Abstract: Disclosed herein are methods and systems for optical coherence tomography (OCT) angiography (OCTA). An interleaved scanning pattern is described herein for both raster and bidirectional scanning methods. The interleaved scanning pattern provides B-scans with different scanning intervals. OCTA images based on the B-scans may be combined to obtain a high dynamic range (HDR) OCTA image. Other embodiments may be described and claimed.

Abstract: Disclosed are methods and systems correcting bulk-motion artifacts in phase-based functional OCT images. The disclosed methods and systems are based on the use of the standard deviation of the phase shift signal present in phase-based OCT imaging. When applied with functional OCT techniques such as OCT angiography, Doppler OCT, and OCT elastography, the disclosed methods provide improved image quality and decreased computational cost compared to other methods of bulk motion compensation.

Abstract: Methods for automatically identifying retinal boundaries from a reflectance image are disclosed. An example of the method includes identifying a reflectance image of the retina of a subject; generating a gradient map of the reflectance image, the gradient map representing dark-to-light or light-to-dark reflectance differentials between adjacent pixel pairs in the reflectance image; generating a guidance point array corresponding to a retinal layer boundary depicted in the reflectance image using the gradient map; generating multiple candidate paths estimating the retinal layer boundary in the reflectance image by performing a guided bidirectional graph search on the reflectance image using the guidance point array; and identifying the retinal layer boundary by merging two or more of the multiple candidate paths.

Abstract: Methods of applying OCT angiography are disclosed. In particular, methods of detecting, visualizing and measuring the extent of retinal neovascularization are disclosed. Further disclosed are methods measuring retinal nonperfusion area and choriocapillaris defect area.

Abstract: Disclosed herein are methods and systems for capillary oximetry (e.g., retinal capillary oximetry) using optical coherence tomography (OCT). The method may include obtaining an OCT angiography dataset, performing capillary segmentation based on the OCT angiography dataset to obtain capillary segments, resampling, registering, and/or averaging B-scans of the OCT angiography dataset that correspond to a first capillary segment of the capillary segments to obtain an averaged B-scan for the first capillary segment, determining an anterior and posterior border of the first capillary segment, and determining an oxygen saturation of the first capillary segment based on the averaged B-scan, the anterior border, and the posterior border. Other embodiments may be described and claimed.

Abstract: Embodiments provide systems and methods associated with a reflectance-based projection-resolved (rbPR) optical coherence tomography angiography (OCTA) algorithm which uses optical coherence tomography (OCT) reflectance to enhance the flow signal and suppress the projection artifacts in 3-dimensional OCTA. rbPR improves the vascular connectivity and improved the discrimination of the deeper plexus angiograms in healthy eyes, compared to prior PR-OCTA method. Additionally, rbPR removes flow projection artifacts more completely from the outer retinal slab in the eyes with age-related macular degeneration, and preserves vascular integrity of the intermediate and deep capillary plexuses in the eyes with diabetic retinopathy. Additionally, the rbPR method improves the resolution of the choriocapillaris and demonstrates details comparable to scanning electron microscopy.

Abstract: An example method includes generating, using a multi-scale block of a convolutional neural network (CNN), a first output image based on an optical coherence tomography (OCT) reflectance image of a retina and an OCT angiography (OCTA) image of the retina. The method further includes generating, using an encoder of the CNN, at least one second output image based on the first output image and generating, using a decoder of the CNN, a third output image based on the at least one second output image. An avascular map is generated based on the third output image. The avascular map indicates at least one avascular area of the retina depicted in the OCTA image.

Abstract: Disclosed herein are methods and systems for automated detection of shadow artifacts in optical coherence tomography (OCT) and/or OCT angiography (OCTA). The shadow detection includes applying a machine-learning algorithm to the OCT dataset and the OCTA dataset to detect one or more shadow artifacts in the sample. The machine-learning algorithm is trained with first training data from first training samples that include manufactured shadows and no perfusion defects and second training data from second training samples that include perfusion defects and no manufactured shadows. The shadow artifacts in the OCTA dataset and/or OCT dataset may be suppressed to generate a shadow-suppressed OCTA dataset and/or a shadow-suppressed OCT dataset, respectively. Other embodiments may be described and claimed.

Abstract: Methods and systems for suppressing shadowgraphic flow projection artifacts in OCT angiography images of a sample are disclosed. In one example approach, normalized OCT angiography data is analyzed at the level of individual A-scans to classify signals as either flow or projection artifact. This classification information is then used to suppress projection artifacts in the three dimensional OCT angiography dataset.

Abstract: Described herein is an algorithm to remove decorrelation noise due to bulk motion in optical coherence tomography angiography (OCTA). OCTA B-frames are divided into segments within which the bulk motion velocity could be assumed constant. This velocity is recovered using linear regression of decorrelation versus the logarithm of reflectance in axial lines (A-lines) identified as bulk tissue by percentile analysis. The fitting parameters are used to calculate a reflectance-adjusted threshold for bulk motion decorrelation. Below this threshold, voxels are identified as non-flow tissue, and their flow values are set to zeros. Above this threshold, the voxels are identified as flow voxels and bulk motion velocity is subtracted from each using a nonlinear decorrelation-velocity relationship.

Abstract: Impaired intraocular blood flow within vascular beds in the human eye is associated with certain ocular diseases including, for example, glaucoma, diabetic retinopathy and age-related macular degeneration. A reliable method to quantify blood flow in the various intraocular vascular beds could provide insight into the vascular component of ocular disease pathophysiology. Using ultrahigh-speed optical coherence tomography (OCT), a new 3D angiography algorithm called split-spectrum amplitude-decorrelation angiography (SSADA) was developed for imaging microcirculation within different intraocular regions. A method to quantify SSADA results was developed and used to detect perfusion changes in early stage ocular disease. Associated embodiments relating to methods for quantitatively measuring blood flow at various intraocular vasculature sites, systems for practicing such methods, and use of such methods and systems for diagnosing certain ocular diseases are herein described.

Abstract: Disclosed are methods and systems for measuring areas of nonperfusion in the retina using OCT imaging. The disclosed methods and systems allow for the automated segmentation and quantification of avascular areas of the retina utilizing information obtained from both structural OCT and OCT angiography (OCTA) data. The disclosed methods include filtering approaches which enhance vessel structure while suppressing noise, dynamic thresholding approaches to mitigate the detrimental effects of within-scan variability and low scan quality, and distance transform-based approaches to improve detection of ischemic regions. When combined with methods such as projection-resolved OCTA, the sensitivity to detect nonperfusion within different plexuses of the inner retina is demonstrated. In the clinical setting of diabetic retinopathy, the disclosed methods and systems show high sensitivity and specificity to detect the mild non-proliferative form of the disease with high reproducibility.

Abstract: A train window structure and a train with the train window structure, the train window structure comprising: a train window frame; train window glass disposed in the train window frame; and a fastener penetrating through an inner side of the train window frame and disposed on a train body to fasten the train window frame, the axis of the fastener being parallel to a plane where the train window glass is provided. The fastener penetrates through the train window frame from an inner side of the train window frame and is screwed into the train body; the fastener is internally installed, thus reducing a gap between the adjacent train window structures, so that the train body is more aesthetically pleasing and wind resistance is lower.

Abstract: Methods and systems for improving quantification of OCT angiography data are disclosed. The disclosure specifically relates to methods for compensating for the effect of tissue reflectance to improve the accuracy and repeatability of OCT angiography measurements. These improvements are effected by deriving and then utilizing a dynamic thresholding approach to process decorrelation data to properly classify flow versus non-flow data in OCT angiograms. The disclosed methods overcome quantification errors associated with within-scan variations in reflectance as well as repeatability problems associated with differences in scan quality over successive imaging sessions.

Abstract: Methods and systems for suppressing shadowgraphic flow projection artifacts in OCT angiography images of a sample are disclosed. In one example approach, normalized OCT angiography data is analyzed at the level of individual A-scans to classify signals as either flow or projection artifact. This classification information is then used to suppress projection artifacts in the three dimensional OCT angiography dataset.

Abstract: Disclosed are systems and methods for generating wide-field optical coherence tomography angiography (OCTA) images. In embodiments, multiple OCTA scans of a sample are automatically acquired at overlapping locations. The systems and methods include functionality to adaptively control the scanning procedure such that eye blink and eye motion events are detected in real time and accounted for during 3D scan acquisition. Also disclosed are methods for detecting and correcting motion-related artifacts in OCTA datasets which allow for the longer scan times over larger fields of view required for wide-field imaging. These methods may include division of en face angiogram images into a set of motion-free parallel strips, and application of gross and fine registration methods to align overlapping strips into a motion-corrected composite image. A series of overlapping motion-corrected composite images may be combined into a larger montage to enable wide-field OCTA imaging using multiple OCTA scans.

Abstract: Disclosed herein are methods and systems for the identification and characterization of fluid accumulation in the retina using OCT imaging. The disclosed methods and systems are directed to the automated segmentation of retinal fluid using 2D or 3D structural OCT scan images. Approaches for visualization and quantification of both intraretinal and subretinal fluid are presented. Methods are also disclosed for using OCT angiography data to improve the quality of retinal fluid segmentation, and to provide combined visualization of fluid accumulation and retinal vasculature to inform clinical interpretation of results.

Abstract: Methods and systems for suppressing shadowgraphic flow projection artifacts in OCT angiography images of a sample are disclosed. In one example approach, normalized OCT angiography data is analyzed at the level of individual A-scans to classify signals as either flow or projection artifact. This classification information is then used to suppress projection artifacts in the three dimensional OCT angiography dataset.

Abstract: Disclosed herein are methods and systems for the identification and characterization of fluid accumulation in the retina using OCT imaging. The disclosed methods and systems are directed to the automated segmentation of retinal fluid using 2D or 3D structural OCT scan images. Approaches for visualization and quantification of both intraretinal and subretinal fluid are presented. Methods are also disclosed for using OCT angiography data to improve the quality of retinal fluid segmentation, and to provide combined visualization of fluid accumulation and retinal vasculature to inform clinical interpretation of results.

Abstract: Methods of applying OCT angiography are disclosed. In particular, methods of detecting, visualizing and measuring the extent of retinal neovascularization are disclosed. Further disclosed are methods measuring retinal nonperfusion area and choriocapillaris defect area.