A body-mounted laser-indirect ophthalmoscope (LIO) system for delivering laser energy into an eye of a patient includes a wearable assembly which secures a control module, laser module, and/or power module (including a battery) to the body of the user. The control module receives activation signals and parameter information from an activation unit a mobile computing device and controls the laser energy emitted by the laser module based on the parameter information. The parameter information is user-provided via a graphical user interface or by voice control (e.g. recognizing voice commands in audio data captured by the mobile computing device). In the preferred embodiment, the wearable assembly includes only a headset, in which case the control, power and laser modules are provided on the headset; however, an alternative embodiment includes a utility belt from which a fiber optic cable for emitting the laser energy is routed to the headset.

An apparatus for producing a fundus image includes: a processor and a memory; an illumination component including a light source and operatively coupled to the processor; a camera including a lens and operatively coupled to the processor, wherein the memory stores instructions that, when executed by the processor, cause the apparatus to capture fundus images and provide controls for re-imaging the fundus.

An ophthalmic device for observing a subject eye, including: a light source; a scanning section that scans light from the light source; and an objective optical system configured to form a pupil, which has a conjugate relationship with a pupil of the subject eye, at the scanning section, wherein the objective optical system has, in order from the scanning section toward the subject eye, a first lens group that is positive, a second lens group that is positive, and a third lens group that is disposed between the first lens group and the second lens group, and that includes a concave surface configured to diverge light.

A retinal diagnostics instrument can include an imaging device configured to capture image data of an eye of a patient and an electronic processing circuitry configured to execute a communication control method. The communication control method can include providing input data to and receiving output data from a plurality of modules configured to facilitate diagnosing a retina of the eye of the patient using the image data. The communication control method can further includes causing independent processing of input data by any first module of the plurality of modules and any second module of the plurality of modules, any second module being different than any first module, where processing of input data by any first module does not depend on directly providing data to or receiving data from any second module and vice versa.

Systems and methods are disclosed for facilitating the evaluation of eye health and vision. The system is a mobile system and comprises at least one diagnostic device for performing a vision diagnostic test, the device being a VR headset; a portable computer communicatively coupled to the at least one diagnostic device, the computer having hardware adapted to guide a patient through the test, to compile test data, and to transmit the test data via a data connection; and a server in communication with the computer via the data connection, the server gathering the test data and presenting test data to a physician so that treatment may be provided to the patient. The at least one diagnostic device may include multiple portable, handheld diagnostic devices.

A mobile communication device-based corneal topography system includes an illumination system, an imaging system, a topography processor, an image sensor, and a mobile communication device. The illumination system is configured to generate an illumination pattern reflected off a cornea of a subject. The imaging system is coupled to an image sensor to capture an image of the reflected illumination pattern. A topography processor is coupled to the image sensor to process the image of the reflected illumination pattern. The mobile communications device includes a display, the mobile communications device is operatively coupled to the image sensor. The mobile communications device includes a mobile communications device (MCD) processor. A housing at least partially encloses one or more of the illumination system, the imaging system, or the topography processor.

System and Method pertaining to the modification and integration of an existing consumer digital camera, for example, with an optical imaging module to enable point and shoot fundus photography of the eye. The auto-focus macro capability of existing consumer cameras is adapted to photograph the retina over an extended diopter range, eliminating the need for manual diopter focus adjustment. The thru-the-lens (TTL) auto-exposure flash capability of existing consumer cameras is adapted to photograph the retina with automatic flash exposure eliminating the need for manual flash adjustment. The consumer camera imaging sensor and flash are modified to allow the camera sensor to perform both non-mydriatic focusing of the retina using infrared illumination and standard color flash photography of the retina without the need for additional imaging sensors or mechanical filters. These modifications and integration of existing consumer cameras for fundus photography of the eye significantly improve ease of manufacture and usability.

Some embodiments of the disclosure provide a diabetic retinopathy recognition system (S) based on fundus image. According to an embodiment, the system includes an image acquisition apparatus (1) configured to collect fundus images. The fundus images include target fundus images and reference fundus images taken from a person. The system further includes an automatic recognition apparatus (2) configured to process the fundus images from the image acquisition apparatus by using a deep learning method. The automatic recognition apparatus automatically determines whether a fundus image has a lesion and outputs the diagnostic result. According to another embodiment, the diabetic retinopathy recognition system (S) utilizes a deep learning method to automatically determine the fundus images and output the diagnostic result.

Principles of the present disclosure are directed to novel methods and devices for focal or global optical stimulation of retina and detecting activity of the retina by collecting and processing the back-scattered optical signal from the retina (Optical RetinoGram). Specifically, the invention provides device and method for quantitatively determining the layer specific activity of retina from the acquired intrinsic back reflected signal by monitoring phase/intensity fluctuations and thereafter employing multifractality algorithm on optical signal for obtaining various multifractal parameters such as width of singularity spectrum, Hurst exponent, fractal dimension, locally connected fractal mapping as well as artificial intelligence based classification for the use of diagnosis of retinal degenerative/ocular disease(s) and asses the progression of diseases or recovery of function due to one or more treatment by therapeutic drugs, devices, protocols.