Automated Quantification of Pneumothorax in CT

An automated, computer-aided diagnosis (CAD) algorithm for the quantification of pneumothoraces from Multidetector Computed Tomography (MDCT) images has been developed. Algorithm performance was evaluated through comparison to manual segmentation by expert radiologists. A combination of two-dimensio...

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Detalles Bibliográficos
Autores principales: Do, Synho, Salvaggio, Kristen, Gupta, Supriya, Kalra, Mannudeep, Ali, Nabeel U., Pien, Homer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2012
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3469107/
https://www.ncbi.nlm.nih.gov/pubmed/23082091
http://dx.doi.org/10.1155/2012/736320
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author Do, Synho
Salvaggio, Kristen
Gupta, Supriya
Kalra, Mannudeep
Ali, Nabeel U.
Pien, Homer
author_facet Do, Synho
Salvaggio, Kristen
Gupta, Supriya
Kalra, Mannudeep
Ali, Nabeel U.
Pien, Homer
author_sort Do, Synho
collection PubMed
description An automated, computer-aided diagnosis (CAD) algorithm for the quantification of pneumothoraces from Multidetector Computed Tomography (MDCT) images has been developed. Algorithm performance was evaluated through comparison to manual segmentation by expert radiologists. A combination of two-dimensional and three-dimensional processing techniques was incorporated to reduce required processing time by two-thirds (as compared to similar techniques). Volumetric measurements on relative pneumothorax size were obtained and the overall performance of the automated method shows an average error of just below 1%.
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spelling pubmed-34691072012-10-18 Automated Quantification of Pneumothorax in CT Do, Synho Salvaggio, Kristen Gupta, Supriya Kalra, Mannudeep Ali, Nabeel U. Pien, Homer Comput Math Methods Med Research Article An automated, computer-aided diagnosis (CAD) algorithm for the quantification of pneumothoraces from Multidetector Computed Tomography (MDCT) images has been developed. Algorithm performance was evaluated through comparison to manual segmentation by expert radiologists. A combination of two-dimensional and three-dimensional processing techniques was incorporated to reduce required processing time by two-thirds (as compared to similar techniques). Volumetric measurements on relative pneumothorax size were obtained and the overall performance of the automated method shows an average error of just below 1%. Hindawi Publishing Corporation 2012 2012-10-03 /pmc/articles/PMC3469107/ /pubmed/23082091 http://dx.doi.org/10.1155/2012/736320 Text en Copyright © 2012 Synho Do et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Do, Synho
Salvaggio, Kristen
Gupta, Supriya
Kalra, Mannudeep
Ali, Nabeel U.
Pien, Homer
Automated Quantification of Pneumothorax in CT
title Automated Quantification of Pneumothorax in CT
title_full Automated Quantification of Pneumothorax in CT
title_fullStr Automated Quantification of Pneumothorax in CT
title_full_unstemmed Automated Quantification of Pneumothorax in CT
title_short Automated Quantification of Pneumothorax in CT
title_sort automated quantification of pneumothorax in ct
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3469107/
https://www.ncbi.nlm.nih.gov/pubmed/23082091
http://dx.doi.org/10.1155/2012/736320
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