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Status: Bibliographieeintrag

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Verfasst von:Liao, Wei [VerfasserIn]   i
 Rohr, Karl [VerfasserIn]   i
 Kang, Chang-Ki [VerfasserIn]   i
 Cho, Zang-Hee [VerfasserIn]   i
 Wörz, Stefan [VerfasserIn]   i
Titel:Automatic 3D segmentation and quantification of lenticulostriate arteries from high-resolution 7 Tesla MRA images
Verf.angabe:Wei Liao, Karl Rohr, Chang-Ki Kang, Zang-Hee Cho, and Stefan Wörz
E-Jahr:2016
Jahr:February 2016
Umfang:14 S.
Fussnoten:Gesehen am 04.06.2020
Titel Quelle:Enthalten in: Institute of Electrical and Electronics EngineersIEEE transactions on image processing
Ort Quelle:New York, NY : IEEE, 1992
Jahr Quelle:2016
Band/Heft Quelle:25(2016), 1, Seite 400-413
ISSN Quelle:1941-0042
Abstract:We propose a novel hybrid approach for automatic 3D segmentation and quantification of high-resolution 7 Tesla magnetic resonance angiography (MRA) images of the human cerebral vasculature. Our approach consists of two main steps. First, a 3D model-based approach is used to segment and quantify thick vessels and most parts of thin vessels. Second, remaining vessel gaps of the first step in low-contrast and noisy regions are completed using a 3D minimal path approach, which exploits directional information. We present two novel minimal path approaches. The first is an explicit approach based on energy minimization using probabilistic sampling, and the second is an implicit approach based on fast marching with anisotropic directional prior. We conducted an extensive evaluation with over 2300 3D synthetic images and 40 real 3D 7 Tesla MRA images. Quantitative and qualitative evaluation shows that our approach achieves superior results compared with a previous minimal path approach. Furthermore, our approach was successfully used in two clinical studies on stroke and vascular dementia.
DOI:doi:10.1109/TIP.2015.2499085
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: https://doi.org/10.1109/TIP.2015.2499085
 DOI: https://doi.org/10.1109/TIP.2015.2499085
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:3D minimal path approach
 3D model-based approach
 3D synthetic imaging
 3D vessel segmentation
 7T MRA data
 automatic 3D segmentation
 biomedical MRI
 blood vessels
 Cerebral Cortex
 cerebral vasculature
 Data models
 Dementia, Vascular
 directional speed function
 energy minimization
 fast marching
 high-resolution 7 tesla magnetic resonance angiography imaging
 high-resolution 7 tesla MRA imaging
 human cerebral vasculature
 Humans
 image denoising
 image resolution
 image segmentation
 Image segmentation
 Imaging, Three-Dimensional
 lenticulostriate arteries
 low-contrast noisy regions
 magnetic flux density 7 tesla
 Magnetic Resonance Angiography
 medical disorders
 medical image processing
 Middle Cerebral Artery
 minimal path
 minimal path approach
 minimal path approaches
 Noise measurement
 parametric intensity model
 Probabilistic logic
 probabilistic sampling
 probability
 Shape
 Solid modeling
 Stroke
 stroke dementia
 thin vessels
 Three-dimensional displays
 vascular dementia
 vessel gaps
K10plus-PPN:1699780617
Verknüpfungen:→ Zeitschrift

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