Adaptive K-space Updating Methods for Dynamic MRI Sequence Estimation

In dynamic magnetic resonance imaging (MRI), due to the limitation of imaging speed, it is commonly required to reconstruct the images from a reduced Fourier encoded K-space sequence. This paper presents two temporal model based methods to estimate the un-acquired K-space data, called adaptive K-space updating (AKU) methods. The AKU reconstruction algorithms are directly applicable to the truncated K-space sequence generated by the well known Fourier keyhole (FK) encoding scheme. The experimental study on the real MRI data shows that the proposed AKU methods can produce images with much lower reconstruction error than conventional FK method