A strategy to quantitatively evaluate MRI/PET cardiac rigid registration methods using a Monte Carlo simulator

Authors:
Nicoleta Pauna;Pierre Croisille;Nicolas Costes;Anthonin Reilhac;Timo Mäkelä;Onuc Cozar;Marc Janier;Patrick Clarysse
Affiliations:
CREATIS, INSA, Batiment Blaise Pascal, Villeurbanne Cedex, France and Department of Physics, Babes-Bolyai University, Cluj-Napoca, Romania;CREATIS, INSA, Batiment Blaise Pascal, Villeurbanne Cedex, France;CERMEP, Neurological Hospital, Lyon, France;CERMEP, Neurological Hospital, Lyon, France and McGill University, McConnel Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec, Canada;CREATIS, INSA, Batiment Blaise Pascal, Villeurbanne Cedex, France and Laboratory of Biomedical Engeeniering, Helsinki University of Technology, Finland;Department of Physics, Babes-Bolyai University, Cluj-Napoca, Romania;CREATIS, INSA, Batiment Blaise Pascal, Villeurbanne Cedex, France and CERMEP, Neurological Hospital, Lyon, France;CREATIS, INSA, Batiment Blaise Pascal, Villeurbanne Cedex, France
Venue:
FIMH'03 Proceedings of the 2nd international conference on Functional imaging and modeling of the heart
Year:
2003

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Abstract

The goal of this work is to present a strategy to validate cardiac MRI/PET registration methods. The strategy relies on a MRI/PET image reference data set including a computer generated PET data set of the thorax and its structures. This data set was produced using a Monte Carlo simulator from segmented T1-weighted MRI thorax data. From the reference data set as a gold standard, test transformations are randomly generated and used to quantify registration accuracy. The validation approach has been applied to our own rigid registration method with three different similarity measures: Correlation Ratio, Correlation Coefficient and Mutual Information. In this study, we observed that the Correlation Ratio gave better results both for thorax and heart image registration.