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公开(公告)号：US20220151482A1
公开(公告)日：2022-05-19
申请号：US17501868
申请日：2021-10-14
Applicant: Alcon Inc.
Inventor： Robert Dimitri Angelopoulos , Bryan Stanfill
Abstract: A method for estimating biometric landmark dimensional measurements of a human eye includes, in a possible embodiment, receiving one or more images of the human eye via a host computer. In response to receiving the one or more images, the method includes generating a preliminary set of landmark point locations in the one or more images via the host computer using a deep-learning algorithm, and then refining the preliminary set of landmark point locations using a post-hoc processing routine of the host computer to thereby generate a final set of estimated landmark point locations. Additionally, the biometric landmark dimensional measurements are automatically generated via the host computer using the final set of estimated landmark point locations. A data set is then output that is inclusive of the set of estimated landmark point locations. A host computer that executes instructions from memory to perform the method.
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公开(公告)号：US20240090995A1
公开(公告)日：2024-03-21
申请号：US18463168
申请日：2023-09-07
Applicant: Alcon Inc.
CPC classification number: A61F2/16 , A61B3/0025 , G16H20/00 , G16H50/70
Abstract: Certain aspects of the present disclosure provide techniques for performing surgical ophthalmic procedures, such as cataract surgeries. An example method of determining one or more intraocular lens (IOL) parameters for an IOL to be used in a cataract surgery procedure includes generating, using a fused machine learning model, recommendations including one or more IOL parameters for the IOL to be used in the cataract surgery based, at least in part, on first predicted lens behavior for each of one or more IOLs by an emulated finite element analysis (EFEA) model and the second predicted lens behavior for each of the one or more IOLs by an IOL power calculator (IPC) machine learning model.
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