Document Detail


Cerebral arteries: fully automated segmentation from CT angiography--a feasibility study.
MedLine Citation:
PMID:  18487538     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The purpose of this study was to retrospectively assess the feasibility of a fully automated image postprocessing tool for the segmentation of the arterial cerebrovasculature from computed tomographic (CT) angiography in 27 patients (nine men, 18 women; mean age, 55 years; age range, 33-76 years) with subarachnoid hemorrhage. The institutional review board approved this study, and informed consent was waived. The proposed method, which does not require the acquisition of an additional CT scan for bone suppression, consists of the following: (a) automatic detection of the main arteries for initialization, (b) segmentation of these arteries through the skull base, and (c) suppression of the large veins near the skull. The parameters of this method were optimized on the training subset of nine patients, and the method was successful at segmentation of the arteries in 15 (83%) of the 18 remaining patients. The difference between automatic and manual diameter measurements was 0.0 mm +/- 0.4 (standard deviation). The study results showed that fully automated segmentation of the cerebral arteries is feasible.
Authors:
Rashindra Manniesing; Max A Viergever; Aad van der Lugt; Wiro J Niessen
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Radiology     Volume:  247     ISSN:  1527-1315     ISO Abbreviation:  Radiology     Publication Date:  2008 Jun 
Date Detail:
Created Date:  2008-05-19     Completed Date:  2008-06-17     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0401260     Medline TA:  Radiology     Country:  United States    
Other Details:
Languages:  eng     Pagination:  841-6     Citation Subset:  AIM; IM    
Copyright Information:
(c) RSNA, 2008.
Affiliation:
Departments of Medical Informatics and Radiology, Erasmus MC-University Medical Center Rotterdam, Dr. Molewaterplein 40/50, 3015 GE Rotterdam, the Netherlands. r.manniesing@erasmusmc.nl
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MeSH Terms
Descriptor/Qualifier:
Adult
Aged
Angiography, Digital Subtraction
Automation
Cerebral Angiography / methods*
Cerebral Arteries
Contrast Media
Feasibility Studies
Female
Humans
Iohexol / analogs & derivatives,  diagnostic use
Male
Middle Aged
Radiographic Image Interpretation, Computer-Assisted / methods*
Retrospective Studies
Subarachnoid Hemorrhage / radiography*
Tomography, X-Ray Computed*
Chemical
Reg. No./Substance:
0/Contrast Media; 66108-95-0/Iohexol; 73334-07-3/iopromide

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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