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Use of three‐dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four‐dimensional computed tomography data
A three‐dimensional (3D) optical flow program that includes a multi‐resolution feature has been developed and applied to 3D anatomic structure and gross tumor volume (GTV) contour mapping for four‐dimensional computed tomography (4D CT) data. The present study includes contour mapping for actual CT...
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/PMC5721534/ https://www.ncbi.nlm.nih.gov/pubmed/18449166 http://dx.doi.org/10.1120/jacmp.v9i1.2738 |
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author | Zhang, Geoffrey Huang, Tzung‐Chi Guerrero, Thomas Lin, Kang‐Ping Stevens, Craig Starkschall, George Forster, Ken |
author_facet | Zhang, Geoffrey Huang, Tzung‐Chi Guerrero, Thomas Lin, Kang‐Ping Stevens, Craig Starkschall, George Forster, Ken |
author_sort | Zhang, Geoffrey |
collection | PubMed |
description | A three‐dimensional (3D) optical flow program that includes a multi‐resolution feature has been developed and applied to 3D anatomic structure and gross tumor volume (GTV) contour mapping for four‐dimensional computed tomography (4D CT) data. The present study includes contour mapping for actual CT data sets from 3 patients and also for a thoracic phantom in which the displacement for each voxel was known. Of the CT data sets for the actual patients, one set was used to map lung and GTV contours over all respiration phases, and the other two were studied using only the end inspiration and end expiration phases, in which the displacements between phases were the largest. Including the residual motion in the 4D CT data and motion from table shaking, the optical flow calculation agrees with the known displacement to within 1 mm. Excluding errors not introduced by the optical flow algorithm, agreement for a displacement magnitude of 24 mm can be within 0.1 mm. The mapped contours in 4D CT images of lungs, liver, esophagus, GTV, and other structures for actual patients were acceptable to clinicians. The 3D optical flow program is a good tool for contour mapping of anatomic structure and tumor volume across 4D CT scans. PACS numbers: 87.55.D‐, 87.59.bd |
format | Online Article Text |
id | pubmed-5721534 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57215342018-04-02 Use of three‐dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four‐dimensional computed tomography data Zhang, Geoffrey Huang, Tzung‐Chi Guerrero, Thomas Lin, Kang‐Ping Stevens, Craig Starkschall, George Forster, Ken J Appl Clin Med Phys Radiation Oncology Physics A three‐dimensional (3D) optical flow program that includes a multi‐resolution feature has been developed and applied to 3D anatomic structure and gross tumor volume (GTV) contour mapping for four‐dimensional computed tomography (4D CT) data. The present study includes contour mapping for actual CT data sets from 3 patients and also for a thoracic phantom in which the displacement for each voxel was known. Of the CT data sets for the actual patients, one set was used to map lung and GTV contours over all respiration phases, and the other two were studied using only the end inspiration and end expiration phases, in which the displacements between phases were the largest. Including the residual motion in the 4D CT data and motion from table shaking, the optical flow calculation agrees with the known displacement to within 1 mm. Excluding errors not introduced by the optical flow algorithm, agreement for a displacement magnitude of 24 mm can be within 0.1 mm. The mapped contours in 4D CT images of lungs, liver, esophagus, GTV, and other structures for actual patients were acceptable to clinicians. The 3D optical flow program is a good tool for contour mapping of anatomic structure and tumor volume across 4D CT scans. PACS numbers: 87.55.D‐, 87.59.bd John Wiley and Sons Inc. 2008-02-05 /pmc/articles/PMC5721534/ /pubmed/18449166 http://dx.doi.org/10.1120/jacmp.v9i1.2738 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 Zhang, Geoffrey Huang, Tzung‐Chi Guerrero, Thomas Lin, Kang‐Ping Stevens, Craig Starkschall, George Forster, Ken Use of three‐dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four‐dimensional computed tomography data |
title | Use of three‐dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four‐dimensional computed tomography data |
title_full | Use of three‐dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four‐dimensional computed tomography data |
title_fullStr | Use of three‐dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four‐dimensional computed tomography data |
title_full_unstemmed | Use of three‐dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four‐dimensional computed tomography data |
title_short | Use of three‐dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four‐dimensional computed tomography data |
title_sort | use of three‐dimensional (3d) optical flow method in mapping 3d anatomic structure and tumor contours across four‐dimensional computed tomography data |
topic | Radiation Oncology Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5721534/ https://www.ncbi.nlm.nih.gov/pubmed/18449166 http://dx.doi.org/10.1120/jacmp.v9i1.2738 |
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