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3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes

By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT) scan. After a density field is computed based...

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Detalles Bibliográficos
Autores principales: Zhong, Zichun, Guo, Xiaohu, Cai, Yiqi, Yang, Yin, Wang, Jing, Jia, Xun, Mao, Weihua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4785510/
https://www.ncbi.nlm.nih.gov/pubmed/27019849
http://dx.doi.org/10.1155/2016/4382854
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author Zhong, Zichun
Guo, Xiaohu
Cai, Yiqi
Yang, Yin
Wang, Jing
Jia, Xun
Mao, Weihua
author_facet Zhong, Zichun
Guo, Xiaohu
Cai, Yiqi
Yang, Yin
Wang, Jing
Jia, Xun
Mao, Weihua
author_sort Zhong, Zichun
collection PubMed
description By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT) scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs) are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs) of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes.
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spelling pubmed-47855102016-03-27 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes Zhong, Zichun Guo, Xiaohu Cai, Yiqi Yang, Yin Wang, Jing Jia, Xun Mao, Weihua Biomed Res Int Research Article By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT) scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs) are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs) of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes. Hindawi Publishing Corporation 2016 2016-02-25 /pmc/articles/PMC4785510/ /pubmed/27019849 http://dx.doi.org/10.1155/2016/4382854 Text en Copyright © 2016 Zichun Zhong et al. https://creativecommons.org/licenses/by/4.0/ 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
Zhong, Zichun
Guo, Xiaohu
Cai, Yiqi
Yang, Yin
Wang, Jing
Jia, Xun
Mao, Weihua
3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes
title 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes
title_full 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes
title_fullStr 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes
title_full_unstemmed 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes
title_short 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes
title_sort 3d-2d deformable image registration using feature-based nonuniform meshes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4785510/
https://www.ncbi.nlm.nih.gov/pubmed/27019849
http://dx.doi.org/10.1155/2016/4382854
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