  Shadow artifacts from retinal vessels hinder the development of quantitative
choroidal biomarkers in Optical Coherence Tomography (OCT), which limits the
clinical applications of the choroidal OCT to the measures of layer thickness.
In this paper, we present a novel framework that could eliminate the retinal
shadows and realize the quantification of choroidal vasculature. Different from
existing methods, we convert the shadow elimination into an object removal
task, which can be handled by image inpainting techniques. We adopt and
finetune a two-stage generative inpainting network which connects the edges of
the vessels ahead of refilling the shadow-contaminated areas. It shows
surpassing performance in repairing the choroidal vasculature compared with
traditional inpainting algorithms. We further verify the feasibility of the
proposed frame using a prospective observational study, which detects the
choroidal vascular changes related to the Intra-Ocular Pressure (IOP) elevation
of 34 healthy volunteers. As the average IOP increases from $15.84\pm1.99$ mmHg
to $34.48\pm5.35$ mmHg, we achieve the decreases of the choroidal vessel
density and flow index from $0.491\pm0.020$ to $0.463\pm0.019$ and from
$0.336\pm0.025$ to $0.300\pm0.019$, respectively.
