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.