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Image processing for IMRT QA dosimetry
We have automated the determination of the placement location of the dosimetry ion chamber within intensity‐modulated radiotherapy (IMRT) fields, as part of streamlining the entire IMRT quality assurance process. This paper describes the mathematical image‐processing techniques to arrive at the appr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5723455/ https://www.ncbi.nlm.nih.gov/pubmed/16421497 http://dx.doi.org/10.1120/jacmp.v6i4.2071 |
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author | Zaini, Mehran R. Forest, Gary J. Loshek, David D. |
author_facet | Zaini, Mehran R. Forest, Gary J. Loshek, David D. |
author_sort | Zaini, Mehran R. |
collection | PubMed |
description | We have automated the determination of the placement location of the dosimetry ion chamber within intensity‐modulated radiotherapy (IMRT) fields, as part of streamlining the entire IMRT quality assurance process. This paper describes the mathematical image‐processing techniques to arrive at the appropriate measurement locations within the planar dose maps of the IMRT fields. A specific spot within the found region is identified based on its flatness, radiation magnitude, location, area, and the avoidance of the interleaf spaces. The techniques used include applying a Laplacian, dilation, erosion, region identification, and measurement point selection based on three parameters: the size of the erosion operator, the gradient, and the importance of the area of a region versus its magnitude. These three parameters are adjustable by the user. However, the first one requires tweaking in extremely rare occasions, the gradient requires rare adjustments, and the last parameter needs occasional fine‐tuning. This algorithm has been tested in over 50 cases. In about 5% of cases, the algorithm does not find a measurement point due to the extremely steep and narrow regions within the fluence maps. In such cases, manual selection of a point is allowed by our code, which is also difficult to ascertain, since the fluence map does not yield itself to an appropriate measurement point selection. PACS numbers: 87.53.Xd, 87.66.Cd, 87.57.Nk |
format | Online Article Text |
id | pubmed-5723455 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57234552018-04-02 Image processing for IMRT QA dosimetry Zaini, Mehran R. Forest, Gary J. Loshek, David D. J Appl Clin Med Phys Radiation Oncology Physics We have automated the determination of the placement location of the dosimetry ion chamber within intensity‐modulated radiotherapy (IMRT) fields, as part of streamlining the entire IMRT quality assurance process. This paper describes the mathematical image‐processing techniques to arrive at the appropriate measurement locations within the planar dose maps of the IMRT fields. A specific spot within the found region is identified based on its flatness, radiation magnitude, location, area, and the avoidance of the interleaf spaces. The techniques used include applying a Laplacian, dilation, erosion, region identification, and measurement point selection based on three parameters: the size of the erosion operator, the gradient, and the importance of the area of a region versus its magnitude. These three parameters are adjustable by the user. However, the first one requires tweaking in extremely rare occasions, the gradient requires rare adjustments, and the last parameter needs occasional fine‐tuning. This algorithm has been tested in over 50 cases. In about 5% of cases, the algorithm does not find a measurement point due to the extremely steep and narrow regions within the fluence maps. In such cases, manual selection of a point is allowed by our code, which is also difficult to ascertain, since the fluence map does not yield itself to an appropriate measurement point selection. PACS numbers: 87.53.Xd, 87.66.Cd, 87.57.Nk John Wiley and Sons Inc. 2005-11-22 /pmc/articles/PMC5723455/ /pubmed/16421497 http://dx.doi.org/10.1120/jacmp.v6i4.2071 Text en © 2005 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 Zaini, Mehran R. Forest, Gary J. Loshek, David D. Image processing for IMRT QA dosimetry |
title | Image processing for IMRT QA dosimetry |
title_full | Image processing for IMRT QA dosimetry |
title_fullStr | Image processing for IMRT QA dosimetry |
title_full_unstemmed | Image processing for IMRT QA dosimetry |
title_short | Image processing for IMRT QA dosimetry |
title_sort | image processing for imrt qa dosimetry |
topic | Radiation Oncology Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5723455/ https://www.ncbi.nlm.nih.gov/pubmed/16421497 http://dx.doi.org/10.1120/jacmp.v6i4.2071 |
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