Abstract
Laser speckle contrast analysis (LASCA) is limited to being a qualitative method for the measurement of blood flow and tissue perfusion as it is sensitive to the measurement configuration. The signal intensity is one of the parameters that can affect the contrast values due to the quantization of the signals by the camera and analog-to-digital converter (ADC). In this paper we deduce the theoretical relationship between signal intensity and contrast values based on the probability density function (PDF) of the speckle pattern and simplify it to a rational function. A simple method to correct this contrast error is suggested. The experimental results demonstrate that this relationship can effectively compensate the bias in contrast values induced by the quantized signal intensity and correct for bias induced by signal intensity variations across the field of view.
Highlights
Laser speckle contrast analysis (LASCA) is a full-field imaging method for measuring changes in blood flow speed [1,2]
In this paper we explore the influence of digitization on the contrast for different intensity levels, which results in an apparently higher contrast value for low intensity signals that do not fill many gray levels
The correlation between the contrast and the signal intensity for a selection of four of the camera bit depths and a fully developed speckle pattern is shown in Fig. 2 under the condition that similar intensities corresponded to a similar fraction of full well depth (FWD) in each case
Summary
Laser speckle contrast analysis (LASCA) is a full-field imaging method for measuring changes in blood flow speed [1,2]. The signal changes with the flow speed, which is calculated by determining the local image contrast, since scatterers that move on the time scale of the camera integration time induce a blurring of the speckle pattern and decrease the image contrast. In addition to the sensitivity to scatterer motion, the LASCA signal changes depending on a number of experimental parameters, for instance the polarization state of the illuminated and detected light [10], the number of speckles per camera pixel [11] and the integration time of the detector [12]. There are sources of noise such as the readout noise of the digital camera and the dark current or background signal, which affects the final contrast values [13,14]
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