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71.发明公开公开(公告)号：US20240257296A1
公开(公告)日：2024-08-01
申请号：US18630072
申请日：2024-04-09
申请人： PAIGE.AI, Inc.
摘要： A method for processing an electronic image including receiving, by a viewer, the electronic image and a FOV (field of view), wherein the FOV includes at least one coordinate, at least one dimension, and a magnification factor, loading, by the viewer, a plurality of tiles within the FOV, determining, by the viewer, a state of the plurality of tiles in a cache, and in response to determining that the state of the plurality of tiles in the cache is a fully loaded state, rendering, by the viewer, the plurality of tiles to a display.
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72.发明授权公开(公告)号：US11995903B2
公开(公告)日：2024-05-28
申请号：US18186252
申请日：2023-03-20
申请人： PAIGE.AI, Inc.
发明人： Brandon Rothrock , Christopher Kanan , Julian Viret , Thomas Fuchs , Leo Grady
IPC分类号： G06V20/69 , G06F18/214 , G06N20/00 , G06T7/00 , G06T7/136 , G06T7/194 , G06V10/26 , G06V10/28
CPC分类号： G06V20/695 , G06F18/2155 , G06N20/00 , G06T7/0012 , G06T7/136 , G06T7/194 , G06V10/26 , G06V10/28 , G06V20/698 , G06T2207/20081 , G06T2207/30024
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：US20240144477A1
公开(公告)日：2024-05-02
申请号：US18400016
申请日：2023-12-29
申请人： PAIGE.AI, Inc.
发明人： Christopher KANAN , Belma DOGDAS , Patricia RACITI , Matthew LEE , Alican BOZKURT , Leo GRADY , Thomas FUCHS , Jorge S. REIS-FILHO
IPC分类号： G06T7/00 , G06F18/214 , G06N20/00 , G06T7/11 , G06V10/46 , G16H10/60 , G16H30/40 , G16H50/20
CPC分类号： G06T7/0012 , G06F18/214 , G06N20/00 , G06T7/11 , G06V10/462 , G16H10/60 , G16H30/40 , G16H50/20 , G06T2207/10081 , G06T2207/10088 , G06T2207/10104 , G06T2207/20081 , G06T2207/20084 , G06T2207/30024 , G06T2207/30068 , G06V2201/03
摘要： Systems and methods are disclosed for processing digital images to predict at least one continuous value comprising receiving one or more digital medical images, determining whether the one or more digital medical images includes at least one salient region, upon determining that the one or more digital medical images includes the at least one salient region, predicting, by a trained machine learning system, at least one continuous value corresponding to the at least one salient region, and outputting the at least one continuous value to an electronic storage device and/or display.
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公开(公告)号：US11928820B2
公开(公告)日：2024-03-12
申请号：US18174284
申请日：2023-02-24
申请人： PAIGE.AI, Inc.
发明人： Jillian Sue , Razik Yousfi , Peter Schueffler , Thomas Fuchs , Leo Grady
CPC分类号： G06T7/0014 , G16H30/40 , G16H50/20 , G16H70/60 , G06T2207/10056 , G06T2207/20081 , G06T2207/30024 , G06T2207/30168
摘要： Systems and methods are disclosed for receiving a digital image corresponding to a target specimen associated with a pathology category, determining a quality control (QC) machine learning model to predict a quality designation based on one or more artifacts, providing the digital image as an input to the QC machine learning model, receiving the quality designation for the digital image as an output from the machine learning model, and outputting the quality designation of the digital image. A quality assurance (QA) machine learning model may predict a disease designation based on one or more biomarkers. The digital image may be provided to the QA model which may output a disease designation. An external designation may be compared to the disease designation and a comparison result may be output.
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75.发明公开公开(公告)号：US20240062376A1
公开(公告)日：2024-02-22
申请号：US18487264
申请日：2023-10-16
申请人： PAIGE.AI, Inc.
发明人： Patricia RACITI , Christopher KANAN , Thomas FUCHS , Leo GRADY
IPC分类号： G06T7/00 , G06T7/194 , G06T7/11 , G06V10/764 , G06V10/776 , G06V10/82 , G06V10/98 , G06V20/69
CPC分类号： G06T7/0012 , G06T7/194 , G06T7/11 , G06V10/764 , G06V10/776 , G06V10/82 , G06V10/993 , G06V20/69 , G06T2207/20084 , G06T2207/30024 , G06T2207/20081 , G06T2207/10056 , G06V2201/03
摘要： Systems and methods are disclosed for receiving one or more digital images associated with a tissue specimen, detecting one or more image regions from a background of the one or more digital images, determining a prediction, using a machine learning system, of whether at least one first image region of the one or more image regions comprises at least one external contaminant, the machine learning system having been trained using a plurality of training images to predict a presence of external contaminants and/or a location of any external contaminants present in the tissue specimen, and determining, based on the prediction of whether a first image region comprises an external contaminant, whether to process the image region using an processing algorithm.
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公开(公告)号：US20230410987A1
公开(公告)日：2023-12-21
申请号：US18461617
申请日：2023-09-06
申请人： PAIGE.AI, Inc.
CPC分类号： G16H30/40 , G16H10/60 , G16H30/20 , G06N20/00 , G06T7/0012 , G06F18/2413
摘要： Systems and methods are disclosed for using an integrated computing platform to view and transfer digital pathology slides using artificial intelligence, the method including receiving at least one whole slide image in a cloud computing environment located in a first geographic region, the whole slide image depicting a medical sample associated with a patient, the patient being located in the first geographic region; storing the received whole slide image in a first encrypted bucket; applying artificial intelligence to perform a classification of the at least one whole slide image, the classification comprising steps to determine whether portions of the medical sample depicted in the whole slide image are healthy or diseased; based on the classification of the at least one whole slide image, generating metadata associated with the whole slide image; and storing the metadata in a second encrypted bucket.
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公开(公告)号：US11823436B2
公开(公告)日：2023-11-21
申请号：US17710613
申请日：2022-03-31
申请人： PAIGE.AI, Inc.
发明人： Belma Dogdas , Christopher Kanan , Thomas Fuchs , Leo Grady
CPC分类号： G06V10/764 , G06T7/0012 , G06V10/82 , G06V20/698 , G16H30/40 , G16H50/20 , G06T2207/20081 , G06T2207/30024 , G06T2207/30096
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：US20230368894A1
公开(公告)日：2023-11-16
申请号：US18316736
申请日：2023-05-12
申请人： PAIGE.AI, Inc.
发明人： Jeremy Daniel KUNZ , Donghun LEE
CPC分类号： G16H30/20 , G06T7/0012 , G06V10/761 , G06T2207/20081
摘要： Systems and methods are described herein for processing electronic medical images. For example, one or more digital medical images of at least one pathology specimen, the pathology specimen being associated with a patient may be received. Additionally, an external designation of the one or more digital medical images may be received. The one or more digital medical images may be provided to one or more machine learning systems, the one or more machine learning systems each having been trained to analyze medical images using one of a plurality of versions of a protocol. The one or more machine learning systems, may determine machine learning system designations for the one or more digital medical images. The external designation may be compared to the machine learning system designations and, based on the comparison, determining whether the external designation matches a predetermined protocol.
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79.发明公开公开(公告)号：US20230360414A1
公开(公告)日：2023-11-09
申请号：US18346391
申请日：2023-07-03
申请人： PAIGE.AI, Inc.
发明人： Brandon ROTHROCK , Jillian SUE , Matthew HOULISTON , Patricia RACITI , Leo GRADY
CPC分类号： G06V20/695 , G06T7/11 , G06N20/00 , G06V20/698 , G06T7/194 , G16H30/40 , G06T7/0012 , G06F18/2431 , G06T2207/20081 , G06T2207/30024
摘要： A method of using a machine learning model to output a task-specific prediction may include receiving a digitized cytology image of a cytology sample and applying a machine learning model to isolate cells of the digitized cytology image. The machine learning model may include identifying a plurality of sub-portions of the digitized cytology image, identifying, for each sub-portion of the plurality of sub-portions, either background or cell, and determining cell sub-images of the digitized cytology image. Each cell sub-image may comprise a cell of the digitized cytology image, based on the identifying either background or cell. The method may further comprise determining a plurality of features based on the cell sub-images, each of the cell sub-images being associated with at least one of the plurality of features, determining an aggregated feature based on the plurality of features, and training a machine learning model to predict a target task based on the aggregated feature.
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公开(公告)号：US11791035B2
公开(公告)日：2023-10-17
申请号：US17539664
申请日：2021-12-01
申请人： PAIGE.AI, Inc.
CPC分类号： G16H30/40 , G06N20/00 , G06T7/0014 , G16H50/20 , G16H70/60
摘要： 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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