公开(公告)号：US20210193300A1

公开(公告)日：2021-06-24

申请号：US17107121

申请日：2020-11-30

Applicant: PAIGE.AI, Inc.

Inventor： Christopher KANAN ,  Rodrigo CEBALLOS LENTINI ,  Jillian SUE ,  Thomas FUCHS ,  Leo GRADY

IPC: G16H30/40 ,  G16H50/20 ,  G06T7/00

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.

公开(公告)号：US20250166794A1

公开(公告)日：2025-05-22

申请号：US19028063

申请日：2025-01-17

Applicant: PAIGE.AI, Inc.

Inventor： Rodrigo CEBALLOS LENTINI ,  Christopher KANAN

IPC: G16H30/20 ,  G06N20/00 ,  G06T7/00 ,  G06T7/11 ,  G16H30/40 ,  G16H50/50

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.

公开(公告)号：US20230342931A1

公开(公告)日：2023-10-26

申请号：US18342032

申请日：2023-06-27

Applicant: PAIGE.AI, Inc.

Inventor： Rodrigo CEBALLOS LENTINI ,  Christopher KANAN ,  Belma DOGDAS

IPC: G06T7/00 ,  G06T7/11 ,  G16H50/20 ,  G06N20/00 ,  G06V10/762 ,  G06V30/19 ,  G16B40/00 ,  G06F18/23213

CPC classification number: G06T7/0012 ,  G06T7/11 ,  G16H50/20 ,  G06N20/00 ,  G06V10/763 ,  G06V30/19107 ,  G16B40/00 ,  G06F18/23213 ,  G06T2207/20081 ,  G06T2207/30024 ,  G06T2207/30096

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.

公开(公告)号：US20220366563A1

公开(公告)日：2022-11-17

申请号：US17815671

申请日：2022-07-28

Applicant: PAIGE.AI, Inc.

Inventor： Rodrigo CEBALLOS LENTINI ,  Christopher KANAN ,  Belma DOGDAS

IPC: G06T7/00 ,  G06T7/11 ,  G16H50/20 ,  G06N20/00 ,  G06K9/62 ,  G06V10/762 ,  G06V30/19

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.

公开(公告)号：US20210193301A1

公开(公告)日：2021-06-24

申请号：US17119885

申请日：2020-12-11

Applicant: PAIGE.AI, Inc.

Inventor： Christopher KANAN ,  Rodrigo CEBALLOS LENTINI ,  Jillian SUE ,  Thomas FUCHS ,  Leo GRADY

IPC: G16H30/40 ,  G16H50/20 ,  G06T7/00

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.

公开(公告)号：US20210118553A1

公开(公告)日：2021-04-22

申请号：US17137769

申请日：2020-12-30

Applicant: PAIGE.AI, Inc.

Inventor： Rodrigo CEBALLOS LENTINI ,  Christopher KANAN ,  Patricia RACITI ,  Leo GRADY ,  Thomas FUCHS

IPC: G16H30/40 ,  G16H50/20 ,  G06K9/62 ,  G06T7/00

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.

公开(公告)号：US20240095920A1

公开(公告)日：2024-03-21

申请号：US18523098

申请日：2023-11-29

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

CPC classification number: G06T7/0012 ,  G06F18/214 ,  G16H30/40 ,  G16H50/20 ,  G06T2207/10056 ,  G06T2207/20081 ,  G06T2207/30024 ,  G06T2207/30096 ,  G06V2201/03

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.

公开(公告)号：US20230215546A1

公开(公告)日：2023-07-06

申请号：US18181630

申请日：2023-03-10

Applicant: PAIGE.AI, Inc.

Inventor： Rodrigo CEBALLOS LENTINI ,  Christopher KANAN

IPC: G16H30/20 ,  G06T7/00 ,  G16H30/40 ,  G16H50/50 ,  G06N20/00

CPC classification number: G16H30/20 ,  G06T7/0012 ,  G16H30/40 ,  G16H50/50 ,  G06N20/00 ,  G06T7/11

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.

公开(公告)号：US20230012002A1

公开(公告)日：2023-01-12

申请号：US17806519

申请日：2022-06-13

Applicant: PAIGE.AI, Inc.

Inventor： Rodrigo CEBALLOS LENTINI ,  Christopher KANAN

IPC: G16H30/20 ,  G16H50/50 ,  G16H30/40 ,  G06N20/00 ,  G06T7/00

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.

公开(公告)号：US20220293251A1

公开(公告)日：2022-09-15

申请号：US17804123

申请日：2022-05-26

Applicant: PAIGE.AI, Inc.

Inventor： Rodrigo CEBALLOS LENTINI ,  Christopher KANAN ,  Patricia RACITI ,  Leo GRADY ,  Thomas FUCHS

IPC: G16H30/40 ,  G06T7/00 ,  G06K9/62 ,  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.