieves higher signal to error ratio and structure similarity index for medium to high acceleration factors.Conclusions: Reconstruction methods based on groupwise registration show higher quality reconstructions for cardiac cine images than the pairwise counterparts tested.
机译:目的:已经提出了利用运动估计和补偿技术的压缩传感方法来重建加速动态MRI。然而,压缩感测重建程序中自然产生的伪像阻碍了从重建图像估计运动,特别是在高加速因子下。这项工作介绍了一种用于动态心脏MRI序列压缩感知重建的鲁棒的分组非刚性运动估计技术。理论和方法:一种基于B样条变形模型和最小二乘的时空正则化分组非刚性注册方法。度量标准用于估计和补偿屏气电影采集中的心脏运动,并获得在时间转换域中具有高度稀疏表示的准静态序列。结果:体内短轴数据集用于验证,原始多线圈以及DICOM数据。使用各种加速因子对全部采样数据进行追溯欠采样,并将重建结果与两种著名的方法k-t FOCUSS和MASTeR进行比较。结论:基于成组配准的重构方法显示的心脏电影图像重构质量高于成对成对的重构图像。

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