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.
Keywords