Abstract: A probe for iridocorneal angle imaging of an eye, the probe comprising: a distal end having a corneal contact surface; a camera having an imaging lens at the distal end and an imaging axis orthogonal to the corneal contact surface; and at least two illumination sources, each illumination source having an illumination axis at an angle to the corneal contact surface such that the imaging axis and the illumination axes converge in the eye.

Abstract: According to various embodiments, there is provided an imaging device including a Bessel beam generator configured to provide a Bessel beam; a scanning mirror configured to scan the Bessel beam across a two-dimensional plane; a scan lens configured to receive the Bessel beam from the scanning mirror, a centre of the scan lens being at least substantially a focal length of the scan lens away from the scanning mirror; an illumination tube lens configured to receive the Bessel beam from the scan lens, a centre of the illumination tube lens being at least substantially a sum of the focal length of the scan lens and a focal length of the illumination tube lens away from the centre of the scan lens; an illumination objective lens positioned in direct line-of-sight to a specimen, the illumination objective lens configured to receive the Bessel beam from the illumination tube lens and further configured to illuminate the specimen with the Bessel beam, wherein a centre of the illumination objective lens is at least su

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 probe for iridocorneal angle imaging of an eye, the probe comprising: a distal end having a corneal contact surface; a camera having an imaging lens at the distal end and an imaging axis orthogonal to the corneal contact surface; and at least two illumination sources, each illumination source having an illumination axis at an angle to the corneal contact surface such that the imaging axis and the illumination axes converge in the eye.

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 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 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 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 proposed for analysing 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: An optical coherence tomography (OCT) image of the anterior chamber of an eye is processed to determine automatically a location in the image corresponding to Schwalbe's line. First, the method finds the location of the corneal endothelium. Then the method fits a model to the detected corneal endothelium. Then the method determines the location of Schwalbe's line based on the relationship between the detected corneal endothelium and the fitted model, such as where the detected corneal endothelium diverges most from the fitted model. The Schwalbe's line is used to obtain a numerical measure of the anterior chamber angle of the eye. The method can be used in a process for screening patients for glaucoma. In the case of patients found to be suffering from glaucoma, treatment can be performed.

Abstract: An optical coherence tomography (OCT) image of the anterior chamber of an eye is processed to determine automatically a location in the image corresponding to Schwalbe's line. First, the method finds the location of the corneal endothelium. Then the method fits a model to the detected corneal endothelium. Then the method determines the location of Schwalbe's line based on the relationship between the detected corneal endothelium and the fitted model, such as where the detected corneal endothelium diverges most from the fitted model. The Schwalbe's line is used to obtain a numerical measure of the anterior chamber angle of the eye. The method can be used in a process for screening patients for glaucoma. In the case of patients found to be suffering from glaucoma, treatment can be performed.

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 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.