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: A system for polarization-sensitive optical coherence tomography (PS-OCT) of a sample comprises an interferometric arrangement comprising a reference arm and a sample arm, the sample arm being arranged to emit optical radiation towards the sample; a phase modulation system arranged at an input to the sample arm; and a detector arranged to detect a signal generated by interference between a reference beam from the reference arm and a sample beam from the sample arm. The phase modulation system comprises: an electro-optic modulator; a polarizer arranged at a rotation angle relative to the fast axis of the electro-optic modulator; and a signal generator for delivering a driving voltage to the electro-optic modulator; wherein the rotation angle and the driving voltage are selected such that the phase modulation system generates three mutually orthogonal polarization states.

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 invention relates to a method to treat certain ocular complications, comprising the administration of an effective amount of a FAD to a patient in need of such treatment.

Abstract: The present invention relates to a method to treat certain ocular complications, comprising the administration of an effective amount of a FAD to a patient in need of such treatment.