Processing of laser speckle contrast images to analyze the impact of aging on moving blood cells when a Lorentzian velocity profile is assumed. Khalil, A., Humeau-Heurtier, A., Abraham, P., & Mahé, G. In 2014 22nd European Signal Processing Conference (EUSIPCO), pages 2035-2039, Sep., 2014. abstract bibtex It has long been recognized that age alters microcirculation. The follow-up of such alterations can be performed by monitoring microvascular blood flow. Laser speckle contrast imaging (LSCI) has recently been commercialized to monitor microvascular blood flow. From laser speckle contrast images, velocity of microvascular moving scatterers (mainly red blood cells) can be computed when a profile for velocity distribution is assumed. Our goal herein is to analyze if alterations of microcirculation with age can be determined by processing experimental LSCI data. In our work a Lorentzian velocity profile is assumed and the presence of static scatterers, like skin, is taken into account. Our results show that moving scatterers velocities computed from LSCI data vary with age: blood cells velocities increase with age. Moreover, the more the static scatterers, the higher the moving scatterers velocity values. Our findings are a first step in the analysis of the impact of aging from the processing of laser speckle contrast images.
@InProceedings{6952747,
author = {A. Khalil and A. Humeau-Heurtier and P. Abraham and G. Mahé},
booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},
title = {Processing of laser speckle contrast images to analyze the impact of aging on moving blood cells when a Lorentzian velocity profile is assumed},
year = {2014},
pages = {2035-2039},
abstract = {It has long been recognized that age alters microcirculation. The follow-up of such alterations can be performed by monitoring microvascular blood flow. Laser speckle contrast imaging (LSCI) has recently been commercialized to monitor microvascular blood flow. From laser speckle contrast images, velocity of microvascular moving scatterers (mainly red blood cells) can be computed when a profile for velocity distribution is assumed. Our goal herein is to analyze if alterations of microcirculation with age can be determined by processing experimental LSCI data. In our work a Lorentzian velocity profile is assumed and the presence of static scatterers, like skin, is taken into account. Our results show that moving scatterers velocities computed from LSCI data vary with age: blood cells velocities increase with age. Moreover, the more the static scatterers, the higher the moving scatterers velocity values. Our findings are a first step in the analysis of the impact of aging from the processing of laser speckle contrast images.},
keywords = {haemodynamics;haemorheology;image processing;medical signal processing;laser speckle contrast images processing;Lorentzian velocity;microvascular blood flow;laser speckle contrast imaging;microvascular moving scatterers;red blood cells;static scatterers;Speckle;Senior citizens;Blood;Lasers;Imaging;Skin;Cells (biology);Laser speckle contrast imaging;Image processing;Blood flow;Lorentzian profile},
issn = {2076-1465},
month = {Sep.},
}
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Mahé},\n booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},\n title = {Processing of laser speckle contrast images to analyze the impact of aging on moving blood cells when a Lorentzian velocity profile is assumed},\n year = {2014},\n pages = {2035-2039},\n abstract = {It has long been recognized that age alters microcirculation. The follow-up of such alterations can be performed by monitoring microvascular blood flow. Laser speckle contrast imaging (LSCI) has recently been commercialized to monitor microvascular blood flow. From laser speckle contrast images, velocity of microvascular moving scatterers (mainly red blood cells) can be computed when a profile for velocity distribution is assumed. Our goal herein is to analyze if alterations of microcirculation with age can be determined by processing experimental LSCI data. In our work a Lorentzian velocity profile is assumed and the presence of static scatterers, like skin, is taken into account. 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