迭代重建
计算机科学
压缩传感
算法
重建算法
人工智能
计算机视觉
迭代法
断层摄影术
图像质量
作者
Madison Elizabeth Kretzler,Jesse I. Hamilton,Mark A. Griswold,Nicole Seiberlich
标识
DOI:10.1109/tmi.2018.2872419
摘要
Non-Cartesian trajectories are advantageous in the collection and reconstruction of dynamic MR images. Like many other fast imaging methods, the reconstruction technique k-t broad-use linear acquisition speed-up technique (BLAST) has been extended to non-Cartesian k-t BLAST through a conjugate gradient-based approach. However, it is necessary to transform and grid the data to a Cartesian domain as part of the reconstruction, a process which can be time consuming and computationally intensive. In this paper, a new non-iterative reconstruction, a-f BLAST, is proposed to extend k-t BLAST to radial sampling. The a-f BLAST reconstruction is performed in a previously unexplored domain termed the angular frequency-temporal frequency (a-f) space and uses similar steps to Cartesian k-t BLAST. The performance of this method was demonstrated on retrospectively undersampled numerical phantoms and compared with k-t BLAST, non-Cartesian k-t BLAST, and the sliding window technique. In addition, the reconstruction was tested on retrospectively and prospectively undersampled in vivo cardiac data. The a-f BLAST is shown to have a similar reconstruction time as k-t BLAST as well as outperform k-t BLAST in terms of root-mean-square error.
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