Image retention and stitching for minimal-flash eye disease diagnosis

    公开(公告)号:AU2021238305B2

    公开(公告)日:2025-01-23

    申请号:AU2021238305

    申请日:2021-03-15

    Abstract: Systems and methods are provided herein for minimizing retinal exposure to flash during image gathering for diagnosis. In an embodiment, a system captures a plurality of retinal images of different retinal regions. The system determines that a first portion of a first image does not meet a criterion while a second portion of the first image does meet the criterion, identifies a portion of the retina depicted in the first portion that does not meet the criterion, and determines whether the portion of the retina is depicted in a third portion of a second image and whether the third portion meets the criterion. Responsive to determining that the third portion meets the criterion, the system performs the diagnosis. Responsive to determining that the portion of the retina is not depicted in the second image, the system captures an additional image of the retinal region.

    Dynamic adjustment of flash intensity based on retinal pigmentation

    公开(公告)号:IL296367B1

    公开(公告)日:2024-10-01

    申请号:IL29636722

    申请日:2022-09-11

    Abstract: Systems and methods are disclosed herein for adjusting flash intensity based on retinal pigmentation. In an embodiment, a processor determines a retinal pigmentation of a retina of an eye positioned at an imaging device. The processor commands the imaging device to adjust an intensity of a flash component from a first intensity to a second intensity based on the retinal pigmentation. The processor commands the imaging device to capture an image that is lit by the flash component at the second intensity, and receives the image from the imaging device.

    Monitoring surface cleaning of medical surfaces using video streaming

    公开(公告)号:AU2020302909A1

    公开(公告)日:2022-02-17

    申请号:AU2020302909

    申请日:2020-06-26

    Abstract: A cleaning wizard monitors and provides feedback for cleaning of medical equipment to ensure that cleaning is performed based on best practices. The cleaning wizard receives a video stream comprising an item of medical equipment and inputs a first set of video frames from the video stream into a first machine learning model. The first machine learning model is trained to output whether the first set of video frames corresponds to activity that initiates a cleaning protocol for the item of medical equipment. Responsive to the cleaning protocol being initiated, the cleaning wizard inputs a second set of video frames into a second machine learning model trained to output whether the second set of frames meets criteria of the cleaning protocol. Responsive to all criteria of the cleaning protocol being met, the cleaning wizard transmits a notification to an operator that the cleaning protocol is complete.

    Dynamic adjustment of flash intensity based on retinal pigmentation

    公开(公告)号:IL296367A

    公开(公告)日:2022-11-01

    申请号:IL29636722

    申请日:2022-09-11

    Abstract: Systems and methods are disclosed herein for adjusting flash intensity based on retinal pigmentation. In an embodiment, a processor determines a retinal pigmentation of a retina of an eye positioned at an imaging device. The processor commands the imaging device to adjust an intensity of a flash component from a first intensity to a second intensity based on the retinal pigmentation. The processor commands the imaging device to capture an image that is lit by the flash component at the second intensity, and receives the image from the imaging device.

    Image retention and stitching for minimal-flash eye disease diagnosis

    公开(公告)号:IL296332A

    公开(公告)日:2022-11-01

    申请号:IL29633222

    申请日:2022-09-08

    Abstract: Systems and methods are provided herein for minimizing retinal exposure to flash during image gathering for diagnosis. In an embodiment, a system captures a plurality of retinal images of different retinal regions. The system determines that a first portion of a first image does not meet a criterion while a second portion of the first image does meet the criterion, identifies a portion of the retina depicted in the first portion that does not meet the criterion, and determines whether the portion of the retina is depicted in a third portion of a second image and whether the third portion meets the criterion. Responsive to determining that the third portion meets the criterion, the system performs the diagnosis. Responsive to determining that the portion of the retina is not depicted in the second image, the system captures an additional image of the retinal region.

    Diagnosing skin conditions using machine-learned models

    公开(公告)号:AU2020299568A1

    公开(公告)日:2022-02-17

    申请号:AU2020299568

    申请日:2020-06-30

    Abstract: A diagnosis system trains a set of machine-learned diagnosis models that are configured to receive an image of a patient and generate predictions on whether the patient has one or more health conditions. In one embodiment, the set of machine-learned models are trained to generate predictions for images that contain two or more underlying health conditions of the patient. In one instance, the symptoms for the two or more health conditions are shown as two or more overlapping skin abnormalities on the patient. By using the architectures of the set of diagnosis models described herein, the diagnosis system can generate more accurate predictions for images that contain overlapping symptoms for two or more health conditions compared to existing systems.

    Dynamic adjustment of flash intensity based on retinal pigmentation

    公开(公告)号:IL296367B2

    公开(公告)日:2025-02-01

    申请号:IL29636722

    申请日:2022-09-11

    Abstract: Systems and methods are disclosed herein for adjusting flash intensity based on retinal pigmentation. In an embodiment, a processor determines a retinal pigmentation of a retina of an eye positioned at an imaging device. The processor commands the imaging device to adjust an intensity of a flash component from a first intensity to a second intensity based on the retinal pigmentation. The processor commands the imaging device to capture an image that is lit by the flash component at the second intensity, and receives the image from the imaging device.

    Monitoring surface cleaning of medical surfaces using video streaming

    公开(公告)号:IL289140D0

    公开(公告)日:2022-02-01

    申请号:IL28914021

    申请日:2021-12-19

    Abstract: A cleaning wizard monitors and provides feedback for cleaning of medical equipment to ensure that cleaning is performed based on best practices. The cleaning wizard receives a video stream comprising an item of medical equipment and inputs a first set of video frames from the video stream into a first machine learning model. The first machine learning model is trained to output whether the first set of video frames corresponds to activity that initiates a cleaning protocol for the item of medical equipment. Responsive to the cleaning protocol being initiated, the cleaning wizard inputs a second set of video frames into a second machine learning model trained to output whether the second set of frames meets criteria of the cleaning protocol. Responsive to all criteria of the cleaning protocol being met, the cleaning wizard transmits a notification to an operator that the cleaning protocol is complete.

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