We propose a simplification for a robust and easy to implement fast phase unwrapping (FPU) algorithm that is used to solve the phase wrapping problem encountered in various fields of optical imaging and metrology. We show that the number of necessary computations using the algorithm can be reduced compared to its original version. FPU can be easily extended from two to three spatial dimensions. We demonstrate the applicability of the two-and three-dimensional FPU algorithm for Doppler optical coherence tomography (DOCT) in numerical simulations, and in the imaging of a flow phantom and blood flow in the human retina in vivo. We introduce an FPU applicability plot for use as a guide in the selection of the most suitable version of the algorithm depending on the phase noise in the acquired data. This plot uses the circular standard deviation of the wrapped phase distribution as a measure of noise and relates it to the root-mean-square error of the recovered, unwrapped phase.

We present a method of OCT angiography (OCTA) data filtering for noise suppression and improved visualization of the retinal vascular networks in en face projection images. In our approach, we use a set of filters applied in three orthogonal axes in the threedimensional (3-D) data sets. Minimization of artifacts generated in B-scan-wise data processing is accomplished by filtering the cross-sections along the slow scanning axis. Ascans are de-noised by axial filtering. The core of the method is the application of directional filtering to the C-scans, i.e. one-pixel thick sections of the 3-D data set, perpendicular to the direction of the scanning OCT beam. The method uses a concept of structuring, directional kernels of shapes matching the geometry of the image features. We use rotating ellipses to find the most likely local orientation of the vessels and use the best matching ellipses for median filtering of the C-scans. We demonstrate our approach in the imaging of a normal human eye with laboratory-grade spectral-domain OCT setup. The "field performance" is demonstrated in imaging of diabetic retinopathy cases with a commercial OCT device. The absolute complex differences method is used for the generation of OCTA images from the data collected in the most noise-wise unfavorable OCTA scanning regime-two frame scanning.

In compression optical coherence elastography (OCE), deformation is quantified as the local strain at each pixel in the OCT field-of-view. A range of strain estimation methods have been demonstrated, yet it is unclear which method provides the best performance. Here, we analyze the two most prevalent strain estimation methods used in phase-sensitive compression OCE, i.e., weighted least squares (WLS) and the vector method. We introduce a framework to compare strain imaging metrics, incorporating strain sensitivity, strain signal-to-noise ratio (SNR), strain resolution, and strain accuracy. In addition, we propose a new phase unwrapping algorithm in OCE, fast phase unwrapping (FPU), and combine it with WLS, termed WLSFPU. Using the framework, we compare this new strain estimation method with both a current implementation of WLS that incorporates weighted phase unwrapping (WPU), termed WLSWPU, and the vector method. Our analysis reveals that the three methods provide similar strain sensitivity, strain SNR, and strain resolution, but that WLSFPU extends the dynamic range of accurate, measurable local strain, e.g., measuring a strain of 2.5 mɛ with ∼4% error, that is ×11 and ×15 smaller than the error measured using WLSWPU and the vector method, respectively. We also demonstrate, for the first time, the capability to detect sub-resolution contrast in compression OCE, i.e., changes in strain occurring within the strain axial resolution, and how this contrast varies between the different strain estimation methods. Lastly, we compare the performance of the three strain estimation methods on mouse skeletal muscle and human breast tissue and demonstrate that WLSFPU avoids strain imaging artifacts resulting from phase unwrapping errors in WLSWPU and provides improved contrast over the other two methods.