Normalized field autocorrelation function-based optical coherence tomography three-dimensional angiography

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Tang J., Erdener S. E., Sunil S., Boas D. A.

JOURNAL OF BIOMEDICAL OPTICS, vol.24, no.3, 2019 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 24 Issue: 3
  • Publication Date: 2019
  • Doi Number: 10.1117/1.jbo.24.3.036005
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Keywords: optical coherence tomography angiography, normalized autocorrelation function, vessel tail artifacts, three-dimensional vascular imaging, MOTION CORRECTION, SCATTERING, MICROVASCULATURE, DECORRELATION, MICROSCOPY, NETWORK, FLOW
  • Hacettepe University Affiliated: Yes


Optical coherence tomography angiography (OCTA) has been widely used for en face visualization of the microvasculature, but is challenged for real three-dimensional (3-D) topologic imaging due to the "tail" artifacts that appear below large vessels. Further, OCTA is generally incapable of differentiating descending arterioles from ascending venules. We introduce a normalized field autocorrelation function-based OCTA (g(1)-OCTA), which minimizes the tail artifacts and is capable of distinguishing penetrating arterioles from venules in the 3-D image. g(1) (tau) is calculated from repeated optical coherence tomography (OCT) acquisitions for each spatial location. The decay amplitude of g(1) (tau) is retrieved to represent the dynamics for each voxel. To account for the small g(1) (tau) decay in capillaries where red blood cells are flowing slowly and discontinuously, Intralipid is injected to enhance the OCT signal. We demonstrate that the proposed technique realizes 3-D OCTA with negligible tail projections and the penetrating arteries are readily identified. In addition, compared to regular OCTA, the proposed g(1)-OCTA largely increased the depth-of-field. This technique provides a more accurate rendering of the vascular 3-D anatomy and has the potential for more quantitative characterization of vascular networks. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.