Viton Vitanis1, Robert Manka, 1,2, Henrik Pedersen3, Peter Boesiger1, Sebastian Kozerke1
1Institute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland; 2German Heart Institute Berlin, Berlin, Germany; 3Functional Imaging Unit, Glostrup Hospital, Glostrup, Denmark
k-t PCA is an extension of k-t SENSE aiming at improving reconstruction of non-periodic dynamic images. It is based on a decomposition of the training and undersampled data into a temporally and a spatially invariant term using principal component analysis. In this abstract, a compartment based k-t PCA reconstruction approach is presented, which aims at improving highly undersampled, high-resolution 3D myocardial perfusion imaging by constraining the temporal content of different compartments in the image series based on the bolus arrival times and prior knowledge about the perfusion curves.