Gradient characterization in magnetic resonance imaging

Special magnetic resonance (MR) scans, such as spiral imaging and echo-planar imaging, require speed and gradient accuracy while putting high demands on the MR gradient system that may cause gradient distortion. Additionally, high field MR scans are prone to inhomogeneities that disturb the gradient system. Regardless of the source, gradient characterization provides a simple tool for distortion correction. An improved method, named the self-encoded slice selection algorithm, of characterizing the gradient system of the magnetic resonance system is proposed. It improves and combines the self-encode method and the direct slice selection method. The new approach is simple and fast, and allows for the measurement of waveform gradients that reach the system's limits. The technique is used to model the gradient system as a linear time-invariant transfer function through frequency-domain analysis and time-domain analysis. A transfer function model of the gradient system on the 3T Siemens Tim Trio scanner is presented here along with the characterization and analysis of common waveform gradients. Possible distortion correction approaches are also suggested.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2007

Author dc:creator

• Cheng, Joseph Yitan

Advisor dc:contributor.advisor

• Elfar Adalsteinsson.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/41257

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/41257