Dynamic Magnetic Resonance Imaging

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Erturk, Onur

Contributors dc:contributor

• Kamalabadi, Farzad

• Kalman filter
• ensemble Kalman filter
• magnetic resonance imaging (MRI)
• optical flow
• dynamic imaging
• cardiac imaging

Statement dc:rights

• Copyright 2011 Onur Erturk

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/24080

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/24080