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In Depth Flow Inspection Using Dynamic Laser Speckle Temporal Statistics

Mark Golberg, Ran Califa, Sagi Polani, Javier Garcia, Zeev Zalevsky
doi: https://doi.org/10.1101/680330
Mark Golberg
1Faculty of Engineering and Nanotechnology, Bar Ilan University, Ramat Gan, 5290002, Israel
2ContinUse Biometrics Ltd., HaBarzel 32b st., Tel Aviv 6971048, Israel
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  • For correspondence: mark.golberg@cu-bx.com
Ran Califa
2ContinUse Biometrics Ltd., HaBarzel 32b st., Tel Aviv 6971048, Israel
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Sagi Polani
2ContinUse Biometrics Ltd., HaBarzel 32b st., Tel Aviv 6971048, Israel
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Javier Garcia
2ContinUse Biometrics Ltd., HaBarzel 32b st., Tel Aviv 6971048, Israel
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Zeev Zalevsky
1Faculty of Engineering and Nanotechnology, Bar Ilan University, Ramat Gan, 5290002, Israel
2ContinUse Biometrics Ltd., HaBarzel 32b st., Tel Aviv 6971048, Israel
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Abstract

We present novel optical approach based on statistical analysis of temporal laser speckle patterns for tissue in-depth flow characteristics. An ability to distinguish between Brownian motion of particles and laminar flow is well proved. The main steps in the post processing algorithm and the in-vivo and in-vitro experimental results are presented and demonstrated.

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Posted June 23, 2019.
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In Depth Flow Inspection Using Dynamic Laser Speckle Temporal Statistics
Mark Golberg, Ran Califa, Sagi Polani, Javier Garcia, Zeev Zalevsky
bioRxiv 680330; doi: https://doi.org/10.1101/680330
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In Depth Flow Inspection Using Dynamic Laser Speckle Temporal Statistics
Mark Golberg, Ran Califa, Sagi Polani, Javier Garcia, Zeev Zalevsky
bioRxiv 680330; doi: https://doi.org/10.1101/680330

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