02223nas a2200217   4500008004100000020002300041245007800064210006900142260003200211300001200243520148200255100001801737700001701755700001901772700001801791700001901809700001801828700002101846700002401867856011401891       2011                        eng d  a978-1-4577-2006-2 00aA non-linear diffeomorphic framework for prostate multimodal registration0 anonlinear diffeomorphic framework for prostate multimodal regist  aNoosa, QLD bIEEEcDec 2011  a31 - 363 a<p>This paper presents a novel method for non-rigid registration of prostate multimodal images based on a nonlinear framework. The parametric estimation of the non-linear diffeomorphism between the 2D fixed and moving images has its basis in solving a set of non-linear equations of thin-plate splines. The regularized bending energy of the thin-plate splines along with the localization error of established correspondences is jointly minimized with the fixed and transformed image difference, where, the transformed image is represented by the set of non-linear equations defined over the moving image. The traditional thin-plate splines with established correspondences may provide good registration of the anatomical targets inside the prostate but may fail to provide improved contour registration. On the contrary, the proposed framework maintains the accuracy of registration in terms of overlap due to the non-linear thinplate spline functions while also producing smooth deformations of the anatomical structures inside the prostate as a result of established corrspondences. The registration accuracies of the proposed method are evaluated in 20 pairs of prostate midgland ultrasound and magnetic resonance images in terms of Dice similarity coefficient with an average of 0.982 ± 0.004, average 95% Hausdorff distance of 1.54 ± 0.46 mm and mean target registration and target localization errors of 1.90±1.27 mm and 0.15 ± 0.12 mm respectively. © 2011 IEEE.</p>1 aMitra, Jhimli1 aKato, Zoltan1 aMartí, Robert1 aArnau, Oliver1 aLladó, Xavier1 aGhose, Soumya1 aVilanova, Joan C1 aMeriaudeau, Fabrice  uhttps://inf.u-szeged.hu/publication/a-non-linear-diffeomorphic-framework-for-prostate-multimodal-registration