公开(公告)号：EP4364103A1

公开(公告)日：2024-05-08

申请号：EP22743774.6

申请日：2022-06-29

Applicant: Université de Lausanne

Inventor： HÜGLE, Thomas

IPC: G06V10/82 ,  G06V40/10

CPC classification number: G06V10/82 ,  G06V40/107 ,  G06V2201/0320220101 ,  G06V2201/03320220101

公开(公告)号：EP4361947A2

公开(公告)日：2024-05-01

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：EP4325201A3

公开(公告)日：2024-05-01

申请号：EP23210069.3

申请日：2022-07-26

Applicant: HONEYWELL INTERNATIONAL INC.

Inventor： SHTYLENKO, Andrey ,  BROWN, Andy Walker ,  McBRADY, Adam Dewey ,  TUMULURI, Ratna Dinakar

IPC: G01N15/14

CPC classification number: G01N15/1434 ,  G01N2015/145420130101 ,  G01N15/0227 ,  G01N2015/004620130101 ,  G01N15/1429 ,  G01N2015/149320130101 ,  G01N2015/148620130101 ,  G01N15/0612 ,  G03H2001/088320130101 ,  G03H2001/003820130101 ,  G06V2201/0320220101 ,  G06V10/774 ,  G06V10/54 ,  G06V10/764 ,  G01N15/01 ,  G01N15/1433

Abstract: Embodiments of the present disclosure provide for improved generation and outputting of object identification data indicating object classifications for object representations. Such objects representations may correspond to depictions of objects in images captured using digital holographic microscopy. Some embodiments generate object identification data by comparing object representations in focused image(s) with specially configured annotated focused images, for example using a specially trained neural network or other machine learning model trained based on such annotated focused images. The annotated focused images are generated including a plurality of channels, each associated with a different grayscale focused image at a different target focal length of a range of target focal lengths. In this regard, model(s), algorithm(s), and/or other specially configured implementations may learn the spatial features of particular object representations and associated object identification data. The trained models may be used to perform accurate comparisons with the annotated focused images.

公开(公告)号：EP3680821B1

公开(公告)日：2024-04-24

申请号：EP19217485.2

申请日：2019-12-18

IPC: G06V10/44 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06V10/454 ,  G06V2201/0320220101 ,  G06V10/82 ,  G06V10/764

公开(公告)号：EP4352706A1

公开(公告)日：2024-04-17

申请号：EP22747805.4

申请日：2022-06-10

Applicant: GENENTECH, INC.

Inventor： ZHANG, Miao ,  MOVVA, Nagamurali K. ,  ABBASPOUR TEHRANI, Mahdi

IPC: G06V10/94 ,  G06V10/82 ,  G06V10/774 ,  G06V20/70 ,  G06K9/62

CPC classification number: G06V10/945 ,  G06V10/82 ,  G06V10/774 ,  G06V20/70 ,  G06V2201/0320220101 ,  G06F18/25