Abstract: The invention relates to a system of detecting vasculature in optical coherence tomography (OCT) image data of a tissue of a subject, the OCT image data comprising OCT scan data and OCT angiography (OCTA) scan data, the system comprises segmenting the OCT scan data to locate a layer of interest in the tissue; generating an en face vascular network map from the OCTA scan data; projecting one or more vascular regions from the en face vascular network map onto the layer of interest in a cross-sectional image of the OCT scan data to define one or more regions of interest (ROIs), wherein respective ROIs are defined by the intersection between the vascular regions and the layer of interest; and identifying vascular objects in the one or more ROIs. In the preferred embodiment, the tissue is retina, vessels are removed from the layer of interest and the retinal nerve fibre layer (RNFL) thickness is determined.

Abstract: Disclosed herein is a method of segmenting a volumetric image comprising a plurality of slices, the method comprising: inputting a target slice of the volumetric image to a deep neural network (DNN) having a multi-task learning architecture, the multi-task learning architecture comprising: a segmentation DNN that is configured to output a segmentation of the target slice; and a reconstruction DNN that is configured to: receive a plurality of adjacent slices to the target slice; and output a reconstruction of the target slice based on the plurality of adjacent slices; wherein the reconstruction DNN is further configured to share spatial information with the segmentation DNN, the spatial information being indicative of correlations between the adjacent slices and the target slice.

Abstract: The present disclosure generally relates to automated method and system for vision assessment of a subject. The method comprises: determining a set of test patterns for the subject based on a preliminary assessment of an eye of the subject; displaying the set of test patterns sequentially to the subject; collecting data on the subject's gaze in response to each test pattern displayed to the subject; and assessing vision functionality of the subject based on the collected gaze data.

Abstract: The present disclosure generally relates to an automated method and system for generating a three-dimensional (3D) representation of a skin structure of a subject. The method comprises: acquiring a plurality of two-dimensional (2D) cross-sectional images of the skin structure, specifically, using optical coherence tomography (OCT) technique; computing a cost for each 2D cross-sectional image based on a cost function, the cost function comprising an edge-based parameter and a non-edge-based parameter; constructing a 3D graph from the 2D cross-sectional images; and determining a minimum-cost closed set from the 3D graph based on the computed costs for the 2D cross-sectional images, wherein the 3D representation of the skin structure is generated from the minimum-cost closed set.

Abstract: An optical coherence tomography (OCT) image composed of a plurality of A-scans of a structure is analyzed by defining, for each A-scan, a set of neighboring A-scans surrounding the A-slices scan. Following an optional de-noising step, the neighboring A-scans are aligned in the imaging direction, then a matrix X is formed from the aligned A-scans, and matrix completion is performed to obtain a reduced speckle noise image.

Abstract: A method of assessing the quality of an retinal image (such as a fundus image) includes selecting at least one region of interest within a retinal image corresponding to a particular structure of the eye (e.g. the optic disc or the macula), and a quality score is calculated in respect of the, or each, region-of-interest. Each region of interest is typically one associated with pathology, as the optic disc and the macula are. Optionally, a quality score may be calculated also in respect of the eye as a whole (i.e. over the entire image, if the entire image corresponds to the retina).

Abstract: The present disclosure generally relates to automated method and system for vision assessment of a subject. The method comprises: determining a set of test patterns for the subject based on a preliminary assessment of an eye of the subject; displaying the set of test patterns sequentially to the subject; collecting data on the subject's gaze in response to each test pattern displayed to the subject; and assessing vision functionality of the subject based on the collected gaze data.

Abstract: The present disclosure generally relates to an automated method and system for generating a three-dimensional (3D) representation of a skin structure of a subject. The method comprises: acquiring a plurality of two-dimensional (2D) cross-sectional images of the skin structure, specifically, using optical coherence tomography (OCT) technique; computing a cost for each 2D cross-sectional image based on a cost function, the cost function comprising an edge-based parameter and a non-edge-based parameter; constructing a 3D graph from the 2D cross-sectional images; and determining a minimum-cost closed set from the 3D graph based on the computed costs for the 2D cross-sectional images, wherein the 3D representation of the skin structure is generated from the minimum-cost closed set.

Abstract: A method and system are proposed to obtain a reduced speckle noise image of a subject from optical coherence tomography (OCT) image data of the subject. The cross sectional images each comprise a plurality of scan lines obtained by measuring the time delay of light reflected, in a depth direction, from optical interfaces within the subject. The method comprises two aligning steps. First the cross sectional images are aligned, then image patches of the aligned cross sectional images are aligned to form a set of aligned patches. An image matrix is then formed from the aligned patches; and matrix completion is applied to the image matrix to obtain a reduced speckle noise image of the subject.

Abstract: A method of assessing the quality of an retinal image (such as a fundus image) includes selecting at least one region of interest within a retinal image corresponding to a particular structure of the eye (e.g. the optic disc or the macula), and a quality score is calculated in respect of the, or each, region-of-interest. Each region of interest is typically one associated with pathology, as the optic disc and the macula are. Optionally, a quality score may be calculated also in respect of the eye as a whole (i.e. over the entire image, if the entire image corresponds to the retina).

Abstract: The present invention relates to a system for displaying a video image to a user having a visual impairment. The system comprises a video camera, a data storage device, a processor and an image display device for displaying processed images in a display region. The processor is operative to perform at least one of the operations of (i) including in the display region, a marker at a location offset from a centre of the display region, whereby if the user, who suffers from blurred vision at the centre of the user's visual field, looks at the marker, the user sees the captured image in focus; or (ii) deforming a portion of the captured image by a correction matrix, whereby, upon displaying the processed images by the display device, the correction matrix corrects a deformation in a corresponding portion of the visual field of the user due to the visual impairment.

Abstract: A method and apparatus for aligning a two-dimensional eye image with a predefined axis by rotation at a rotation angle are disclosed, the method comprising deriving the rotation angle and a de-noised image, which minimises a cost function comprising (i) a complexity measure of the de-noised image and (ii) magnitude of a noise image obtained by rotating the first image by the rotation angle and subtracting the de-noised image.

Abstract: A numerical parameter indicative of the degree of match between two retina images is produced by comparing two graphs obtained from the respective images. Each graph is composed of edges and vertices. Each vertex is associated with a location the corresponding retina image, and with descriptor data describing a part of the corresponding retina image proximate the corresponding location.

Abstract: A method is proposed for automatically locating the optic disc or the optic cup in an image of the rear of an eye. A portion of the image containing the optic disc or optic cup is divided into sub-regions using a clustering algorithm. Biologically inspired features, and optionally other features, are obtained for each of the sub-regions. An adaptive model uses the features to generate data indicative of whether each sub-region is within or outside the optic disc or optic cup. The result is then smoothed, to form an estimate of the position of the optic disc or optic cup.

Abstract: A method is presented to obtain, from a retinal image, data characterizing the optic cup, such as data indicating the location and/or size of the optic cup in relation to the optic disc. A disc region of the retinal image of an eye, is expressed as a weighted sum of a plurality of pre-existing “reference” retinal images in a library, with the weights being chosen to minimize a cost function. The data characterizing the cup of the eye is obtained from cup data associated with the pre-existing disc images and the corresponding weights. The cost function includes (i) a construction error term indicating a difference between the disc region of the retinal image and a weighted sum of the reference retinal images, and (ii) a cost term, which may be generated using a weighted sum over the reference retinal images of a difference between the reference retinal images and the disc region of the retinal image.

Abstract: A method and system are proposed to obtain a reduced speckle noise image of a subject from optical coherence tomography (OCT) image data of the subject. The cross sectional images each comprise a plurality of scan lines obtained by measuring the time delay of light reflected, in a depth direction, from optical interfaces within the subject. The method comprises two aligning steps. First the cross sectional images are aligned, then image patches of the aligned cross sectional images are aligned to form a set of aligned patches. An image matrix is then formed from the aligned patches; and matrix completion is applied to the image matrix to obtain a reduced speckle noise image of the subject.

Abstract: A method is proposed for analyzing an optical coherence tomography (OCT) image of the anterior segment (AS) of a subject's eye. A region of interest is defined which is a region of the image containing the junction of the cornea and iris, and an estimated position the junction within the region of interest is derived. Using this a second region of the image is obtained, which is a part of the image containing the estimated position of the junction. Features of the second region are obtained, and those features are input to an adaptive model to generate data characterizing the junction.

Abstract: A non-stereo fundus image is used to obtain a plurality of glaucoma indicators. Additionally, genome data for the subject is used to obtain genetic marker data relating to one or more genes and/or SNPs associated with glaucoma. The glaucoma indicators and genetic marker data are input into an adaptive model operative to generate an output indicative of a risk of glaucoma in the subject. In combination, the genetic indicators and genome data are more informative about the risk of glaucoma than either of the two in isolation. The adaptive model may be a two-stage model, having a first stage in which individual genetic indicators are combined with respective portions of the genome data by first adaptive model modules to form respective first outputs, and a second stage in which the first outputs are combined by a second adaptive mode.

Abstract: A non-stereo fundus image is used to obtain a plurality of glaucoma indicators. Additionally, genome data for the subject is used to obtain genetic marker data relating to one or more genes and/or SNPs associated with glaucoma. The glaucoma indicators and genetic marker data are input into an adaptive model operative to generate an output indicative of a risk of glaucoma in the subject. In combination, the genetic indicators and genome data are more informative about the risk of glaucoma than either of the two in isolation. The adaptive model may be a two-stage model, having a first stage in which individual genetic indicators are combined with respective portions of the genome data by first adaptive model modules to form respective first outputs, and a second stage in which the first outputs are combined by a second adaptive mode.

Abstract: A method is presented to obtain, from a retinal image, data characterizing the optic cup, such as data indicating the location and/or size of the optic cup in relation to the optic disc. A disc region of the retinal image of an eye, is expressed as a weighted sum of a plurality of pre-existing “reference” retinal images in a library, with the weights being chosen to minimize a cost function. The data characterizing the cup of the eye is obtained from cup data associated with the pre-existing disc images and the corresponding weights. The cost function includes (i) a construction error term indicating a difference between the disc region of the retinal image and a weighted sum of the reference retinal images, and (ii) a cost term, which may be generated using a weighted sum over the reference retinal images of a difference between the reference retinal images and the disc region of the retinal image.