10 March 2006 Validation of elastic registration algorithms based on adaptive irregular grids for medical applications
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Elastic registration of medical images is an active field of current research. Registration algorithms have to be validated in order to show that they fulfill the requirements of a particular clinical application. Furthermore, validation strategies compare the performance of different registration algorithms and can hence judge which algorithm is best suited for a target application. In the literature, validation strategies for rigid registration algorithms have been analyzed. For a known ground truth they assess the displacement error at a few landmarks, which is not sufficient for elastic transformations described by a huge number of parameters. Hence we consider the displacement error averaged over all pixels in the whole image or in a region-of-interest of clinical relevance. Using artificially, but realistically deformed images of the application domain, we use this quality measure to analyze an elastic registration based on transformations defined on adaptive irregular grids for the following clinical applications: Magnetic Resonance (MR) images of freely moving joints for orthopedic investigations, thoracic Computed Tomography (CT) images for the detection of pulmonary embolisms, and transmission images as used for the attenuation correction and registration of independently acquired Positron Emission Tomography (PET) and CT images. The definition of a region-of-interest allows to restrict the analysis of the registration accuracy to clinically relevant image areas. The behaviour of the displacement error as a function of the number of transformation control points and their placement can be used for identifying the best strategy for the initial placement of the control points.
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Astrid Franz, Astrid Franz, Ingwer C. Carlsen, Ingwer C. Carlsen, Steffen Renisch, Steffen Renisch, Hans-Aloys Wischmann, Hans-Aloys Wischmann, "Validation of elastic registration algorithms based on adaptive irregular grids for medical applications", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 614429 (10 March 2006); doi: 10.1117/12.650577; https://doi.org/10.1117/12.650577

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