Toward label-free imaging of brain vasculature: frame-by-frame spatial adaptive filtration and adaptive PIV approaches
Visualization of the smallest blood vessels in the brain, capillaries, and assessment of the blood flow rate in them is important in many physiological studies. However, it is in this case that conventional label-free imaging methods fail since both the number and velocity of red blood cells in the...
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| Veröffentlicht in: | European physical journal plus 2021-07, Vol.136 (7), p.719, Article 719 |
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| description | Visualization of the smallest blood vessels in the brain, capillaries, and assessment of the blood flow rate in them is important in many physiological studies. However, it is in this case that conventional label-free imaging methods fail since both the number and velocity of red blood cells in the capillaries are often too low. We present a label-free method of capillary blood flow analysis aimed at detecting and counting each single red blood cell in order to build a very detailed map of the vasculature. Such a map, in turn, enables us to more effectively apply the Particle Image Velocimetry method and make label-free blood flow velocity measurements in the smallest capillaries. Technically, our method is based on the adaptive spatial filtering of each frame of the acquired series of images using adaptive Niblack filtration. As a result of frame-by-frame filtering, we can differentiate single moving RBCs from static image artifacts having a similar size and brightness. We show the method applicability using two different biological models, specifically, the chicken embryo and the mouse brain. |
| doi_str_mv | 10.1140/epjp/s13360-021-01700-9 |
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Phys. J. Plus</addtitle><addtitle>EUR PHYS J PLUS</addtitle><description>Visualization of the smallest blood vessels in the brain, capillaries, and assessment of the blood flow rate in them is important in many physiological studies. However, it is in this case that conventional label-free imaging methods fail since both the number and velocity of red blood cells in the capillaries are often too low. We present a label-free method of capillary blood flow analysis aimed at detecting and counting each single red blood cell in order to build a very detailed map of the vasculature. Such a map, in turn, enables us to more effectively apply the Particle Image Velocimetry method and make label-free blood flow velocity measurements in the smallest capillaries. Technically, our method is based on the adaptive spatial filtering of each frame of the acquired series of images using adaptive Niblack filtration. 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| subjects | Applied and Technical Physics Atomic Biological models (mathematics) Blood Blood flow Blood vessels Brain Capillaries Capillary flow Complex Systems Condensed Matter Physics Erythrocytes Filtration Flow velocity Focus Point on Breakthrough Optics- and Complex Systems-based Technologies of Modulation of Drainage and Clearing Functions of the Brain Image acquisition Labels Laboratory animals Mathematical and Computational Physics Methods Molecular Optical and Plasma Physics Particle image velocimetry Physical Sciences Physics Physics and Astronomy Physics, Multidisciplinary Regular Article Science & Technology Spatial filtering Theoretical Visualization |
| title | Toward label-free imaging of brain vasculature: frame-by-frame spatial adaptive filtration and adaptive PIV approaches |
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