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. Martín-Fernández, F. Simmross-Wattenberg, and C. Alberola-Lopez |
| Conference Name | Modulated/Incomplete Data 2016, SFB Workshop. |
| Date Published | 2016 |
| Publisher | Mathematical Optimization and Applications in Biomedical Sciences (MOBIS), SFB Research Center |
| Conference Location | Graz, Austria |
| Abstract | Respiratory motion is still an issue in MRI of the heart despite the introduction of Compressed Sensing (CS) techniques, which significantly accelerate acquisition [1]. Recently [2], 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 [3] or to promote sparsity for reconstruction improvement [4]. 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. [1] Lustig et al. MRM 2007, [2] Feng et al. MRM 2015, [3] Usman et al. MRM 2013. [4] Royuela-del-Val et al. MRM 2015. |