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11.发明申请公开(公告)号：US20200381104A1
公开(公告)日：2020-12-03
申请号：US16884978
申请日：2020-05-27
Applicant: PAIGE.AI, Inc.
Inventor： Rodrigo CEBALLOS LENTINI , Christopher KANAN , Patricia RACITI , Leo GRADY , Thomas FUCHS
Abstract: 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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公开(公告)号：US20250069202A1
公开(公告)日：2025-02-27
申请号：US18944565
申请日：2024-11-12
Applicant: PAIGE.AI, Inc.
Inventor： Rodrigo CEBALLOS LENTINI , Christopher KANAN
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.
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13.发明申请公开(公告)号：US20250014181A1
公开(公告)日：2025-01-09
申请号：US18894147
申请日：2024-09-24
Applicant: PAIGE.AI, Inc.
Inventor： Rodrigo CEBALLOS LENTINI , Christopher KANAN , Patricia RACITI , Leo GRADY , Thomas FUCHS
IPC: G06T7/00 , G06F18/214 , G16H30/40 , G16H50/20
Abstract: 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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Patent Agency Ranking
公开(公告)号：US20240145067A1
公开(公告)日：2024-05-02
申请号：US18400539
申请日：2023-12-29
Applicant: PAIGE.AI, Inc.
Inventor： Rodrigo CEBALLOS LENTINI , Christopher KANAN
Abstract: Systems and methods are disclosed for generating synthetic medical images, including images presenting rare conditions or morphologies for which sufficient data may be unavailable. In one aspect, style transfer methods may be used. For example, a target medical image, a segmentation mask identifying style(s) to be transferred to area(s) of the target, and source medical image(s) including the style(s) may be received. Using the mask, the target may be divided into tile(s) corresponding to the area(s) and input to a trained machine learning system. For each tile, gradients associated with a content and style of the tile may be output by the system. Pixel(s) of at least one tile of the target may be altered based on the gradients to maintain content of the target while transferring the style(s) of the source(s) to the target. The synthetic medical image may be generated from the target based on the altering.
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15.发明公开公开(公告)号：US20230268059A1
公开(公告)日：2023-08-24
申请号：US18310801
申请日：2023-05-02
Applicant: PAIGE.AI, Inc.
Inventor： Christopher KANAN , Rodrigo CEBALLOS LENTINI , Jillian SUE , Thomas FUCHS , Leo GRADY
CPC classification number: G16H30/40 , G06T7/0012 , G16H50/20 , G06T2207/20081 , G06T2207/20084
Abstract: Systems and methods are disclosed for determining at least one geographic region of a plurality of geographic regions, at least one data variable, and/or at least one health variable, estimating a current prevalence of a data variable in a geographic region of the plurality of geographic regions, determining a trend in a relationship between the data variable and the geographic region at a current time, determining a second trend in the relationship between the data variable and the geographic region at at least one prior point in time, determining if the trend in the relationship is irregular within a predetermined threshold with respect to the second trend from the at least one prior point in time, and, upon determining that the trend in the relationship is irregular within a predetermined threshold, generating an alert.
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公开(公告)号：US20230010654A1
公开(公告)日：2023-01-12
申请号：US17732857
申请日：2022-04-29
Applicant: PAIGE.AI, Inc.
Inventor： Rodrigo CEBALLOS LENTINI , Christopher KANAN
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.
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17.发明申请公开(公告)号：US20220199234A1
公开(公告)日：2022-06-23
申请号：US17654614
申请日：2022-03-14
Applicant: PAIGE.AI, Inc.
Inventor： Rodrigo CEBALLOS LENTINI , Christopher KANAN , Patricia RACITI , Leo GRADY , Thomas FUCHS
Abstract: 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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18.发明申请公开(公告)号：US20210304876A1
公开(公告)日：2021-09-30
申请号：US17346923
申请日：2021-06-14
Applicant: PAIGE.AI, Inc.
Inventor： Rodrigo CEBALLOS LENTINI , Christopher KANAN , Patricia RACITI , Leo GRADY , Thomas FUCHS
Abstract: 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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