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31.发明授权公开(公告)号：US11593684B2
公开(公告)日：2023-02-28
申请号：US17705908
申请日：2022-03-28
Applicant: PAIGE.AI, Inc.
Inventor： Supriya Kapur , Christopher Kanan , Thomas Fuchs , Leo Grady
Abstract: Systems and methods are disclosed for receiving a target image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning model, which may also be known as a machine learning system, to the target image to determine at least one characteristic of the target specimen and/or at least one characteristic of the target image, the machine learning model having been generated by processing a plurality of training images to predict at least one characteristic, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the at least one characteristic of the target specimen and/or the at least one characteristic of the target image.
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公开(公告)号：US11501872B2
公开(公告)日：2022-11-15
申请号：US17565629
申请日：2021-12-30
Applicant: PAIGE.AI, Inc.
Inventor： Patricia Raciti , Christopher Kanan , Alican Bozkurt , Belma Dogdas
Abstract: Systems and methods are disclosed for verifying slide and block quality for testing. The method may comprise receiving a collection of one or more digital images at a digital storage device. The collection may be associated with a tissue block and corresponding to an instance. The method may comprise applying a machine learning model to the collection to identify a presence or an absence of an attribute, determining an amount or a percentage of tissue with the attribute from a digital image in the collection that indicates the presence of the attribute, and outputting a quality score corresponding to the determined amount or percentage.
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公开(公告)号：US11475989B2
公开(公告)日：2022-10-18
申请号：US17399571
申请日：2021-08-11
Applicant: PAIGE.AI, Inc.
Inventor： Jeremy Daniel Kunz , Christopher Kanan , Patricia Raciti , Matthew G. Hanna
Abstract: Systems and methods are disclosed for providing automated routing of medical data, comprising determining at least one rule corresponding to at least one condition and at least one receiver, receiving medical data and associated medical metadata, determining whether the medical data, the associated medical metadata, and/or associated artificial intelligence processing satisfies the at least one condition of the at least one rule, and upon determining that the at least one condition of the at least one rule is satisfied, providing, from an originating institution, the medical data to the at least one receiver.
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34.发明授权公开(公告)号：US11455724B1
公开(公告)日：2022-09-27
申请号：US17457962
申请日：2021-12-07
Applicant: PAIGE.AI, Inc.
Inventor： Navid Alemi , Christopher Kanan , Leo Grady
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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35.发明授权公开(公告)号：US11436727B2
公开(公告)日：2022-09-06
申请号：US17406002
申请日：2021-08-18
Applicant: PAIGE.AI, Inc.
Inventor： Rodrigo Ceballos Lentini , Christopher Kanan , Belma Dogdas
Abstract: Systems and methods are disclosed for grouping cells in a slide image that share a similar target, comprising receiving a digital pathology image corresponding to a tissue specimen, applying a trained machine learning system to the digital pathology image, the trained machine learning system being trained to predict at least one target difference across the tissue specimen, and determining, using the trained machine learning system, one or more predicted clusters, each of the predicted clusters corresponding to a subportion of the tissue specimen associated with a target.
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Patent Agency Ranking
公开(公告)号：US11430116B2
公开(公告)日：2022-08-30
申请号：US17470901
申请日：2021-09-09
Applicant: PAIGE.AI, Inc.
Inventor： Antoine Sainson , Brandon Rothrock , Razik Yousfi , Patricia Raciti , Matthew Hanna , Christopher Kanan
Abstract: Systems and methods are disclosed for identifying formerly conjoined pieces of tissue in a specimen, comprising receiving one or more digital images associated with a pathology specimen, identifying a plurality of pieces of tissue by applying an instance segmentation system to the one or more digital images, the instance segmentation system having been generated by processing a plurality of training images, determining, using the instance segmentation system, a prediction of whether any of the plurality of pieces of tissue were formerly conjoined, and outputting at least one instance segmentation to a digital storage device and/or display, the instance segmentation comprising an indication of whether any of the plurality of pieces of tissue were formerly conjoined.
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37.发明授权公开(公告)号：US11315029B2
公开(公告)日：2022-04-26
申请号：US17303164
申请日：2021-05-21
Applicant: PAIGE.AI, Inc.
Inventor： Supriya Kapur , Christopher Kanan , Thomas Fuchs , Leo Grady
Abstract: Systems and methods are disclosed for receiving a target image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning model, which may also be known as a machine learning system, to the target image to determine at least one characteristic of the target specimen and/or at least one characteristic of the target image, the machine learning model having been generated by processing a plurality of training images to predict at least one characteristic, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the at least one characteristic of the target specimen and/or the at least one characteristic of the target image.
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38.发明授权公开(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：US11107573B2
公开(公告)日：2021-08-31
申请号：US17126865
申请日：2020-12-18
Applicant: PAIGE.AI, Inc.
Inventor： Belma Dogdas , Christopher Kanan , Thomas Fuchs , Leo Grady
Abstract: Systems and methods are disclosed for generating a specialized machine learning model by receiving a generalized machine learning model generated by processing a plurality of first training images to predict at least one cancer characteristic, receiving a plurality of second training images, the first training images and the second training images include images of tissue specimens and/or images algorithmically generated to replicate tissue specimens, receiving a plurality of target specialized attributes related to a respective second training image of the plurality of second training images, generating a specialized machine learning model by modifying the generalized machine learning model based on the plurality of second training images and the target specialized attributes, receiving a target image corresponding to a target specimen, applying the specialized machine learning model to the target image to determine at least one characteristic of the target image, and outputting the characteristic of the target image.
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公开(公告)号：US12183451B2
公开(公告)日：2024-12-31
申请号：US18461991
申请日：2023-09-06
Applicant: PAIGE.AI, Inc.
Inventor： Patricia Raciti , Christopher Kanan , Alican Bozkurt , Belma Dogdas
Abstract: Systems and methods are disclosed for verifying slide and block quality for testing. The method may comprise receiving a collection of one or more digital images at a digital storage device. The collection may be associated with a tissue block and corresponding to an instance. The method may comprise applying a machine learning model to the collection to identify a presence or an absence of an attribute, determining an amount or a percentage of tissue with the attribute from a digital image in the collection that indicates the presence of the attribute, and outputting a quality score corresponding to the determined amount or percentage.
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