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1.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：US20240099577A1
公开(公告)日：2024-03-28
申请号：US18475369
申请日：2023-09-27
Applicant: Alcon Inc.
Inventor： John Park , Qing Xiang , Lu Yin , Vignesh Suresh
CPC classification number: A61B3/102 , A61B3/12 , G06T7/00 , G06T2207/10036 , G06T2207/20081 , G06T2207/30041
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. A single device captures OCT and non-OCT images using (a) a sensor of a first imaging device that is shared with a second imaging device and/or (b) an optical component for directing light form the retina to the first imaging device or the second imaging device.
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Patent Agency Ranking
4.发明公开公开(公告)号：US20240094054A1
公开(公告)日：2024-03-21
申请号：US18463088
申请日：2023-09-07
Applicant: Alcon Inc.
Inventor： Lu Yin , Ramesh Sarangapani , Kongfeng Berger , Vignesh Suresh
CPC classification number: G01J3/2823 , A61B3/14 , G01J3/10 , G01J3/433 , G01J2003/102 , G01J2003/2826 , G01J2003/4334
Abstract: In certain embodiments, a system, a computer-implemented method, and computer-readable medium for generating multispectral imaging (MSI) based on performing an analytical MSI operation are described. The analytical MSI operation includes synchronizing a scan of a target by a broadband imaging device with a generation of a plurality of light signals, from a plurality of broadband illumination sources, directed towards the target. A set of spectral information associated with the target is generated, based on the scan of the target with the broadband imaging device. A set of multispectral imaging (MSI) information associated with the target is generated, based on performing an MSI operation using at least the set of spectral information. Ophthalmic information is determined based on the set of MSI information.
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公开(公告)号：US20240107135A1
公开(公告)日：2024-03-28
申请号：US18475390
申请日：2023-09-27
Applicant: Alcon Inc.
Inventor： Lu Yin , Vignesh Suresh , Ramesh Sarangapani
Abstract: In certain embodiments, a system, a computer-implemented method, and computer-readable medium are disclosed for light efficient fluorescence imaging. The retina is flashed with broadband light and returned light is imaged after passing through one or more filters, such as notch filers, low-pass filters, and high-pass filters. Images may be captured with a single camera or at least two cameras, one capturing transmitted light from the filter and the other capturing returned light. Images may be combined by subtraction and/or addition to obtain a combined image representing light within a passband whereas no passband filters are used during imaging.
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公开(公告)号：US20240081975A1
公开(公告)日：2024-03-14
申请号：US18464050
申请日：2023-09-08
Applicant: Alcon Inc.
Inventor： Vignesh Suresh , Lu Yin , Ramesh Sarangapani , Tobias Jura Rapoport
CPC classification number: A61F2/16 , A61B34/10 , A61B2034/105 , A61B2034/107
Abstract: Particular embodiments disclosed herein provide an alignment guide for aligning a toric IOL during surgery. An image with a reference axis is obtained, such as from a digital microscope, and processed, such as using an autoencoder, to label alignment marks on the IOL and possibly other features of the IOL. The label is processed, such as using a logistic regression model, to estimate an IOL axis of the IOL intersecting the alignment marks. An output image is generated from the image that has superimposed thereon guides to a surgeon, such as a line representing the IOL axis, a rotation direction indicator, and a number or other representation of a difference between the reference axis and the IOL axis. Tracking of features of the IOL may be performed across multiple images to predict the location of features not represented in a particular image.
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7.发明公开公开(公告)号：US20230334678A1
公开(公告)日：2023-10-19
申请号：US18299029
申请日：2023-04-11
Applicant: Alcon Inc.
Inventor： Lu Yin , Ramesh Sarangapani , Vignesh Suresh
CPC classification number: G06T7/337 , G06T7/11 , G06T7/0014 , G06T7/37 , A61B3/0025 , G06T2207/20084 , G06T2207/10101 , G06T2207/30041 , G06T2207/10012 , G06T2207/20081
Abstract: In certain embodiments, an ophthalmic system and computer-implemented method for performing ophthalmic image registration are described. The ophthalmic image registration includes obtaining a plurality of images of an eye of a user. Within each image of the plurality of images, a segmented region(s) of the eye within the image is determined based on evaluating the image with a neural network(s), and a set of point features of the eye within the segmented region(s) of the eye is determined based on evaluating the image with the neural network(s). A set of transformation information for transforming at least one of the plurality of images is generated based on performing one or more image processing operations on the set of point features within each image of the plurality of images. At least one of the plurality of images is transformed, based on the set of transformation information.
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公开(公告)号：US20230329907A1
公开(公告)日：2023-10-19
申请号：US18299022
申请日：2023-04-11
Applicant: Alcon Inc.
Inventor： Lu Yin , Kongfeng Berger , Ramesh Sarangapani , Vignesh Suresh
CPC classification number: A61F9/007 , A61B3/14 , A61B34/20 , A61B2090/372
Abstract: Certain embodiments provide a method of performing ophthalmic surgical procedures. The method includes ingesting and preparing pre-operative data and intra-operative data associated with a patient's eye for further processing. In certain embodiments, the method further includes integrating the pre-operative data and intra-operative data to generate context sensitive data for further processing. The method also includes classifying and annotating the pre-operative data, the intra-operative data, and the context sensitive data. The method also includes extracting one or more actionable inferences from the pre-operative data, the intra-operative data, context sensitive data, and the classified and annotated data. The method further includes triggering, based on the one or more actionable inferences, one or more actions on an imaging system or a surgical system.
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