公开(公告)号：US11282595B2

公开(公告)日：2022-03-22

申请号：US17022324

申请日：2020-09-16

Applicant: Enlitic, Inc.

Inventor： Li Yao ,  Jordan Prosky ,  Eric C. Poblenz ,  Kevin Lyman ,  Lionel Lints ,  Ben Covington ,  Anthony Upton

IPC: G06K9/00 ,  G16H10/60 ,  H04L67/01 ,  G16H30/40 ,  G16H15/00 ,  G06K9/62 ,  G06T5/00 ,  G06T5/50 ,  G06T7/00 ,  G06T11/00 ,  G06N5/04 ,  G16H30/20 ,  G06N20/00 ,  G06F9/54 ,  G06T7/187 ,  G06T7/11 ,  G06F3/0482 ,  G06T3/40 ,  A61B5/00 ,  G16H50/20 ,  G06F21/62 ,  G06Q20/14 ,  G16H40/20 ,  G06F3/0484 ,  G06Q10/06 ,  G16H10/20 ,  G06T7/10 ,  G06T11/20 ,  G06F16/245 ,  G06T7/44 ,  G06N20/20 ,  G06K9/20 ,  H04L67/12 ,  G16H50/70 ,  G06T7/70 ,  G16H50/30 ,  A61B5/055 ,  A61B6/03 ,  A61B8/00 ,  G06K9/66 ,  A61B6/00 ,  G06Q50/22 ,  G06F40/295

Abstract: A multi-label heat map generating system is operable to receive a plurality of medical scans and a corresponding plurality of global labels that each correspond to one of a set of abnormality classes. A computer vision model is generated by training on the medical scans and the global labels. Probability matrix data, which includes a set of image patch probability values that each indicate a probability that a corresponding one of the set of abnormality classes is present in each of a set of image patches, is generated by performing an inference function that utilizes the computer vision model on a new medical scan. Heat map visualization data can be generated for transmission to a client device based on the probability matrix data that indicates, for each of the set of abnormality classes, a color value for each pixel of the new medical scan.

公开(公告)号：US20220076793A1

公开(公告)日：2022-03-10

申请号：US17455066

申请日：2021-11-16

Applicant: Enlitic, Inc.

Inventor： Kevin Lyman ,  Anthony Upton ,  Lionel Lints ,  Ben Covington ,  Alexander Rhodes

IPC: G16H10/60 ,  H04L29/06 ,  G16H30/40 ,  G16H15/00 ,  G06K9/62 ,  G06T5/00 ,  G06T5/50 ,  G06T7/00 ,  G06T11/00 ,  G06N5/04 ,  G16H30/20 ,  G06N20/00 ,  G06F9/54 ,  G06T7/187 ,  G06T7/11 ,  G06F3/0482 ,  G06T3/40 ,  A61B5/00 ,  G16H50/20 ,  G06F21/62 ,  G06Q20/14 ,  G16H40/20 ,  G06F3/0484 ,  G06Q10/06 ,  G16H10/20 ,  G06T7/10 ,  G06T11/20 ,  G06F16/245 ,  G06T7/44 ,  G06N20/20 ,  G06K9/20 ,  H04L29/08

Abstract: A medical scan system is operable to receive a set of labeling data corresponding to a set of medical scans from each of a set of client devices corresponding to a set of users. The set of medical scans and each set of labeling data is transmitted to an expert client device associated with an expert user, and a set of golden labeling data and a plurality of sets of correction data are received from the expert client device. A set of performance score data is generated based on the plurality of sets of correction data, and each performance score data of the set of performance score data is assigned to a corresponding one of the set of users. An updated training set that includes the set of golden labeling data is generated, and a medical scan analysis function is retrained based on the updated training set.

公开(公告)号：US10818386B2

公开(公告)日：2020-10-27

申请号：US16299706

申请日：2019-03-12

Applicant: Enlitic, Inc.

Inventor： Li Yao ,  Jordan Prosky ,  Eric C. Poblenz ,  Kevin Lyman ,  Lionel Lints ,  Ben Covington ,  Anthony Upton

IPC: G06K9/00 ,  G16H10/60 ,  H04L29/06 ,  G16H30/40 ,  G16H15/00 ,  G06K9/62 ,  G06T5/00 ,  G06T5/50 ,  G06T7/00 ,  G06T11/00 ,  G06N5/04 ,  G16H30/20 ,  G06N20/00 ,  G06F9/54 ,  G06T7/187 ,  G06T7/11 ,  G06F3/0482 ,  G06T3/40 ,  A61B5/00 ,  G16H50/20 ,  G06F21/62 ,  G06Q20/14 ,  G16H40/20 ,  G06F3/0484 ,  G06Q10/06 ,  G16H10/20 ,  G06T7/10 ,  G06T11/20 ,  G06F16/245 ,  G06T7/44 ,  G06N20/20 ,  G06K9/20 ,  H04L29/08 ,  G16H50/70 ,  G06T7/70 ,  G16H50/30 ,  A61B5/055 ,  A61B6/03 ,  A61B8/00 ,  G06K9/66 ,  A61B6/00 ,  G06Q50/22 ,  G06F40/295

Abstract: A multi-label heat map generating system is operable to receive a plurality of medical scans and a corresponding plurality of global labels that each correspond to one of a set of abnormality classes. A computer vision model is generated by training on the medical scans and the global labels. Probability matrix data, which includes a set of image patch probability values that each indicate a probability that a corresponding one of the set of abnormality classes is present in each of a set of image patches, is generated by performing an inference function that utilizes the computer vision model on a new medical scan. Heat map visualization data can be generated for transmission to a client device based on the probability matrix data that indicates, for each of the set of abnormality classes, a color value for each pixel of the new medical scan.

公开(公告)号：US20200160975A1

公开(公告)日：2020-05-21

申请号：US16299706

申请日：2019-03-12

Applicant: Enlitic, Inc.

Inventor： Li Yao ,  Jordan Prosky ,  Eric C. Poblenz ,  Kevin Lyman ,  Lionel Lints ,  Ben Covington ,  Anthony Upton

IPC: G16H30/40 ,  G06T7/00 ,  G06T11/20 ,  G06T11/00 ,  G06K9/62

Abstract: A multi-label heat map generating system is operable to receive a plurality of medical scans and a corresponding plurality of global labels that each correspond to one of a set of abnormality classes. A computer vision model is generated by training on the medical scans and the global labels. Probability matrix data, which includes a set of image patch probability values that each indicate a probability that a corresponding one of the set of abnormality classes is present in each of a set of image patches, is generated by performing an inference function that utilizes the computer vision model on a new medical scan. Heat map visualization data can be generated for transmission to a client device based on the probability matrix data that indicates, for each of the set of abnormality classes, a color value for each pixel of the new medical scan.