Developing a Method for Distortion Correction in High b-Value Diffusion-Weighted Magnetic Resonance Imaging

Di usion-weighted magnetic resonance imaging (MRI) is a medical imaging technique that utilizes strong magnetic eld and radio waves to measure the speed of di usion of water in the human body. It has been a growing eld in recent years, with new methods continually being developed to further the knowledge of the human body, and especially the brain. Most of these methods are used to calculate tissue characteristics based on information from multiple images showing the same area but showing the speed of di usion in di erent directions. The calculations require thousands of images to hold information regarding the same tissue volume in the same place. These methods are improved by the use of more powerful magnets and larger magnetic eld gradients in the imaging sequences. These stronger elds unfortunately also introduce distortions in the images, caused by undesired induced eddy currents and the heating of the main magnetic eld, causing it to drift from its ideal strength. These distortions can make a part of the subject end up in di erent pixels for di erent images, while they should in fact be in the same place. Such a distortion makes it impossible to correctly calculate tissue characteristics based on multiple images. An example of this kind of characteristic is the fractional anisotropy that tells how much the speed of di usion of water di ers in di erent directions. Di erent correction methods can be applied to counter distortions. Various methods are available to correct distortions for images that use clinical strength di usion gradients (b < 1000 s mm􀀀2), but none are available for research sequences where the di usion gradients can have b-values larger than 4000 s mm􀀀2. This thesis outlines and implements a completely new correction method for such high b-value sequences. The method is a post-processing method that can be applied without any special requirements on the imaging sequence that is used. It is designed to correct for the image distortions caused by eddy current and magnetic eld drift in high b-value di usion MRI. A new post-processing method has been developed to correct for these distortions in high b-value di usion imaging. The method requires multiple b-values to be captured for an image series and works by registering these images to each other, while the low b-value images can be registered to a non-di usion weighted image, resulting in a global correction of the whole set of images. It uses local correlation for image comparison and particle swarm optimization to nd the maximum of the sum of local correlations. The new method has been tested on simulated data, on data from an imaging phantom and on real data from brain scans on volunteers. It is able to nd most of the distortions, being 10-20% o from the true parameters on the simulated data in the presence of a large level of noise. On the phantom data and the in vivo data, it is shown to correct all of the distortions that are visually present in the images. It greatly improves the alignment of the images in the data sets when large distortions are present, while it does not negatively a ect the images when no distortions are present. While the method improves images in its current con guration, further work is required to perfect the method. It does currently not handle patient movement, and optimization method that tries to nd the best correction parameters could be improved to make sure that all distortions are removed.