Reconstruction of Complex Vasculature by Varying the Slope of the Scan Plane in High-Field Magnetic Resonance Imaging

Reconstruction of vascular net of small laboratory animals from magnetic resonance imaging magnetic resonance imaging (MRI) data is associated with some problems. First of all this is due to the physics of nuclear magnetic resonance nuclear magnetic resonance signal registration. Scanner is sensible...

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Bibliographic Details
Published in:Applied magnetic resonance 2016-01, Vol.47 (1), p.23-39
Main Authors: Maltseva, S. V., Cherevko, A. A., Khe, A. K., Akulov, A. E., Savelov, A. A., Tulupov, A. A., Derevtsov, E. Yu, Moshkin, M. P., Chupakhin, A. P.
Format: Article
Language:English
Subjects:
Algorithms
Animals
Atoms and Molecules in Strong Fields
Blood flow
Blood vessels
Circulatory system
Flow velocity
Fragmentation
Hemodynamics
Image reconstruction
Laboratory animals
Laser Matter Interaction
Magnetic fields
Magnetic resonance imaging
Medical imaging
NMR
Nuclear magnetic resonance
Organic Chemistry
Partial differential equations
Physical Chemistry
Physics
Physics and Astronomy
Scanners
Solid State Physics
Spectroscopy/Spectrometry
Veins & arteries
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Summary:Reconstruction of vascular net of small laboratory animals from magnetic resonance imaging magnetic resonance imaging (MRI) data is associated with some problems. First of all this is due to the physics of nuclear magnetic resonance nuclear magnetic resonance signal registration. Scanner is sensible to the blood flow propagating through the section and shows real situation about vessel presence only if it is perpendicular to the scanning plane. If the vessel is parallel to the scanning plane scanner does not shows vessel presence. This circumstance causes the fragmentation of reconstructed vascular net. Despite the fact that all vessels in brain must be connected reconstructed vascular net consists of several fragments. We propose new algorithm allowing for reconstruction fragmentation-free vascular net according to the data of MRI scanner. Our approach is based on multiple scanning, object under consideration is probed by several sets of parallel planes. Our method allows for elimination or significant reduction mentioned disadvantage. The algorithm is applied to real MRI data of small laboratory animals and shows good results.
ISSN:0937-9347
1613-7507
DOI:10.1007/s00723-015-0726-8