A system for obtaining biomechanical parameters of ocular tissue includes an air-puff module to deliver an air-puff stimulus onto the ocular tissue, and an imaging device operatively coupled to the air-puff module.

The air-puff module includes a transparent window at its front with a transparent through hole for delivering the air-puff stimulus. The hole is aligned with an imaging device optical axis, such that the air-puff stimulus delivered onto the ocular tissue can be centred on an apex of the ocular tissue and made collinear with the optical axis. The transparent window and through hole allow continuity of imaging of the ocular surface.

The imaging device captures the 3D coordinates of points distributed on an ocular tissue surface in groups of simultaneous points.

The system includes a component for selecting and changing location and distribution of captured points on the ocular tissue, and a processing component to process the points.

A system for obtaining biomechanical parameters of ocular tissue includes an air-puff module to deliver an air-puff stimulus onto the ocular tissue, and an imaging device operatively coupled to the air-puff module.

The air-puff module includes a transparent window at its front with a transparent through hole for delivering the air-puff stimulus. The hole is aligned with an imaging device optical axis, such that the air-puff stimulus delivered onto the ocular tissue can be centred on an apex of the ocular tissue and made collinear with the optical axis. The transparent window and through hole allow continuity of imaging of the ocular surface.

The imaging device captures the 3D coordinates of points distributed on an ocular tissue surface in groups of simultaneous points.

The system includes a component for selecting and changing location and distribution of captured points on the ocular tissue, and a processing component to process the points.

Peripheral retinal OCT can be used to generate peripheral retinal OCT images allowing for the peripheral retina to be viewed. A peripheral retinal vision system can determine that a set of fiducial markers is in a field-of-view of at least one camera and record positional data comprising a contact lens position and angle with respect to an OCT imaging system having OCT scanning mirrors in a first position. The system can determine whether a retinal layer is in an OCT scan captured while the set of fiducial markers is in the field-of-view of the at least one camera and the OCT scanning minors are in the first position; and for an OCT scan having he retinal layer and being captured while the set of fiducial markers is in the field-of-view of the at least one camera and the OCT scanning minors are in the first position, store that OCT scan.

An ophthalmic information processing apparatus includes a specifying unit and an image deforming unit. The specifying unit is configured to specify a three-dimensional position of each pixel in a two-dimensional front image depicting a predetermined site of a subject's eye, based on OCT data obtained by performing optical coherence tomography on the predetermined site. The image deforming unit is configured to deform the two-dimensional front image, by changing position of at least one pixel in the two-dimensional front image based on the three-dimensional position, to generate a three-dimensional front image.

Deep learning methods and systems for detecting biomarkers within optical coherence tomography volumes using such deep learning methods and systems are provided. Embodiments predict the presence or absence of clinically useful biomarkers in OCT images using deep neural networks. The lack of available training data for canonical deep learning approaches is overcome in embodiments by leveraging a large external dataset consisting of foveal scans using transfer learning. Embodiments represent the three-dimensional OCT volume by “tiling” each slice into a single two dimensional image, and adding an additional component to encourage the network to consider local spatial structure. Methods and systems, according to embodiments are able to identify the presence or absence of AMD-related biomarkers on par with clinicians. Beyond identifying biomarkers, additional models could be trained, according to embodiments, to predict the progression of these biomarkers over time.

Aspects of the present disclosure provide techniques for quantitatively assessing tear-film dynamics associated with contact lenses. An example method includes projecting an image of one or more shapes on a tear film surface of the contact lens worn on the eye, capturing video data, comprising a plurality of image frames, of the one or more shapes projected on the tear film surface of the contact lens over a period of time, performing image segmentation on a plurality of reflection patterns included in the plurality of image frames, generating a plurality of maps of the tear film surface of the contact lens indicating changes to the tear film surface of the contact lens during the period of time, and outputting, based on the plurality of maps, one or more metrics quantifying the changes to the tear film surface of the contact lens over the period of time.

Improved optical coherence tomography systems and methods to measure thickness of the retina are presented. The systems may be compact, handheld, provide in-home monitoring, allow the patient to measure himself or herself, and be robust enough to be dropped while still measuring the retina reliably.

Methods and devices determine an eye strain indicator. In one aspect, an augmented reality (AR) device wearable by a user includes an image sensor and a processor coupled to the image sensor. The processor receives image data from the image sensor, determine that a display is within a field of view (FOV) of the AR device, determine an eye strain indicator based on the determination that the display is within the FOV of the AR device, and provide the eye strain indicator to the user.

Methods and devices determine an eye strain indicator. In one aspect, an augmented reality (AR) device wearable by a user includes an image sensor and a processor coupled to the image sensor. The processor receives image data from the image sensor, determine that a display is within a field of view (FOV) of the AR device, determine an eye strain indicator based on the determination that the display is within the FOV of the AR device, and provide the eye strain indicator to the user.

Systems and methods are provided for measuring the mechanical properties of ocular tissue, such as the lens or corneal tissue, for diagnosis as well as treatment monitoring purposes. A laser locking feedback system is provided to achieve frequency accuracy and sensitivity that facilitates operations and diagnosis with great sensitivity and accuracy. Differential comparisons between eye tissue regions of a patient, either on the same eye or a fellow eye, can further facilitate early diagnosis and monitoring.