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公开(公告)号：US11587656B2
公开(公告)日：2023-02-21
申请号：US17127735
申请日：2020-12-18
Applicant: Alcon Inc.
Inventor： Kevin Baker , Ramesh Sarangapani
Abstract: A personalized assistance system for a user of a vision correction device includes a remote computing unit with a controller having a processor and tangible, non-transitory memory on which instructions are recorded. The controller is configured to selectively execute one or more machine learning models. A user device is operable by the user and includes an electronic diary module configured to prompt the user to answer one or more preselected questions at specific intervals. The electronic diary module is configured to store respective answers, entered by the user in response to the one or more preselected questions, as self-reported data. The controller is configured to obtain the self-reported data from the electronic diary module and generate an analysis of the self-reported data, via the one or more machine learning models. The controller is configured to assist the user based in part on the analysis.
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公开(公告)号：US20220198653A1
公开(公告)日：2022-06-23
申请号：US17507082
申请日：2021-10-21
Applicant: ALCON INC.
Inventor： Lu Yin , Ashok Burton Tripathi , Ramesh Sarangapani
Abstract: A system and method for visually enhancing an original image of an eye includes a visualization module. A controller is configured to convert an output of the visualization module to a first pixel cloud in a first color space and map the first pixel cloud to a second pixel cloud in a second color space. The method includes identifying at least one selected zone in the second color space. The controller is configured to move the selected zone from an original location to a modified location in the second color space. The second pixel cloud is updated to obtain a modified second pixel cloud, which is transformed into a third pixel cloud in the first color space. An enhanced image is formed based in part on the modified second pixel cloud and provides selective visual enhancement in the selected zone without affecting contrast in a remainder of the original image.
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公开(公告)号：US20210186323A1
公开(公告)日：2021-06-24
申请号：US17127693
申请日：2020-12-18
Applicant: Alcon Inc.
Inventor： Ramesh Sarangapani , Mark VonTress
Abstract: A system and method of assessing vision quality of an eye is presented, with a controller having a processor and tangible, non-transitory memory on which instructions are recorded. The controller is configured to selectively execute at least one machine learning model. Execution of the instructions by the processor causes the controller to: receive wavefront aberration data of the eye and express the wavefront aberration data as a collection of Zernike polynomials. The controller is configured to obtain a plurality of input factors based on the collection of Zernike polynomials. The plurality of input factors is fed into the at least one machine learning model, which is trained to analyze the plurality of input factors. The machine learning model generates at least one vision correction factor based in part on the plurality of input factors.
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公开(公告)号：US20200229870A1
公开(公告)日：2020-07-23
申请号：US16746231
申请日：2020-01-17
Applicant: ALCON INC.
Inventor： Ramesh Sarangapani , Mark VonTress
Abstract: Systems and methods for intraocular lens (IOL) selection using emmetropia zone prediction include determining pre-operative measurements of an eye, estimating a post-operative anterior chamber depth (ACD) of an intraocular lens based on the pre-operative measurements, estimating a post-operative manifest refraction in spherical equivalent (MRSE) of the eye with the IOL implanted based on the pre-operative measurements and the estimated post-operative ACD, determining whether the eye with the IOL implanted is likely to be in an emmetropia zone based on the estimated post-operative MRSE, re-estimating the post-operative MRSE of the eye with the IOL implanted using an emmetropia zone prediction model or a non-emmetropia zone prediction model based on the emmetropia zone determining, and providing the re-estimated post-operative MRSE to a user to aid in selection of an IOL for implantation in the eye.
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15.发明申请公开(公告)号：US20250165595A1
公开(公告)日：2025-05-22
申请号：US18951860
申请日：2024-11-19
Applicant: Alcon, Inc.
Inventor： Shruti Siva Kumar , Thomas E. Jackson , Sinchan Bhattacharya , Ramesh Sarangapani , Uma Chandrashekhar , Pranava Kumar Vemula
Abstract: A system includes a machine learning (ML) engine in which a data store is coupled to a processing system. The processing system executes code to receive a dataset from the data store, and produces three models each comprising three tests. Each of the tests seeks to detect one of three anomaly types corresponding to each of the models. The processing system performs at least two of the three tests relating to each of the three anomaly types. Separately for each anomaly type, the processing system detects an anomaly when two-out-of-three (2oo3) tests conclude that the anomaly is present in the dataset. The dataset including the flagged anomalies is stored in a data repository. The anomaly is filtered from the dataset. The processing system is configured to use data from the dataset to retrain an existing trained ML model.
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Patent Agency Ranking
公开(公告)号：US20240197167A1
公开(公告)日：2024-06-20
申请号：US18584409
申请日：2024-02-22
Applicant: Alcon Inc.
Inventor： Ramesh Sarangapani , Kevin Baker
CPC classification number: A61B3/0025 , G06N5/04 , G06N20/00 , G16H50/20 , G16H50/70
Abstract: Systems and methods for determining a compatibility between a multi-focal contact lens and a patient seeking presbyopia vision correction include receiving, from a first device associated with a first eye-care professional (ECP), a request for selecting a contact lens for a consumer, wherein the request comprises biometric information associated with the consumer; obtaining a performance metric associated with the first ECP; determining, using the machine learning model and based on the performance metric, a customized compatibility index indicating a compatibility between a particular contact lens and the consumer for the first ECP; and presenting a report indicating the compatibility index on the first device. Additional systems, methods, and non-transitory machine-readable mediums are also provided.
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17.发明公开公开(公告)号：US20240104731A1
公开(公告)日：2024-03-28
申请号：US18475387
申请日：2023-09-27
Applicant: Alcon Inc.
Inventor： Vignesh Suresh , Lu Yin , Ramesh Sarangapani
CPC classification number: G06T7/0012 , A61B3/14 , G06V10/48 , G16H30/40 , G06T2207/10101 , G06T2207/20081 , G06T2207/20084 , G06T2207/30041 , G06V2201/03
Abstract: In certain embodiments, a system, a computer-implemented method, and computer-readable medium are disclosed for performing integrated analysis of MSI and OCT images to diagnose eye disorders. MSI and OCT are processed using separate input machine learning models to create input feature maps that are input to an intermediate machine learning model. The intermediate machine learning model processes the input feature maps and outputs a final feature map that is processed by one or more output machine learning models that output one or more estimated representations of a pathology of the eye of the patient.
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公开(公告)号：US20240032784A1
公开(公告)日：2024-02-01
申请号：US18358881
申请日：2023-07-25
Applicant: Alcon Inc.
Inventor： Vignesh Suresh , Shruti Siva Kumar , Lu Yin , Ramesh Sarangapani
CPC classification number: A61B3/0025 , A61B3/14 , G16H50/30
Abstract: In certain embodiments, an ophthalmic system and computer-implemented method for analyzing multiple spectral information to generate ophthalmic information are described. In an exemplary ophthalmic system, multiple spectral information associated with an eye of a patient is captured via an imaging system. A first set of information and a second set of information are extracted from the multiple spectral information. A visualization of the multiple spectral information is generated using the first set of information. The first set of information and the second set of information are evaluated using different deep learning models to generate ophthalmic information. The ophthalmic information is sent to a user for diagnostic evaluation.
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公开(公告)号：US20230162828A1
公开(公告)日：2023-05-25
申请号：US18160238
申请日：2023-01-26
Applicant: Alcon Inc.
Inventor： Kevin Baker , Ramesh Sarangapani
Abstract: A personalized assistance system for a user of a vision correction device includes a remote computing unit with a controller having a processor and tangible, non-transitory memory on which instructions are recorded. The controller is configured to selectively execute one or more machine learning models. A user device is operable by the user and includes an electronic diary module configured to prompt the user to answer one or more preselected questions at specific intervals. The electronic diary module is configured to store respective answers, entered by the user in response to the one or more preselected questions, as self-reported data. The controller is configured to obtain the self-reported data from the electronic diary module and generate an analysis of the self-reported data, via the one or more machine learning models. The controller is configured to assist the user based in part on the analysis.
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公开(公告)号：US20230054129A1
公开(公告)日：2023-02-23
申请号：US17880427
申请日：2022-08-03
Applicant: Alcon Inc.
Inventor： Lu Yin , Ramesh Sarangapani
Abstract: Certain aspects of the present disclosure provide an ophthalmic imaging device for enhancing images. The device comprises an image capture component configured to generate an image stream comprising a first frame preceding a second frame, both capturing a branch of veins in an eye. The device further comprises an image processor configured to calculate first order statistics for a plurality of blocks for the first frame and to interpolate first order statistics for the first frame based at least in part on the branch of veins. The image processor is also configured to generate a tone mapping function and calculate tone mapping values for individual pixels of the second frame based on the tone mapping function. The image processor is additionally configured to generate an enhanced frame based on the calculated tone mapping values for individual pixels of the second frame to the pixels of the second frame.
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