Date of Award
Spring 2008
Document Type
Thesis - Restricted
Degree Name
Master of Science (MS)
Department
Electrical and Computer Engineering
First Advisor
Johnson, Michael T.
Second Advisor
Polzin, Jason A.
Third Advisor
Richie, James E.
Abstract
Post processing of magnetic resonance (MR) images generally make use of cubic interpolation to estimate values off of the Cartesian grid, as it does not suffer from the artifacts caused by linear and nearest neighbor interpolation yet is not as computationally expensive as sine interpolation. In this thesis, we look to investigate whether recent advances in generalized interpolation techniques can be extended to improve MR image quality, while keeping in mind the relative computation cost of competing techniques. We start with head to head comparisons of interpolation techniques on compounded rotations of controlled, simulated data. Next, the impact on phantom and in-vivo data sets when this higher order interpolant is used along with complex data in image magnification is demonstrated. Finally, the non-rigid transformation mapping of MR gradient distortion correction is considered and how this separable one-dimensional technique from the prior chapters and references behaves when extended to a nonseparable application.
Recommended Citation
Slavens, Zachary W., "Generalized Interpolation applied to MR Image Magnification and Gradient Nonlinearity Correction" (2008). Master's Theses (1922-2009) Access restricted to Marquette Campus. 4229.
https://epublications.marquette.edu/theses/4229