umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Automatic labeling of cerebral arteries in magnetic resonance angiography
Umeå University, Faculty of Medicine, Department of Radiation Sciences.
Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
Umeå University, Faculty of Medicine, Department of Radiation Sciences.
Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
Show others and affiliations
2016 (English)In: Magnetic Resonance Materials in Physics, Biology and Medicine, ISSN 0968-5243, E-ISSN 1352-8661, Vol. 29, no 1, 39-47 p.Article in journal (Refereed) Published
Resource type
Text
Abstract [en]

In order to introduce 4D flow magnetic resonance imaging (MRI) as a standard clinical instrument for studying the cerebrovascular system, new and faster postprocessing tools are necessary. The objective of this study was to construct and evaluate a method for automatic identification of individual cerebral arteries in a 4D flow MRI angiogram. Forty-six elderly individuals were investigated with 4D flow MRI. Fourteen main cerebral arteries were manually labeled and used to create a probabilistic atlas. An automatic atlas-based artery identification method (AAIM) was developed based on vascular-branch extraction and the atlas was used for identification. The method was evaluated by comparing automatic with manual identification in 4D flow MRI angiograms from 67 additional elderly individuals. Overall accuracy was 93 %, and internal carotid artery and middle cerebral artery labeling was 100 % accurate. Smaller and more distal arteries had lower accuracy; for posterior communicating arteries and vertebral arteries, accuracy was 70 and 89 %, respectively. The AAIM enabled fast and fully automatic labeling of the main cerebral arteries. AAIM functionality provides the basis for creating an automatic and powerful method to analyze arterial cerebral blood flow in clinical routine.

Place, publisher, year, edition, pages
2016. Vol. 29, no 1, 39-47 p.
Keyword [en]
Magnetic resonance angiography, Cerebral angiography, Circle of Willis, Atlases as topic, Automatic data processing
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:umu:diva-117830DOI: 10.1007/s10334-015-0512-5ISI: 000370159800005OAI: oai:DiVA.org:umu-117830DiVA: diva2:917002
Available from: 2016-04-05 Created: 2016-03-04 Last updated: 2016-04-05Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Dunås, ToraWahlin, AndersAmbarki, KhalidZarrinkoob, LalehBirgander, RichardMalm, JanEklund, Anders
By organisation
Department of Radiation SciencesUmeå Centre for Functional Brain Imaging (UFBI)Clinical Neuroscience
In the same journal
Magnetic Resonance Materials in Physics, Biology and Medicine
Radiology, Nuclear Medicine and Medical Imaging

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 278 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf