Advertisement

 

 

Nonlinear image registration with bidirectional metric and reciprocal regularization.

Nonlinear image registration with bidirectional metric and reciprocal regularization.
Author Information (click to view)

Ying S, Li D, Xiao B, Peng Y, Du S, Xu M,


Ying S, Li D, Xiao B, Peng Y, Du S, Xu M, (click to view)

Ying S, Li D, Xiao B, Peng Y, Du S, Xu M,

Advertisement
Share on FacebookTweet about this on TwitterShare on LinkedIn

PloS one 2017 02 2312(2) e0172432 doi 10.1371/journal.pone.0172432
Abstract

Nonlinear registration is an important technique to align two different images and widely applied in medical image analysis. In this paper, we develop a novel nonlinear registration framework based on the diffeomorphic demons, where a reciprocal regularizer is introduced to assume that the deformation between two images is an exact diffeomorphism. In detail, first, we adopt a bidirectional metric to improve the symmetry of the energy functional, whose variables are two reciprocal deformations. Secondly, we slack these two deformations into two independent variables and introduce a reciprocal regularizer to assure the deformations being the exact diffeomorphism. Then, we utilize an alternating iterative strategy to decouple the model into two minimizing subproblems, where a new closed form for the approximate velocity of deformation is calculated. Finally, we compare our proposed algorithm on two data sets of real brain MR images with two relative and conventional methods. The results validate that our proposed method improves accuracy and robustness of registration, as well as the gained bidirectional deformations are actually reciprocal.

Submit a Comment

Your email address will not be published. Required fields are marked *

two × three =

[ HIDE/SHOW ]