Cargando…

Nonlinear image registration with bidirectional metric and reciprocal regularization

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 deformati...

Descripción completa

Detalles Bibliográficos
Autores principales: Ying, Shihui, Li, Dan, Xiao, Bin, Peng, Yaxin, Du, Shaoyi, Xu, Meifeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5322897/
https://www.ncbi.nlm.nih.gov/pubmed/28231342
http://dx.doi.org/10.1371/journal.pone.0172432
_version_ 1782509932826853376
author Ying, Shihui
Li, Dan
Xiao, Bin
Peng, Yaxin
Du, Shaoyi
Xu, Meifeng
author_facet Ying, Shihui
Li, Dan
Xiao, Bin
Peng, Yaxin
Du, Shaoyi
Xu, Meifeng
author_sort Ying, Shihui
collection PubMed
description 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.
format Online
Article
Text
id pubmed-5322897
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-53228972017-03-09 Nonlinear image registration with bidirectional metric and reciprocal regularization Ying, Shihui Li, Dan Xiao, Bin Peng, Yaxin Du, Shaoyi Xu, Meifeng PLoS One Research Article 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. Public Library of Science 2017-02-23 /pmc/articles/PMC5322897/ /pubmed/28231342 http://dx.doi.org/10.1371/journal.pone.0172432 Text en © 2017 Ying et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ying, Shihui
Li, Dan
Xiao, Bin
Peng, Yaxin
Du, Shaoyi
Xu, Meifeng
Nonlinear image registration with bidirectional metric and reciprocal regularization
title Nonlinear image registration with bidirectional metric and reciprocal regularization
title_full Nonlinear image registration with bidirectional metric and reciprocal regularization
title_fullStr Nonlinear image registration with bidirectional metric and reciprocal regularization
title_full_unstemmed Nonlinear image registration with bidirectional metric and reciprocal regularization
title_short Nonlinear image registration with bidirectional metric and reciprocal regularization
title_sort nonlinear image registration with bidirectional metric and reciprocal regularization
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5322897/
https://www.ncbi.nlm.nih.gov/pubmed/28231342
http://dx.doi.org/10.1371/journal.pone.0172432
work_keys_str_mv AT yingshihui nonlinearimageregistrationwithbidirectionalmetricandreciprocalregularization
AT lidan nonlinearimageregistrationwithbidirectionalmetricandreciprocalregularization
AT xiaobin nonlinearimageregistrationwithbidirectionalmetricandreciprocalregularization
AT pengyaxin nonlinearimageregistrationwithbidirectionalmetricandreciprocalregularization
AT dushaoyi nonlinearimageregistrationwithbidirectionalmetricandreciprocalregularization
AT xumeifeng nonlinearimageregistrationwithbidirectionalmetricandreciprocalregularization