Abstract

Determining micron-scale fluid flow velocities using optical coherence tomography (OCT) is important in both biomedical research and clinical diagnosis. Numerous methods have been explored to quantify the flow information, which can be divided into either phase-based or amplitude-based methods. However, phase-based methods, such as Doppler methods, are less sensitive to transverse velocity components and suffer from wrapped phase and phase instability problems for axial velocity components. On the other hand, amplitude-based methods, such as speckle variance OCT, correlation mapping OCT and split-spectrum amplitude-decorrelation angiography, focus more on segmenting flow areas than quantifying flow velocities. In this paper, we propose optical flow OCT (OFOCT) to quantify accurate velocity fields. The equivalence between optical flow and real velocity fields is validated in OCT imaging. The sensitivity fall-off of a Fourier-domain OCT (FDOCT) system is considered in the modified optical flow continuity constraint. Spatial-temporal smoothness constraints are used to make the optical flow problem well-posed and reduce noises in the velocity fields. An iteration solution to the optical flow problem is implemented in a graphics processing unit (GPU) for real-time processing. The accuracy of the velocity fields is verified through phantom flow experiments by using a diluted milk powder solution as a scattering medium. Velocity fields are then used to detect flow turbulence and reconstruct flow trajectory. The results show that OFOCT is accurate in determining velocity fields and applicable to research concerning fluid dynamics.

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