Systems and methods to process electronic images to provide blur robustness

    公开(公告)号:US12169915B2

    公开(公告)日:2024-12-17

    申请号:US17732857

    申请日:2022-04-29

    Applicant: PAIGE.AI, Inc.

    Abstract: A computer-implemented method for processing electronic medical images, the method including receiving a plurality of electronic medical images of a medical specimen. Each of the plurality of electronic medical images may be divided into a plurality of tiles. A plurality of sets of matching tiles may be determined, the tiles within each set corresponding to a given region of a plurality of regions of the medical specimen. For each tile of the plurality of sets of matching tiles, a blur score may be determined corresponding to a level of image blur of the tile. For each set of matching tiles, a tile may be determined with the blur score indicating the lowest level of blur. A composite electronic medical image, comprising a plurality of tiles from each set of matching tiles with the blur score indicating the lowest level of blur, may be determined and provided for display.

    Systems and methods for processing electronic images to determine testing for unstained specimens

    公开(公告)号:US11481899B2

    公开(公告)日:2022-10-25

    申请号:US17547695

    申请日:2021-12-10

    Applicant: PAIGE.AI, INC.

    Abstract: A computer-implemented method may include receiving a collection of unstained digital histopathology slide images at a storage device and running a trained machine learning model on one or more slide images of the collection to infer a presence or an absence of a salient feature. The trained machine learning model may have been trained by processing a second collection of unstained or stained digital histopathology slide images and at least one synoptic annotation for one or more unstained or stained digital histopathology slide images of the second collection. The computer-implemented method may further include determining at least one map from output of the trained machine learning model and providing an output from the trained machine learning model to the storage device.

    Systems and methods for delivery of digital biomarkers and genomic panels

    公开(公告)号:US11475990B2

    公开(公告)日:2022-10-18

    申请号:US17160129

    申请日:2021-01-27

    Applicant: PAIGE.AI, Inc.

    Abstract: Systems and methods are disclosed for receiving one or more digital images associated with a tissue specimen, a related case, a patient, and/or a plurality of clinical information, determining one or more of a prediction, a recommendation, and/or a plurality of data for the one or more digital images using a machine learning system, the machine learning system having been trained using a plurality of training images, to predict a biomarker and a plurality of genomic panel elements, and determining, based on the prediction, the recommendation, and/or the plurality of data, whether to log an output and at least one visualization region as part of a case history within a clinical reporting system.

    Systems and methods to process electronic images to adjust attributes of the electronic images

    公开(公告)号:US11455753B1

    公开(公告)日:2022-09-27

    申请号:US17643036

    申请日:2021-12-07

    Applicant: PAIGE.AI, Inc.

    Abstract: Systems and methods are disclosed for adjusting attributes of whole slide images, including stains therein. A portion of a whole slide image comprised of a plurality of pixels in a first color space and including one or more stains may be received as input. Based on an identified stain type of the stain(s), a machine-learned transformation associated with the stain type may be retrieved and applied to convert an identified subset of the pixels from the first to a second color space specific to the identified stain type. One or more attributes of the stain(s) may be adjusted in the second color space to generate a stain-adjusted subset of pixels, which are then converted back to the first color space using an inverse of the machine-learned transformation. A stain-adjusted portion of the whole slide image including at least the stain-adjusted subset of pixels may be provided as output.

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