Abstract. When laser light illuminates a diffuse object, it produces a random interference effect known as a speckle pattern. If there is movement in the object, the speckles fluctuate in intensity. These fluctuations can provide information about the movement. A simple way of accessing this information is to image the speckle pattern with an exposure time longer than the shortest speckle fluctuation time scale-the fluctuations cause a blurring of the speckle, leading to a reduction in the local speckle contrast. Thus, velocity distributions are coded as speckle contrast variations. The same information can be obtained by using the Doppler effect, but producing a two-dimensional Doppler map requires either scanning of the laser beam or imaging with a high-speed camera: laser speckle contrast imaging (LSCI) avoids the need to scan and can be performed with a normal CCD-or CMOS-camera. LSCI is used primarily to map flow systems, especially blood flow. The development of LSCI is reviewed and its limitations and problems are investigated.

Abstract. Variations in skin perfusion are easily detected by laser speckle contrast maps, but a robust interpretation of the information has been lacking. We show that multiple-exposure laser speckle methods produce the same spectral information as laser Doppler methods when applied to targets with embedded moving scatterers. This enables laser speckle measurements to be interpreted more quantitatively. We do this by using computer simulation of speckle data, and by experimental measurements on Brownian motion and skin perfusion using a laser Doppler system and a multiple-exposure laser speckle system. The power spectral density measurements of the light fluctuations derived using both techniques are exactly equivalent. Dermal perfusion can therefore be measured by laser Doppler or laser speckle contrast methods. In particular, multiexposure laser speckle can be rapidly processed to generate a full-field map of the perfusion index proportional to the concentration and mean velocity of red blood cells.

Background and AimsAnaemia is a major health burden worldwide. Although the finding of conjunctival pallor on clinical examination is associated with anaemia, inter-observer variability is high, and definitive diagnosis of anaemia requires a blood sample. We aimed to detect anaemia by quantifying conjunctival pallor using digital photographs taken with a consumer camera and a popular smartphone. Our goal was to develop a non-invasive screening test for anaemia.Patients and MethodsThe conjunctivae of haemato-oncology in- and outpatients were photographed in ambient lighting using a digital camera (Panasonic DMC-LX5), and the internal rear-facing camera of a smartphone (Apple iPhone 5S) alongside an in-frame calibration card. Following image calibration, conjunctival erythema index (EI) was calculated and correlated with laboratory-measured haemoglobin concentration. Three clinicians independently evaluated each image for conjunctival pallor.ResultsConjunctival EI was reproducible between images (average coefficient of variation 2.96%). EI of the palpebral conjunctiva correlated more strongly with haemoglobin concentration than that of the forniceal conjunctiva. Using the compact camera, palpebral conjunctival EI had a sensitivity of 93% and 57% and specificity of 78% and 83% for detection of anaemia (haemoglobin < 110 g/L) in training and internal validation sets, respectively. Similar results were found using the iPhone camera, though the EI cut-off value differed. Conjunctival EI analysis compared favourably with clinician assessment, with a higher positive likelihood ratio for prediction of anaemia.ConclusionsErythema index of the palpebral conjunctiva calculated from images taken with a compact camera or mobile phone correlates with haemoglobin and compares favourably to clinician assessment for prediction of anaemia. If confirmed in further series, this technique may be useful for the non-invasive screening for anaemia.

Practical laser speckle contrast analysis systems face a problem of spatial averaging of speckles, due to the pixel size in the cameras used. Existing practice is to use a system factor in speckle contrast analysis to account for spatial averaging. The linearity of the system factor correction has not previously been confirmed. The problem of spatial averaging is illustrated using computer simulation of time-integrated dynamic speckle, and the linearity of the correction confirmed using both computer simulation and experimental results. The valid linear correction allows various useful compromises in the system design.

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