Gabor optical coherence tomographic angiography (GOCTA) (Part II): theoretical basis of sensitivity improvement and optimization for processing speed.

We previously proposed a Gabor optical coherence tomography angiography (GOCTA) algorithm for spectral domain optical coherence tomography (SDOCT) to extract microvascular signals from spectral fringes directly, with speed improvement of 4 to 20 times over existing methods. In this manuscript, we explored the theoretical basis of GOCTA with comparison of experimental data using solid and liquid displacement sample targets, demonstrating that the majority of the GOCTA sensitivity advantage over speckle variance based techniques was in the small displacement range (< 10 ∼ 20 µm) of the moving target (such as red blood cells). We further normalized GOCTA signal by root-mean-square (RMS) of original fringes, achieving a more uniform image quality, especially at edges of blood vessels where slow flow could occur. Furthermore, by transecting the spectral fringes and using skipped convolution, the data processing speed could be further improved. We quantified the trade-off in signal-to-noise-ratio (SNR) and contrast-to-noise-ratio (CNR) under various sub-spectral bands and found an optimized condition using 1/4 spectral band for minimal angiography image quality degradation, yet achieving a further 26.7 and 34 times speed improvement on GPU and CPU, respectively. Our optimized GOCTA algorithm has a speed advantage of over 140 times compared to existing speckle variance OCT (SVOCT) method.