Click based contour editing
    1.
    发明授权

    公开(公告)号:US12141420B2

    公开(公告)日:2024-11-12

    申请号:US17960367

    申请日:2022-10-05

    Abstract: Click based contour editing includes detecting a selection input with respect to an image presented on a graphical user interface; designating an area of the image corresponding to the selection input as a region of interest; detecting at least one other selection input on the graphical user interface with respect to the image; determining if the at least one other selection input is within the region of interest or outside of the region of interest; and if the at least one other selection input is within the region of interest, excluding the portion of the image corresponding to the other input; or if the other selection input is outside of the region of interest, including the portion of the image corresponding to an area of the image associated with the other selection input.

    CLICK BASED CONTOUR EDITING
    2.
    发明公开

    公开(公告)号:US20240118796A1

    公开(公告)日:2024-04-11

    申请号:US17960367

    申请日:2022-10-05

    Abstract: Click based contour editing includes detecting a selection input with respect to an image presented on a graphical user interface; designating an area of the image corresponding to the selection input as a region of interest; detecting at least one other selection input on the graphical user interface with respect to the image; determining if the at least one other selection input is within the region of interest or outside of the region of interest; and if the at least one other selection input is within the region of interest, excluding the portion of the image corresponding to the other input; or if the other selection input is outside of the region of interest, including the portion of the image corresponding to an area of the image associated with the other selection input.

    SYSTEMS AND METHODS FOR AUTOMATIC IMAGE ANNOTATION

    公开(公告)号:US20230343438A1

    公开(公告)日:2023-10-26

    申请号:US17726369

    申请日:2022-04-21

    CPC classification number: G16H30/40 G06N3/04 G06F40/169

    Abstract: Described herein are systems, methods, and instrumentalities associated with automatic image annotation. The annotation may be performed based on one or more manually annotated first images of an object and a machine-learned (ML) model trained to extract first features from the one or more first images. To automatically annotate a second, un-annotated image of the object, the ML model may be used to extract second features from the second image, determine information that may be indicative of the characteristics of the object in the second image based on the first and second features, and generate an annotation of the object for the second image using the determined information. The images may be obtained from various sources including, for example, sensors and/or medical scanners, and the object of interest may include anatomical structures such as organs, tumors, etc. The annotated images may be used for multiple purposes including machine learning.

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