A confocal scanning laser ophthalmoscope (cSLO) includes an illumination module, an acquisition module, a scanning element and an imaging lens group. With the scanning element at the nominal position and the illumination beam passing through the centers of the lenses, by controlling the deviation angle between the incident marginal rays and the reflected rays on each surface of the lenses in the illumination path to no less than 0.5 degree.

A method to image an in vivo object in an eye includes illuminating an object in the eye by a light source; configuring one or more detectors to receive light from a conjugate plane behind a confocal plane of the object, the conjugate plane acting as a light screen; receiving at the one or more detectors a backscattered light from the light source which has been refracted at least in part by the object before being backscattered from the light screen to provide a detector data; and processing the detector data over a time period by a computer to generate information about the object.

An example method for automating a quality assessment of digital fundus image can include: obtaining a digital fundus image file; analyzing a first quality of the digital fundus image file using a model to estimate an optimal time to capture a fundus image; and analyzing a second quality of the digital fundus image file using the model to estimate a disease state.

The invention relates to small, conjugatable, orthogonal and tunable fluorophores for imaging of small bioactive molecules. The invention further relates to processes for the preparation of the compounds, and uses of the compounds in therapeutic, diagnostic, surgery and analytical applications. The invention provides a compound of formula (I), a derivative or a salt thereof. Wherein X is selected from the group consisting of NH, O, S, SeR5R6, CR7R8; R1 is selected from the group consisting of amines, alcohols, thiols, thiophenols, selenols, selenophenols and aryl groups; R2 and R3 are independently H or a halogen; R4 tis either H, nitro or cyano; R5 is either absent or methyl or oxygen; R6 is either absent or methyl or oxygen; and R7 and R8 are independently selected from the group consisting of linear or cyclic alkyl groups containing halogen, amino, cyano or carboxylic ester substituents, and alkyl aryl groups.

##STR00001##

An artificial intelligence (AI) system is disclosed that uses machine learning to classify retinal features contained in OCTA data acquired by a data acquisition system and to predict one or more retinopathies based on the classification of retinal features. The AI system comprise a processor configured to run a classifier model comprising a machine learning algorithm and a memory device that stores the classifier model, OCTA training data and acquired OCT A data. The machine learning algorithm performs a process that trains the classifier model to classify retinal features contained in OCT A training data. The trained machine learning algorithm uses the classifier model to process acquired OCT A data to classify retinal features contained in the acquired OCTA data and to predict, based on the classified retinal features, whether the acquired OCTA data is indicative of at least one of a plurality of retinopathies

This disclosure describes systems, devices, and techniques for training neural networks to identify avascular and signal reduction areas of Optical Coherence Tomography Angiography (OCTA) images and for using trained neural networks. By identifying signal reduction areas in OCTA images, the avascular areas can be detected with high accuracy, even when the OCTA images include artifacts and other types of noise. Accordingly, various implementations described herein can accurately identify avascular areas from real-world clinical OCTA images. In various implementations, a method can include identifying images of retinas. The images may include thickness images, reflectance intensity maps, and OCTA images of the retinas. Avascular maps corresponding to the OCTA images can be identified. A neural network can be trained based on the images and the avascular maps.

The invention relates to a device and a method for examining the retinal vascular endothelial function of the vessels of the retina at the fundus (F) of a patient's eye. Using a fundus camera, the vessels of the retina are stimulated with flicker light during a stimulation phase and sequences of images of areas of the fundus (F) are recorded, from which vascular parameters are derived which describe the retinal vascular endothelial function of the vessels. By imaging a macula stop (MB), which covers the macula, onto the fundus (F), the fundus (F) can be illuminated with a higher light intensity, which improves the stimulation effect and the image quality and/or reduces the strain on the patient.

Methods for automatically identifying retinal boundaries from a reflectance image are disclosed. An example of the method includes identifying a reflectance image of the retina of a subject; generating a gradient map of the reflectance image, the gradient map representing dark-to-light or light-to-dark reflectance differentials between adjacent pixel pairs in the reflectance image; generating a guidance point array corresponding to a retinal layer boundary depicted in the reflectance image using the gradient map; generating multiple candidate paths estimating the retinal layer boundary in the reflectance image by performing a guided bidirectional graph search on the reflectance image using the guidance point array; and identifying the retinal layer boundary by merging two or more of the multiple candidate paths.

Imaging various regions of the eye is important for both clinical diagnostic and treatment purposes as well as for scientific research. Diagnosis of a number of clinical conditions relies on imaging of the various tissues of the eye. The subject technology describes a method and apparatus for imaging of the back and/or front of the eye using multiple illumination modalities, which permits the collection of one or more of reflectance, spectroscopic, fluorescence, and laser speckle contrast images.

A method for imaging vertebrate translucent retinal structures includes: imaging a translucent retinal structure at a first imaging plane in the retina with a light source focused at such first imaging plane, and detecting reflected light with a non-confocal off-axis detector, wherein the detector is axially displaced from a plane conjugate to the first imaging plane to a plane conjugate to a reflective layer deeper in the retina along a path of illumination from the light source.