Quantifying effects of deformable CT-MR registration

Abstract: Rigid image registration is an important part of many medical applications. In order to make correct decisions from the registration process the un-certainty of the results should be included. In this thesis a framework for estimating and visualising the spatial uncertainty of rigid image registration without groundtruth measurements is presented. The framework uses a deformable registration algorithm to estimate the errors and a groupwise registration for collocating multiple image sets to generate multiple realisations of the error field. A mean and covariance field are then generated which allows a characterisation of the error field. The framework is used to evaluate errors in CT-MR registration and a statistically significant bias field is detected using random field theory. It is also established that B-spline registration of CT images to themselves exhibit a bias.