Enhancing microvasculature maps for Optical Coherence Tomography Angiography (OCT-A)

Rapolu, Mounika; Niedźwiedziuk, Paulina; Borycki, Dawid; Wnuk, Paweł; Wojtkowski, Maciej

doi:10.4302/plp.v10i3.841

Cited by 1 publication

(1 citation statement)

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“…While 3D Gaussian or Median filters can replace their 2D counterparts in our algorithm, the most comparable filter to replace the notched convolution kernel is a “vesselness” filter. A majority of the existing algorithms use the Hessian or Frangi vesselness filters [ 38 , 39 , 40 , 41 , 42 ]. In our methodology, the stepwise processing reproduces many of the effects of the Hessian gradient and peak enhancing filter, though discrete local filters.…”

Section: Resultsmentioning

confidence: 99%

Spatial-Temporal Speckle Variance in the En-Face View as a Contrast for Optical Coherence Tomography Angiography (OCTA)

Luisi

Lin

Ameredes

2022

Sensors

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Optical Coherence Tomography (OCT) is an adaptable depth-resolved imaging modality capable of creating a non-invasive ‘digital biopsy’ of the eye. One of the latest advances in OCT is optical coherence tomography angiography (OCTA), which uses the speckle variance or phase change in the signal to differentiate static tissue from blood flow. Unlike fluorescein angiography (FA), OCTA is contrast free and depth resolved. By combining high-density scan patterns and image processing algorithms, both morphometric and functional data can be extracted into a depth-resolved vascular map of the retina. The algorithm that we explored takes advantage of the temporal-spatial relationship of the speckle variance to improve the contrast of the vessels in the en-face OCT with a single frame. It also does not require the computationally inefficient decorrelation of multiple A-scans to detect vasculature, as used in conventional OCTA analysis. Furthermore, the spatial temporal OCTA (ST-OCTA) methodology tested offers the potential for post hoc analysis to improve the depth-resolved contrast of specific ocular structures, such as blood vessels, with the capability of using only a single frame for efficient screening of large sample volumes, and additional enhancement by processing with choice of frame averaging methods. Applications of this method in pre-clinical studies suggest that the OCTA algorithm and spatial temporal methodology reported here can be employed to investigate microvascularization and blood flow in the retina, and possibly other compartments of the eye.

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