Laser speckle simulation tool based on stochastic differential equations for bio imaging applications
Laser speckle-based blood flow imaging is a well-accepted and widely used method for pre-clinical and clinical applications. Although it was introduced as a method to measure only superficial blood flow (< 1mm depth), several recently introduced variants resulted in measuring deep tissue blood fl...
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Published in | Biomedical optics express Vol. 13; no. 12; pp. 6745 - 6762 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
United States
Optica Publishing Group
01.12.2022
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Online Access | Get full text |
ISSN | 2156-7085 2156-7085 |
DOI | 10.1364/BOE.470926 |
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Abstract | Laser speckle-based blood flow imaging is a well-accepted and widely
used method for pre-clinical and clinical applications. Although it
was introduced as a method to measure only superficial blood flow
(< 1mm depth), several recently introduced variants resulted in
measuring deep tissue blood flow (a few cm) as well. A means of
simulating laser speckles is often necessary for the analysis and
development of these imaging modalities, as evident from many such
attempts towards developing simulation tools in the past. Such methods
often employ Fourier transforms or statistical tools to simulate
speckles with desired statistical properties. We present the first
method to use a stochastic differential equation to generate laser
speckles with a pre-determined probability density function and a
temporal auto-correlation. The method allows the choice of apriori
gamma distribution along with simple exponential or more complex
temporal auto-correlation statistics for simulated speckles, making it
suitable for different blood flow profiles. In contrast to the
existing methods that often generate speckles associated with
superficial flow, we simulate both superficial and diffuse speckles
leading to applications in deep tissue blood flow imaging. In
addition, we have also incorporated appropriate models for noise
associated with the detectors to simulate realistic speckles. We have
validated our model by comparing the simulated speckles with those
obtained from
in-vivo
studies in mice and healthy
human subject. |
---|---|
AbstractList | Laser speckle-based blood flow imaging is a well-accepted and widely
used method for pre-clinical and clinical applications. Although it
was introduced as a method to measure only superficial blood flow
(< 1mm depth), several recently introduced variants resulted in
measuring deep tissue blood flow (a few cm) as well. A means of
simulating laser speckles is often necessary for the analysis and
development of these imaging modalities, as evident from many such
attempts towards developing simulation tools in the past. Such methods
often employ Fourier transforms or statistical tools to simulate
speckles with desired statistical properties. We present the first
method to use a stochastic differential equation to generate laser
speckles with a pre-determined probability density function and a
temporal auto-correlation. The method allows the choice of apriori
gamma distribution along with simple exponential or more complex
temporal auto-correlation statistics for simulated speckles, making it
suitable for different blood flow profiles. In contrast to the
existing methods that often generate speckles associated with
superficial flow, we simulate both superficial and diffuse speckles
leading to applications in deep tissue blood flow imaging. In
addition, we have also incorporated appropriate models for noise
associated with the detectors to simulate realistic speckles. We have
validated our model by comparing the simulated speckles with those
obtained from
in-vivo
studies in mice and healthy
human subject. Laser speckle-based blood flow imaging is a well-accepted and widely used method for pre-clinical and clinical applications. Although it was introduced as a method to measure only superficial blood flow (< 1mm depth), several recently introduced variants resulted in measuring deep tissue blood flow (a few cm) as well. A means of simulating laser speckles is often necessary for the analysis and development of these imaging modalities, as evident from many such attempts towards developing simulation tools in the past. Such methods often employ Fourier transforms or statistical tools to simulate speckles with desired statistical properties. We present the first method to use a stochastic differential equation to generate laser speckles with a pre-determined probability density function and a temporal auto-correlation. The method allows the choice of apriori gamma distribution along with simple exponential or more complex temporal auto-correlation statistics for simulated speckles, making it suitable for different blood flow profiles. In contrast to the existing methods that often generate speckles associated with superficial flow, we simulate both superficial and diffuse speckles leading to applications in deep tissue blood flow imaging. In addition, we have also incorporated appropriate models for noise associated with the detectors to simulate realistic speckles. We have validated our model by comparing the simulated speckles with those obtained from in-vivo studies in mice and healthy human subject.Laser speckle-based blood flow imaging is a well-accepted and widely used method for pre-clinical and clinical applications. Although it was introduced as a method to measure only superficial blood flow (< 1mm depth), several recently introduced variants resulted in measuring deep tissue blood flow (a few cm) as well. A means of simulating laser speckles is often necessary for the analysis and development of these imaging modalities, as evident from many such attempts towards developing simulation tools in the past. Such methods often employ Fourier transforms or statistical tools to simulate speckles with desired statistical properties. We present the first method to use a stochastic differential equation to generate laser speckles with a pre-determined probability density function and a temporal auto-correlation. The method allows the choice of apriori gamma distribution along with simple exponential or more complex temporal auto-correlation statistics for simulated speckles, making it suitable for different blood flow profiles. In contrast to the existing methods that often generate speckles associated with superficial flow, we simulate both superficial and diffuse speckles leading to applications in deep tissue blood flow imaging. In addition, we have also incorporated appropriate models for noise associated with the detectors to simulate realistic speckles. We have validated our model by comparing the simulated speckles with those obtained from in-vivo studies in mice and healthy human subject. Laser speckle-based blood flow imaging is a well-accepted and widely used method for pre-clinical and clinical applications. Although it was introduced as a method to measure only superficial blood flow (< 1mm depth), several recently introduced variants resulted in measuring deep tissue blood flow (a few cm) as well. A means of simulating laser speckles is often necessary for the analysis and development of these imaging modalities, as evident from many such attempts towards developing simulation tools in the past. Such methods often employ Fourier transforms or statistical tools to simulate speckles with desired statistical properties. We present the first method to use a stochastic differential equation to generate laser speckles with a pre-determined probability density function and a temporal auto-correlation. The method allows the choice of apriori gamma distribution along with simple exponential or more complex temporal auto-correlation statistics for simulated speckles, making it suitable for different blood flow profiles. In contrast to the existing methods that often generate speckles associated with superficial flow, we simulate both superficial and diffuse speckles leading to applications in deep tissue blood flow imaging. In addition, we have also incorporated appropriate models for noise associated with the detectors to simulate realistic speckles. We have validated our model by comparing the simulated speckles with those obtained from studies in mice and healthy human subject. |
Author | K, Murali Varma, Hari M. |
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Snippet | Laser speckle-based blood flow imaging is a well-accepted and widely
used method for pre-clinical and clinical applications. Although it
was introduced as a... Laser speckle-based blood flow imaging is a well-accepted and widely used method for pre-clinical and clinical applications. Although it was introduced as a... |
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Title | Laser speckle simulation tool based on stochastic differential equations for bio imaging applications |
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