AUGMENTATION OF OPTICAL COHERENCE TOMOGRAPHY IMAGE OF EYE BASED ON LEARNING MODULES

    公开(公告)号:US20220198654A1

    公开(公告)日:2022-06-23

    申请号:US17507644

    申请日:2021-10-21

    Applicant: Alcon Inc.

    Abstract: A system and method for augmenting an original OCT (optical coherence tomography) image includes a controller having a processor and a tangible, non-transitory memory on which instructions are recorded. The system includes one or more learning modules selectively executable by the controller. The learning modules are trained by a training network with a training dataset having a plurality of training ultrasound bio-microscopy images and respective training OCT images. Execution of the instructions by the processor causes the controller to obtain the original OCT image, captured through an OCT device. The controller is configured to generate an augmented OCT image based in part on the original OCT image, by executing the (trained) learning modules. The augmented OCT image at least partially extends a peripheral portion of the original OCT image.

    BIOMETRIC OCULAR MEASUREMENTS USING DEEP LEARNING

    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.

    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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