Date of Degree
MS (Master of Science)
Electrical and Computer Engineering
Gary E. Christensen
In medical image registration the goal is to find point by point correspondences between a source image and a target image such that the two images are aligned. There are rigid and non-rigid registration algorithms. Rigid registration uses rigid transformation methods which preserve distances between every pair of points. Non-rigid registration uses transformation methods that do not have to preserve the distances. Image registration has many medical applications -tracking tumors, anatomical changes over time, differences between characteristics like age and gender, etc. A gold standard transformation to compare and evaluate the registration algorithms would be ideal to use to verify if the two images are perfectly aligned. However, there is hardly if ever a gold standard transformation for non-rigid registration algorithms. The reason why there is no gold standard transformation for non-rigid registration algorithms is that pointwise correspondence between two registered points is not unique. In the absence of a gold standard various evaluation methods are used to gauge registration performance. However, each evaluation method only evalutes the error in the transformation from a limited perspective and therefore has its advantages and drawbacks. The Non-Rigid Image Registration Evaluation Project (NIREP) was was created to provide one central tool that has a collection of evaluation methods to perform the evaluations on non-rigid image registration algorithms and rank the registration algorithms based on the outputs of the evaluation methods in the absence of without having to use a gold standard.
viii, 114 pages
Includes bibliographical references (pages 113-114).
Copyright 2011 Jeffrey Hawley