公开(公告)号：EP4402645A1

公开(公告)日：2024-07-24

申请号：EP22870719.6

申请日：2022-09-15

Applicant: Kaliber Labs Inc.

Inventor： JONELAGADDA, Chandra ,  JONELAGADDA, Aneesh ,  RUIZ, Mark

IPC: G06V10/40

CPC classification number: G06V20/49 ,  G06V2201/0320220101 ,  G06V10/82

公开(公告)号：EP4088649B1

公开(公告)日：2024-07-17

申请号：EP21198357.2

申请日：2021-09-22

IPC: G06V40/18 ,  G06V10/44 ,  G06V10/82 ,  A61B3/12 ,  G16H30/40 ,  G16H50/20

CPC classification number: G06V10/82 ,  G06V40/18 ,  G06V2201/0320220101 ,  G06V10/454 ,  G16H50/20 ,  G16H30/40

公开(公告)号：EP4391958A1

公开(公告)日：2024-07-03

申请号：EP22859732.4

申请日：2022-08-22

Applicant: Aicad Dental Inc.

Inventor： COULOMBE, Fabien ,  PATEL, Akshaykumar Ketankumar

IPC: A61C9/00 ,  A61C7/00 ,  A61C13/00 ,  G06N3/08 ,  G06T11/00 ,  G06T17/20

CPC classification number: G06T19/00 ,  G06T2219/00820130101 ,  G06T15/06 ,  G06T2210/4120130101 ,  G06V10/82 ,  G06V20/64 ,  G06V2201/0320220101

公开(公告)号：EP4361947A3

公开(公告)日：2024-06-19

申请号：EP23192041.4

申请日：2019-03-22

Applicant: Memorial Sloan-Kettering Cancer Center

Inventor： FUCHS, Thomas ,  CAMPANELLA, Gabriele

IPC: G06T7/00

CPC classification number: G16H50/70 ,  G16H50/30 ,  G16H50/20 ,  G06T7/0012 ,  G06T2207/1005620130101 ,  G06T2207/2002120130101 ,  G06T2207/2008120130101 ,  G06T2207/2008420130101 ,  G06T2207/3009620130101 ,  G06T2207/3002420130101 ,  G06V2201/0320220101 ,  G06V10/7635 ,  G06V10/764 ,  G06F18/2323

Abstract: The present disclosure is directed to systems and methods for classifying biomedical images. A feature classifier may generate a plurality of tiles from a biomedical image. Each tile may correspond to a portion of the biomedical image. The feature classifier may select a subset of tiles from the plurality of tiles by applying an inference model. The subset of tiles may have highest scores. Each score may indicate a likelihood that the corresponding tile includes a feature indicative of the presence of the condition. The feature classifier may determine a classification result for the biomedical image by applying an aggregation model. The classification result may indicate whether the biomedical includes the presence or lack of the condition.

公开(公告)号：EP3738100B1

公开(公告)日：2024-06-12

申请号：EP19700465.8

申请日：2019-01-10

IPC: G06T7/11 ,  G06V10/44 ,  G06V10/764

CPC classification number: G06T2207/1007220130101 ,  G06T2207/2002120130101 ,  G06T2207/2008120130101 ,  G06T2207/3000420130101 ,  G06T7/11 ,  G06T2207/2008420130101 ,  G06V10/454 ,  G06V2201/0320220101 ,  G06V10/764

公开(公告)号：EP4375857A1

公开(公告)日：2024-05-29

申请号：EP22845039.1

申请日：2022-06-15

Applicant: Tencent Technology (Shenzhen) Company Limited

Inventor： WEN, Qingfu ,  DU, Yuexi ,  YANG, Sen ,  YANG, Peng ,  ZHANG, Jun ,  HAN, Xiao

IPC: G06F18/00 ,  G06N3/08

CPC classification number: G06V10/82 ,  G06V2201/0320220101 ,  G06V10/771 ,  G06T7/0012 ,  G06T2207/1002420130101 ,  G06T2207/1005620130101 ,  G06T2207/2008120130101 ,  G06T2207/2008420130101 ,  G06T2207/3002420130101

Abstract: Provided are a supervised learning method and apparatus for image features, a device, and a storage medium, relating to the field of artificial intelligence. The method includes: performing (401) a data enhancement on an original medical image to obtain a first enhanced image and a second enhanced image, the first enhanced image and the second enhanced image being positive samples of each other; performing (402) feature extractions on the first enhanced image and the second enhanced image by a feature extraction model to obtain a first image feature of the first enhanced image and a second image feature of the second enhanced image; determining (403) a model loss of the feature extraction model based on the first image feature, the second image feature, and a negative sample image feature, the negative sample image feature being an image feature corresponding to other original medical images; and training (404) the feature extraction model based on the model loss. The self-supervised learning is used to enable the feature extraction model learn the image features of the medical image, without manual annotation on the image, which improves a model training efficiency.

公开(公告)号：EP4367605A1

公开(公告)日：2024-05-15

申请号：EP22753873.3

申请日：2022-07-18

Applicant: GOOGLE LLC

Inventor： SELLERGREN, Andrew ,  KRISHNAN, Dilip ,  SHETTY, Shravya

IPC: G06N3/08 ,  G06N3/04 ,  G06F18/40 ,  G06V10/77 ,  G06V10/774 ,  G06V10/776 ,  G06V10/94 ,  G16H30/40 ,  G16H50/70

CPC classification number: G16H30/40 ,  G16H50/70 ,  G06V10/77 ,  G06V10/774 ,  G06V10/776 ,  G06V10/95 ,  G06V2201/0320220101 ,  G06F18/2137 ,  G06F18/217 ,  G06F18/214 ,  G06N3/0464 ,  G06N3/09 ,  G06N3/096 ,  G06N3/0455

公开(公告)号：EP4366656A1

公开(公告)日：2024-05-15

申请号：EP22836432.9

申请日：2022-07-05

Applicant: Orthodontia Vision Inc.

Inventor： FALLAHA, Charles ,  BACH, Normand

IPC: A61C19/05 ,  G06N3/08 ,  G06V10/82 ,  G06V10/764

CPC classification number: A61C19/05 ,  G06V10/82 ,  G06V10/77 ,  G06V2201/0320220101 ,  G06N3/09 ,  G06N3/048 ,  G06N5/01 ,  G06N3/045 ,  G16H50/20 ,  G16H30/40 ,  G16H50/70

公开(公告)号：EP4061230B1

公开(公告)日：2024-05-15

申请号：EP20807701.6

申请日：2020-11-13

IPC: A61B8/00 ,  G05B13/02 ,  G06N3/02 ,  G06N7/00 ,  G06N20/00 ,  G16H50/20 ,  A61B8/08 ,  G16H30/40 ,  G16H30/20 ,  G06V10/82 ,  G06V10/44 ,  G06N3/08 ,  G06N3/045 ,  G06F18/214

CPC classification number: G16H50/20 ,  A61B8/4245 ,  A61B8/5223 ,  G16H30/40 ,  G16H30/20 ,  G06N3/08 ,  G06V10/454 ,  G06V2201/0320220101 ,  G06V10/82 ,  G06N3/045 ,  G06F18/214

公开(公告)号：EP3873339B1

公开(公告)日：2024-05-15

申请号：EP19797560.0

申请日：2019-10-30

IPC: A61B5/055 ,  G06T7/00

CPC classification number: A61B5/055 ,  A61B5/4088 ,  G06V10/267 ,  G06V2201/0320220101