A stochastic differential equation based algorithm to simulate laser speckles for deep tissue blood flow imaging applications

TL;DR

This paper introduces a novel stochastic differential equation-based algorithm for simulating laser speckles, accounting for spatial variations and auto-correlation decay, to enhance deep tissue blood flow imaging techniques.

Contribution

The paper presents a new speckle simulation method that models diffuse speckles with spatially varying mean and auto-correlation, improving accuracy for deep tissue blood flow imaging.

Findings

Validated through simulation studies for surface and deep tissue blood flow.

Accurately models speckle intensity distribution and auto-correlation decay.

Potential to improve diffuse correlation spectroscopy applications.

Abstract

We present an intensity speckle simulation algorithm based on stochastic differential equations. Intensity speckles are generated with a negative exponential distribution and an exponential auto-correlation decay. The mean of the distribution is spatially varying dictated by photon diffusion to take into account of diffuse speckles. The algorithm is validated using simulation studies for both surface and deep tissue blood flow with potential applications in diffuse correlation spectroscopy.