Upsampling of cardiac MR images: Comparison of averaging and super-resolution for the combination of multiple views

In cardiac imaging quantitative analysis heavily depends on the quality of the available image data. Cardiac MRI provides highly anisotropic voxel data. By combining multiple orthogonal data sets, isotropic volume data can be reconstructed. In this paper we investigate the increase in image quality by the use of a super-resolution reconstruction (SRR) algorithm. In particular, we compare a simple averaging with an SRR for combining two and three orthogonal views, respectively. We show that SRR outperforms averaging in case of the combination of two views, but that in case of three views SRR has no additional benefit compared to averaging. We conclude that for cardiac images where motion of the organ plays an important role the prior alignment of the image data sets is a limiting factor for successfully applying an SRR.