Probabilistic volumetric speckle suppression in OCT using deep learning.

We present a deep learning framework for volumetric speckle reduction in optical coherence tomography (OCT) based on a conditional generative adversarial network (cGAN) that leverages the volumetric nature of OCT data. In order to utilize the volumetric nature of OCT data, our network takes partial OCT volumes as input, resulting in artifact-free despeckled volumes that exhibit excellent speckle reduction and resolution preservation in all three dimensions. Furthermore, we address the ongoing challenge of generating ground truth data for supervised speckle suppression deep learning frameworks by using volumetric non-local means despeckling-TNode- to generate training data.

Probabilistic volumetric speckle suppression in OCT using deep learning.

We present a deep learning framework for volumetric speckle reduction in optical coherence tomography (OCT) based on a conditional generative adversarial network (cGAN) that leverages the volumetric nature of OCT data. In order to utilize the volumetric nature of OCT data, our network takes partial OCT volumes as input, resulting in artifact-free despeckled volumes that exhibit excellent speckle reduction and resolution preservation in all three dimensions. Furthermore, we address the ongoing challenge of generating ground truth data for supervised speckle suppression deep learning frameworks by using volumetric non-local means despeckling-TNode to generate training data.

Computational refocusing in phase-unstable polarization-sensitive optical coherence tomography.

We present computational refocusing in polarization-sensitive optical coherence tomography (PS-OCT) to improve spatial resolution in the calculated polarimetric parameters and extend the depth-of-field in phase-unstable, fiber-based PS-OCT systems. To achieve this, we successfully adapted short A-line range phase-stability adaptive optics (SHARP), a computational aberration correction technique compatible with phase-unstable systems, into a Stokes-based PS-OCT system with inter-A-line polarization modulation. Together with the spectral binning technique to mitigate system-induced chromatic polarization effects, we show that computational refocusing improves image quality in tissue polarimetry of swine eye anterior segment ex vivo with PS-OCT.

Experimental generation of adjustable partially coherent optical vortices from coherent and incoherent light sources.

Adjustable spatial coherence systems allow the possibility to make different intensity distributions using one source. Most common adjustable sources are based on the Collet-Wolf system. However, it is also possible to adjust the spatial coherence of the illumination field from white light sources by spatially filtering the source mutual intensity spectrum.

Computational adaptive optics in phase-unstable optical coherence tomography.

We present a scheme for correction of --separable aberrations in optical coherence tomography (OCT) designed to work with phase unstable systems with no hardware modifications. Our approach, termed SHARP, is based on computational adaptive optics and numerical phase correction and follows from the fact that local phase stability is sufficient for the deconvolution of optical aberrations. We demonstrate its applicability in a raster-scan polygon-laser OCT system with strong phase-jitter noise, achieving successful refocusing at depths up to 4 times the Rayleigh range.

Volumetric non-local-means based speckle reduction for optical coherence tomography.

We present a novel tomographic non-local-means based despeckling technique, TNode, for optical coherence tomography. TNode is built upon a weighting similarity criterion derived for speckle in a three-dimensional similarity window. We present an implementation using a two-dimensional search window, enabling the despeckling of volumes in the presence of motion artifacts, and an implementation using a three-dimensional window with improved performance in motion-free volumes.

Vortex-enhanced coherent-illumination phase diversity for phase retrieval in coherent imaging systems.

We propose a phase-retrieval method based on the numerical optimization of a new objective function using coherent phase-diversity images as inputs for the characterization of aberrations in coherent imaging systems. By employing a spatial light modulator to generate multiple-order spiral phase masks as diversities, we obtain an increase in the accuracy of the retrieved phase compared with similar state-of-the-art phase-retrieval techniques that use the same number of input images. We present simulations that show a consistent advantage of our technique, and experimental validation where our implementation is used to characterize a highly aberrated 4F optical system.

Electronic speckle pattern interferometry using vortex beams.

We show that it is possible to perform electronic speckle pattern interferometry (ESPI) using, for the first time to our knowledge, vortex beams as the reference beam. The technique we propose is easy to implement, and the advantages obtained are, among others, environmental stability, lower processing time, and the possibility to switch between traditional ESPI and spiral ESPI. The experimental results clearly show the advantages of using the proposed technique for deformation studies of complex structures.