Flow Properties of Heterogeneous Turbid Media Probed by Diffusing Temporal Correlation

Abstract

Variations in the amplitude and phase of diffuse photon density waves is known to yield important information about the structural properties of turbid media, such as the scattering and absorption coefficients. Information on the dynamical properties of turbid media may be obtained from the temporal fluctuations of light fields emanating from the media. In this contribution, we demonstrate that variations in temporal correlation functions of the temporal intensity fluctuations of different speckles of light can be used to derive information about the spatially varying dynamical properties of turbid media. We first present a diffusion for the temporal correlation function for systems where the dynamics are governed by Brownian motion and shear and random flow. We demonstrate the validity of the correlation diffusion for heterogeneous systems by comparing the theoretical results with experimental results for systems governed by different dynamical processes, e.g. flow. As an illustration of the usefulness of this correlation technique to biomedical optics, we discuss the application of this technique to diagnosing the thickness of burned tissue. The correlation diffusion is an important, unique tool for analyzing the complex dynamical signals that arise from heterogeneous biological systems.

Quantitative hemodynamic imaging: a method to correct the effects of optical properties on laser speckle imaging

“… – 41 However, the theory of MESI only focused on fitting the shape of the contrast-versus-exposure-time functions and did not account directly for optical properties. Meanwhile, our method utilized the solution of the correlation diffusion equation 42 to relate speckle contrast K to μa, μs′, and Db. This method allows for directly estimating Db using the measured LSI and SFDI data.…”

Periodic-net: an end-to-end data driven framework for diffuse optical imaging of breast cancer from noisy boundary data

“…Signals are generated by photon radiance L(r,sfalse^,t) in forward solver, where s^ denotes the direction of light r is position vector at time t. Photon radiance is calculated from radiation transport equation (RTE) in the presence of a nonlinear source term Q(r,sfalse^,t) to characterize tissue by the scattering coefficient μs and the absorption coefficient μa; formulation of optical-property is given as 28 (1c∂∂t+s^.∇+μt)L(r,s^,t)=μs∫4πL(r,s^′,t)f(s^′,s^)d…”

Comparison of cerebral metabolic rate of oxygen, blood flow, and bispectral index under general anesthesia

“…The data were first evaluated by fitting the respective semi-infinite medium solutions of the photon diffusion equation to the optical measurements. [70][71][72] The fitting was done using the downhill-simplex or Nelder-Mead method in MATLAB™'s implemented fminsearch function. 73,74 Further data analysis was then carried out in R 75 (v4.0.1, R Core Team, 2019) and the integrated development environment RStudio (v1.1.5042, RStudio, Inc., Boston), especially for the calculation of OEF and CMRO 2 , 70 artifacts removal and data re-sampling.…”

“…47 This together with the knowledge of the readily available pulse oxygen saturation (SpO 2 ) allows one to estimate the oxygen extraction fraction (OEF) and the above-mentioned CMRO 2 . [48][49][50][51] Both diffuse optical techniques have been employed in the investigation of the human brain's autoregulatory mechanisms and hemodynamic properties in vivo. [52][53][54][55] Some studies in the DO field have emphasized the importance of focusing on the moments of loss of conscience (LOC), caused by the injection of anesthetic, and recovery of conscience (ROC), after the vanishing of drugs.…”