Robust quantitative single-exposure laser speckle imaging with true flow speckle contrast in the temporal and spatial domains

Abstract

A systematic and robust laser speckle contrast imaging (LSCI) method and procedure is presented, covering the LSCI system calibration, static scattering removal, and measurement noise estimation and correction to obtain a true flow speckle contrast 2 f K and the flow speed from single-exposure LSCI measurements. We advocate to use 2 K as the speckle contrast instead of the conventional contrast K as the former relates simply to the flow velocity and is with additive noise alone. We demonstrate the efficacy of the proposed true flow speckle contrast by imaging phantom flow at varying speeds, showing that (1) the proposed recipe greatly enhances the linear sensitivity of the flow index (inverse decorrelation time) and the linearity covers the full span of flow speeds from 0 mm/s to 40 mm/s; and (2) the true flow speed can be recovered regardless of the overlying static scattering layers and the type of speckle statistics (temporal or spatial). The fundamental difference between the apparent temporal and spatial speckle contrasts is further revealed. The flow index recovered in the spatial domain is much more susceptible to static scattering and exhibit a shorter linearity range than that obtained in the temporal domain. The proposed LSCI analysis framework paves the way to estimate the true flow speed in the wide array of laser speckle contrast imaging applications.

Real-time video-rate perfusion imaging using multi-exposure laser speckle contrast imaging and machine learning

“…Dark noise and shot noise in the raw images give rise to an unwanted increase in the contrast images. 11 As has been described by others, 7,16 in variance space, this can be modeled as a firstdegree polynomial of the average intensity. For the exposure time used to capture images, T ¼ 1 ms, we get E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 0 2 ; 1 1 6 ; 3 7 4…”

“…5,6 Recent work has gone into calibrating and correcting for these issues to make LSCI a more accurate technique. 7 Despite this, while it is generally accepted that LSCI is related to microcirculatory perfusion, the relationship is complex and a direct mapping is still not known. 4,8 For the older laser Doppler flowmetry (LDF) technique, the relation to microcircular perfusion is better understood, where it is, for example, possible to theoretically show that the perfusion estimate is linearly related to the flow speed.…”

Real-time multi-exposure laser speckle contrast imaging of skin microcirculatory perfusion

“…where the noise constants N shot and N dark can be measured experimentally [69,70]. By reversing the equation to get σ 2 speckle , it is possible to compute the noise-corrected and calibrated speckle contrast by Equations 3.10c and 3.12, as…”

Movement correction method for laser speckle contrast imaging of cerebral blood flow in cranial windows in rodents

“…Continuous development of the technique has led to its integration in microendoscopy to image deep brain structures [7] and to its combination with optical clearing agents to improve spatial resolution when imaging cutaneous microcirculation [8,9]. Recent efforts have also improved the linearity of the technique when inferring blood velocity through noise correction methods [10,11] as well as flow detection accuracy through proper model selection [12]. LSCI is also notably used for functional imaging in living animals, mapping changes in CBF which serve as a proxy for neuronal activation through neurovascular coupling [13][14][15].…”