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CT images and radiotherapy treatment planning of patients with breast cancer: A dataset
The data presented here were originally collected for the research project “CT-Scan processing and analysis in patient with breast cancer after radiotherapy”. Also, it reported in our study “Prediction of Lung Tissue Damage by Evaluating Clinical and Dosimetric Parameters in Breast Cancer Patients”...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5480817/ https://www.ncbi.nlm.nih.gov/pubmed/28664175 http://dx.doi.org/10.1016/j.dib.2017.06.002 |
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author | Rezaei, Mohammad Mohammadbeigi, Ahmad Khoshgard, Karim Haghparast, Abbas |
author_facet | Rezaei, Mohammad Mohammadbeigi, Ahmad Khoshgard, Karim Haghparast, Abbas |
author_sort | Rezaei, Mohammad |
collection | PubMed |
description | The data presented here were originally collected for the research project “CT-Scan processing and analysis in patient with breast cancer after radiotherapy”. Also, it reported in our study “Prediction of Lung Tissue Damage by Evaluating Clinical and Dosimetric Parameters in Breast Cancer Patients” (Hasanabdali et al., 2016) [1]. This article describes and directly links to 52 subjects referred to Mahdieh Oncology and Radiotherapy Center from February to August 2015. Treatment planning was done for delivering 50 Gy dose to PTV in 25 fractions. the lungs and heart objects were extracted from CT images along with compliance Dose plan. Dose-volume histogram (DVH) and Dose-mass histogram (DMH) extracted using CT images and dose plan matrix. Moreover, the complete clinical and dosimetric specifications of subjects is attached. |
format | Online Article Text |
id | pubmed-5480817 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-54808172017-06-29 CT images and radiotherapy treatment planning of patients with breast cancer: A dataset Rezaei, Mohammad Mohammadbeigi, Ahmad Khoshgard, Karim Haghparast, Abbas Data Brief Data Article The data presented here were originally collected for the research project “CT-Scan processing and analysis in patient with breast cancer after radiotherapy”. Also, it reported in our study “Prediction of Lung Tissue Damage by Evaluating Clinical and Dosimetric Parameters in Breast Cancer Patients” (Hasanabdali et al., 2016) [1]. This article describes and directly links to 52 subjects referred to Mahdieh Oncology and Radiotherapy Center from February to August 2015. Treatment planning was done for delivering 50 Gy dose to PTV in 25 fractions. the lungs and heart objects were extracted from CT images along with compliance Dose plan. Dose-volume histogram (DVH) and Dose-mass histogram (DMH) extracted using CT images and dose plan matrix. Moreover, the complete clinical and dosimetric specifications of subjects is attached. Elsevier 2017-06-10 /pmc/articles/PMC5480817/ /pubmed/28664175 http://dx.doi.org/10.1016/j.dib.2017.06.002 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Rezaei, Mohammad Mohammadbeigi, Ahmad Khoshgard, Karim Haghparast, Abbas CT images and radiotherapy treatment planning of patients with breast cancer: A dataset |
title | CT images and radiotherapy treatment planning of patients with breast cancer: A dataset |
title_full | CT images and radiotherapy treatment planning of patients with breast cancer: A dataset |
title_fullStr | CT images and radiotherapy treatment planning of patients with breast cancer: A dataset |
title_full_unstemmed | CT images and radiotherapy treatment planning of patients with breast cancer: A dataset |
title_short | CT images and radiotherapy treatment planning of patients with breast cancer: A dataset |
title_sort | ct images and radiotherapy treatment planning of patients with breast cancer: a dataset |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5480817/ https://www.ncbi.nlm.nih.gov/pubmed/28664175 http://dx.doi.org/10.1016/j.dib.2017.06.002 |
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