Optical coherence tomography (OCT) is a powerful interferometric technique to noninvasively obtain tissue cross section images with micrometer resolution, millimeter penetration depth and video-rate imaging speed [1
]. The extension of the OCT technique to functionally image blood flow has generated great interests. Doppler optical coherence tomography (DOCT) or optical Doppler tomography (ODT) is one type of functional extension of OCT which combines the Doppler principle with OCT and provides in-vivo imaging of blood vessels, blood flow direction, and blood flow speed [2
]. Phase-resolved Doppler OCT has become one of the favored methods for blood vessels imaging because of its high velocity sensitivity [5
]. The method is based on the phase information obtained from complex OCT data. By analyzing the phase information, blood flow speed, blood flow direction, etc. can be obtained [5
]. Optical microangiography (OMAG) is a type of DOCT extension that filters out the lower Doppler frequency component with numerical or hardware methods [6
]. OMAG is sensitive to the phase term although it may not use the phase term directly.
The phase-resolved method is sensitive to the phase term, and phase stability of the OCT system is important for obtaining high quality images. The minimum velocity that can be resolved by the phase resolved method is determined by the phase stability of the OCT system. A dense beam scan will be required to provide the effective over sampling ratio and ensure phase correlation between adjacent A-lines [9
]. Intensity-based methods have also been proposed to image blood vessels. Barton et al. proposed a method based on the speckle of conventional amplitude optical coherence tomography images [10
]. Mariampillai et al. used the speckle variance in a small 3D volume to image blood vessels [11
]. Yasuno et al. used the intensity threshold binarization-based method, scattering optical coherence angiography (SOCA), for retinal and choroidal blood vessel imaging [13
]. SOCA does not need a dense scan as required by the phase resolved method and does not require a high phase stable system. However, the intensity threshold based method loses the functional information of blood flow, it is difficult for it to distinguish the flow signals from structure signals [8
]. Jonathan et al. used a 2-D correlation map based on the OCT intensity images for blood vessel extraction [14
The Doppler variance method is a method that uses the bandwidth of the Doppler frequency spectrum to image blood vessels [15
]. Doppler variance has the advantages of being less sensitive to the pulsatile nature of the blood flow and the incident angle, as well as the capability of being used for quantifying the transverse flow velocity [16
]. Doppler variance is not sensitive to gradient phase changes and can be used without bulk-motion-correction for in-vivo
]. In this paper, we modified the averaging Doppler variance algorithm to make it an intensity based method for blood vessel imaging. Intensity-based methods do not require a phase stabilized system and can be used for a phase instable situation, such as a swept source Fourier domain OCT (FDOCT) system. Performances of the proposed algorithm are compared with traditional phase resolved Doppler variance and color Doppler (CD) methods for both phase stable and phase instable systems.
For the phase instable situation, the proposed algorithm demonstrates good results without phase instability induced artifacts. In-vivo imaging of window-chamber hamster skin is shown using a spectrometer-based FDOCT system under phase instable situation. A microelectromechanical systems (MEMS) based swept source OCT (SSOCT) system was also used to demonstrate the performance of the proposed method in a phase instable situation. The phase stability of the MEMS laser SSOCT system is analyzed. In-vivo imaging of the blood vessel of human skin is demonstrated with the proposed method. For the phase stable situation, the proposed algorithm also demonstrates comparable performance with the traditional phase resolved methods. In-vivo imaging of a human choroidal blood vessel network is demonstrated with the proposed method under the phase stable situation. Depth-resolved image of fine choroidal blood vessel network is shown.