Mean-Subtraction Method for De-Shadowing of Tail Artifacts in Cerebral OCTA Images: A Proof of Concept

Abstract

When imaging brain vasculature with optical coherence tomography angiography (OCTA), volumetric analysis of cortical vascular networks in OCTA datasets is frequently challenging due to the presence of artifacts, which appear as multiple-scattering tails beneath superficial large vessels in OCTA images. These tails shadow underlying small vessels, making the assessment of vascular morphology in the deep cortex difficult. In this work, we introduce an image processing technique based on mean subtraction of the depth profile that can effectively reduce these tails to better reveal small hidden vessels compared to the current tail removal approach. With the improved vascular image quality, we demonstrate that this simple method can provide better visualization of three-dimensional vascular network topology for quantitative cerebrovascular studies.

Blood vessel tail artifacts suppression in optical coherence tomography angiography

“…The high NA approach suppressed the blood vessel tail artifacts using the short confocal depth to reject multiple scattered photons out of this focus region, but at the expense of repeated data acquisition at multiple focal depth. The subtraction-based methods 15 , 53 , 54 , 57 remove the tails by subtracting the vessel signal in the superficial layers from the deep layers, which however suffers from broken flows due to the removal of voxels under the large vessels. The PR-OCTA and rbPR-OCTA approaches can alleviate this issue to some extent but still can’t fully address this problem.…”

“…To realize real 3D OCTA imaging of blood vasculatures, a series of methods have been proposed to suppress the blood vessel tail artifacts in OCTA, including using high numerical aperture (NA) objectives 50 , 51 to reject signals from deeper layers and many data processing algorithm-based approaches. 15 , 16 , 52 – 60 Here, we review the existing methods used for blood vessel tail artifacts suppression in OCTA and the advantage and limitations of each approach.…”

“…Choi et al. 57 further proposed a mean-subtraction method using a weighted mean value of all pixels of each A-line to suppress the signal in the subluminal area of the large blood vessel. Mathematically, this mean-subtraction method is expressed as where and represent the ’th A-lines of the de-shadowed and original image, respectively; is the magnitude at the ’th pixel point of the ’th A-line of the original image; is equal to the number of all pixel points of the A-line; is a weighted average, which was set to 2.…”

Automated counting of cerebral penetrating vessels using optical coherence tomography images of a mouse brain in vivo

“…It should be noted that the comet tail-like signals below the superficial vessels are artifacts induced by the forward scattering through the vessels. 36 However, as shown in Figure 2c, the OCT signal intensities underneath the penetrating arteriole (2) were relatively weaker than those below other vessels, including the arteriole (1), due to lower backscattering along the penetrating vasculature. This can be seen from the depth profiles in Figure 2c, where the means are 3 for (1) and 2.2 for (2) on a logarithmic scale, in accordance with the first hypothesis presented in Section 2.5.…”

Advances in multimodal imaging in ophthalmology

“…31,56 Additional image artifacts, such as shadowing from large retinal vessels, axially smeared vessel cross sections as a result of scattering, and out-of-focus OCTA projections, can significantly impact vessel segmentation algorithms and quantitative analysis of retinal vascularity. [57][58][59][60] Motion-compensation methods, such as novel scanning or eye-tracking technologies, are actively being studied to overcome these limitations. [61][62][63][64] Furthermore, vessel enhancement techniques, such as the complex continuous wavelet transform and multiple en face registration and averaging, can be applied to improve the accuracy of vessel segmentation.…”