Meeting Banner
Abstract #3129

Direct & accelerated parameter mapping using the unscented Kalman filter

Li Zhao 1 and Craig H. Meyer 1,2

1 Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States, 2 Radiology, University of Virginia, Charlottesville, Virginia, United States

Parameter mapping is essential for clinic diagnose and its acceleration is highly demanded. With under sampling in kspace-parameter encoding space, we proposed an unscented Kalman filter based method to estimation the parameter directly without reconstruction of the interval images. This method was verified in accelerated T2 mapping on numerical phantom and volunteer data. Comparing to compressed sensing with K-SVD, unscented Kalman filter provides more accurate T2 map in less reconstruction time.

This abstract and the presentation materials are available to members only; a login is required.

Join Here