公开(公告)号：US11710235B2

公开(公告)日：2023-07-25

申请号：US17552438

申请日：2021-12-16

Applicant: PAIGE.AI, Inc.

Inventor： Danielle Gorton ,  Patricia Raciti ,  Jillian Sue ,  Razik Yousfi

IPC: G06K9/00 ,  G06T7/00 ,  G06V10/25 ,  G06V10/12 ,  G06V10/77 ,  G16H10/40 ,  G16H15/00 ,  G16H50/20 ,  G16H30/40 ,  G16H80/00 ,  G06T11/60

CPC classification number: G06T7/0014 ,  G06T11/60 ,  G06V10/12 ,  G06V10/25 ,  G06V10/7715 ,  G16H10/40 ,  G16H15/00 ,  G16H30/40 ,  G16H50/20 ,  G16H80/00 ,  G06T2207/10004 ,  G06T2207/30004 ,  G06T2207/30024 ,  G06V2201/03

Abstract: A computer-implemented method of using a machine learning model to categorize a sample in digital pathology may include receiving one or more cases, each associated with digital images of a pathology specimen; identifying, using the machine learning model, a case as ready to view; receiving a selection of the case, the case comprising a plurality of parts; determining, using the machine learning model, whether the plurality of parts are suspicious or non-suspicious; receiving a selection of a part of the plurality of parts; determining whether a plurality of slides associated with the part are suspicious or non-suspicious; determining, using the machine learning model, a collection of suspicious slides, of the plurality of slides, the machine learning model having been trained by processing a plurality of training images; and annotating the collection of suspicious slides and/or generating a report based on the collection of suspicious slides.

公开(公告)号：US20230230398A1

公开(公告)日：2023-07-20

申请号：US18002423

申请日：2021-06-02

Applicant: SONY GROUP CORPORATION

Inventor： YOHEI KOBAYASHI ,  TAKESHI KUNIHIRO ,  JUNICHIRO ENOKI ,  KENJI YAMANE ,  YUTAKA HASEGAWA

IPC: G06V20/69 ,  G06V10/44 ,  G06V10/22 ,  G06T7/73 ,  G06T7/00 ,  G06V10/77 ,  G16H30/40 ,  G06T7/11

CPC classification number: G06V20/695 ,  G06V10/44 ,  G06V10/22 ,  G06T7/73 ,  G06T7/0012 ,  G06V10/7715 ,  G06V20/698 ,  G16H30/40 ,  G06T7/11 ,  G06T2207/10056 ,  G06V2201/03 ,  G06T2207/30096 ,  G06T2207/30024

Abstract: An image processing device 100 includes, in a case where designation of a plurality of partial regions corresponding to a cell morphology is received, the plurality of partial regions being extracted from a pathological image, a generation unit 154 that generates auxiliary information indicating information about a feature amount effective when a plurality of partial regions is classified or extracted with respect to a plurality of feature amounts calculated from the image; and in a case where setting information about an adjustment item according to the auxiliary information is received, an image processing unit 155 that performs an image process on the image using the setting information.

公开(公告)号：US20230222664A1

公开(公告)日：2023-07-13

申请号：US18009839

申请日：2021-06-14

Applicant: MELANIE CROMBIE WILLIAMS CAMPBELL ,  YUNYI QIU ,  PETER ANDREW CHARLES NEATHWAY

Inventor： MELANIE CROMBIE WILLIAMS CAMPBELL ,  YUNYI QIU ,  PETER ANDREW CHARLES NEATHWAY

IPC: G06T7/00 ,  G06V10/764 ,  G06V10/60 ,  G06V10/22 ,  A61B3/12 ,  A61B3/00 ,  A61B5/00

CPC classification number: G06T7/0016 ,  A61B3/0008 ,  A61B3/12 ,  A61B5/4088 ,  G06V10/60 ,  G06V10/225 ,  G06V10/764 ,  G06T2207/20084 ,  G06T2207/30041 ,  G06T2207/30204 ,  G06V2201/03

Abstract: The present disclosure provides methods and an apparatus for imaging and analysing images of presumed protein deposits in the retina, retinal tissue or retinal structures and discloses methods differentiating or classifying these deposits and other optical signals from retinal structures into 1) whether they contain or do not contain classes, of proteins or protein deposits called amyloids or other proteins and/or protein deposits related to neurodegenerative eye and brain disease(s); 2) which type(s) of amyloid or other proteins or protein deposits they contain, as well as 3) whether the form and/or properties of the deposit are associated with a class of diseases or with one or another specific condition(s) (or disease(s)); whether or not this is a disease or class of disease associated with the retina or more generally with the nervous system, including the brain or 4) classified as associated with one or another level of severity of condition(s), or disease(s).

公开(公告)号：US20230206447A1

公开(公告)日：2023-06-29

申请号：US18177733

申请日：2023-03-02

Applicant: NATIONAL CANCER CENTER ,  FUJIFILM Corporation

Inventor： Kazuma KOBAYASHI ,  Mototaka MIYAKE ,  Ryuji HAMAMOTO ,  Jun MASUMOTO

IPC: G06T7/00 ,  G06V10/25 ,  G06V10/774 ,  G06V20/70 ,  G06V10/74 ,  G06V10/77 ,  G06F16/532

CPC classification number: G06T7/0014 ,  G06V10/25 ,  G06V10/774 ,  G06V20/70 ,  G06V10/761 ,  G06V10/7715 ,  G06F16/532 ,  G06V2201/03 ,  G06T2200/04 ,  G06T2207/30016 ,  G06T2207/20081 ,  G06T2207/20076 ,  G06T2207/20021

Abstract: A processor encodes a target image to derive at least one first feature amount indicating an image feature for an abnormality of a region of interest included in the target image. In addition, the processor encodes the target image to derive at least one second feature amount indicating an image feature for an image in a case in which the region of interest included in the target image is a normal region.

公开(公告)号：US11681962B2

公开(公告)日：2023-06-20

申请号：US17453082

申请日：2021-11-01

Applicant: Enlitic, Inc.

Inventor： Kevin Lyman ,  Anthony Upton ,  Li Yao ,  Ben Covington

IPC: G16H15/00 ,  G16H30/20 ,  G06Q10/0631 ,  G16H10/60 ,  G16H30/40 ,  G06T5/00 ,  G06T5/50 ,  G06T7/00 ,  G06T11/00 ,  G06N5/04 ,  G06N20/00 ,  G06F9/54 ,  G06T7/187 ,  G06T7/11 ,  G06F3/0482 ,  G06T3/40 ,  A61B5/00 ,  G16H50/20 ,  G06F21/62 ,  G06Q20/14 ,  G16H40/20 ,  G06F3/0484 ,  G16H10/20 ,  G06N5/045 ,  G06T7/10 ,  G06T11/20 ,  G06F16/245 ,  G06T7/44 ,  G06N20/20 ,  H04L67/12 ,  H04L67/01 ,  G06V10/82 ,  G06F18/40 ,  G06F18/214 ,  G06F18/21 ,  G06F18/2115 ,  G06F18/2415 ,  G06V10/25 ,  G06V30/19 ,  G06V10/764 ,  G06V40/16 ,  G06V10/22 ,  G16H50/70 ,  G06T7/70 ,  G16H50/30 ,  A61B5/055 ,  A61B6/03 ,  A61B8/00 ,  A61B6/00 ,  G06Q50/22 ,  G06F40/295 ,  G06F18/24 ,  G06F18/2111 ,  G06V30/194

CPC classification number: G06Q10/06315 ,  A61B5/7264 ,  G06F3/0482 ,  G06F3/0484 ,  G06F9/542 ,  G06F16/245 ,  G06F18/214 ,  G06F18/217 ,  G06F18/2115 ,  G06F18/2415 ,  G06F18/41 ,  G06F21/6254 ,  G06N5/04 ,  G06N5/045 ,  G06N20/00 ,  G06N20/20 ,  G06Q20/14 ,  G06T3/40 ,  G06T5/002 ,  G06T5/008 ,  G06T5/50 ,  G06T7/0012 ,  G06T7/0014 ,  G06T7/10 ,  G06T7/11 ,  G06T7/187 ,  G06T7/44 ,  G06T7/97 ,  G06T11/001 ,  G06T11/006 ,  G06T11/206 ,  G06V10/225 ,  G06V10/25 ,  G06V10/764 ,  G06V10/82 ,  G06V30/19173 ,  G06V40/171 ,  G16H10/20 ,  G16H10/60 ,  G16H15/00 ,  G16H30/20 ,  G16H30/40 ,  G16H40/20 ,  G16H50/20 ,  H04L67/01 ,  H04L67/12 ,  A61B5/055 ,  A61B6/032 ,  A61B6/5217 ,  A61B8/4416 ,  G06F18/2111 ,  G06F18/24 ,  G06F40/295 ,  G06Q50/22 ,  G06T7/70 ,  G06T2200/24 ,  G06T2207/10048 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/10116 ,  G06T2207/10132 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30004 ,  G06T2207/30008 ,  G06T2207/30016 ,  G06T2207/30061 ,  G06V30/194 ,  G06V2201/03 ,  G16H50/30 ,  G16H50/70

Abstract: A peer-review flagging system is operable to train a computer vision model and to generate automated assessment data by performing an inference function on a first medical scan by utilizing the computer vision model. Human assessment data is generated based on a first medical report written by a medical professional in conjunction with review of the first medical scan. First consensus data is generated based on the automated assessment data, the human assessment data, and a first threshold, and the first medical scan is determined to be flagged based on the first consensus data. A second threshold is selected use in generating second consensus data for a second medical scan and a second medical report written by the medical professional in conjunction with review of the second medical scan, and is selected to be stricter than the first threshold based on determining to flag the first medical scan.

公开(公告)号：US20230187056A1

公开(公告)日：2023-06-15

申请号：US17923683

申请日：2021-05-10

Applicant: Verily Life Sciences LLC

Inventor： Ian ATKINSON ,  Ryan KRAMER ,  Eliezer GLIK ,  Aaron Haywood STOERTZ

IPC: G16H30/40 ,  G16H30/20 ,  A61B3/12 ,  A61B3/14 ,  G06V40/14 ,  G06V40/18 ,  A61B3/00

CPC classification number: G16H30/40 ,  G16H30/20 ,  A61B3/12 ,  A61B3/14 ,  G06V40/14 ,  G06V40/197 ,  A61B3/0025 ,  G06V2201/03

Abstract: Introduced here are approaches to ensuring that digital images generated during diagnostic sessions are properly associated with the appropriate patients. By implementing these approaches, a diagnostic platform can minimize the time needed to manually input information prior to a diagnostic session and improve the accuracy of this information.

公开(公告)号：US20230177645A1

公开(公告)日：2023-06-08

申请号：US18104812

申请日：2023-02-02

Applicant: Xidian University

Inventor： Xueli CHEN ,  Huan KANG ,  Hui XIE ,  Duofang CHEN ,  Shenghan REN ,  Wangting ZHOU

IPC: G06T3/40 ,  G06T7/00 ,  H04N25/76 ,  H04N23/955 ,  H04N23/56 ,  G06V10/764 ,  G06V10/774 ,  G06V20/70 ,  G06V10/26 ,  G06V10/82 ,  G06V10/762 ,  G06V10/74 ,  G02B21/36 ,  G02B21/26

CPC classification number: G06T3/4053 ,  G06T7/0012 ,  H04N25/76 ,  H04N23/955 ,  H04N23/56 ,  G06T3/4007 ,  G06T3/4046 ,  G06V10/764 ,  G06V10/774 ,  G06V20/70 ,  G06V10/26 ,  G06V10/82 ,  G06V10/763 ,  G06V10/761 ,  G02B21/365 ,  G02B21/26 ,  G06T2207/10056 ,  G06T2207/20132 ,  G06T2207/30024 ,  G06T2207/20081 ,  G06T2207/20192 ,  G06T2207/20084 ,  G06V2201/03

Abstract: A large-field-of-view, high-throughput and high-resolution pathological section analyzer includes an image collector for collecting a set of computing microscopic images of a pathological section sample; a data preprocessing circuit for iteratively updating the set of computing microscopic images by a multi-height phase recovery algorithm to obtain a low-resolution reconstructed image; an image super-resolution circuit for super-resolving the low-resolution reconstructed image according to a pre-trained super-resolution model to obtain a high-resolution reconstructed image; and an image analysis circuit for automatically analyzing the high-resolution reconstructed image according to different tasks, and specifically selecting different analysis models according to the different tasks to obtain corresponding auxiliary diagnosis results. Imaging visual field of the pathological section analyzer is hundreds of times that of the traditional optical microscope, a deep learning network is adopted to analyze pathological conditions of unstained pathological sections, so that the analysis process of pathological sections is simplified.

公开(公告)号：US20230169756A1

公开(公告)日：2023-06-01

申请号：US17979828

申请日：2022-11-03

Applicant: CANON KABUSHIKI KAISHA

Inventor： Keita Nagai ,  Kazuomi Toguchi ,  Honami Watanabe

IPC: G06V10/774 ,  G06T7/00 ,  G16H50/50 ,  A61B5/00

CPC classification number: G06V10/774 ,  G06T7/0016 ,  G16H50/50 ,  A61B5/0077 ,  A61B5/7267 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06V2201/03

Abstract: A learning system which is capable of easily collecting data of affected parts having completely recovered, as training data. When it is determined that an affected part has completely recovered based on affected-part image data generated by shooting the affected part, image data accompanied with the same affected part ID as that of the affected-part image data is identified from among image data set stored in a storage device of the learning system. The actual number of days to a complete recovery of the affected part is calculated from shooting dates of the identified image data and the affected-part image data, and is added to the affected-part image data. The affected-part image data accompanied with the actual number of days to the complete recovery is used as training data to create a trained model that predicts the number of days to a complete recovery of the affected part.

公开(公告)号：US20230169753A1

公开(公告)日：2023-06-01

申请号：US17887637

申请日：2022-08-15

Applicant: Medtronic Navigation, Inc. ,  The Johns Hopkins University

Inventor： Patrick A. HELM ,  Jeffrey H. SIEWERDSEN ,  Ali UNERI ,  Craig K. JONES ,  Yixuan HUANG ,  Xiaoxuan ZHANG

IPC: G06V10/764 ,  G06V10/40 ,  G06V10/22 ,  G06T7/73 ,  G06V10/82 ,  G06T7/33 ,  A61B90/00

CPC classification number: G06V10/764 ,  G06V10/40 ,  G06V10/22 ,  G06T7/73 ,  G06V10/82 ,  G06T7/337 ,  A61B90/37 ,  G06T2207/20212 ,  G06T2207/20084 ,  G06T2207/10116 ,  G06V2201/03 ,  A61B2090/376

Abstract: A method and system is disclosed for analyzing image data of a subject. The image data can be collected with an imaging system in a selected manner and/or motion. The image data may include selected overlap and be acquired with an imaging system that generates a plurality of perspectives for more than one location. An automatic system and method may then define or identify various features and/or allow for registration for alternative image data.

公开(公告)号：US12131513B2

公开(公告)日：2024-10-29

申请号：US17392875

申请日：2021-08-03

Applicant: FUJIFILM Corporation

Inventor： Seiya Takenouchi

IPC: G06V10/25 ,  G06F18/2431 ,  G06T7/00 ,  G06T11/00 ,  G06V10/44 ,  G06V10/82 ,  G09G5/373 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20

CPC classification number: G06V10/25 ,  G06F18/2431 ,  G06T7/0012 ,  G06T11/00 ,  G06V10/454 ,  G06V10/82 ,  G09G5/373 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G06T2207/10068 ,  G06T2207/30096 ,  G06V2201/03 ,  G09G2380/08

Abstract: The medical image processing apparatus includes: an image acquiring unit that acquires a medical image; a classification unit that classifies, on the basis of the medical image acquired by the image acquiring unit, the medical image or a region of interest included in the medical image; a notification information generating unit that generates, in accordance with a classification result of the classification, first notification information for display and second notification information for storage, the second notification information differing from the first notification information; and a storage that stores the medical image and the second notification information.