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Nonrigid Medical Image Registration Based on Mesh Deformation Constraints

Regularizing the deformation field is an important aspect in nonrigid medical image registration. By covering the template image with a triangular mesh, this paper proposes a new regularization constraint in terms of connections between mesh vertices. The connection relationship is preserved by the...

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Detalles Bibliográficos
Autores principales: Lin, XiangBo, Ruan, Su, Qiu, TianShuang, Guo, DongMei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3574660/
https://www.ncbi.nlm.nih.gov/pubmed/23424604
http://dx.doi.org/10.1155/2013/373082
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author Lin, XiangBo
Ruan, Su
Qiu, TianShuang
Guo, DongMei
author_facet Lin, XiangBo
Ruan, Su
Qiu, TianShuang
Guo, DongMei
author_sort Lin, XiangBo
collection PubMed
description Regularizing the deformation field is an important aspect in nonrigid medical image registration. By covering the template image with a triangular mesh, this paper proposes a new regularization constraint in terms of connections between mesh vertices. The connection relationship is preserved by the spring analogy method. The method is evaluated by registering cerebral magnetic resonance imaging (MRI) image data obtained from different individuals. Experimental results show that the proposed method has good deformation ability and topology-preserving ability, providing a new way to the nonrigid medical image registration.
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spelling pubmed-35746602013-02-19 Nonrigid Medical Image Registration Based on Mesh Deformation Constraints Lin, XiangBo Ruan, Su Qiu, TianShuang Guo, DongMei Comput Math Methods Med Research Article Regularizing the deformation field is an important aspect in nonrigid medical image registration. By covering the template image with a triangular mesh, this paper proposes a new regularization constraint in terms of connections between mesh vertices. The connection relationship is preserved by the spring analogy method. The method is evaluated by registering cerebral magnetic resonance imaging (MRI) image data obtained from different individuals. Experimental results show that the proposed method has good deformation ability and topology-preserving ability, providing a new way to the nonrigid medical image registration. Hindawi Publishing Corporation 2013 2013-02-03 /pmc/articles/PMC3574660/ /pubmed/23424604 http://dx.doi.org/10.1155/2013/373082 Text en Copyright © 2013 XiangBo Lin et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Lin, XiangBo
Ruan, Su
Qiu, TianShuang
Guo, DongMei
Nonrigid Medical Image Registration Based on Mesh Deformation Constraints
title Nonrigid Medical Image Registration Based on Mesh Deformation Constraints
title_full Nonrigid Medical Image Registration Based on Mesh Deformation Constraints
title_fullStr Nonrigid Medical Image Registration Based on Mesh Deformation Constraints
title_full_unstemmed Nonrigid Medical Image Registration Based on Mesh Deformation Constraints
title_short Nonrigid Medical Image Registration Based on Mesh Deformation Constraints
title_sort nonrigid medical image registration based on mesh deformation constraints
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3574660/
https://www.ncbi.nlm.nih.gov/pubmed/23424604
http://dx.doi.org/10.1155/2013/373082
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