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.