k-T PCA: Temporally Constrained k-T BLAST Reconstruction Using Principal Component Analysis

Henrik Pedersen¹, Sebastian Kozerke²

The k-t BLAST technique has become widespread for achieving faster dynamic MRI. In its basic form k-t BLAST speeds up the data acquisition by undersampling k-t space and resolves the resulting aliasing in the reciprocal x-f space using an adaptive filter derived from low-resolution training images. However, this filtering process tends to increase the reconstruction error or lower the achievable acceleration factor. We show that temporal basis functions calculated by subjecting the training data to principal component analysis (PCA) can be used to constrain the reconstruction such that the temporal resolution is improved. The presented method is called k-t PCA.