Director of Research (if dissertation) or Advisor (if thesis)
Kamalabadi, Farzad
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Kalman filter
ensemble Kalman filter
magnetic resonance imaging (MRI)
optical flow
dynamic imaging
cardiac imaging
Abstract
We propose a cost-effective algorithm for the dynamic image reconstruction problem in magnetic resonance imaging (MRI). The proposed imaging method, the ensemble Kalman filter, is a Monte Carlo approximation to the Kalman filter with reduced computational cost. The technique reconstructs images of snapshots taken during a cardiac cycle from a low number of measurements that can be obtained during the time interval. The algorithm makes use of a dynamic imaging model of the object derived from prior information.
The results are produced by applying the method on the extended
cardiac-torso (XCAT) human body phantom with real life parameter selections. The reconstructions are sharp, accurate and fast without any ringing artifacts caused by the conventional methods.
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