Abstract
A multi-step Volterra integral equation-based algorithm was developed to measure the electric field auto-correlation function from multi-exposure speckle contrast data. This enabled us to derive an estimate of the full diffuse correlation spectroscopy data-type from a low-cost, camera-based system. This method is equally applicable for both single and multiple scattering field auto-correlation models. The feasibility of the system and method was verified using simulation studies, tissue mimicking phantoms and subsequently in in vivo experiments.
Highlights
Quantitative in vivo imaging of blood flow using laser speckles have been investigated by several researchers in the past
A direct auto-correlation on the measured intensity speckles requires a camera with high frame rate along with a good sensitivity (Quantum Efficiency (QE) > 50% and dynamic range > 30000 e−), high signal-to-noise ratio (SNR) and a wide range of exposure control
In Ref. [52], the intensity correlation was measured for laser speckle contrast imaging using camera of high frame rate (20000 Hz)
Summary
Quantitative in vivo imaging of blood flow using laser speckles have been investigated by several researchers in the past. A multi-exposure speckle contrast data was used to quantify flow using least square minimization, without attempting to recover the field auto-correlation function [13,23,33]. The algorithm is based on multi-step Volterra integral method (MVIM) [37] which uses multi-exposure speckle contrast measurement to recover the normalized field auto-correlation. Where the term Ψ(T, τ) is called the kernel defined as Ψ(T, τ) ≡ (T − τ) With these definitions, the problem to recover field auto-correlation function using MVIM is stated as follows: Given κ2(r, T) for all T ∈ [Tmin, Tmax] and for every source detector separation r, find g1(r, τ) for all τ ∈ [τmin, τmax]. The optimal selection of the above parameters for the better recovery of g1(τ), is explained
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