Title
A fast three-dimensional dynamic light scattering computational model for imaging through turbid media
Conference Dates
June 2-6, 2019
Abstract
We present a fast numerical Monte Carlo based method (DLS-MC) to rapidly simulate and model dynamic light scattering through three-dimensional heterogeneous tissue volume. Speckle Contrast Imaging (LSCI) uses spatiotemporal fluctuations of random interference patterns of scattered coherent light known as speckle to measure blood flow non-invasively at a micron scale. Laser speckle intensity fluctuations are captured with a camera, and relative blood flow in tissue is analytically inferred by making assumptions about the form of the electric field autocorrelation function1. However, in the intermediate regime between the single and multiple scattering such as in tissue, the form of electric field autocorrelation function (g1) is complex and sample-dependent, leading to erroneous measurements if generalized2. We use our model to directly compute g1 without explicit assumptions on its form, furthering our understanding of depth and geometry dependent blood flow variations on the observed Speckle Contrast Image. Additionally, this highly scalable technique is capable of rapidly modeling, in the order of a few seconds, the effect of three-dimensional particle motion perturbations (i.e., blood flow), thus making it feasible to be used as an accurate forward model in volumetric blood flow inverse reconstruction, given that the geometry is known a-priori.
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Recommended Citation
Chakameh Zahed Jafari, Andrew K. Dunn, Samuel A. Mihelic, Colin T. Sullender, and David R. Miller, "A fast three-dimensional dynamic light scattering computational model for imaging through turbid media" in "Advances in Optics for Biotechnology, Medicine and Surgery XVI", Erin Buckley, Emory University/Georgia Institute of Technology, USA Christophe Moser, Polytechnique Fédérale de Lausanne (EPFL), Switzerland Brian Pogue, Dartmouth College, USA David Sampson, University of Western Australia, Australia Eds, ECI Symposium Series, (2019). https://dc.engconfintl.org/biotech_med_xvi/13