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. 2011 Jun 6;19(12):11429-40.
doi: 10.1364/OE.19.011429.

Intensity-based modified Doppler variance algorithm: application to phase instable and phase stable optical coherence tomography systems

Gangjun Liu  1 , Lidek Chou, Wangcun Jia, Wenjuan Qi, Bernard Choi, Zhongping Chen
Affiliations

Intensity-based modified Doppler variance algorithm: application to phase instable and phase stable optical coherence tomography systems

Gangjun Liu et al. Opt Express. .

Abstract

The traditional phase-resolved Doppler method demonstrates great success for in-vivo imaging of blood flow and blood vessels. However, the phase-resolved method always requires high phase stability of the system. In phase instable situations, the performance of the phase-resolved methods will be degraded. We propose a modified Doppler variance algorithm that is based on the intensity or amplitude value. Performances of the proposed algorithm are compared with traditional phase-resolved Doppler variance and color Doppler methods for both phase stable and phase instable systems. For the phase instable situation, the proposed algorithm demonstrates images without phase instability induced artifacts. In-vivo imaging of window-chamber hamster skin is demonstrated for phase instable situation with a spectrometer-based Fourier domain OCT system. A microelectromechanical systems (MEMS) based swept source OCT (SSOCT) system is also used to demonstrate the performance of the proposed method in a phase instable situation. The phase stability of the SSOCT system is analyzed. In-vivo imaging of the blood vessel of human skin is demonstrated with the proposed method and the SSOCT system. For the phase stable situation, the proposed algorithm also demonstrates comparable performance with traditional phase-resolved methods. In-vivo imaging of the human choroidal blood vessel network is demonstrated with the proposed method under the phase stable situation. Depth-resolved fine choroidal blood vessel networks are shown.

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Figures

Fig. 1
Fig. 1
Schematic of the spectrometer-based FDOCT system. SLD: Super luminescent diode; C: Collimator; NDF: Neutral density filter; M: Mirror; G: Grating; L: Lens; GS: Galvanometer mirror scanner.
Fig. 2
Fig. 2
(a) OCT structure image; (b) CD image; (c) PRDV image; (d) IBDV image. (e) Zoomed image for the region in the white rectangle in (b). (f). Zoomed image for the region in the white rectangle in (c).
Fig. 3
Fig. 3
Schematic of the swept source Fourier domain OCT system. SS: Swept source laser: C: Collimator; Cir: Circulator; NDF: Neutral density filter; M: Mirror; BD: Balanced detector; L: lens; GS: Galvanometer mirror scanner.
Fig. 4
Fig. 4
Phase stability analysis of the SSOCT system. (a) Phase differences between adjacent A-lines at the static mirror location. (b). Histogram of the phase difference distribution.
Fig. 5
Fig. 5
(a) OCT structure image; (b) CD image; (c) PRDV image; (d) IBDV image. (e) Zoomed image of the region in the white rectangle in (b).
Fig. 6
Fig. 6
(a) OCT structure image; (b) CD image; (c) Doppler variance image obtained with Eq. (3); (d) Doppler variance image obtained with modified algorithm Eq. (5).
Fig. 7
Fig. 7
En-face and projection view IBDV images. (a)–(k) are depth-resolved en-face IBDV images. (a)–(k) are, respectively, at a depth of 18.5 µm, 37 µm, 55.5 µm, 74 µm, 92.5 µm, 111 µm, 129.5 µm, 148 µm, 166.5 µm, 185 µm, 203.5 µm below the RPE layer. The depth difference between adjacent images is 18.5 µm. (l) Projection view of the IBDV image for all layers below the RPE layer.
See this image and copyright information in PMC

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