Montesinos, PhilippeAbascal, JuanChamorro Servent, JuditChavarrías, CristinaBenito, M.Vaquero López, Juan JoséDesco Menéndez, Manuel2015-03-032015-03-0320112011 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC): Valencia, Spain. 23-29 October 2011 (2011). IEEE, 3462-3464.978-1-4673-0118-31082-3654https://hdl.handle.net/10016/20132Proceedings of: 2011 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). Valencia, Spain, 23-29 October 2011Dynamic cardiac magnetic resonance imaging in small animals is an important tool in the study of cardiovascular diseases. The reduction of the long acquisition times required for cardiovascular applications is crucial to achieve good spatiotemporal resolution and signal-to-noise ratio. Nowadays there are many acceleration techniques which can reduce acquisition time, including compressed sensing technique. Compressed sensing allows image reconstruction from undersampled data, by means of a non linear reconstruction which minimizes the total variation of the image. The recently appeared Split Bregman methodology has proved to be more computationally efficient to solve this problem than classic optimization methods. In the case of dynamic magnetic resonance imaging, compressed sensing can exploit time sparsity by the minimization of total variation across both space and time. In this work, we propose and validate the Split Bregman method to minimize spatial and time total variation, and apply this method to accelerate cardiac cine acquisitions in rats. We found that applying a quasi-random variable density pattern along the phase-encoding direction, accelerations up to a factor 5 are possible with low error. In the future, we expect to obtain higher accelerations using spatiotemporal undersampling.3application/pdfeng© 2011 IEEE.Biomedical MRICardiovascular systemCompressed sensingDiseasesImage codingImage reconstructionImage samplingOptimisationPhase codingSpatiotemporal phenomenaVariational techniquesconference paperMedicinaBiología y Biomedicina10.1109/NSSMIC.2011.6152633open access346234642011 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC)CC/0000016115