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A new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism

The lack of publicly available datasets of computed-tomography angiography (CTA) images for pulmonary embolism (PE) is a problem felt by physicians and researchers. Although a number of computer-aided detection (CAD) systems have been developed for PE diagnosis, their performance is often evaluated...

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Autores principales: Masoudi, Mojtaba, Pourreza, Hamid-Reza, Saadatmand-Tarzjan, Mahdi, Eftekhari, Noushin, Zargar, Fateme Shafiee, Rad, Masoud Pezeshki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122162/
https://www.ncbi.nlm.nih.gov/pubmed/30179235
http://dx.doi.org/10.1038/sdata.2018.180
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author Masoudi, Mojtaba
Pourreza, Hamid-Reza
Saadatmand-Tarzjan, Mahdi
Eftekhari, Noushin
Zargar, Fateme Shafiee
Rad, Masoud Pezeshki
author_facet Masoudi, Mojtaba
Pourreza, Hamid-Reza
Saadatmand-Tarzjan, Mahdi
Eftekhari, Noushin
Zargar, Fateme Shafiee
Rad, Masoud Pezeshki
author_sort Masoudi, Mojtaba
collection PubMed
description The lack of publicly available datasets of computed-tomography angiography (CTA) images for pulmonary embolism (PE) is a problem felt by physicians and researchers. Although a number of computer-aided detection (CAD) systems have been developed for PE diagnosis, their performance is often evaluated using private datasets. In this paper, we introduce a new public dataset called FUMPE (standing for Ferdowsi University of Mashhad's PE dataset) which consists of three-dimensional PE-CTA images of 35 different subjects with 8792 slices in total. For each benchmark image, two expert radiologists provided the ground-truth with the assistance of a semi-automated image processing software tool. FUMPE is a challenging benchmark for CAD methods because of the large number (i.e., 3438) of PE regions and, more especially, because of the location of most of them (i.e., 67%) in lung peripheral arteries. Moreover, due to the reporting of the Qanadli score for each PE-CTA image, FUMPE is the first public dataset which can be used for the analysis of mortality and morbidity risks associated with PE. We also report some complementary prognosis information for each subject.
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spelling pubmed-61221622018-09-07 A new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism Masoudi, Mojtaba Pourreza, Hamid-Reza Saadatmand-Tarzjan, Mahdi Eftekhari, Noushin Zargar, Fateme Shafiee Rad, Masoud Pezeshki Sci Data Data Descriptor The lack of publicly available datasets of computed-tomography angiography (CTA) images for pulmonary embolism (PE) is a problem felt by physicians and researchers. Although a number of computer-aided detection (CAD) systems have been developed for PE diagnosis, their performance is often evaluated using private datasets. In this paper, we introduce a new public dataset called FUMPE (standing for Ferdowsi University of Mashhad's PE dataset) which consists of three-dimensional PE-CTA images of 35 different subjects with 8792 slices in total. For each benchmark image, two expert radiologists provided the ground-truth with the assistance of a semi-automated image processing software tool. FUMPE is a challenging benchmark for CAD methods because of the large number (i.e., 3438) of PE regions and, more especially, because of the location of most of them (i.e., 67%) in lung peripheral arteries. Moreover, due to the reporting of the Qanadli score for each PE-CTA image, FUMPE is the first public dataset which can be used for the analysis of mortality and morbidity risks associated with PE. We also report some complementary prognosis information for each subject. Nature Publishing Group 2018-09-04 /pmc/articles/PMC6122162/ /pubmed/30179235 http://dx.doi.org/10.1038/sdata.2018.180 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
spellingShingle Data Descriptor
Masoudi, Mojtaba
Pourreza, Hamid-Reza
Saadatmand-Tarzjan, Mahdi
Eftekhari, Noushin
Zargar, Fateme Shafiee
Rad, Masoud Pezeshki
A new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism
title A new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism
title_full A new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism
title_fullStr A new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism
title_full_unstemmed A new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism
title_short A new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism
title_sort new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122162/
https://www.ncbi.nlm.nih.gov/pubmed/30179235
http://dx.doi.org/10.1038/sdata.2018.180
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