Alcon, Inc.

Novartis Ag

Alcon Pharmaceuticals Ltd.

Sensomotoric Instruments Gmbh

Martin Gründig

John Alfred Campin

Peter Zieger

George H Pettit

Horia Grecu

Mark Andrew Zielke

Daniil Nekrassov

Sascha Birkner

Tobias Jura Rapoport

Jessica Jurich

Oliver Kersting

Tillmann Wieland

Brant Gillen

Armin Haupt

Robert Moore

A system and method for selecting a preferred intraocular lens, for implantation into an eye, includes a controller having a processor and a tangible, non-transitory memory on which instructions are recorded. The controller is in communication with a diagnostic module adapted to store pre-operative anatomic data of the eye as an eye model. The controller is configured to determine respective imputed post-operative variables for each of a plurality of intraocular lenses, via a projection module. A respective pseudophakic eye model is generated for each of the plurality of intraocular lenses by incorporating the respective imputed post-operative variables into the eye model. A ray tracing module is executed in the respective pseudophakic eye model to determine at least one respective metric for the plurality of intraocular lenses. The preferred intraocular lens is selected based on a comparison of the respective metric.

Selection of a preferred intraocular lens based on ray tracing

In certain embodiments, a system for tracking movement of an eye comprises a camera system, a computer system, and an output device. The camera system generates images of the eye. The computer system stores the images and at least one of the images as a reference image. The computer system also tracks movement of the eye within a tracking range by comparing a current image with the reference image, and by determining a movement of the eye from the comparison of the current image and the reference image. The tracking range has one or more alert points. The computer system also determines an orientation of the eye relative to at least one alert point of the tracking range. The output device outputs a range indicator that indicates the orientation of the eye relative to the at least one alert point of the tracking range.

Tracking movement of an eye within a tracking range

In certain embodiments, an ophthalmic system for assessing a tear film of an eye comprises measuring devices and a computer. The measuring devices detect light reflected from the eye, where an ocular surface of the eye comprises the tear film, and generate data from the reflected light that describes the eye. The computer aligns the data corresponding to the same location for a plurality of locations, assesses the data at the locations to detect one or more abnormalities of the tear film, and determines a tear film description from the assessment of the data at the locations.

Multi-detector analysis of the tear film of an eye

The present disclosure provides a non-invasive technique to determine a true set of refractive indices of a patient's eye in order to generate an accurate model of the patient's eye. Certain aspects provide a system for generating a three-dimensional reconstruction model of a patient's eye. The system includes an imaging device configured to generate first and second measurements of a patient's eye at first and second angles relative to a line of sight of the patient's eye. The system includes an image processor configured to generate a first and second plurality of models of the patient's eye based on applying a plurality of sets of refractive indices to the first and second measurements; identify a first model from the first plurality of models that is congruent with a second model from the second plurality of models; and determine a set of refractive indices associated with the first and second models.

Refractive index determination by multi-directional ophthalmic image processing

A system and method for selecting an intraocular lens, for implantation into an eye, includes a controller having a processor and a tangible, non-transitory memory on which instructions are recorded. The controller is configured to selectively execute a machine learning model trained with a training dataset. Execution of the instructions by the processor causes the controller to obtain pre-operative objective data for the patient, including one or more anatomic eye measurements. The controller is configured to obtain pre-operative questionnaire data for the patient, including at least one personality trait. The pre-operative objective data and the pre-operative questionnaire data are entered as respective inputs to the machine learning model. A predicted subjective outcome score for the patient is generated as an output of the machine learning model. The intraocular lens is selected based in part on the predicted subjective outcome score.

Selection of intraocular lens based on a predicted subjective outcome score

An ophthalmic system for generating a topography of an anterior corneal surface of an eye comprises an illuminator, cameras, and a computer. The illuminator illuminates the anterior corneal surface of the eye with a Placido pattern, which reflects the Placido pattern. Each camera generates an image of the reflected Placido pattern to yield multiple images. At least one camera is oriented off an axis of the eye. For each image, the computer calculates a curvature value for each data point of the image, where a data point corresponds to a surface point of the anterior corneal surface. The calculations yield curvature values for each surface point. The computer determines the curvature at each surface point from one or more curvature values for the surface point. The computer generates the topography of the anterior corneal surface from the curvatures at the surface points of the anterior corneal surface.

Multi-view corneal topographer

Systems and methods for tracking eye movement during a diagnostic procedure include an eye tracker capturing images of an eye, and a control processor configured to detect an eye position and orientation in each of the images, determine an eye fixation position and orientation relative to an optical axis of the eye tracker, estimate eye fixation parameters based at least in part on the determined eye fixation position and orientation, and track the eye position and orientation by analyzing the images to determine the eye position and orientation relative to the eye fixation parameters. The eye fixation parameters may comprise a reference position and orientation of the eye when fixated. A histogram is constructed of detected eye positions and orientations and analyzed to determine an eye fixation position and orientation.

Eye tracking fixation monitoring systems and methods

An ophthalmic system for measuring an eye comprises measuring devices and a computer. The measuring devices comprise an optical coherence tomography (OCT) device and an aberrometer. The OCT device directs OCT light towards the eye, and detects the OCT light reflected from the eye to measure the eye. The aberrometer directs aberrometer light towards the eye, and detects the aberrometer light reflected from the eye to measure the eye. The computer generates an ocular model of the eye according to the reflected OCT light. The ocular model comprises parameters for the eye, where each parameter is assigned a value. The computer determines an OCT-based wavefront according to the ocular model, determines an aberrometer-based wavefront according to the reflected aberrometer light, ascertains a deviation between the OCT-based wavefront and the aberrometer-based wavefront, and evaluates measurements from one or more of the measuring devices according to the deviation.

Evaluating measurements using information from multiple measuring devices

An ophthalmic system for generating an ocular model of an eye includes an optical coherence tomography (OCT) device, an aberrometer, and a computer. The OCT device detects OCT light reflected from the eye. The aberrometer detects aberrometer light reflected from the eye. The computer generates the ocular model of the eye according to the reflected OCT light. The ocular model includes parameters describing the eye. The parameters include lens parameters that describe the lens of the eye. The computer determines an OCT-based wavefront according to the ocular model, determines an aberrometer-based wavefront according to the reflected aberrometer light, and compares the OCT-based and the aberrometer-based wavefronts. If the wavefronts differ beyond a predefined tolerance, the computer adjusts one or more values assigned to the parameters until the wavefronts satisfy the predefined tolerance. At least one adjusted value is assigned to a lens parameter.

Refining lens parameters of an ocular model

Systems and methods for tracking the position and condition of an eye during an ophthalmic procedure include an ophthalmic device configured to measure characteristics of an eye, an eye tracker configured to capture a stream of eye images, and a logic device configured to analyze the stream of images to determine whether the eye is fixating on a target object, detect a predetermined blink sequence in the first stream of images, delay for a predetermined tear stabilization period, start a stable tear film interval, and during the stable tear film interval, capture at least one measurement of the eye using the ophthalmic device when the eye is fixating. The blink sequence may include a plurality of blinks in succession and the detection of the blink sequence may include processing the images through a neural network trained to detect an open eye and/or a closed eye.

Patient-induced trigger of a measurement for ophthalmic diagnostic devices

A method for assessing a lens capsule stability condition in an eye of a human patient includes directing electromagnetic energy in a predetermined spectrum onto a pupil of the eye, via an energy source, concurrently subsequent to a movement of the eye causing eye saccades to occur therein. The method also includes acquiring images of the eye indicative of the eye saccades using an image capture device, and computing, via the ECU, a motion curve of the lens capsule using the images. Additionally, the method includes extracting time-normalized lens capsule oscillation traces based on the motion curve via the ECU, and then model-fitting the lens capsule oscillation traces via the ECU to thereby assess the lens capsule instability condition. An automated system for performing an embodiment of the method is also disclosed herein, including the energy source, image capture device, and ECU.

Automated assessment of human lens capsule stability

Systems and methods for initializing and calibrating an eye tracking system include an eye tracker configured to capture a first image of an eye from a first location and a second image of the eye from a second location, and a control processor configured to detect a first plurality of eye characteristics from the first image, the eye characteristics having first corresponding image coordinates, detect a second plurality of eye characteristics from the second image, the eye characteristics having second corresponding image coordinates, and determine a calibration offset and a calibration gain. The control processor may be further configured to determine an eye fixation position and orientation relative to an optical axis of the eye tracker based at least in part on the first corresponding image coordinates and/or the second corresponding image coordinates.

Instant eye gaze calibration systems and methods

Systems and methods for tracking eye movement during a diagnostic procedure include a retina imaging system configured to capture a first plurality of images of an eye and detect a presence of a fovea, an eye tracker configured to capture a second plurality of images of the eye and track a position and orientation of the eye; and a control processor configured to synchronize the first and second plurality of images, determine a time at which the fovea is detected in the first plurality of images, and determine one or more images from the second plurality of images to be classified as representative of fixation. The classified images are analyzed to determine eye fixation status during the diagnostic procedure based on eye tracking data.

Growing community of inventors

Rangsdorf, Germany

Martin Gründig