Abstract: An ophthalmic imaging system provides a user interface to facilitate the montaging of scan images collected with various imaging modalities, such as images collected with a fundus imaging system or an optical coherence tomography (OCT) system. The amount of each constituent image used in the montage is dependent upon its respective quality. During the collecting of scans (constituent images) for montaging, any scan may be designated for rescanning, such as if its current quality is deemed less than sufficient. In the case of using an OCT system to collect constituent images (e.g., cube scans), the scanned region of a constituent image may be modified based on physical characteristics of the eye being scanned.

Abstract: An optical coherence tomography (OCT) unit provides a mechanism/method for automatic artery and vein identification. The method may be embodied by specialized algorithm or by a machine learning model, such as a support vector machine or neural network. The present method may identify a vascular configuration that forms a vortex structure in the deep capillary plexus (DCP) of an OCT-based (e.g., OCTA) image of a retina. The identified vortex may then be designated a vein, and other vascular structures from other plexuses, such as from the superficial vascular plexus (SVP), that connect to the identified vortex structure are likewise designated veins. Additional criteria, some based on the vein designations, may be used to identify arteries.

Abstract: Methods for improved acquisition and processing of optical coherence tomography (OCT) angiography data are presented. One embodiment involves improving the acquisition of the data by evaluating the quality of different portions of the data to identify sections having non-uniform acquisition parameters or non-uniformities due to opacities in the eye such as floaters. The identified sections can then be brought to the attention of the user or automatically reacquired. In another embodiment, segmentation of layers in the retina includes both structural and flow information derived from motion contrast processing. In a further embodiment, the health of the eye is evaluating by comparing a metric reflecting the density of vessels at a particular location in the eye determined by OCT angiography to a database of values calculated on normal eyes.

Abstract: An ophthalmic image diagnostic tool and method submits a test image to a neural network trained to identify abnormal regions of an ophthalmic image, to distinguish between multiple types of abnormalities, and to associate an abnormality type with each identified potentially abnormal region. Each potentially abnormal region in the test image is highlighted, and in response to a user-selection of a highlighted region, a previously diagnosed sample (e.g., from a library of samples) of the abnormality type associated with the selected highlighted region is displayed.

Abstract: Methods for improved acquisition and processing of optical coherence tomography (OCT) angiography data are presented. One embodiment involves improving the acquisition of the data by evaluating the quality of different portions of the data to identify sections having non-uniform acquisition parameters or non-uniformities due to opacities in the eye such as floaters. The identified sections can then be brought to the attention of the user or automatically reacquired. In another embodiment, segmentation of layers in the retina includes both structural and flow information derived from motion contrast processing. In a further embodiment, the health of the eye is evaluating by comparing a metric reflecting the density of vessels at a particular location in the eye determined by OCT angiography to a database of values calculated on normal eyes.

Abstract: An ophthalmic image diagnostic tool and method submits a test image to a neural network trained to identify abnormal regions of an ophthalmic image, to distinguish between multiple types of abnormalities, and to associate an abnormality type with each identified potentially abnormal region. Each potentially abnormal region in the test image is highlighted, and in response to a user-selection of a highlighted region, a previously diagnosed sample (e.g., from a library of samples) of the abnormality type associated with the selected highlighted region is displayed.

Abstract: Methods and systems in ophthalmic imaging are presented that increase the sensitivity of automated diagnoses by the use of a combination of both functional and structural information derived from a variety of ophthalmic imaging modalities. An example method to analyze image data of an eye of a patient includes processing a first image dataset to obtain one or more functional metrics; processing a second image dataset to obtain one or more structural metrics; comparing the one or more structural metrics to the one or more functional metrics; and processing the results of said comparison to derive the probability of a disease or normality of the eye.

Abstract: Methods for improved acquisition and processing of optical coherence tomography (OCT) angiography data are presented. One embodiment involves improving the acquisition of the data by evaluating the quality of different portions of the data to identify sections having non-uniform acquisition parameters or non-uniformities due to opacities in the eye such as floaters. The identified sections can then be brought to the attention of the user or automatically reacquired. In another embodiment, segmentation of layers in the retina includes both structural and flow information derived from motion contrast processing. In a further embodiment, the health of the eye is evaluating by comparing a metric reflecting the density of vessels at a particular location in the eye determined by OCT angiography to a database of values calculated on normal eyes.

Abstract: An ophthalmic imaging system provides a user interface to facilitate the montaging of scan images collected with various imaging modalities, such as images collected with a fundus imaging system or an optical coherence tomography (OCT) system. The amount of each constituent image used in the montage is dependent upon its respective quality. During the collecting of scans (constituent images) for montaging, any scan may be designated for rescanning, such as if its current quality is deemed less than sufficient. In the case of using an OCT system to collect constituent images (e.g., cube scans), the scanned region of a constituent image may be modified based on physical characteristics of the eye being scanned.

Abstract: Systems and methods to improve the detection and classification of inflammation in the eye are presented. The inflammatory markers in image data can be graded by comparing identified and extracted characteristics from the images with characteristics derived from a set of images of eyes from a general population of subjects. The image data can be divided into sub-regions for analysis to better isolate the true inflammatory markers from the impacts of cataracts or other opacities. In another embodiment, the location of an imaging beam can be controlled to minimize the impact of lens opacities from the collected data used to analyze the inflammation state of an eye.

Abstract: Systems and methods for improving the assessment of disruption or abnormalities to retinal layers are presented. The disruptions are detected by analyzing at least one segmented boundary of optical coherence tomography data. Several different types of analysis can be used alone or in combination to make an assessment of the level of disruption to the particular boundary or layer defined by the boundary. The results can be presented as an end face image and quantified to report an amount of disruption. In one embodiment, a method for determining the disruption to the photoreceptor outer segment is described.

Abstract: Methods for improved acquisition and processing of optical coherence tomography (OCT) angiography data are presented. One embodiment involves improving the acquisition of the data by evaluating the quality of different portions of the data to identify sections having non-uniform acquisition parameters or non-uniformities due to opacities in the eye such as floaters. The identified sections can then be brought to the attention of the user or automatically reacquired. In another embodiment, segmentation of layers in the retina includes both structural and flow information derived from motion contrast processing. In a further embodiment, the health of the eye is evaluating by comparing a metric reflecting the density of vessels at a particular location in the eye determined by OCT angiography to a database of values calculated on normal eyes.

Abstract: Methods for analyzing optical coherence tomography (OCT) images of the macula to reduce variance and improve disease diagnosis are presented. One embodiment of the invention is directed towards selecting analysis locations and data segmentation techniques to take advantage of structural homogeneities. Another embodiment is directed towards reducing the variance in a collection of normative data by transforming the individual members of the database to correspond to a Standard Macula. Variations in foveal size are corrected by radial transformation. Variations in layer thickness are corrected by axial shifting. Diagnosis is performed by comparing OCT images from a patient to the improved normative database.

Abstract: Methods for improved acquisition and processing of optical coherence tomography (OCT) angiography data are presented. One embodiment involves improving the acquisition of the data by evaluating the quality of different portions of the data to identify sections having non-uniform acquisition parameters or non-uniformities due to opacities in the eye such as floaters. The identified sections can then be brought to the attention of the user or automatically reacquired. In another embodiment, segmentation of layers in the retina includes both structural and flow information derived from motion contrast processing. In a further embodiment, the health of the eye is evaluating by comparing a metric reflecting the density of vessels at a particular location in the eye determined by OCT angiography to a database of values calculated on normal eyes.

Abstract: Methods for analyzing and visualizing OCT angiography data are presented. In one embodiment, an automated method for identifying the foveal avascular zone in a two dimensional en face image generated from motion contrast data is presented. Several 3D visualization techniques are presented including one in which a particular vessel is selected in a motion contrast image and all connected vessels are highlighted. A further embodiment includes a stereoscopic visualization method. In addition, a variety of metrics for characterizing OCT angiography image data are described.

Abstract: Methods and systems in ophthalmic imaging are presented that increase the sensitivity of automated diagnoses by the use of a combination of both functional and structural information derived from a variety of ophthalmic imaging modalities. An example method to analyze image data of an eye of a patient includes processing a first image dataset to obtain one or more functional metrics; processing a second image dataset to obtain one or more structural metrics; comparing the one or more structural metrics to the one or more functional metrics; and processing the results of said comparison to derive the probability of a disease or normality of the eye.

Abstract: Methods for improved acquisition and processing of optical coherence tomography (OCT) angiography data are presented. One embodiment involves improving the acquisition of the data by evaluating the quality of different portions of the data to identify sections having non-uniform acquisition parameters or non-uniformities due to opacities in the eye such as floaters. The identified sections can then be brought to the attention of the user or automatically reacquired. In another embodiment, segmentation of layers in the retina includes both structural and flow information derived from motion contrast processing. In a further embodiment, the health of the eye is evaluating by comparing a metric reflecting the density of vessels at a particular location in the eye determined by OCT angiography to a database of values calculated on normal eyes.

Abstract: Methods for analyzing and visualizing OCT angiography data are presented. In one embodiment, an automated method for identifying the foveal avascular zone in a two dimensional en face image generated from motion contrast data is presented. Several 3D visualization techniques are presented including one in which a particular vessel is selected in a motion contrast image and all connected vessels are highlighted. A further embodiment includes a stereoscopic visualization method. In addition, a variety of metrics for characterizing OCT angiography image data are described.

Abstract: Systems and methods to improve the detection and classification of inflammation in the eye are presented. The inflammatory markers in image data can be graded by comparing identified and extracted characteristics from the images with characteristics derived from a set of images of eyes from a general population of subjects. The image data can be divided into sub-regions for analysis to better isolate the true inflammatory markers from the impacts of cataracts or other opacities. In another embodiment, the location of an imaging beam can be controlled to minimize the impact of lens opacities from the collected data used to analyze the inflammation state of an eye.

Abstract: Methods for analyzing optical coherence tomography (OCT) images of the macula to reduce variance and improve disease diagnosis are presented. One embodiment of the invention is directed towards selecting analysis locations and data segmentation techniques to take advantage of structural homogeneities. Another embodiment is directed towards reducing the variance in a collection of normative data by transforming the individual members of the database to correspond to a Standard Macula. Variations in foveal size are corrected by radial transformation. Variations in layer thickness are corrected by axial shifting. Diagnosis is performed by comparing OCT images from a patient to the improved normative database.