Machine learning technologies are used to identify and separating abnormal and normal subjects and identifying possible disease types with images (e.g., optical coherence tomography (OCT) images of the eye), where the machine learning technologies are trained with only normative data. In one example, a feature or a physiological structure of an image is extracted, and the image is classified based on the extracted feature. In another example, a region of the image is masked and then reconstructed, and a similarity is determined between the reconstructed region and the original region of the image. A label (indicating an abnormality) and a score (indicating a severity) can be determined based on the classification and/or the similarity.

A retinal imaging system is provided. The system comprises: a fundus camera having a focusing mechanism; an imaging module configured for imaging user's face and eyes and providing image date indicative of a relative orientation between an optical axis of the fundus camera and a line of sight of user's eye at user's eye target position; a position and alignment system configured and operable to utilize the image data indicative of said relative orientation for positioning the fundus camera at an operative position such that the optical axis substantially coincides with the line of sight of user's eye, to enable focusing the fundus camera on the retina; a sensing system comprising one or more sensors, configured and operable for monitoring a user's face position with respect to a predetermined registration position and generating corresponding sensing data; and a safety controller configured and operable to be responsive to the sensing data, and upon identifying that the user's face position with respect to the predetermined registration position

A retinal imaging system is provided. The system comprises: a fundus camera having a focusing mechanism; an imaging module configured for imaging user's face and eyes and providing image date indicative of a relative orientation between an optical axis of the fundus camera and a line of sight of user's eye at user's eye target position; a position and alignment system configured and operable to utilize the image data indicative of said relative orientation for positioning the fundus camera at an operative position such that the optical axis substantially coincides with the line of sight of user's eye, to enable focusing the fundus camera on the retina; a sensing system comprising one or more sensors, configured and operable for monitoring a user's face position with respect to a predetermined registration position and generating corresponding sensing data; and a safety controller configured and operable to be responsive to the sensing data, and upon identifying that the user's face position with respect to the predetermined registration position

Examples relate to a surgical microscope system, and to a system, a method and a computer program for a surgical microscope system. The system comprises one or more processors and one or more storage devices. The system is configured to obtain intraoperative sensor data of at least a portion of an eye from a Doppler-based imaging sensor of the surgical microscope system. The system is configured to process the intraoperative sensor data to determine information on a blood flow within the eye. The system is configured to generate a visualization of the blood flow. The system is configured to provide a display signal to a display device of the surgical microscope system based on the visualization of the blood flow within the eye.

Improved optical coherence tomography systems and methods to measure retinal data are presented. The systems may be compact, provide in-home monitoring, and have automation to allow the patient to measure himself or herself.

Improved optical coherence tomography systems and methods to measure retinal data are presented. The systems may be compact, provide in-home monitoring, and have automation to allow the patient to measure himself or herself.

The present disclosure provides systems and methods for diagnosing disease. In some aspects, an imaging system is provided that includes a light source configured to illuminate a retina of the eye with light, one or more imaging devices configured to receive light returned from the retina to generate one or more spatial-spectral images of the retina, and a computing device configured to receive the one or more spatial-spectral images of the retina, evaluate the one or more spatial-spectral images, and identify one or more biomarkers indicative of a neurogenerative pathology.

The present disclosure provides systems and methods for diagnosing disease. In some aspects, an imaging system is provided that includes a light source configured to illuminate a retina of the eye with light, one or more imaging devices configured to receive light returned from the retina to generate one or more spatial-spectral images of the retina, and a computing device configured to receive the one or more spatial-spectral images of the retina, evaluate the one or more spatial-spectral images, and identify one or more biomarkers indicative of a neurogenerative pathology.

An ophthalmic apparatus includes an illumination optical system that generates slit-shaped illumination light using a first light source; an optical scanner that deflects the illumination light to a fundus of a subject's eye; an imaging optical system that captures light from the fundus using a rolling shutter method; an acquisition unit that acquires a fundus image of the subject's eye using light from a second light source; a flare determination unit that determines whether or not flare occurs by analyzing the fundus image; a controller that performs flare optimization control by controlling at least one of the first light source, the illumination optical system, the optical scanner, the imaging optical system, and the image sensor based on a first determination result obtained by the flare determination unit; and an image forming unit that forms an image of the fundus when the flare does not occur.

An ophthalmic apparatus includes an illumination optical system that generates slit-shaped illumination light using a first light source; an optical scanner that deflects the illumination light to a fundus of a subject's eye; an imaging optical system that captures light from the fundus using a rolling shutter method; an acquisition unit that acquires a fundus image of the subject's eye using light from a second light source; a flare determination unit that determines whether or not flare occurs by analyzing the fundus image; a controller that performs flare optimization control by controlling at least one of the first light source, the illumination optical system, the optical scanner, the imaging optical system, and the image sensor based on a first determination result obtained by the flare determination unit; and an image forming unit that forms an image of the fundus when the flare does not occur.