3352 20190219081243.0 INPRO--2009-082 eng Hernández, Mónica Comparing algorithms for diffeomorphic registration: Stationary LDDMM and Diffeomorphic Demons 2009-09-15 mult. p The stationary parameterization of diffeomorphisms is being increasingly used in computational anatomy. In certain applications it provides similar results to th e non-stationary parameterization alleviating the computational charge. With this characterization for diffeomorphisms, two different registration algor ithms have been recently proposed: stationary LDDMM and diffeomorphic Demons. To our knowledge, their theoretical and practical differences have not been anal yzed yet. In this article we provide a comparison between both algorithms in a common fram ework. To this end, we have studied the differences in the elements of both registratio n scenarios. We have analyzed the sensitivity of the regularization parameters in the smoothn ess of the final transformations and compared the performance of the registration re sults. Moreover, we have studied the potential of both algorithms for the computation o f essential operations for further statistical analysis. We have found that both methods have comparable performance in terms of image ma tching although the transformations are qualitatively different in some cases. Diffeomo rphic Demons shows a slight advantage in terms of computational time. However, it does not pr ovide as stationary LDDMM the vector field in the tangent space needed to compute statist ics or exact inverse transformations. info:eu-repo/semantics/openAccess Esta obra está sujeta a una licencia de uso Creative Commons. Se permite la reproducción total o parcial, la distribución, la comunicación pública de la obra y la creación de obras derivadas, siempre que no sea con finalidades comerciales, y sempre que se reconzca la autoria de la obra original. https://creativecommons.org/licenses/by-nc/4.0/ Computational Anatomy diffeomorphic registration stationary parameterization stationary LDDMM diffeomorphic Demons Pennec, Xavier Olmos Gassó, Salvador mhg@unizar.es 364241 http://zaguan.unizar.es/record/3352/files/INPRO--2009-082.pdf Archivo asociado Informática e Ingeniería de Sistemas PREPRINT