Cardio-respiratory motion estimation for compressed sensing reconstruction of free-breathing 2D cine MRI
|Title||Cardio-respiratory motion estimation for compressed sensing reconstruction of free-breathing 2D cine MRI|
|Publication Type||Conference Paper|
|Year of Publication||2016|
|Authors||Royuela-del-Val, J., M. Martin-Fernandez, F. Simmross-Wattenberg, and C. Alberola López|
|Conference Name||Modulated/Incomplete Data 2016, SFB Workshop.|
|Publisher||Mathematical Optimization and Applications in Biomedical Sciences (MOBIS), SFB Research Center|
|Conference Location||Graz, Austria|
Respiratory motion is still an issue in MRI of the heart despite the introduction of Compressed Sensing (CS) techniques, which significantly accelerate acquisition . Recently , a double-binning scheme was introduced in which k-space data is split according both to the cardiac and respiratory phases (Fig. 1); at reconstruction, sparsity along both dimensions is exploited. Other methods introduce motion estimation and compensation in CS (MC-CS) either to correct the respiratory motion  or to promote sparsity for reconstruction improvement . In this work, we propose a technique to jointly estimate the respiratory and cardiac motions within a double-binning scheme, enabling the MC-CS reconstruction of respiratory resolved free-breathing 2D CINE MRI. Preliminary results on synthetic, highly undersampled (x16) Cartesian setup are shown.
 Lustig et al. MRM 2007,  Feng et al. MRM 2015,  Usman et al. MRM 2013.  Royuela-del-Val et al. MRM 2015.