Abstract: Methods and devices for detecting refraction parameter involve an initial pattern displayed on a screen of a first detection unit of a handheld portable autorefractive device for a user to view through a viewing unit. In response to the initial pattern displayed on the screen, the refractive parameter and visual acuity of the eye of the user are detected based on feedback provided by the user or may be detected automatically by the autorefractive device. The refractive parameter value and vision acuity value detected are displayed on a display screen of the autorefractive device.

Abstract: The present subject matter provides systems and methods for distributed training of artificial intelligence (AI) systems for medical image analysis. The systems allow for offline prediction of abnormalities of medical images on a local AI system associated with an imaging device (102). In one example, the local AI system (100) extracts image parameters from the analyzed medical images and sends it to a global AI system (120) for training a global AI model. In another example, the local AI system (100) retrains a previously trained local AI model based on the image parameters to obtain a local AI model. Model parameters are extracted from the local AI model and are sent to the global AI system to retrain a global AI model. The retrained global AI model is deployed back to the local AI system (100) for updating the local AI model.

Abstract: An ophthalmic imaging device (300) includes a fundus module (210) and a slit lamp 5 module (220) movably coupled to each other. The fundus module (210) includes an illumination module (230) and an imaging module (240). The illumination module (230) is adapted to yield a first partially blocked beam. The imaging module (240) includes a mirror (324) with a hole and an objective lens (326) to produce a reflected first partially blocked beam and a second partially blocked beam, to form a cornea 10 illuminating doughnut (502) and pupil illuminating doughnut (504), respectively, on an anterior region of the eye and form an image of the posterior\\region of the eye on an image plane (346). The slit lamp module (220) is adapted to view and capture the image of anterior and posterior regions of the eye.

Abstract: The present subject matter relates to a 3-dimensional (3D) imaging device (100) for imaging various structures of eye. The 3D imaging device (100) comprises a 3D viewing unit (102) detachably coupled to an eye imaging unit (104). An imaging module (103) may be placed in between the 3D viewing unit (102) and the eye imaging unit (104) for capturing images or videos of eye The eye imaging unit 104 comprises an imaging lens (106), an illumination module (108), a machine learning module (110), a control module (112), a processor (114), and a memory (116). The components of the eye imaging unit (104) are arranged in such a way that they are used for both slit lamp imaging and ophthalmic imaging of the eye.

Abstract: The present subject matter relates to an ophthalmologic imaging apparatus, which can capture reflex-free retinal images of a subject's eye. The imaging apparatus comprises light sources arranged on an illumination axis. A first shield placed at a distance from a first condenser lens, which is placed in front of a photographic light source on the illumination axis. The first shield has a central opaque portion on which an observation light source is mounted, and an outer pair of coaxial annular transparent regions. A diffuser is placed in front of the observation light source. A second shield has a central opening portion and mounted on the diffuser. The imaging apparatus further comprises a porosity mirror mounted on a porosity tube.

Abstract: The present subject matter provides systems and methods for distributed training of artificial intelligence (AI) systems for medical image analysis. The systems allow for offline prediction of abnormalities of medical images on a local AI system associated with an imaging device (102). In one example, the local AI system (100) extracts image parameters from the analyzed medical images and sends it to a global AI system (120) for training a global AI model. In another example, the local AI system (100) retrains a previously trained local AI model based on the image parameters to obtain a local AI model. Model parameters are extracted from the local AI model and are sent to the global AI system to retrain a global AI model. The retrained global AI model is deployed back to the local AI system (100) for updating the local AI model.

Abstract: An ophthalmic imaging device (300) includes a fundus module (210) and a slit lamp 5 module (220) movably coupled to each other. The fundus module (210) includes an illumination module (230) and an imaging module (240). The illumination module (230) is adapted to yield a first partially blocked beam. The imaging module (240) includes a mirror (324) with a hole and an objective lens (326) to produce a reflected first partially blocked beam and a second partially blocked beam, to form a cornea 10 illuminating doughnut (502) and pupil illuminating doughnut (504), respectively, on an anterior region of the eye and form an image of the posterior\\region of the eye on an image plane (346). The slit lamp module (220) is adapted to view and capture the image of anterior and posterior regions of the eye.

Abstract: The present subject matter relates to an ophthalmologic imaging apparatus, which can capture reflex-free retinal images of a subject's eye. The imaging apparatus comprises light sources arranged on an illumination axis. A first shield placed at a distance from a first condenser lens, which is placed in front of a photographic light source on the illumination axis. The first shield has a central opaque portion on which an observation light source is mounted, and an outer pair of coaxial annular transparent regions. A diffuser is placed in front of the observation light source. A second shield has a central opening portion and mounted on the diffuser. The imaging apparatus further comprises a porosity mirror mounted on a porosity tube.