Deep learning for optical coherence tomography segmentation

    公开(公告)号:US11562484B2

    公开(公告)日:2023-01-24

    申请号:US17127651

    申请日:2020-12-18

    Applicant: Alcon Inc.

    Abstract: Systems and methods are presented for providing a machine learning model for segmenting an optical coherence tomography (OCT) image. A first OCT image is obtained, and then labeled with identified boundaries associated with different tissues in the first OCT image using a graph search algorithm. Portions of the labeled first OCT image are extracted to generate a first plurality of image tiles. A second plurality of image tiles is generated by manipulating at least one image tile from the first plurality of image tiles, such as by rotating and/or flipping the at least one image tile. The machine learning model is trained using the first plurality of image tiles and the second plurality of image tiles. The trained machine learning model is used to perform segmentation in a second OCT image.

    OPHTHALMIC OPTICAL COHERENCE TOMOGRAPHY WITH MULTIPLE RESOLUTIONS

    公开(公告)号:US20200367744A1

    公开(公告)日:2020-11-26

    申请号:US16876960

    申请日:2020-05-18

    Applicant: Alcon Inc.

    Abstract: Systems and methods are disclosed for performing ophthalmic optical coherence tomography with multiple resolutions. In some embodiments, a system comprises a light source, an output lens, and a set of optical components between the light source and the output lens, the set of optical components comprising an afocal zoom telescope. The set of optical components is adapted to provide imaging both at a first field of view with a first resolution and at a second field of view with a second resolution, wherein the first field of view is wider than the second field of view and the second resolution is higher than the first resolution. A method of performing ophthalmic optical coherence tomography with multiple resolutions may be performed using one or more of the systems described herein.

    Ophthalmic optical coherence tomography with multiple resolutions

    公开(公告)号:US11602272B2

    公开(公告)日:2023-03-14

    申请号:US16876960

    申请日:2020-05-18

    Applicant: Alcon Inc.

    Abstract: Systems and methods are disclosed for performing ophthalmic optical coherence tomography with multiple resolutions. In some embodiments, a system comprises a light source, an output lens, and a set of optical components between the light source and the output lens, the set of optical components comprising an afocal zoom telescope. The set of optical components is adapted to provide imaging both at a first field of view with a first resolution and at a second field of view with a second resolution, wherein the first field of view is wider than the second field of view and the second resolution is higher than the first resolution. A method of performing ophthalmic optical coherence tomography with multiple resolutions may be performed using one or more of the systems described herein.

    Dual-edge sampling with k-clock to avoid aliasing in optical coherence tomography

    公开(公告)号:US10767973B2

    公开(公告)日:2020-09-08

    申请号:US16173146

    申请日:2018-10-29

    Applicant: Alcon Inc.

    Abstract: Techniques and apparatus for producing sampled Optical Coherence Tomography (OCT) interference signals without aliasing, based on a swept-source OCT interference signal. An example apparatus comprises a k-clock circuit configured to selectively output a k-clock signal at any of a plurality of k-clock frequencies ranging from a minimum k-clock frequency to a maximum k-clock frequency, and an anti-aliasing filter configured to filter a swept-source OCT interference signal, to produce a filtered OCT interference signal, where the anti-aliasing filter has a cut-off frequency greater than one-half the minimum k-clock frequency but less than the minimum k-clock frequency. The apparatus further comprises an analog-to-digital (A/D) converter circuit configured to sample the filtered OCT interference signal at twice the k-clock frequency, to produce a sampled OCT interference signal. In some embodiments, the A/D converter circuit samples the filtered OCT interference signal at both rising and falling edges of the k-clock signal.

    DEEP LEARNING FOR OPTICAL COHERENCE TOMOGRAPHY SEGMENTATION

    公开(公告)号:US20230124674A1

    公开(公告)日:2023-04-20

    申请号:US18068978

    申请日:2022-12-20

    Applicant: Alcon Inc.

    Abstract: Systems and methods are presented for providing a machine learning model for segmenting an optical coherence tomography (OCT) image. A first OCT image is obtained, and then labeled with identified boundaries associated with different tissues in the first OCT image using a graph search algorithm. Portions of the labeled first OCT image are extracted to generate a first plurality of image tiles. A second plurality of image tiles is generated by manipulating at least one image tile from the first plurality of image tiles, such as by rotating and/or flipping the at least one image tile. The machine learning model is trained using the first plurality of image tiles and the second plurality of image tiles. The trained machine learning model is used to perform segmentation in a second OCT image.

    Phase-sensitive optical coherence tomography to measure optical aberrations in anterior segment

    公开(公告)号:US10966607B2

    公开(公告)日:2021-04-06

    申请号:US16149380

    申请日:2018-10-02

    Applicant: Alcon Inc.

    Abstract: Techniques for measuring optical aberrations of the eye are disclosed. An example method comprises positioning the eye in a measurement location adjacent to a measurement arm of an optical coherence tomography (OCT) interferometer apparatus, so that source light from the measurement arm passes into the anterior segment of the eye and detecting an interference pattern, the interference pattern resulting from a combination of light reflected from the eye and light reflected from a reference arm of the OCT interferometer apparatus. Based on the interference pattern, an optical delay between a reference surface in the anterior segment of the eye and a measured surface in the eye is calculated, the reference surface being the anterior surface of the cornea or the lens, wherein said calculating comprises measuring an optical phase shift between the reference surface and the measured surface, based on the detected interference pattern.

    DEEP LEARNING FOR OPTICAL COHERENCE TOMOGRAPHY SEGMENTATION

    公开(公告)号:US20210192732A1

    公开(公告)日:2021-06-24

    申请号:US17127651

    申请日:2020-12-18

    Applicant: Alcon Inc.

    Abstract: Systems and methods are presented for providing a machine learning model for segmenting an optical coherence tomography (OCT) image. A first OCT image is obtained, and then labeled with identified boundaries associated with different tissues in the first OCT image using a graph search algorithm. Portions of the labeled first OCT image are extracted to generate a first plurality of image tiles. A second plurality of image tiles is generated by manipulating at least one image tile from the first plurality of image tiles, such as by rotating and/or flipping the at least one image tile. The machine learning model is trained using the first plurality of image tiles and the second plurality of image tiles. The trained machine learning model is used to perform segmentation in a second OCT image.

    LASER TREATMENT OF MEDIA OPACITIES

    公开(公告)号:US20210186753A1

    公开(公告)日:2021-06-24

    申请号:US17126899

    申请日:2020-12-18

    Applicant: Alcon Inc.

    Abstract: The present disclosure provides a laser treatment system that includes an optical coherence tomography (OCT) imaging system that generates a plurality of profile depth scans and executes instructions on a processor to detect a position, a volume, or a combination thereof, of a media opacity in an eye based on the plurality of profile depth scans. The system further includes a three-dimensional (3D) eye tracker that executes instructions on the processor to track the position, the volume, or a combination thereof, of the media opacity in the eye based on the plurality of profile depth scans. The system also includes a laser system that includes a treatment laser and that precisely targets a plurality of ultra-short laser pulses generated by the treatment laser at the media opacity in the eye to at least partially remove the media opacity.

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