Mahdi Salmani Rahimi1, Steve R. Kecskemeti2, Walter F. Block1,3, Orhan Unal3
1Biomedical Engineering, University of Wisconsin, Madison, WI, United States; 2Physics, University of Wisconsin, Madison, WI, United States; 3Medical Physics, University of Wisconsin, Madison, WI, United States
A novel method has been proposed to use adaptive Kalman filtering and causal DCF based tornado filtering together to reconstruct undersampled MR images for dynamic and time resolved applications. Existing Kalman method uses an initialization scan or a sliding window to estimate system dynamics. In this work, we used tornado filter to infer motion maps for the Kalman process. This helps us to have a better estimation of image changes at every time frame and therefore a more accurate reconstruction. Simulations have been done on a cardiac phantom using radial projections and results were compared to existing techniques.