Abstract: Machine learning technologies are used to identify and separating abnormal and normal subjects and identifying possible disease types with images (e.g., optical coherence tomography (OCT) images of the eye), where the machine learning technologies are trained with only normative data. In one example, a feature or a physiological structure of an image is extracted, and the image is classified based on the extracted feature. In another example, a region of the image is masked and then reconstructed, and a similarity is determined between the reconstructed region and the original region of the image. A label (indicating an abnormality) and a score (indicating a severity) can be determined based on the classification and/or the similarity.

Abstract: Methods and systems for angiographic imaging with optical coherence tomography (OCT) are described using ratio-based and angiographic deviation based calculations. In using these calculations to determine motion, arbitrary interframe permutations may be used, post- calculated, non-linear results for projection visualization may be averaged, poor matches may be eliminated on an A-line by A-line basis, windowing functions may be used to improve results, partial spectrums may be used when capturing data, and a minimum intensity threshold may be used for determining which pixels to use.

Abstract: Methods and systems for angiographic imaging with optical coherence tomography (OCT) are described using ratio-based and angiographic deviation based calculations. In using these calculations to determine motion, arbitrary interframe permutations may be used, post- calculated, non-linear results for projection visualization may be averaged, poor matches may be eliminated on an A-line by A-line basis, windowing functions may be used to improve results, partial spectrums may be used when capturing data, and a minimum intensity threshold may be used for determining which pixels to use.

Abstract: Methods and systems for angiographic imaging with optical coherence tomography (OCT) are described using ratio-based and angiographic deviation based calculations. In using these calculations to determine motion, arbitrary interframe permutations may be used, post-calculated, non-linear results for projection visualization may be averaged, poor matches may be eliminated on an A-line by A-line basis, windowing functions may be used to improve results, partial spectrums may be used when capturing data, and a minimum intensity threshold may be used for determining which pixels to use.

Abstract: Machine learning technologies are used to identify and separating abnormal and normal subjects and identifying possible disease types with images (e.g., optical coherence tomography (OCT) images of the eye), where the machine learning technologies are trained with only normative data. In one example, a feature or a physiological structure of an image is extracted, and the image is classified based on the extracted feature. In another example, a region of the image is masked and then reconstructed, and a similarity is determined between the reconstructed region and the original region of the image. A label (indicating an abnormality) and a score (indicating a severity) can be determined based on the classification and/or the similarity.

Abstract: Provided is a method of processing image data and detecting a region of an image represented by the image data to be excluded from an analysis of the image. According to the method, image data captured by a medical modality is received. An evaluation of a portion of the image data representing a two-dimensional view of a subject appearing in the image is conducted to locate, in the two-dimensional view, the region to be excluded from the analysis of the image. A feature pertinent to the analysis appearing in a remaining portion of the image, that is outside of the region to be excluded from the analysis located by the evaluation, is detected.

Abstract: An interferometric imaging apparatus utilizes a split spectrum and/or frequency filtering process for generating fundus images. According to the split spectrum process, a bandwidth of a light source is divided into sub-spectrums of light, each used to generate pixel data for the fundus image. Data capture can thus be increased by a factor corresponding to the number of sub-spectrums. According to the frequency filtering process, a frequency filter associated with a depth of interest selectively retains data corresponding to that depth.

Abstract: Optical coherence tomography light sources can be non-linear and attempts to linearize them can lead to asynchrony between the light source and A-line scans and missampling in the scans causing signal noise. Accordingly, a system and methods are provided herein to detect missampling by obtaining a plurality of interferograms; providing at least two wavenumber reference signals at different wavenumbers, wherein the wavenumber reference signals comprise attenuated or enhanced portions of each of the plurality of interferograms; aligning each of the plurality of interferograms according to one of the at least two wavenumber reference signals; and for each of the plurality of interferograms, identifying an interferogram as missampled if another of the at least two reference signals does not align with a corresponding reference signal in a statistically significant number of the plurality of interferograms. An optical element, for example, an optical notch, may be used to generate the reference signals.

Abstract: Geographic atrophy of the eye can be detected and measured by imaging the eye at a depth greater than the retinal pigment epithelium (RPE) at a plurality of locations of the eye, for example, using optical coherence tomography (OCT); determining a ratio of the intensities of imaging signals of a retinal layer(s) with respect to the intensity of imaging signals of a sub-RPE layer(s) at each location; determining representative values based at least in part on the determined ratios; generating a map of the representative values; and identifying diseased areas from the map. Contours and binary maps may be generated based on the identified diseased areas. The size and shape of the identified areas may be analyzed and monitored over a period of time to phenotype subjects and classify diseases.

Abstract: Optical coherence tomography (OCT) scan data of a subject is acquired over a region of interest which can include an optic disc or a macula of a retina. Layer boundaries of retinal layers are identified in the OCT scan data to facilitate measurements. In one aspect, a measurement related to ratio value between a total backscattered signal intensity of one or more target layers of the retina and a total backscattered signal intensity of one or more reference layers is computed on a location-by-location basis within a region of interest of the OCT scan data. Measurements can be collected, aggregated, analyzed, and displayed in connection with other information taken or derived from the OCT scan data.

Abstract: Methods and systems for angiographic imaging with optical coherence tomography (OCT) are described using ratio-based and angiographic deviation based calculations. In using these calculations to determine motion, arbitrary interframe permutations may be used, post-calculated, non-linear results for projection visualization may be averaged, poor matches may be eliminated on an A-line by A-line basis, windowing functions may be used to improve results, partial spectrums may be used when capturing data, and a minimum intensity threshold may be used for determining which pixels to use.

Abstract: Methods and systems for angiographic imaging with optical coherence tomography (OCT) are described using ratio-based and angiographic deviation based calculations. In using these calculations to determine motion, arbitrary interframe permutations may be used, post-calculated, non-linear results for projection visualization may be averaged, poor matches may be eliminated on an A-line by A-line basis, windowing functions may be used to improve results, partial spectrums may be used when capturing data, and a minimum intensity threshold may be used for determining which pixels to use.

Abstract: Geographic atrophy of the eye can be detected and measured by imaging the eye at a depth greater than the retinal pigment epithelium (RPE) at a plurality of locations of the eye, for example, using optical coherence tomography (OCT); determining a ratio of the intensities of imaging signals of a retinal layer(s) with respect to the intensity of imaging signals of a sub-RPE layer(s) at each location; determining representative values based at least in part on the determined ratios; generating a map of the representative values; and identifying diseased areas from the map. Contours and binary maps may be generated based on the identified diseased areas. The size and shape of the identified areas may be analyzed and monitored over a period of time.

Abstract: Optical coherence tomography (OCT) scan data of a subject is acquired over a region of interest which can include an optic disc or a macula of a retina. Layer boundaries of retinal layers are identified in the OCT scan data to facilitate measurements. In one aspect, a measurement related to ratio value between a total backscattered signal intensity of one or more target layers of the retina and a total backscattered signal intensity of one or more reference layers is computed on a location-by-location basis within a region of interest of the OCT scan data. Measurements can be collected, aggregated, analyzed, and displayed in connection with other information taken or derived from the OCT scan data.

Abstract: Geographic atrophy of the eye can be detected and measured by imaging the eye at a depth greater than the retinal pigment epithelium (RPE) at a plurality of locations of the eye, for example, using optical coherence tomography (OCT); determining a ratio of the intensities of imaging signals of a retinal layer(s) with respect to the intensity of imaging signals of a sub-RPE layer(s) at each location; determining representative values based at least in part on the determined ratios; generating a map of the representative values; and identifying diseased areas from the map. Contours and binary maps may be generated based on the identified diseased areas. The size and shape of the identified areas may be analyzed and monitored over a period of time.

Abstract: Geographic atrophy of the eye can be detected and measured by imaging the eye at a depth greater than the retinal pigment epithelium (RPE) at a plurality of locations of the eye, for example, using optical coherence tomography (OCT); determining a ratio of the intensities of imaging signals of a retinal layer(s) with respect to the intensity of imaging signals of a sub-RPE layer(s) at each location; determining representative values based at least in part on the determined ratios; generating a map of the representative values; and identifying diseased areas from the map. Contours and binary maps may be generated based on the identified diseased areas. The size and shape of the identified areas may be analyzed and monitored over a period of time.

Abstract: Optical coherence tomography (OCT) scan data of a subject is acquired over a region of interest which can include an optic disc or a macula of a retina. Layer boundaries of retinal layers are identified in the OCT scan data to facilitate measurements. In one aspect, a measurement related to ratio value between a total backscattered signal intensity of one or more target layers of the retina and a total backscattered signal intensity of one or more reference layers is computed on a location-by-location basis within a region of interest of the OCT scan data. Measurements can be collected, aggregated, analyzed, and displayed in connection with other information taken or derived from the OCT scan data.

Abstract: Methods and systems for angiographic imaging with optical coherence tomography (OCT) are described using ratio-based and angiographic deviation based calculations. In using these calculations to determine motion, arbitrary interframe permutations may be used, post-calculated, non-linear results for projection visualization may be averaged, poor matches may be eliminated on an A-line by A-line basis, windowing functions may be used to improve results, partial spectrums may be used when capturing data, and a minimum intensity threshold may be used for determining which pixels to use.

Abstract: Geographic atrophy of the eye can be detected and measured by imaging the eye at a depth greater than the retinal pigment epithelium (RPE) at a plurality of locations of the eye, for example, using optical coherence tomography (OCT); determining a ratio of the intensities of imaging signals of a retinal layer(s) with respect to the intensity of imaging signals of a sub-RPE layer(s) at each location; determining representative values based at least in part on the determined ratios; generating a map of the representative values; and identifying diseased areas from the map. Contours and binary maps may be generated based on the identified diseased areas. The size and shape of the identified areas may be analyzed and monitored over a period of time to phenotype subjects and classify diseases.

Abstract: Optical coherence tomography (OCT) scan data of a subject is acquired over a region of interest which can include an optic disc or a macula of a retina. Layer boundaries of retinal layers are identified in the OCT scan data to facilitate measurements. In one aspect, a measurement related to ratio value between a total backscattered signal intensity of one or more target layers of the retina and a total backscattered signal intensity of one or more reference layers is computed on a location-by-location basis within a region of interest of the OCT scan data. Measurements can be collected, aggregated, analyzed, and displayed in connection with other information taken or derived from the OCT scan data.