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公开(公告)号：US12131817B2
公开(公告)日：2024-10-29
申请号：US18045907
申请日：2022-10-12
申请人： PAIGE.AI, Inc.
CPC分类号： G16H20/40 , A61N5/103 , G06N20/00 , G06T7/0012 , G06V10/25 , G16H50/30 , G06T2207/20081 , G06T2207/30024 , G06T2207/30096
摘要： Systems and methods are disclosed for predicting a resistance index associated with a tumor and surrounding tissue, comprising receiving one or more digital images of a pathology specimen, receiving additional information about a patient and/or a disease associated with the pathology specimen, determining at least one target region of the one or more digital images for analysis and removing a non-relevant region of the one or more digital images, applying a machine learning system to the one or more digital images to determine a resistance index for the target region of the one or more digital images, the machine learning system having been trained using a plurality of training images to predict the resistance index for the target region using a plurality of images of pathology specimens, and outputting the resistance index corresponding to the target region.
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公开(公告)号：US11887304B2
公开(公告)日：2024-01-30
申请号：US17655524
申请日：2022-03-18
申请人： PAIGE.AI, Inc.
发明人： Jason Locke , Jillian Sue , Christopher Kanan , Sese Ih
IPC分类号： G06K9/00 , A61B6/00 , G06T7/00 , G16H70/60 , G16H10/40 , G16H30/40 , G06N20/00 , G06T3/40 , G06T11/60
CPC分类号： G06T7/0012 , G06N20/00 , G06T3/40 , G06T11/60 , G16H10/40 , G16H30/40 , G16H70/60 , G06T2207/20081 , G06T2207/30024
摘要： Systems and methods are disclosed for analyzing an image of a slide corresponding to a specimen, the method including receiving at least one digitized image of a pathology specimen; determining, using the digitized image at an artificial intelligence (AI) system, at least one salient feature, the at least one salient comprising a biomarker, cancer, cancer grade, parasite, toxicity, inflammation, and/or cancer sub-type; determining, at the AI system, a salient region overlay for the digitized image, wherein the AI system indicates a value for each pixel; and suppressing, based on the value for each pixel, one or more non-salient regions of the digitized image.
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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
申请人： PAIGE.AI, Inc.
发明人： Brandon Rothrock , Christopher Kanan , Julian Viret , Thomas Fuchs , Leo Grady
摘要： 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：US11501869B2
公开(公告)日：2022-11-15
申请号：US17493917
申请日：2021-10-05
申请人： PAIGE.AI, Inc.
摘要： Systems and methods are disclosed for predicting a resistance index associated with a tumor and surrounding tissue, comprising receiving one or more digital images of a pathology specimen, receiving additional information about a patient and/or a disease associated with the pathology specimen, determining at least one target region of the one or more digital images for analysis and removing a non-relevant region of the one or more digital images, applying a machine learning system to the one or more digital images to determine a resistance index for the target region of the one or more digital images, the machine learning system having been trained using a plurality of training images to predict the resistance index for the target region using a plurality of images of pathology specimens, and outputting the resistance index corresponding to the target region.
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5.发明授权公开(公告)号：US11482319B2
公开(公告)日：2022-10-25
申请号：US17457451
申请日：2021-12-03
申请人： PAIGE.AI, INC.
摘要： 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.
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公开(公告)号：US11482317B2
公开(公告)日：2022-10-25
申请号：US17486371
申请日：2021-09-27
申请人： PAIGE.AI, Inc.
摘要： Systems and methods are disclosed for predicting a resistance index associated with a tumor and surrounding tissue, comprising receiving one or more digital images of a pathology specimen, receiving additional information about a patient and/or a disease associated with the pathology specimen, determining at least one target region of the one or more digital images for analysis and removing a non-relevant region of the one or more digital images, applying a machine learning system to the one or more digital images to determine a resistance index for the target region of the one or more digital images, the machine learning system having been trained using a plurality of training images to predict the resistance index for the target region using a plurality of images of pathology specimens, and outputting the resistance index corresponding to the target region.
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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
申请人： PAIGE.AI, Inc.
发明人： Brandon Rothrock , Christopher Kanan , Julian Viret , Thomas Fuchs , Leo Grady
摘要： 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：US20210210195A1
公开(公告)日：2021-07-08
申请号：US17126865
申请日：2020-12-18
申请人： PAIGE.AI, Inc.
发明人： Belma Dogdas , Christopher Kanan , Thomas Fuchs , Leo Grady
摘要： 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：US12131473B2
公开(公告)日：2024-10-29
申请号：US18523098
申请日：2023-11-29
申请人： PAIGE.AI, Inc.
IPC分类号： G06T7/00 , G06F18/214 , G16H30/40 , G16H50/20
CPC分类号： G06T7/0012 , G06F18/214 , G16H30/40 , G16H50/20 , G06T2207/10056 , G06T2207/20081 , G06T2207/30024 , G06T2207/30096 , G06V2201/03
摘要： Systems and methods are disclosed for processing an electronic image corresponding to a specimen. One method for processing the electronic image includes: receiving a target electronic image of a slide corresponding to a target specimen, the target specimen including a tissue sample from a patient, applying a machine learning system to the target electronic image to determine deficiencies associated with the target specimen, the machine learning system having been generated by processing a plurality of training images to predict stain deficiencies and/or predict a needed recut, the training images including images of human tissue and/or images that are algorithmically generated; and based on the deficiencies associated with the target specimen, determining to automatically order an additional slide to be prepared.
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10.发明授权公开(公告)号：US11994665B2
公开(公告)日：2024-05-28
申请号：US17815034
申请日：2022-07-26
申请人： PAIGE.AI, Inc.
CPC分类号： G02B21/365 , G02B21/368 , G06T7/70
摘要： A computer-implemented method of reviewing digital pathology data may include receiving a digital pathology image into a digital storage device, the digital pathology image being associated with a patient, providing for display the digital pathology image on a display, pairing the digital pathology image with a physical token of the digital pathology image in an interactive system, receiving one or more commands from the interactive system, determining one or more manipulations or modifications to the displayed digital pathology image based on the one or more commands, and providing for display a modified digital pathology image on the display according to the determined one or more manipulations or modifications.
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