Symmetric Log-Domain Diffeomorphic Registration: A Demons-Based Approach
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Symmetric inverse consistent nonlinear registration driven by mutual information
Computer Methods and Programs in Biomedicine
A new consistent image registration formulation with a B-spline deformation model
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Fast free-form deformation using graphics processing units
Computer Methods and Programs in Biomedicine
Diffeomorphic registration using b-splines
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
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Bias in image registration has to be accounted for when performing morphometric studies. The presence of bias can lead to unrealistic power estimates and can have an adverse effect in group separation studies. Most image registration algorithms are formulated in an asymmetric fashion and the solution is biased towards the transformation direction. The popular free-form deformation algorithm has been shown to be a robust and accurate method for medical image registration. However, it suffers from the lack of symmetry which could potentially bias the result. This work presents a symmetric and inverse-consistent variant of the free form deformation. We first assess the proposed framework in the context of segmentation-propagation. We also applied it to longitudinal images to assess regional volume change. In both evaluations, the symmetric algorithm outperformed a non-symmetric formulation of the free-form deformation.