公开(公告)号：US11948345B2

公开(公告)日：2024-04-02

申请号：US17046387

申请日：2019-04-09

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Haibo Wang ,  Hua Xie ,  Grzegorz Andrzej Toporek

IPC: G06V10/764 ,  A61B8/00 ,  A61B8/08 ,  G06F18/2413 ,  G06V10/82 ,  G06V40/16

CPC classification number: G06V10/764 ,  A61B8/463 ,  A61B8/467 ,  A61B8/5207 ,  A61B8/5223 ,  A61B8/54 ,  G06F18/24133 ,  G06V10/82 ,  G06V40/16 ,  G06V2201/03

Abstract: A system and method for ultrasound imaging may involve the use of an ultrasound probe and a processor coupled to the probe and to a source of previously-acquired ultrasound image data. The processor may be configured to receive patient identification information (e.g., responsive to user input and/or supplemented by additional information such a photo of the patient), to determine whether the patient identification information identifies a recurring patient, and if so, to retrieve, from the source of previously-acquired ultrasound image data, previous ultrasound images associated with the recurring patient. The processor may be further configured to generate a current ultrasound image based on signals received from the prove and to apply a neural network to the current ultrasound image and the previous ultrasound images to identify a matching pair of images, such that imaging settings from the matched previous image may be applied to the system for subsequent imaging.

公开(公告)号：US11948080B2

公开(公告)日：2024-04-02

申请号：US17159171

申请日：2021-01-27

Applicant: FUJIFILM Corporation

Inventor： Shumpei Kamon

IPC: G06N3/08 ,  G06F18/20 ,  G06F18/214 ,  G06N3/04 ,  G06V10/25 ,  G06V10/44 ,  G06V10/70 ,  G06V10/82 ,  G06V10/94

CPC classification number: G06N3/08 ,  G06F18/2148 ,  G06F18/285 ,  G06N3/04 ,  G06V10/25 ,  G06V10/454 ,  G06V10/82 ,  G06V10/87 ,  G06V10/95 ,  G06V2201/03

Abstract: An object of the present invention is to provide an image processing method and an image processing apparatus that make it possible to efficiently learn images having different identities. In learning and recognition using a hierarchical network, it is known that, based on experiences, a layer near the input functions as a feature extractor for extracting a feature that is necessary for recognition, and a layer near the output performs recognition by combining extracted features. Thus, performing learning by setting a higher learning rate to a layer near the input side of the hierarchical network than a learning rate in a layer near the output side in second learning processing as in an aspect of the present invention corresponds to mainly relearning (adjusting) a feature extraction portion in data sets having different identities. Accordingly, the difference between data sets can be absorbed, and learning can be performed more efficiently than in the case of simply performing transfer learning.

公开(公告)号：US20240105143A1

公开(公告)日：2024-03-28

申请号：US18523831

申请日：2023-11-29

Applicant: FUJIFILM Corporation

Inventor： Masaaki OOSAKE

IPC: G09G5/14 ,  A61B1/00 ,  G06T7/00 ,  G06V10/25 ,  G09G5/37 ,  G16H30/40

CPC classification number: G09G5/14 ,  A61B1/000094 ,  G06T7/0012 ,  G06V10/25 ,  G09G5/37 ,  G16H30/40 ,  G06T2207/30004 ,  G06V2201/03 ,  G09G2354/00 ,  G09G2380/08

Abstract: A medical image processing apparatus includes the following. A processor is configured to: acquire a medical image obtained by capturing an image of an observation target; detect a region of interest from the medical image; and cause a display to display report information and the medical image, the report information reporting that the region of interest has been detected. A screen displayed on the display has a first region in which the medical image is displayed, and a second region provided outside the first region. The second region is divided into four regions by using line segments passing through a center of the first region, and a detected location of the region of interest is reported by displaying the report information in one of the four regions.

公开(公告)号：US20240105072A1

公开(公告)日：2024-03-28

申请号：US18276188

申请日：2022-01-14

Applicant: NEC Corporation

Inventor： Shin Norieda ,  Hiroo HARADA ,  Haruki MIZUTANI ,  Hirotaka MAESHIMA ,  Masami SAKAGUCHI

IPC: G09B5/08 ,  A61B5/16 ,  G06V40/16 ,  G09B7/00

CPC classification number: G09B5/08 ,  A61B5/165 ,  G06V40/174 ,  G09B7/00 ,  G06V2201/03

Abstract: Provided is an analysis apparatus or the like capable of appropriately determining emotions of a learner or an examinee in online learning or an online examination. An analysis apparatus includes: an emotion data acquisition unit that acquires emotion data regarding learning of each learner, the emotion data being obtained by performing emotion analysis on face image data of a plurality of learners in online learning; and an analysis data generation unit that aggregates emotion data regarding the plurality of learners, compares the emotion data of the plurality of learners, and generates analysis data in which the emotion data of one or more learners is identified.

公开(公告)号：US20240104948A1

公开(公告)日：2024-03-28

申请号：US18516417

申请日：2023-11-21

Applicant: Genentech, Inc.

Inventor： Jeffrey Ryan EASTHAM ,  Hartmut Koeppen ,  Xiao Li ,  Darya Yuryevna Orlova

IPC: G06V20/69 ,  G06T7/00 ,  G06T7/11 ,  G06V10/25 ,  G06V10/26 ,  G06V10/77 ,  G06V10/82

CPC classification number: G06V20/698 ,  G06T7/0012 ,  G06T7/11 ,  G06V10/25 ,  G06V10/267 ,  G06V10/77 ,  G06V10/82 ,  G06V20/695 ,  G06T2207/10056 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/30024 ,  G06T2207/30096 ,  G06V2201/03

Abstract: Systems and methods relate to processing digital pathology images. More specifically, techniques include accessing a digital pathology image that depicts a section of a biological sample, wherein the digital pathology image comprises regions displaying reactivity to a plurality of stains. For each of a plurality of tiles of the digital pathology image, a local-density measurement is calculated for each of a plurality of biological object types. One or more spatial-distribution metrics may be generated for the biological object types based at least in part on the calculated local-density measurements. A tumor immunophenotype may then be generated for the digital pathology image based at least in part on the local-density measurements or the one or more spatial-distribution metrics.

公开(公告)号：US20240103105A1

公开(公告)日：2024-03-28

申请号：US18027213

申请日：2021-09-15

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Cecilia Possanzini

IPC: G01R33/34 ,  G01R33/28 ,  G01R33/36 ,  G01R33/54 ,  G06V40/10

CPC classification number: G01R33/34084 ,  G01R33/288 ,  G01R33/3692 ,  G01R33/543 ,  G06V40/10 ,  G06V2201/03

Abstract: Disclosed herein is a medical system comprising: —a memory storing machine executable instructions; —a computational system, wherein execution of the machine executable instructions causes the computational system to perform a mismatch check comprising: —receive posture recognition system data, wherein the posture recognition system data comprises a set of subject coordinates and a set of coil coordinates described using a current coordinate system, wherein the set of subject coordinates are descriptive of anatomical features of a subject, wherein the set of coil coordinates are descriptive of a coil location of a magnetic resonance imaging coil, wherein coil data comprising a predefined range of coil positioning coordinates referenced to the anatomical features is associated with the magnetic resonance imaging coil; —determine an allowed range of coil coordinates by mapping the predefined range of coil positioning coordinates to the current coordinate system using the set of subject coordinates and the anatomical features; and —provide a warning signal in case of a mismatch between the set of coil coordinates and the allowed range of coil coordinates.

公开(公告)号：US20240096048A1

公开(公告)日：2024-03-21

申请号：US18451656

申请日：2023-08-17

Applicant: Imago Systems, Inc.

Inventor： Thomas E. Ramsay ,  Eugene B. Ramsay

IPC: G06V10/54 ,  A61B5/00 ,  A61B6/00 ,  A61B8/08 ,  G06T7/00 ,  G06T7/11 ,  G06T7/174 ,  G06T7/48 ,  G06T11/00 ,  G06V10/46 ,  G06V10/56 ,  H04N1/46 ,  H04N1/60

CPC classification number: G06V10/54 ,  A61B5/4312 ,  A61B6/502 ,  A61B6/5217 ,  A61B8/0825 ,  A61B8/5223 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/174 ,  G06T7/48 ,  G06T11/001 ,  G06V10/462 ,  G06V10/56 ,  H04N1/465 ,  H04N1/6027 ,  A61B2503/40 ,  G06T2207/10116 ,  G06T2207/30016 ,  G06T2207/30056 ,  G06T2207/30061 ,  G06T2207/30068 ,  G06T2207/30081 ,  G06T2207/30084 ,  G06T2207/30096 ,  G06V2201/03

Abstract: A method of visualization, characterization, and detection of objects within an image by applying a local micro-contrast convergence algorithm to a first image to produce a second image that is different from the first image, wherein all like objects converge into similar patterns or colors in the second image.

公开(公告)号：US20240095909A1

公开(公告)日：2024-03-21

申请号：US18257050

申请日：2021-12-10

Applicant: NUREA

Inventor： Florian BERNARD ,  Romain LEGUAY

IPC: G06T7/00 ,  A61B5/02 ,  G06T7/11 ,  G06T7/136 ,  G06T7/62 ,  G06V10/764 ,  G06V10/77 ,  G06V10/82 ,  G06V20/64 ,  G06V20/70

CPC classification number: G06T7/0012 ,  A61B5/02014 ,  G06T7/11 ,  G06T7/136 ,  G06T7/62 ,  G06V10/764 ,  G06V10/7715 ,  G06V10/82 ,  G06V20/64 ,  G06V20/70 ,  G06T2200/04 ,  G06T2207/10028 ,  G06T2207/10081 ,  G06T2207/20072 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30101 ,  G06T2207/30172 ,  G06V2201/03

Abstract: A method for aiding in the diagnosis of a cardiovascular disease, comprising the following steps: providing a three-dimensional representation of a blood vessel of a patient; segmenting, by means of a classifier, the three-dimensional representation to obtain a segmented three-dimensional map; comparing the value of a plurality of voxels of the three-dimensional representation, the allocated labels on the three-dimensional map of the voxels being those of the blood vessel, with a predetermined threshold value, a label different from those of the blood vessel being allocated to each voxel with a value that exceeds the predetermined threshold value; determining the change in a geometric indicator of the blood vessel by means of the voxels of the three-dimensional representation, the allocated labels on the three-dimensional map of the aforementioned voxels being those of the blood vessel.

公开(公告)号：US11935232B2

公开(公告)日：2024-03-19

申请号：US17257999

申请日：2020-08-17

Applicant: Google LLC

Inventor： Jason Yim ,  Reena Kumari Chopra ,  Terry Spitz ,  Jim Huibrecht Winkens ,  Annette Ada Nkechinyere Obika ,  Trevor Back ,  Joseph R. Ledsam ,  Pearse A. Keane ,  Jeffrey De Fauw

IPC: A61B5/00 ,  G06T7/00 ,  G06T7/11 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06T7/0012 ,  A61B5/4842 ,  A61B5/7275 ,  G06T7/11 ,  G06V10/764 ,  G06V10/82 ,  G06T2200/04 ,  G06T2207/10012 ,  G06T2207/10101 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30041 ,  G06V2201/03

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a final progression score characterizing a likelihood that a state of a medical condition affecting eye tissue will progress to a target state in a future interval of time. In one aspect, a method comprises: obtaining: (i) an input image of eye tissue captured using an imaging modality, and (ii) a segmentation map of the eye tissue in the input image into a plurality of tissue types; providing the input image to each of one or more first classification neural networks to obtain a respective first progression score from each first classification neural network; providing the segmentation map to each of one or more second classification neural networks to obtain a respective second progression score from each second classification neural network; and generating the final progression score based on the first and second progression scores.

公开(公告)号：US20240087304A1

公开(公告)日：2024-03-14

申请号：US18354031

申请日：2023-07-18

Applicant: Siemens Healthcare GmbH

Inventor： Halid Yerebakan ,  Anna Jerebko

IPC: G06V10/70 ,  G06V10/762 ,  G06V10/82 ,  G06V10/94 ,  G16H30/20

CPC classification number: G06V10/87 ,  G06V10/762 ,  G06V10/82 ,  G06V10/945 ,  G16H30/20 ,  G06V2201/03

Abstract: A framework for medical data analysis, comprising a tool generation unit configured for automatically generating a first number of data analysis tools based on first medical image data and first analysis data related to the first medical image data.