Reconstruction method by using sparse and low-rank structures for fast 4D-MRI acquisition

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Abstract

Previously, we proposed a method for reconstructing 4D-MRI of thoracoabdominal organs that can visualize and quantify the three-dimensional dynamics of organs due to respiration. However, the data acquisition time of the method is long, say, 30 min. In this study, we assume an interleave acquisition of images with a smaller number of the encoding in the k-space to shorten the data acquisition time. We also propose to use a reconstruction technique named k-t SLR that utilizes sparse and low rank structures of the data matrix to avoid image degradation due to the small number of data acquisition. We performed a simulation experiment where we regarded 4D-MR images by our previous method as ideal images, generated down sampled data in k-space, and applied k-t SLR reconstruction to those data. We evaluated the resultant images from three viewpoints and confirmed that the combination of fast data collection with a small number of encoding and the subsequent k-t SLR reconstruction can produce high quality MR images.

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APA

Kitakami, Y., Ohnishi, T., Masuda, Y., Matsumoto, K., & Haneishi, H. (2014). Reconstruction method by using sparse and low-rank structures for fast 4D-MRI acquisition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8676, pp. 269–277). Springer Verlag. https://doi.org/10.1007/978-3-319-13692-9_26

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