September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Comparison between a complex based OCT angiography and an intensity based OCT angiography
Author Affiliations & Notes
  • Lin An
    Carl Zeiss Meditec, Walnut Creek, California, United States
  • Qinqin Zhang
    University of Washington, Seattle, Washington, United States
  • Shaozhen Song
    University of Washington, Seattle, Washington, United States
  • Chieh-Li Chen
    University of Washington, Seattle, Washington, United States
  • Ruikang K Wang
    University of Washington, Seattle, Washington, United States
  • Mary K Durbin
    Carl Zeiss Meditec, Walnut Creek, California, United States
  • Footnotes
    Commercial Relationships   Lin An, Carl Zeiss Meditec (E); Qinqin Zhang, None; Shaozhen Song, None; Chieh-Li Chen, None; Ruikang Wang, Carl Zeiss Meditec (F), Carl Zeiss Meditec (C), Carl Zeiss Meditec (R), Carl Zeiss Meditec (P); Mary Durbin, Carl Zeiss Meditec (E)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 4618. doi:
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    • Get Citation

      Lin An, Qinqin Zhang, Shaozhen Song, Chieh-Li Chen, Ruikang K Wang, Mary K Durbin; Comparison between a complex based OCT angiography and an intensity based OCT angiography. Invest. Ophthalmol. Vis. Sci. 2016;57(12):4618.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : To demonstrate that a complex data based OCT angiography algorithm delivers better flow sensitivity compared to an intensity based angiography algorithm.

Methods : A phantom experiment was performed using a CIRRUS5000 AngioPlex prototype. A phantom made of gelatin mixed with ~0.5% milk was created to simulate the background optical heterogeneity of tissue. The mixed gel was well solidified to minimize the possible Brownian motion of particles in the background. A capillary tube with an inner diameter of ~400 μm was submerged in this background tissue and ~0.1% TiO2 particle solution made to flow through it in a controlled manner by a precision syringe pump. The integrated signal within a region of interest around the capillary tube was compared to the signal within a background area. As another comparison, three dimensional OCT data captured from the eye of a normal subject was processed using both intensity-based and complex-based approaches.

Results : Fig.1 show the results of a phantom experiment. Fig.1 (a) shows the OCT micro structure image showing scattering fluid (red arrow). Through the OCT angiography algorithms, the presence of scattering fluid (mimicking the blood cells in the blood vessels) could be enhanced compared to the background (marked by the yellow squares in (b) and (c)). Compared to the intensity based approach (Fig. 1 (b)), Fig.1(c) shows higher flow signal (signal within the yellow square) and lower background (e.g. signal within the green square). The ratio of integrated signal within the capillary tube to signal within a background ROI was ~2.2 times higher than the same ratio calculated within the intensity-based image, which demonstrates that a complex approach has higher flow signal to noise ratio compared to an intensity approach. Fig.2 shows the results of in vivo human experiments. FIG.2(a) is the intensity result and FIG. 2(b) is the complex result. Compared to FIG. 2(a), Fig.2(b) shows better defined capillary networks and lower noise in the foveal avascular zone area.

Conclusions : A complex data based OCT angiography algorithm delivers better performance than an intensity based OCT angiography algorithm.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

 

Fig.1 Flow phantom experiment. (a) Phantom B-scan image; (b) and (c) are Flow contrast image obtained from intensity based and complex based algorithms.

Fig.1 Flow phantom experiment. (a) Phantom B-scan image; (b) and (c) are Flow contrast image obtained from intensity based and complex based algorithms.

 

Fig.2 OCT angiography images processed by (a) intensity based algorithm and (b) complex based algorithm

Fig.2 OCT angiography images processed by (a) intensity based algorithm and (b) complex based algorithm

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