Schultz G. Magnetic Resonance Imaging with Nonlinear Gradient Fields. Signal Encoding and Image Reconstruction

Springer, 2013. — 343 p.This work was accepted as a PhD thesis by the Faculty of Mathematics and Physics of the University of Freiburg, Germany. It spans five years of research conducted from April 2007 until March 2012.
In particular researchers and engineers who work in the field of biomedical engineering might profit from reading this text. A new approach of image encoding in magnetic resonance imaging is described: The fundamental principle of gradient linearity is challenged by investigating the possibilities of acquiring anatomical images with the help of nonlinear gradient fields. Besides a thorough theoretical analysis with a focus on signal encoding and image reconstruction, initial hardware implementations are tested using phantom as well as in-vivo measurements. Several applications are presented that give an impression about the implications that this technological advancement may have for future medical diagnostics.
Without the help of a great number of people, it would not have been possible to accomplish this piece of work.Physical and Technical Background
Image Reconstruction in MRI
Overview of PatLoc Imaging and Presentation of Initial Hardware Designs
Contributions of this Thesis and Current State of Research
Basics of Signal Encoding and Image Reconstruction inPatLoc Imaging
Direct Reconstruction for Cartesian PatLoc Imaging
Direct Reconstruction for Radial PatLoc Imaging
Iterative Reconstruction in PatLoc Imaging
Summary and Outlook