Abstract: The present invention is directed to systems and methods for generating virtually averaged optical coherence tomography (Oct.) images. An illustrative method can include receiving an image, identifying a first voxel of the image, and selecting a plurality of local voxels of the image. Each of the plurality of local voxels is within a defined region of the first voxel. The values of the plurality of local voxels can indicate an appearance of the local voxels in the image.

Abstract: A method for determining a disease state transition path includes receiving a patient data having functional data and/or structural data related to a patient. Based on the patient data, a first disease state of a plurality of non-overlapping disease states each associated with a predetermined range of functional and/or structural degeneration values may be identified. A second, non-adjacent disease state of the plurality of disease states may be identified based on the patient data. A most probable path between the first disease state and the second disease state may be determined using a two dimensional continuous-time hidden Markov model.

Abstract: The present invention is directed to systems and methods for generating virtually averaged optical coherence tomography (OCT) images. An illustrative method can include receiving an image, identifying a first voxel of the image, and selecting a plurality of local voxels of the image. Each of the plurality of local voxels is within a defined region of the first voxel. The values of the plurality of local voxels can indicate an appearance of the local voxels in the image.

Abstract: The present disclosure is directed to systems and methods for normalizing an image of an eye among multiple optical coherence tomography (OCT) devices. The system can receive an OCT image and generate a normalized OCT image. The system is configured to normalize a sample density of the received image, normalize an amount of noise using a suitable noise reduction technique, normalize a distribution of signal amplitudes of the image, and then normalize a signal quality of the image. The resulting normalized image of the eye can then be used in the comparison among OCT images taken from multiple OCT devices.

Abstract: Advances in optical coherence tomography (OCT) have prompted a transition from time domain OCT, providing 2D OCT images, to spectral domain OCT, which has a 3D imaging capability. Yet conventional technology offers little toward the goal of inter-device compatibility between extant 2D OCT images and newer 3D OCT images for the same or comparable subjects, as in the context of ongoing monitoring the quantitative status of a patient's eyes. The inventive methodology is particularly useful to identify the scan location of tissue in a 2D OCT image within the 3D OCT volumetric data, thereby allowing clinicians to image a patient via 3D OCT, based on available 2D OCT images, with minimal inter-device variation.

Abstract: A method for determining a disease state transition path includes receiving a patient data having functional data and/or structural data related to a patient. Based on the patient data, a first disease state of a plurality of non-overlapping disease states each associated with a predetermined range of functional and/or structural degeneration values may be identified. A second, non-adjacent disease state of the plurality of disease states may be identified based on the patient data. A most probable path between the first disease state and the second disease state may be determined using a two dimensional continuous-time hidden Markov model.

Abstract: The present disclosure is directed to systems and methods for normalizing an image of an eye among multiple optical coherence tomography (OCT) devices. The system can receive an OCT image and generate a normalized OCT image. The system is configured to normalize a sample density of the received image, normalize an amount of noise using a suitable noise reduction technique, normalize a distribution of signal amplitudes of the image, and then normalize a signal quality of the image. The resulting normalized image of the eye can then be used in the comparison among OCT images taken from multiple OCT devices.

Abstract: A scan location matching (SLM) method identifies conventional time domain optical coherence tomography (TD-OCT) circle scan locations within three-dimensional spectral domain OCT scan volumes. A technique uses both the SLM algorithm and a mathematical retinal nerve fiber bundle distribution (RNFBD) model, which is a simplified version of the anatomical retinal axon bundle distribution pattern, to normalize TD-OCT thickness measurements for the retinal nerve fiber layer (RNFL) of an off-centered TD-OCT circle scan to a virtual location, centered on the optic nerve head. The RNFBD model eliminates scan-to-scan RNFL thickness measurement variation caused by manual placement of TD-OCT circle scan.

Abstract: Systems and methods of analyzing an optical coherence tomography image of a retina are discussed. A 2-dimensional slice of the image can be aligned to produce an approximately horizontal image of the retina and an edge map based at least in part on the aligned slice. Also, at least one global representation can be determined based on a (multi-scale) spatial division, such as multi-scale spatial pyramid, on the slice and/or edge map. Creating the local features is based on the specified cell structure of the global representation. The local features can be constructed based on local binary pattern (LBP)-based features. Additionally, a slice can be categorized into one or more categories via one or more classifiers (e.g., support vector machines). Each category can be associated with at least one ocular pathology, and classifying can be based on the constructed global descriptors, which can include the LBP-based local descriptors.

Abstract: A scan location matching (SLM) method identifies conventional time domain optical coherence tomography (TD-OCT) circle scan locations within three-dimensional spectral domain OCT scan volumes. A technique uses both the SLM algorithm and a mathematical retinal nerve fiber bundle distribution (RNFBD) model, which is a simplified version of the anatomical retinal axon bundle distribution pattern, to normalize TD-OCT thickness measurements for the retinal nerve fiber layer (RNFL) of an off-centered TD-OCT circle scan to a virtual location, centered on the optic nerve head. The RNFBD model eliminates scan-to-scan RNFL thickness measurement variation caused by manual placement of TD-OCT circle scan.

Abstract: Systems and methods of analyzing an optical coherence tomography image of a retina are discussed. A 2-dimensional slice of the image can be aligned to produce an approximately horizontal image of the retina and an edge map based at least in part on the aligned slice. Also, at least one global representation can be determined based on a (multi-scale) spatial division, such as multi-scale spatial pyramid, on the slice and/or edge map. Creating the local features is based on the specified cell structure of the global representation. The local features can be constructed based on local binary pattern (LBP)-based features. Additionally, a slice can be categorized into one or more categories via one or more classifiers (e.g., support vector machines). Each category can be associated with at least one ocular pathology, and classifying can be based on the constructed global descriptors, which can include the LBP-based local descriptors.

Abstract: A system. The system includes a computing device configured for communication with an imaging system and with a display device. The computing device includes a contour modeling module. The contour modeling module is configured for superimposing reference anchors on a cross-sectional image generated from 3D image data, for generating a line which connects the reference anchors, for sampling the 3D image data in a variable thickness plane defined by the connecting line, and for generating a contour-modeled C-mode image from the sampled 3D image data.

Abstract: A fully automated optic nerve head assessment system, based on spectral domain optical coherence tomography, provides essential disc parameters for clinical analysis, early detection, and monitoring of progression.

Abstract: Advances in optical coherence tomography (OCT) have prompted a transition from time domain OCT, providing 2D OCT images, to spectral domain OCT, which has a 3D imaging capability. Yet conventional technology offers little toward the goal of inter-device compatibility between extant 2D OCT images and newer 3D OCT images for the same or comparable subjects, as in the context of ongoing monitoring the quantitative status of a patient's eyes. The inventive methodology is particularly useful to identify the scan location of tissue in a 2D OCT image within the 3D volumetric data, thereby allowing clinicians to image a patient via 3D OCT, based on available 2D OCT images, with minimal inter-device variation.

Abstract: A fully automated optic nerve head assessment system, based on spectral domain optical coherence tomography, provides essential disc parameters for clinical analysis, early detection, and monitoring of progression.

Abstract: A system. The system includes a computing device configured for communication with an imaging system and with a display device. The computing device includes a contour modeling module. The contour modeling module is configured for superimposing reference anchors on a cross-sectional image generated from 3D image data, for generating a line which connects the reference anchors, for sampling the 3D image data in a variable thickness plane defined by the connecting line, and for generating a contour-modeled C-mode image from the sampled 3D image data.