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Proceedings Paper

Hybrid averaging optical coherence tomography angiography and applications in brain (Conference Presentation)
Author(s): Peng Li; Pei Li; Shanshan Yang; Zhihua Ding

Paper Abstract

Optical coherence tomography angiography (OCTA) is a promising imaging modality that enables an in vivo label-free, high-resolution and high-contrast visualization of three-dimensional biological microvasculature. The blood flow contrast in OCTA is achieved by mathematically distinguishing the dynamic flow from the static surrounding tissue. However, the residual surrounding tissue remains as the background in the angiogram, which severely hinders the interpretation and quantification of the angiographic outcomes. The current temporal, wavelength, angular and spatial averaging approaches have been employed to enhance the flow contrast by trading imaging time and resolution for multiple independent measurements. Our study has further demonstrated that these averaging approaches are equivalent in principle, offering almost the same flow contrast improvement as the number of averages increases. Given a sufficient number, an ideal flow contrast can be achieved, while the cost of imaging time or resolution is unaffordable for any individual averaging approach alone. Thus, we have proposed a hybrid averaging strategy for a desired flow contrast by cost apportionment. It is demonstrated that, compared with any individual approach, hybrid averaging is able to offer a desired flow contrast without severe degradation of imaging time and resolution. In addition, making use of the extended range of a VCSEL based swept source OCT, an angular averaging approach by path length encoding is also demonstrated for flow contrast enhancement. This study is beneficial to providing useful guidance for the design of OCTA and facilitating the interpretation of OCT angiograms in clinical applications.

Paper Details

Date Published: 14 March 2018
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Proc. SPIE 10481, Neural Imaging and Sensing 2018, 104810O (14 March 2018); doi: 10.1117/12.2289926
Show Author Affiliations
Peng Li, Zhejiang Univ. (China)
Pei Li, Zhejiang Univ. (China)
Shanshan Yang, Zhejiang Univ. (China)
Zhihua Ding, Zhejiang Univ. (China)


Published in SPIE Proceedings Vol. 10481:
Neural Imaging and Sensing 2018
Qingming Luo; Jun Ding, Editor(s)

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