Abstract: There is provided a method of processing image data defining a fundus image of a retina to include supplementary information on a designated feature in the fundus image, comprising: designating (S10) a feature in the fundus image; receiving (S20) OCT data of a C-scan of the retina; selecting (S30) a subset of the OCT data representing a volumetric image of a part of the retina at a location on the retina corresponding to a location of the designated feature in the fundus image; processing (S40) the selected subset to generate, as the supplementary information, supplementary image data indicative of a variation, along a depth direction of the retina, of a measured reflectance of the eye in the selected subset; and combining (S50) the image data with the supplementary image data, such that an image defined by the combined data provides an indication of the variation at the designated feature.

Abstract: An apparatus for rendering optical coherence tomography, OCT, retinal image data, acquired by an OCT scanner scanning a retina of an eye over a range of scan locations, wherein each scan location is associated with a respective coordinate in a first coordinate system, and each pixel of the rendered OCT retinal image data is associated with a respective coordinate in a second coordinate system different from the first coordinate system. The apparatus comprises a communication module arranged to receive the OCT retinal image data, and a coordinate-determining module arranged to determine values of coordinates in the second coordinate system of pixels in the received OCT retinal image using a transformation from coordinates in the first to second coordinate system. The apparatus further comprises an interpolation module arranged to interpolate between values of pixels at the determined values to calculate values of the pixels of the rendered OCT retinal image data.

Abstract: A computer-implemented method, system, and computer-readable medium, for determining a level of hypertension of a person. The method has steps of: acquiring image data defining a retinal image of a retina of the person that has been captured by a retinal imaging system; processing the image data to identify a plurality of vessel segments present in the retinal image; determining respective widths of vessel segments of at least a subset of the plurality of vessel segments present in the retinal image; and calculating, as a vascular summary metric, at least one average value or median value of the determined widths of the vessel segments present in the retinal image, to determine a level of hypertension by which the person has been affected.

Abstract: A computer-implemented method, system, and computer-readable medium, for determining a pathologic condition from a medical image of a portion of a subject. The method includes acquiring a plurality of lesion locations in the medical image; applying a clustering algorithm to the plurality of lesion locations to identify at least one lesion cluster and corresponding lesion cluster data; categorizing each lesion cluster into one of a set of predetermined categories based on the identified lesion cluster data; applying at least one function to the lesion cluster data with regard to each category of the set of predetermined categories, wherein the at least one function provides a fixed number of data outputs; and determining a pathologic condition by processing the fixed number of data outputs of each category of the set based on a classification algorithm trained on image data defining medical images of the portion of a plurality of subjects.

Abstract: An apparatus for rendering optical coherence tomography, OCT, retinal image data, acquired by an OCT scanner scanning a retina of an eye over a range of scan locations, wherein each scan location is associated with a respective coordinate in a first coordinate system, and each pixel of the rendered OCT retinal image data is associated with a respective coordinate in a second coordinate system different from the first coordinate system. The apparatus comprises a communication module arranged to receive the OCT retinal image data, and a coordinate-determining module arranged to determine values of coordinates in the second coordinate system of pixels in the received OCT retinal image using a transformation from coordinates in the first to second coordinate system. The apparatus further comprises an interpolation module arranged to interpolate between values of pixels at the determined values to calculate values of the pixels of the rendered OCT retinal image data.

Abstract: The disclosure relates to a non-transitory computer-readable storage medium storing computer program instructions which, when executed by a processor, cause the processor to process image data defining an image of a retina to determine a location of an anatomical feature of the retina in the image by receiving the image data; calculating, for each of a plurality of pixels of the image data, a respective local orientation vector indicative of the orientation of any blood vessel present in the image; calculating a normalized local orientation vector for each of the plurality of pixels; operating on an array of accumulators, wherein each accumulator in the array is associated with a respective pixel of the image data; and determining the location of the anatomical feature in the image of the retina using the location of a pixel of the image data which is associated with an accumulator having accumulated an accumulated value.

Abstract: The present disclosure relates to a computer-readable storage medium storing instructions that can cause a processor to process image data defining an image of a vascular structure of temporal vascular arcades of a retina to estimate a location of the fovea of the retina in the image by transforming received image data such that the vascular structure in the image defined by the transformed image data is more circular than the vascular structure defined by the image data; calculating, for each of a plurality of pixels of the transformed image data, a respective local orientation vector indicative of the orientation of any blood vessel present in the image; calculating a normalized local orientation vector for each of the pixels; operating on an array of accumulators; and estimating the location of the fovea in the image of the retina using the location of a pixel of the transformed image data.

Abstract: The present disclosure relates to a computer-readable storage medium storing instructions that can cause a processor to process image data defining an image of a vascular structure of temporal vascular arcades of a retina to estimate a location of the fovea of the retina in the image by transforming received image data such that the vascular structure in the image defined by the transformed image data is more circular than the vascular structure defined by the image data; calculating, for each of a plurality of pixels of the transformed image data, a respective local orientation vector indicative of the orientation of any blood vessel present in the image; calculating a normalised local orientation vector for each of the pixels; operating on an array of accumulators; and estimating the location of the fovea in the image of the retina using the location of a pixel of the transformed image data.

Abstract: The disclosure relates to a non-transitory computer-readable storage medium storing computer program instructions which, when executed by a processor, cause the processor to process image data defining an image of a retina to determine a location of an anatomical feature of the retina in the image by receiving the image data; calculating, for each of a plurality of pixels of the image data, a respective local orientation vector indicative of the orientation of any blood vessel present in the image; calculating a normalised local orientation vector for each of the plurality of pixels; operating on an array of accumulators, wherein each accumulator in the array is associated with a respective pixel of the image data; and determining the location of the anatomical feature in the image of the retina using the location of a pixel of the image data which is associated with an accumulator having accumulated an accumulated value.

Abstract: A method of generating output data providing an indication of the presence or absence of disease from at least one retinal image of a patient. The method comprises receiving first data associated with detection of a first lesion type in the at least one image, receiving second data associated with detection of a second lesion type in the at least one image, and receiving third data associated with detection of a third lesion type in the at least one image, wherein at least one of said first data, said second data and said third data is a quantitative indication associated with detection of the respective lesion type in said image. The first data, second data and third data are combined to generate the output data providing an indication of the presence or absence of disease.

Abstract: Systems and methods of processing a retinal input image to identify an area representing a predetermined feature. One method comprises processing said retinal input image to generate a plurality of images, each of said plurality of images having been scaled by a respective associated scaling factor, and each of said plurality of images having been subjected to a morphological closing operation with a two-dimensional structuring element arranged to affect the image substantially equally in at least two perpendicular directions. The plurality of images are processed to identify said area representing said predetermined feature.

Abstract: Systems and methods of processing a retinal input image to identify an area representing a predetermined feature. One method comprises processing said retinal input image to generate a plurality of images, each of said plurality of images having been scaled by a respective associated scaling factor, and each of said plurality of images having been subjected to a morphological closing operation with a two-dimensional structuring element arranged to affect the image substantially equally in at least two perpendicular directions. The plurality of images are processed to identify said area representing said predetermined feature.