Int J Comput Assist Radiol Surg - Intensity-based hierarchical elastic registration using approximating splines.

Tópicos

{ imag(1057) registr(996) error(939) }
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Resumo

RPOSE: We introduce a new hierarchical approach for elastic medical image registration using approximating splines. In order to obtain the dense deformation field, we employ Gaussian elastic body splines (GEBS) that incorporate anisotropic landmark errors and rotation information. Since the GEBS approach is based on a physical model in form of analytical solutions of the Navier equation, it can very well cope with the local as well as global deformations present in the images by varying the standard deviation of the Gaussian forces.METHODS: The proposed GEBS approximating model is integrated into the elastic hierarchical image registration framework, which decomposes a nonrigid registration problem into numerous local rigid transformations. The approximating GEBS registration scheme incorporates anisotropic landmark errors as well as rotation information. The anisotropic landmark localization uncertainties can be estimated directly from the image data, and in this case, they represent the minimal stochastic localization error, i.e., the Cram?r-Rao bound. The rotation information of each landmark obtained from the hierarchical procedure is transposed in an additional angular landmark, doubling the number of landmarks in the GEBS model.RESULTS: The modified hierarchical registration using the approximating GEBS model is applied to register 161 image pairs from a digital mammogram database. The obtained results are very encouraging, and the proposed approach significantly improved all registrations comparing the mean-square error in relation to approximating TPS with the rotation information. On artificially deformed breast images, the newly proposed method performed better than the state-of-the-art registration algorithm introduced by Rueckert et al. (IEEE Trans Med Imaging 18:712-721, 1999). The average error per breast tissue pixel was less than 2.23 pixels compared to 2.46 pixels for Rueckert's method.CONCLUSION: The proposed hierarchical elastic image registration approach incorporates the GEBS approximation scheme extended with anisotropic landmark localization uncertainties as well as rotation information. Our experimental results show that the proposed scheme improved the registration result significantly.

Resumo Limpo

rpose introduc new hierarch approach elast medic imag registr use approxim spline order obtain dens deform field employ gaussian elast bodi spline geb incorpor anisotrop landmark error rotat inform sinc geb approach base physic model form analyt solut navier equat can well cope local well global deform present imag vari standard deviat gaussian forcesmethod propos geb approxim model integr elast hierarch imag registr framework decompos nonrigid registr problem numer local rigid transform approxim geb registr scheme incorpor anisotrop landmark error well rotat inform anisotrop landmark local uncertainti can estim direct imag data case repres minim stochast local error ie cramrrao bound rotat inform landmark obtain hierarch procedur transpos addit angular landmark doubl number landmark geb modelresult modifi hierarch registr use approxim geb model appli regist imag pair digit mammogram databas obtain result encourag propos approach signific improv registr compar meansquar error relat approxim tps rotat inform artifici deform breast imag newli propos method perform better stateoftheart registr algorithm introduc rueckert et al ieee tran med imag averag error per breast tissu pixel less pixel compar pixel rueckert methodconclus propos hierarch elast imag registr approach incorpor geb approxim scheme extend anisotrop landmark local uncertainti well rotat inform experiment result show propos scheme improv registr result signific

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