Laser Speckle Modeling and Simulation for Biophysical Dynamics: Influence of Sample Statistics

Kosar Khaksari; Sean J. Kirkpatrick

doi:10.18287/JBPE17.03.040302

Authors

Kosar Khaksari Department of Biomedical Engineering, Tufts University, Medford, CT, ‎USA
Sean J. Kirkpatrick Department of Biomedical Engineering, Michigan Technological University, Houghton, MI, USA

DOI:

https://doi.org/10.18287/JBPE17.03.040302

Keywords:

Laser speckle, speckle contrast, sample statistic, speckle imagings

Abstract

Laser speckle is a statistical phenomenon and should be treated as such when establishing experimental parameters for using laser speckle techniques to infer information about the dynamics of a coherently illuminated medium, such as biological tissue. Herein, we demonstrate that when sampling (imaging) speckle patterns, it is critical that the sampled speckle patterns are unbiased estimators of the underlying random speckle field. If this condition is not met, the quality of the results will be compromised. Specifically, this study examines the effects of first and second order spatial statistics of speckle intensity images on laser speckle contrast imaging results. Finally, it is recommended that when using speckle techniques such as laser speckle contrast imaging, investigators should examine the first and second order spatial statistics of a speckle image prior to collecting actual data. If this examination reveals that the imaged speckle intensity image is not an unbiased estimator of the underlying random speckle field, then adjustments should be made to ensure that the images taken are unbiased estimators of the true speckle field.

Author Biographies

Kosar Khaksari, Department of Biomedical Engineering, Tufts University, Medford, CT, ‎USA

Dr. Kosar Khaksari is a post-doctoral fellow in the Department of Biomedical Engineering at Tufts University in Medford, MA, USA
Sean J. Kirkpatrick, Department of Biomedical Engineering, Michigan Technological University, Houghton, MI, USA

Sean J. Kirkpatrick is the Department Chair and Professor of Biomedical Engineering at the Michigan Technological University. He is a Fellow of the SPIE and the AIMBE

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