Cargando…

Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries

Automated hemorrhage detection and segmentation in traumatic pelvic injuries is vital for fast and accurate treatment decision making. Hemorrhage is the main cause of deaths in patients within first 24 hours after the injury. It is very time consuming for physicians to analyze all Computed Tomograph...

Descripción completa

Detalles Bibliográficos
Autores principales: Davuluri, Pavani, Wu, Jie, Tang, Yang, Cockrell, Charles H., Ward, Kevin R., Najarian, Kayvan, Hargraves, Rosalyn H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3418697/
https://www.ncbi.nlm.nih.gov/pubmed/22919433
http://dx.doi.org/10.1155/2012/898430
_version_ 1782240661606498304
author Davuluri, Pavani
Wu, Jie
Tang, Yang
Cockrell, Charles H.
Ward, Kevin R.
Najarian, Kayvan
Hargraves, Rosalyn H.
author_facet Davuluri, Pavani
Wu, Jie
Tang, Yang
Cockrell, Charles H.
Ward, Kevin R.
Najarian, Kayvan
Hargraves, Rosalyn H.
author_sort Davuluri, Pavani
collection PubMed
description Automated hemorrhage detection and segmentation in traumatic pelvic injuries is vital for fast and accurate treatment decision making. Hemorrhage is the main cause of deaths in patients within first 24 hours after the injury. It is very time consuming for physicians to analyze all Computed Tomography (CT) images manually. As time is crucial in emergence medicine, analyzing medical images manually delays the decision-making process. Automated hemorrhage detection and segmentation can significantly help physicians to analyze these images and make fast and accurate decisions. Hemorrhage segmentation is a crucial step in the accurate diagnosis and treatment decision-making process. This paper presents a novel rule-based hemorrhage segmentation technique that utilizes pelvic anatomical information to segment hemorrhage accurately. An evaluation measure is used to quantify the accuracy of hemorrhage segmentation. The results show that the proposed method is able to segment hemorrhage very well, and the results are promising.
format Online
Article
Text
id pubmed-3418697
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher Hindawi Publishing Corporation
record_format MEDLINE/PubMed
spelling pubmed-34186972012-08-23 Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries Davuluri, Pavani Wu, Jie Tang, Yang Cockrell, Charles H. Ward, Kevin R. Najarian, Kayvan Hargraves, Rosalyn H. Comput Math Methods Med Research Article Automated hemorrhage detection and segmentation in traumatic pelvic injuries is vital for fast and accurate treatment decision making. Hemorrhage is the main cause of deaths in patients within first 24 hours after the injury. It is very time consuming for physicians to analyze all Computed Tomography (CT) images manually. As time is crucial in emergence medicine, analyzing medical images manually delays the decision-making process. Automated hemorrhage detection and segmentation can significantly help physicians to analyze these images and make fast and accurate decisions. Hemorrhage segmentation is a crucial step in the accurate diagnosis and treatment decision-making process. This paper presents a novel rule-based hemorrhage segmentation technique that utilizes pelvic anatomical information to segment hemorrhage accurately. An evaluation measure is used to quantify the accuracy of hemorrhage segmentation. The results show that the proposed method is able to segment hemorrhage very well, and the results are promising. Hindawi Publishing Corporation 2012 2012-07-19 /pmc/articles/PMC3418697/ /pubmed/22919433 http://dx.doi.org/10.1155/2012/898430 Text en Copyright © 2012 Pavani Davuluri 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
Davuluri, Pavani
Wu, Jie
Tang, Yang
Cockrell, Charles H.
Ward, Kevin R.
Najarian, Kayvan
Hargraves, Rosalyn H.
Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries
title Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries
title_full Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries
title_fullStr Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries
title_full_unstemmed Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries
title_short Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries
title_sort hemorrhage detection and segmentation in traumatic pelvic injuries
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3418697/
https://www.ncbi.nlm.nih.gov/pubmed/22919433
http://dx.doi.org/10.1155/2012/898430
work_keys_str_mv AT davuluripavani hemorrhagedetectionandsegmentationintraumaticpelvicinjuries
AT wujie hemorrhagedetectionandsegmentationintraumaticpelvicinjuries
AT tangyang hemorrhagedetectionandsegmentationintraumaticpelvicinjuries
AT cockrellcharlesh hemorrhagedetectionandsegmentationintraumaticpelvicinjuries
AT wardkevinr hemorrhagedetectionandsegmentationintraumaticpelvicinjuries
AT najariankayvan hemorrhagedetectionandsegmentationintraumaticpelvicinjuries
AT hargravesrosalynh hemorrhagedetectionandsegmentationintraumaticpelvicinjuries