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Accuracy of 3D volumetric image registration based on CT, MR and PET/CT phantom experiments
Registration is critical for image‐based treatment planning and image‐guided treatment delivery. Although automatic registration is available, manual, visual‐based image fusion using three orthogonal planar views (3P) is always employed clinically to verify and adjust an automatic registration resul...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5722361/ https://www.ncbi.nlm.nih.gov/pubmed/19020479 http://dx.doi.org/10.1120/jacmp.v9i4.2781 |
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author | Li, Guang Xie, Huchen Ning, Holly Citrin, Deborah Capala, Jacek Maass‐Moreno, Roberto Guion, Peter Arora, Barbara Coleman, Norman Camphausen, Kevin Miller, Robert W. |
author_facet | Li, Guang Xie, Huchen Ning, Holly Citrin, Deborah Capala, Jacek Maass‐Moreno, Roberto Guion, Peter Arora, Barbara Coleman, Norman Camphausen, Kevin Miller, Robert W. |
author_sort | Li, Guang |
collection | PubMed |
description | Registration is critical for image‐based treatment planning and image‐guided treatment delivery. Although automatic registration is available, manual, visual‐based image fusion using three orthogonal planar views (3P) is always employed clinically to verify and adjust an automatic registration result. However, the 3P fusion can be time consuming, observer dependent, as well as prone to errors, owing to the incomplete 3‐dimensional (3D) volumetric image representations. It is also limited to single‐pixel precision (the screen resolution). The 3D volumetric image registration (3DVIR) technique was developed to overcome these shortcomings. This technique introduces a 4th dimension in the registration criteria beyond the image volume, offering both visual and quantitative correlation of corresponding anatomic landmarks within the two registration images, facilitating a volumetric image alignment, and minimizing potential registration errors. The 3DVIR combines image classification in real‐time to select and visualize a reliable anatomic landmark, rather than using all voxels for alignment. To determine the detection limit of the visual and quantitative 3DVIR criteria, slightly misaligned images were simulated and presented to eight clinical personnel for interpretation. Both of the criteria produce a detection limit of 0.1 mm and 0.1°. To determine the accuracy of the 3DVIR method, three imaging modalities (CT, MR and PET/CT) were used to acquire multiple phantom images with known spatial shifts. Lateral shifts were applied to these phantoms with displacement intervals of [Formula: see text]. The accuracy of the 3DVIR technique was determined by comparing the image shifts determined through registration to the physical shifts made experimentally. The registration accuracy, together with precision, was found to be: [Formula: see text] for CT/CT images, [Formula: see text] for MR/MR images, and [Formula: see text] for PET/CT images. This accuracy is consistent with the detection limit, suggesting an absence of detectable systematic error. This 3DVIR technique provides a superior alternative to the 3P fusion method for clinical applications. PACS numbers: 87.57.nj, 87.57.nm, 87.57.‐N, 87.57.‐s |
format | Online Article Text |
id | pubmed-5722361 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57223612018-04-02 Accuracy of 3D volumetric image registration based on CT, MR and PET/CT phantom experiments Li, Guang Xie, Huchen Ning, Holly Citrin, Deborah Capala, Jacek Maass‐Moreno, Roberto Guion, Peter Arora, Barbara Coleman, Norman Camphausen, Kevin Miller, Robert W. J Appl Clin Med Phys Radiation Oncology Physics Registration is critical for image‐based treatment planning and image‐guided treatment delivery. Although automatic registration is available, manual, visual‐based image fusion using three orthogonal planar views (3P) is always employed clinically to verify and adjust an automatic registration result. However, the 3P fusion can be time consuming, observer dependent, as well as prone to errors, owing to the incomplete 3‐dimensional (3D) volumetric image representations. It is also limited to single‐pixel precision (the screen resolution). The 3D volumetric image registration (3DVIR) technique was developed to overcome these shortcomings. This technique introduces a 4th dimension in the registration criteria beyond the image volume, offering both visual and quantitative correlation of corresponding anatomic landmarks within the two registration images, facilitating a volumetric image alignment, and minimizing potential registration errors. The 3DVIR combines image classification in real‐time to select and visualize a reliable anatomic landmark, rather than using all voxels for alignment. To determine the detection limit of the visual and quantitative 3DVIR criteria, slightly misaligned images were simulated and presented to eight clinical personnel for interpretation. Both of the criteria produce a detection limit of 0.1 mm and 0.1°. To determine the accuracy of the 3DVIR method, three imaging modalities (CT, MR and PET/CT) were used to acquire multiple phantom images with known spatial shifts. Lateral shifts were applied to these phantoms with displacement intervals of [Formula: see text]. The accuracy of the 3DVIR technique was determined by comparing the image shifts determined through registration to the physical shifts made experimentally. The registration accuracy, together with precision, was found to be: [Formula: see text] for CT/CT images, [Formula: see text] for MR/MR images, and [Formula: see text] for PET/CT images. This accuracy is consistent with the detection limit, suggesting an absence of detectable systematic error. This 3DVIR technique provides a superior alternative to the 3P fusion method for clinical applications. PACS numbers: 87.57.nj, 87.57.nm, 87.57.‐N, 87.57.‐s John Wiley and Sons Inc. 2008-07-09 /pmc/articles/PMC5722361/ /pubmed/19020479 http://dx.doi.org/10.1120/jacmp.v9i4.2781 Text en © 2008 The Authors. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/3.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Radiation Oncology Physics Li, Guang Xie, Huchen Ning, Holly Citrin, Deborah Capala, Jacek Maass‐Moreno, Roberto Guion, Peter Arora, Barbara Coleman, Norman Camphausen, Kevin Miller, Robert W. Accuracy of 3D volumetric image registration based on CT, MR and PET/CT phantom experiments |
title | Accuracy of 3D volumetric image registration based on CT, MR and PET/CT phantom experiments |
title_full | Accuracy of 3D volumetric image registration based on CT, MR and PET/CT phantom experiments |
title_fullStr | Accuracy of 3D volumetric image registration based on CT, MR and PET/CT phantom experiments |
title_full_unstemmed | Accuracy of 3D volumetric image registration based on CT, MR and PET/CT phantom experiments |
title_short | Accuracy of 3D volumetric image registration based on CT, MR and PET/CT phantom experiments |
title_sort | accuracy of 3d volumetric image registration based on ct, mr and pet/ct phantom experiments |
topic | Radiation Oncology Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5722361/ https://www.ncbi.nlm.nih.gov/pubmed/19020479 http://dx.doi.org/10.1120/jacmp.v9i4.2781 |
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