Abstract: Optical coherence tomography (OCT) may be used to acquire cross-sectional or volumetric images of any specimen, including biological specimens such as the retina. Additional processing of the OCT data may be performed to generate images of features of interest. In some embodiments, these features may be in motion relative to their surroundings, e.g., blood in the retinal vasculature. In some embodiments, an acquired image may be degraded by motion artifact. The proposed invention describes OCT system embodiments that may be configured for multi-scale imaging, with the capability of switching between low or high lateral resolution, and with the assistance of adaptive optics for aberration correction. The invention also describes a method for enhancing OCT image quality by reducing or eliminating the negative effects introduced by sources and speed by performing bidirectional scanning.

Abstract: Optical coherence tomography (OCT) may be used to acquire cross-sectional or volumetric images of any specimen, including biological specimens such as the retina. Additional processing of the OCT data may be performed to generate images of features of interest. In some embodiments, these features may be in motion relative to their surroundings, e.g., blood in the retinal vasculature. The proposed invention describes a combination of images acquired by OCT, manual segmentations of these images by experts, and an artificial neural network for the automated segmentation and classification of features in the OCT images. As a specific example, the performance of the systems and methods described herein are presented for the automatic segmentation of blood vessels in images acquired with OCT angiography.

Abstract: A method for rapid OCT image acquisition includes acquiring by OCT a plurality of compressive measurements (y) representing a set of under-sampled OCT data in a Dirac domain below a Nyquist rate by sampling an object of interest at randomly spaced vertical and horizontal lines in a Cartesian geometry using a raster scan, and recovering a 3D volumetric OCT image (f) from the compressive measurements (y) using compressive sampling. The method may also include recovering the 3D volumetric OCT image (f) from the compressive measurements (y) based at least in part on a sparsifying matrix (S) capable of transforming the 3D volumetric OCT image (f) into a sparse representation, such as a matrix representation of the 3D volumetric OCT image (f) in a shift-invariant wavelet transform domain. The method may also be applied to radial OCT scan patterns.

Abstract: A method for rapid OCT image acquisition includes acquiring by OCT a plurality of compressive measurements (y) representing a set of under-sampled OCT data in a Dirac domain below a Nyquist rate by sampling an object of interest at randomly spaced vertical and horizontal lines in a Cartesian geometry using a raster scan, and recovering a 3D volumetric OCT image (f) from the compressive measurements (y) using compressive sampling. The method may also include recovering the 3D volumetric OCT image (f) from the compressive measurements (y) based at least in part on a sparsifying matrix (S) capable of transforming the 3D volumetric OCT image (f) into a sparse representation, such as a matrix representation of the 3D volumetric OCT image (f) in a shift-invariant wavelet transform domain. The method may also be applied to radial OCT scan patterns.