Normalized field autocorrelation function-based optical coherence tomography 3D angiography

Jianbo Tang; Sefik Evren Erdener; David A. Boas

doi:10.1117/12.2507003

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22 February 2019 Normalized field autocorrelation function-based optical coherence tomography 3D angiography

Jianbo Tang, Sefik Evren Erdener, David A. Boas

Proceedings Volume 10867, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIII; 108672U (2019) https://doi.org/10.1117/12.2507003
Event: SPIE BiOS, 2019, San Francisco, California, United States

Abstract

Optical coherence tomography angiography (OCTA) has been widely used for en face visualization of vasculatures but challenged for real 3D topologic imaging due to the ‘tail’ artifacts that appear below large vessel because of multiple scattered light within the vessel. We introduce a normalized field autocorrelation function-based OCTA (𝒈_𝟏-OCTA) which minimizes the projection artifacts and is capable of 3D topologic vasculature imaging. 𝒈_𝟏(τ) is calculated from repeated OCT acquisitions for each spatial location. The largest decay of 𝒈_𝟏(τ) is retrieved to represent the dynamics for each voxel. To account for the small 𝒈_𝟏(τ) decay in capillaries where red blood cells (RBCs) are flowing slowly and discontinuously, Intralipid is injected to enhance the OCT signal. With the Intralipid-enhanced signal and shorter decorrelation time processing, we demonstrate that the proposed technique realized 3D OCTA with high signal-to-noise ratio and a negligible ‘tail’ projection. In addition, compared to regular OCTA, the proposed 𝒈_𝟏-OCTA doubles the imaging depth. By reducing ‘tail’ artifacts, this technique provides a more accurate rendering of the vascular anatomy for more quantitative characterization of the vascular networks.

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Jianbo Tang, Sefik Evren Erdener, and David A. Boas "Normalized field autocorrelation function-based optical coherence tomography 3D angiography", Proc. SPIE 10867, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIII, 108672U (22 February 2019); https://doi.org/10.1117/12.2507003

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