Quantified speckle variance optical coherence tomography algorithm for high-contrast imaging in vitro and in vivo

Optical coherence tomography angiography (OCTA) holds promise as a non-invasive, label-free technique for visualizing blood vessels and monitoring angiogenesis. However, the traditional speckle variance (SV) algorithm, an intensity-based OCTA algorithm, cannot distinguish between variance in signal intensity caused by red blood cell movement and those arising from system noise (e.g., shot noise). This limitation results in poor image contrast in angiography images. As imaging depth increases, signal attenuation due to scattering and absorption becomes more pronounced, making it difficult to visualize deeper blood vessels. The traditional SV algorithm fails to adequately address depth- and intensity-dependent noise, leading to reduced image contrast with increasing depth. In this work, we used a quantified speckle variance (qSV) algorithm that effectively mitigates the influence of system noise and enhances the contrast of regions exhibiting motion. The qSV algorithm normalizes the SV intensity relative to system noise, allowing a quantitative assessment of intensity fluctuations due to motion above the noise floor. The algorithm's effectiveness in maintaining high image contrast at greater depths is demonstrated using a phantom flow system of intralipid flowing through a thick tube embedded in gel. Furthermore, the algorithm is applied to human blood flow data, revealing high contrast even for blood vessels located deeper within the dermal layer. This highlights the algorithm's potential for improved visualization of deeper vascular structures.