Abstract #1256

2D Image-Based Respiratory Motion Estimation for Free-Breathing Coronary MRA

Taehoon Shin¹, Holden H. Wu^1,2, Michael V. McConnell^1,2, Dwight G. Nishimura¹

¹Electrical Engineering, Stanford University, Stanford, CA, United States; ²Cardiovascular Medicine, Stanford University, Stanford, CA, United States

Correction for respiratory motion remains a major challenge in free-breathing coronary MRA. Motion estimation directly from the heart is potentially superior to conventional diaphragmatic navigator, and several methods based on DC or 1D projection signals have been proposed. We propose a 2D image-based respiratory navigator which allows accurate estimation of SI and AP motion of the heart. Despite the use of 2D images, the navigator acquisition time was significantly shortened by utilizing preserved motion correlation between aliased images. The feasibility of the proposed approach is demonstrated by phantom and in-vivo experiments.