Davide Piccini1, Arne Littmann2, Hui Xue3, Jens Guehring2, Michael O. Zenge2
1Pattern Recognition Lab,, University of Erlangen-Nuremberg, Erlangen, Germany; 2MR Applications & Workflow Development,, Siemens AG, Healthcare Sector, Erlangen, Germany; 3Imaging and Visualization, Siemens Corporate Research, Princeton, NJ, United States
In recent approaches implementing image-based 3D respiratory motion correction for interleaved whole-heart coronary MRA, the interleaves are straightforwardly grouped in equally spaced bins on the respiratory cycle. This allows to obtain undersampled images with minimal intra-bin respiratory motion that can be registered to a reference. However, for bins with a low number of interleaves or non-uniform spatial distribution, image quality is degraded by streaking and undersampling artifacts. Hence, image registration might fail and such bins are usually discarded. In this work an optimized binning approach is proposed which maximizes the uniformity of the distribution of the interleaves. With this method 3D affine motion correction is allowed for all bins.