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.
| Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-2613 |
| Date | 01 July 2011 |
| Creators | Hawley, Jeffrey Allan |
| Contributors | Christensen, Gary Edward |
| Publisher | University of Iowa |
| Source Sets | University of Iowa |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | Copyright 2011 Jeffrey Hawley |
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