公开(公告)号：US20220139533A1

公开(公告)日：2022-05-05

申请号：US17511871

申请日：2021-10-27

Applicant: PAIGE.AI, Inc.

Inventor： Brandon ROTHROCK ,  Jillian SUE ,  Matthew HOULISTON ,  Patricia RACITI ,  Leo GRADY

IPC: G16H30/40 ,  G06N20/00 ,  G06T7/00 ,  G06V20/69 ,  G06T7/194

Abstract: 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.

公开(公告)号：US20220138450A1

公开(公告)日：2022-05-05

申请号：US17519847

申请日：2021-11-05

Applicant: PAIGE.AI, Inc.

Inventor： Brandon ROTHROCK ,  Jillian SUE ,  Matthew HOULISTON ,  Patricia RACITI ,  Leo GRADY

IPC: G06K9/00 ,  G06T7/11 ,  G06N20/00 ,  G06K9/62

Abstract: 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.

公开(公告)号：US20220108446A1

公开(公告)日：2022-04-07

申请号：US17492745

申请日：2021-10-04

Applicant: PAIGE.AI, Inc.

Inventor： Antoine SAINSON ,  Brandon ROTHROCK ,  Razik YOUSFI ,  Patricia RACITI ,  Matthew HANNA ,  Christopher KANAN

IPC: G06T7/00 ,  G06T7/11

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.

公开(公告)号：US20220108444A1

公开(公告)日：2022-04-07

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

IPC: G06T7/00 ,  G06T7/11

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.