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Automated Calculation of Water‐equivalent Diameter (D(W)) Based on AAPM Task Group 220
The purpose of this study is to accurately and effectively automate the calculation of the water‐equivalent diameter ([Formula: see text]) from 3D CT images for estimating the size‐specific dose. [Formula: see text] is the metric that characterizes the patient size and attenuation. In this study, [F...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690059/ https://www.ncbi.nlm.nih.gov/pubmed/27455491 http://dx.doi.org/10.1120/jacmp.v17i4.6171 |
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author | Anam, Choirul Haryanto, Freddy Widita, Rena Arif, Idam Dougherty, Geoff |
author_facet | Anam, Choirul Haryanto, Freddy Widita, Rena Arif, Idam Dougherty, Geoff |
author_sort | Anam, Choirul |
collection | PubMed |
description | The purpose of this study is to accurately and effectively automate the calculation of the water‐equivalent diameter ([Formula: see text]) from 3D CT images for estimating the size‐specific dose. [Formula: see text] is the metric that characterizes the patient size and attenuation. In this study, [Formula: see text] was calculated for standard CTDI phantoms and patient images. Two types of phantom were used, one representing the head with a diameter of 16 cm and the other representing the body with a diameter of 32 cm. Images of 63 patients were also taken, 32 who had undergone a CT head examination and 31 who had undergone a CT thorax examination. There are three main parts to our algorithm for automated [Formula: see text] calculation. The first part is to read 3D images and convert the CT data into Hounsfield units (HU). The second part is to find the contour of the phantoms or patients automatically. And the third part is to automate the calculation of [Formula: see text] based on the automated contouring for every slice ([Formula: see text]). The results of this study show that the automated calculation of [Formula: see text] and the manual calculation are in good agreement for phantoms and patients. The differences between the automated calculation of [Formula: see text] and the manual calculation are less than 0.5%. The results of this study also show that the estimating of [Formula: see text] using [Formula: see text] (central slice along longitudinal axis) produces percentage differences of [Formula: see text] and [Formula: see text] , and estimating [Formula: see text] using [Formula: see text] produces percentage differences of [Formula: see text] and [Formula: see text] , for thorax and head examinations, respectively. From this study, the percentage differences between normalized size‐specific dose estimate for every slice ([Formula: see text]) and [Formula: see text] are [Formula: see text] and [Formula: see text] for thorax and head examinations, respectively; between [Formula: see text] and [Formula: see text] are [Formula: see text] and [Formula: see text] for thorax and head examinations, respectively. PACS number(s): 87.57.Q‐, 87.57.uq‐ |
format | Online Article Text |
id | pubmed-5690059 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-56900592018-04-02 Automated Calculation of Water‐equivalent Diameter (D(W)) Based on AAPM Task Group 220 Anam, Choirul Haryanto, Freddy Widita, Rena Arif, Idam Dougherty, Geoff J Appl Clin Med Phys Medical Imaging The purpose of this study is to accurately and effectively automate the calculation of the water‐equivalent diameter ([Formula: see text]) from 3D CT images for estimating the size‐specific dose. [Formula: see text] is the metric that characterizes the patient size and attenuation. In this study, [Formula: see text] was calculated for standard CTDI phantoms and patient images. Two types of phantom were used, one representing the head with a diameter of 16 cm and the other representing the body with a diameter of 32 cm. Images of 63 patients were also taken, 32 who had undergone a CT head examination and 31 who had undergone a CT thorax examination. There are three main parts to our algorithm for automated [Formula: see text] calculation. The first part is to read 3D images and convert the CT data into Hounsfield units (HU). The second part is to find the contour of the phantoms or patients automatically. And the third part is to automate the calculation of [Formula: see text] based on the automated contouring for every slice ([Formula: see text]). The results of this study show that the automated calculation of [Formula: see text] and the manual calculation are in good agreement for phantoms and patients. The differences between the automated calculation of [Formula: see text] and the manual calculation are less than 0.5%. The results of this study also show that the estimating of [Formula: see text] using [Formula: see text] (central slice along longitudinal axis) produces percentage differences of [Formula: see text] and [Formula: see text] , and estimating [Formula: see text] using [Formula: see text] produces percentage differences of [Formula: see text] and [Formula: see text] , for thorax and head examinations, respectively. From this study, the percentage differences between normalized size‐specific dose estimate for every slice ([Formula: see text]) and [Formula: see text] are [Formula: see text] and [Formula: see text] for thorax and head examinations, respectively; between [Formula: see text] and [Formula: see text] are [Formula: see text] and [Formula: see text] for thorax and head examinations, respectively. PACS number(s): 87.57.Q‐, 87.57.uq‐ John Wiley and Sons Inc. 2016-07-08 /pmc/articles/PMC5690059/ /pubmed/27455491 http://dx.doi.org/10.1120/jacmp.v17i4.6171 Text en © 2016 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 | Medical Imaging Anam, Choirul Haryanto, Freddy Widita, Rena Arif, Idam Dougherty, Geoff Automated Calculation of Water‐equivalent Diameter (D(W)) Based on AAPM Task Group 220 |
title | Automated Calculation of Water‐equivalent Diameter (D(W)) Based on AAPM Task Group 220 |
title_full | Automated Calculation of Water‐equivalent Diameter (D(W)) Based on AAPM Task Group 220 |
title_fullStr | Automated Calculation of Water‐equivalent Diameter (D(W)) Based on AAPM Task Group 220 |
title_full_unstemmed | Automated Calculation of Water‐equivalent Diameter (D(W)) Based on AAPM Task Group 220 |
title_short | Automated Calculation of Water‐equivalent Diameter (D(W)) Based on AAPM Task Group 220 |
title_sort | automated calculation of water‐equivalent diameter (d(w)) based on aapm task group 220 |
topic | Medical Imaging |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690059/ https://www.ncbi.nlm.nih.gov/pubmed/27455491 http://dx.doi.org/10.1120/jacmp.v17i4.6171 |
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