Abstract: A method and system for correction of decorrelation tail artifacts in optical coherence tomography (OCT) angiography volumetric data defines a movable target subvolume within the OCT-A volumetric data. The target subvolume is axially moveable within the OCT-A volumetric data in discrete axial steps. At each axial step, a reference subvolume corresponding to a depth location in the OCT A volumetric data is defined axially offset from the target subvolume. The reference subvolume may be defined within the OCT A volumetric data, or defined within a different (previously corrected) OCT-A volume. Irrespective, corrected OCT-A data that corrects for decorrelation tail artifacts in the target subvolume is defined using information in the reference subvolume and information in the target subvolume.

Abstract: Various methods for reducing artifacts in OCT images of an eye are described. In one exemplary method, three dimensional OCT image data of the eye is collected. Motion contrast information is calculated in the OCT image data. A first image and a second image are created from the motion contrast information. The first and the second images depict vasculature information regarding one or more upper portions and one or more deeper portions, respectively. The second image contains artifacts. Using an inverse calculation, a third image is determined that can be mixed with the first image to generate the second image. The third image depicts vasculature regarding the same one or more deeper portions as the second image but has reduced artifacts. A depth dependent correction method is also described that can be used in combination with the inverse problem based method to further reduce artifacts in OCT angiography images.

Abstract: Various systems and methods for improved OCT angiography imaging are described. An example method of identifying intraretinal fluid in optical coherence tomography (OCT) image data of an eye includes collecting OCT image data using an OCT system. The data includes at least one cluster scan containing OCT image data collected at approximately same set of locations on the sample. A first motion contrast image is generated by applying a first OCT angiography processing technique to the cluster scan to highlight motion contrast in the sample. A second motion contrast image is generated by applying a second OCT angiography processing technique to the cluster scan to highlight motion contrast in the sample. An image displaying intraretinal fluid in the eye is generated using the first and second motion contrast images and then displayed or stored or a further analysis thereof.

Abstract: Methods and systems are presented to analyze a retinal image of an eye and assigns features to known anatomical structures such as retinal layers. One example method includes receiving interferometric image data of an eye. A set of features is identified in the image data. A first subset of identified features is associated with known retinal structures using prior knowledge. A first set of characteristic metrics is determined of the first subset of features. A second set of characteristic metrics is determined of a second subset of features. Using the characteristic metrics of the first and the second sets, the second subset of features is associated with the retinal structures. Another example method includes dividing interferometric image data into patches. The image data in each patch is segmented to identify one or more layer boundaries. The segmentation results from each patch are stitched together into a single segmentation dataset.

Abstract: Methods and systems are presented to analyze a retinal image of an eye and assigns features to known anatomical structures such as retinal layers. One example method includes receiving interferometric image data of an eye. A set of features is identified in the image data. A first subset of identified features is associated with known retinal structures using prior knowledge. A first set of characteristic metrics is determined of the first subset of features. A second set of characteristic metrics is determined of a second subset of features. Using the characteristic metrics of the first and the second sets, the second subset of features is associated with the retinal structures. Another example method includes dividing interferometric image data into patches. The image data in each patch is segmented to identify one or more layer boundaries. The segmentation results from each patch are stitched together into a single segmentation dataset.

Abstract: Various methods for automatically identifying the Schwalbe's line location in an optical coherence tomography (OCT) image of the anterior chamber of an eye are described. In one example method, the posterior corneal surface in the ROI is segmented by using one or more segmentation approaches to produce a segmented output. A curvature is computed at each segmented point to identify a set of local curvature maxima locations. Features at each local curvature maxima location are evaluated. The Schwalbe's line location is identified using the evaluated features at each maxima location. Other methods for identifying the Schwalbe's line location discussed in the present application are based on identification of a location of maximum curvature in the curvature function and identification of a maximum distance to the convex-hull of a model fit.

Abstract: An efficient method of evaluating the level of contrast of an OCT dataset is presented. The method develops a metric to segregate useful and not-so-useful data in one or more OCT B-scans, in order to reduce spurious subsequent analyses of the data by downstream segmentation algorithms. It is designed to be fast and efficient and is applied to determining autofocus of an OCT instrument real-time and in identifying a real image from its complex conjugate twin.

Abstract: Various systems and methods for improved OCT angiography imaging are described. An example method of identifying intraretinal fluid in optical coherence tomography (OCT) image data of an eye includes collecting OCT image data using an OCT system. The data includes at least one cluster scan containing OCT image data collected at approximately same set of locations on the sample. A first motion contrast image is generated by applying a first OCT angiography processing technique to the cluster scan to highlight motion contrast in the sample. A second motion contrast image is generated by applying a second OCT angiography processing technique to the cluster scan to highlight motion contrast in the sample. An image displaying intraretinal fluid in the eye is generated using the first and second motion contrast images and then displayed or stored or a further analysis thereof.

Abstract: Various methods for the detection and enhanced visualization of a particular structure or pathology of interest in a human eye are discussed in the present disclosure. An example method to visualize a given pathology (e.g., CNV) in an eye includes collecting optical coherence tomography (OCT) image data of the eye from an OCT system. The OCT image data is segmented to identify two or more retinal layer boundaries located in the eye. The two or more retinal layer boundaries are located at different depth locations in the eye. One of the identified layer boundaries is moved and reshaped to optimize visualization of the pathology located between the identified layer boundaries. The optimized visualization is displayed or stored or for a further analysis thereof.

Abstract: An efficient method of evaluating the level of contrast of an OCT dataset is presented. The method develops a metric to segregate useful and not-so-useful data in one or more OCT B-scans, in order to reduce spurious subsequent analyses of the data by downstream segmentation algorithms. It is designed to be fast and efficient and is applied to determining autofocus of an OCT instrument real-time and in identifying a real image from its complex conjugate twin.

Abstract: Various methods and systems for improved anterior segment optical coherence tomography (OCT) imaging are described. One example method includes collecting a set of OCT data of the cornea of the eye; segmenting the set of OCT data to identify one or more corneal layers; fitting a two-dimensional model of corneal surfaces to the one or more corneal layers; determining motion-correction parameters by minimizing error between the one or more corneal layers and the two-dimensional model of the corneal surfaces; and creating a motion-corrected corneal image dataset from the set of OCT data using the motion-correction parameters. The motion-corrected corneal image dataset can be used to create a model of the anterior and/or posterior surfaces of the cornea. The model of the cornea is used to generate high density and motion-artifact free epithelial thickness maps, which are used for identifying or quantifying pathology such as keratoconus.

Abstract: The present application discloses methods and systems to track the anterior segment while establishing a position of the delay which will permit good control of the placement of anterior segment structures. This allows accurate dewarping by maximizing the amount of corneal surface that is imaged as well as reducing or eliminating overlap between real and complex conjugate images present in frequency-domain optical coherence tomography. A method to dewarp surfaces given partial corneal surface information is also disclosed.

Abstract: An efficient method of evaluating the level of contrast of an OCT dataset is presented. The method develops a metric to segregate useful and not-so-useful data in one or more OCT B-scans, in order to reduce spurious subsequent analyses of the data by downstream segmentation algorithms. It is designed to be fast and efficient and is applied to determining autofocus of an OCT instrument real-time and in identifying a real image from its complex conjugate twin.

Abstract: Systems and methods for enhanced accuracy in optical coherence tomography imaging of the cornea are presented, including approaches for more accurate corneal surface modeling, pachymetry maps, keratometric values, and corneal power. These methods involve new scan patterns, an eye tracking mechanism for transverse motion feedback, and advanced motion correction algorithms. In one embodiment the methods comprise acquiring a first sparse set of data, using that data to create a corneal surface model, and then using the model to register a second set of denser data acquisition. This second set of data is used to create a more accurate, motion-corrected model of the cornea, from which pachymetry maps, keratometric values, and corneal power information can be generated. In addition, methods are presented for determining simulated keratometry values from optical coherence tomography data, and for better tracking and registration by using both rotation about three axes and the corneal apex.

Abstract: Systems and methods are presented which allow the detection of the presence, type, and misalignment of optical components in the optical train of an optical coherence tomographic instrument to be determined from the use of OCT depth information.

Abstract: The present application discloses methods and systems to track the anterior segment while establishing a position of the delay which will permit good control of the placement of anterior segment structures. This allows accurate dewarping by maximizing the amount of corneal surface that is imaged as well as reducing or eliminating overlap between real and complex conjugate images present in frequency-domain optical coherence tomography. A method to dewarp surfaces given partial corneal surface information is also disclosed.

Abstract: Systems and methods for enhanced accuracy in optical coherence tomography imaging of the cornea are presented, including approaches for more accurate corneal surface modeling, pachymetry maps, keratometric values, and corneal power. These methods involve new scan patterns, an eye tracking mechanism for transverse motion feedback, and advanced motion correction algorithms. In one embodiment the methods comprise acquiring a first sparse set of data, using that data to create a corneal surface model, and then using the model to register a second set of denser data acquisition. This second set of data is used to create a more accurate, motion-corrected model of the cornea, from which pachymetry maps, keratometric values, and corneal power information can be generated. In addition, methods are presented for determining simulated keratometry values from optical coherence tomography data, and for better tracking and registration by using both rotation about three axes and the corneal apex.

Abstract: Systems and methods for enhanced accuracy in optical coherence tomography imaging of the cornea are presented, including approaches for more accurate corneal surface modeling, pachymetry maps, keratometric values, and corneal power. These methods involve new scan patterns, an eye tracking mechanism for transverse motion feedback, and advanced motion correction algorithms. In one embodiment the methods comprise acquiring a first sparse set of data, using that data to create a corneal surface model, and then using the model to register a second set of denser data acquisition. This second set of data is used to create a more accurate, motion-corrected model of the cornea, from which pachymetry maps, keratometric values, and corneal power information can be generated. In addition, methods are presented for determining simulated keratometry values from optical coherence tomography data, and for better tracking and registration by using both rotation about three axes and the corneal apex.

Abstract: Presented here are new processing techniques for optical coherence tomography (OCT) data that allow for improved visualization and use of full-range OCT images. These techniques minimize the central line artifact and the complex conjugate artifact without requiring additional system hardware or significantly increasing post-processing time. The central line artifact is minimized by normalizing each A-scan to account for ripples at the zero-delay position. The complex conjugate artifact is minimized by segmentation of a layer or layers that cross the zero-delay position, and in some embodiments by further segmentation of other surfaces based on the segmentation of the initial layer or layers. The segmentation information is then used to selectively attenuate the complex conjugate image. It may also be used for other purposes, such as dewarping.

Abstract: Systems and methods are presented which allow the detection of the presence, type, and misalignment of optical components in the optical train of an optical coherence tomographic instrument to be determined from the use of OCT depth information.