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公开(公告)号：US11176676B2
公开(公告)日：2021-11-16
申请号：US17159849
申请日：2021-01-27
Applicant: PAIGE.AI, Inc.
Inventor： Brandon Rothrock , Christopher Kanan , Julian Viret , Thomas Fuchs , Leo Grady
Abstract: Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.
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公开(公告)号：US11995903B2
公开(公告)日：2024-05-28
申请号：US18186252
申请日：2023-03-20
Applicant: PAIGE.AI, Inc.
Inventor： Brandon Rothrock , Christopher Kanan , Julian Viret , Thomas Fuchs , Leo Grady
CPC classification number: G06V20/695 , G06F18/2155 , G06N20/00 , G06T7/0012 , G06T7/136 , G06T7/194 , G06V10/26 , G06V10/28 , G06V20/698 , G06T2207/20081 , G06T2207/30024
Abstract: Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.
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公开(公告)号：US11640719B2
公开(公告)日：2023-05-02
申请号：US17811960
申请日：2022-07-12
Applicant: PAIGE.AI, Inc.
Inventor： Brandon Rothrock , Christopher Kanan , Julian Viret , Thomas Fuchs , Leo Grady
Abstract: Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.
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公开(公告)号：US11423547B2
公开(公告)日：2022-08-23
申请号：US17480826
申请日：2021-09-21
Applicant: PAIGE.AI, Inc.
Inventor： Brandon Rothrock , Christopher Kanan , Julian Viret , Thomas Fuchs , Leo Grady
Abstract: Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.
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