Accelerated dynamic MRI via inter-frame motion estimation

Chuqing Cao, Ying Sun
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引用次数: 1

Abstract

The sparsity of MR images has been utilized to significantly undersample k-space measurements for accelerated MRI. In dynamic MRI, besides the spatiotemporal structures of images, the motion information should be considered to improve the reconstruction performance. Motivated by this, we propose a new method to recover dynamic MR images using partial k-space data based on the estimation of inter-frame motion. Our method consists of three main steps: single frame reconstruction, inter-frame motion estimation, and image sequence recovery. In contrast to algorithms which use a single reference frame for motion estimation, the motion information of each image in a dynamic MRI sequence is estimated according to adjacent frames. Since motion is estimated from the reconstructed images, the recovery process is robust against both noise and artifacts. The proposed method was evaluated on two dynamic MRI datasets, and compared with several state-of-the-art reconstruction methods. Experimental results demonstrate the effectiveness and robustness of the proposed method.
通过帧间运动估计加速动态MRI
磁共振图像的稀疏性已被用于显著欠样本k空间测量加速MRI。在动态MRI中,除了考虑图像的时空结构外,还应考虑运动信息以提高重建性能。基于此,我们提出了一种基于帧间运动估计的局部k空间数据恢复动态MR图像的新方法。我们的方法包括三个主要步骤:单帧重建、帧间运动估计和图像序列恢复。与使用单个参考帧进行运动估计的算法不同,动态MRI序列中每个图像的运动信息是根据相邻帧进行估计的。由于运动是从重建图像中估计的,因此恢复过程对噪声和伪像都具有鲁棒性。该方法在两个动态MRI数据集上进行了评估,并与几种最新的重建方法进行了比较。实验结果证明了该方法的有效性和鲁棒性。
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