公开(公告)号：US20230274440A1

公开(公告)日：2023-08-31

申请号：US18143300

申请日：2023-05-04

Applicant: LightLab Imaging, Inc.

Inventor： Shimin Li ,  Ajay Gopinath ,  Kyle Savidge

IPC: G06T7/11 ,  G06F18/214 ,  G06F18/40 ,  G06N3/04 ,  G06N3/08 ,  G06F18/211

CPC classification number: G06T7/11 ,  G06F18/214 ,  G06F18/40 ,  G06N3/04 ,  G06N3/08 ,  G06F18/211 ,  G06V2201/03

Abstract: In part, the disclosure relates to methods, and systems suitable for evaluating image data from a patient on a real time or substantially real time basis using machine learning (ML) methods and systems. Systems and methods for improving diagnostic tools for end users such as cardiologists and imaging specialists using machine learning techniques applied to specific problems associated with intravascular images that have polar representations. Further, given the use of rotating probes to obtain image data for OCT, IVUS, and other imaging data, dealing with the two coordinate systems associated therewith creates challenges. The present disclosure addresses these and numerous other challenges relating to solving the problem of quickly imaging and diagnosis a patient such that stenting and other procedures may be applied during a single session in the cath lab.

公开(公告)号：US11740321B2

公开(公告)日：2023-08-29

申请号：US15926557

申请日：2018-03-20

Applicant: Apple Inc.

Inventor： Oleg Naroditsky ,  Kuen-Han Lin ,  Dimitrios Kottas

IPC: G01S5/16 ,  G06T7/246 ,  G01S19/47 ,  G06F18/21 ,  G06F18/2413 ,  G06N3/042 ,  G06V10/764 ,  G01S19/52

CPC classification number: G01S5/16 ,  G01S19/47 ,  G06F18/217 ,  G06F18/24133 ,  G06N3/042 ,  G06T7/251 ,  G06V10/764 ,  G01S19/52 ,  G06F2218/12 ,  G06V2201/03

Abstract: Systems, methods, and computer readable media to track and estimate the accuracy of a visual inertial odometry (VIO) system. Various embodiments are able to receive one or more VIO feature measurements associated with a set of image frames from a VIO system and generate a plurality of feature models to estimate health values for the VIO system. The various embodiments determine a plurality of feature health values with the feature models based on the VIO feature measurements and compare the feature health values with ground truth health scores associated with the set of image frames to determine one or more errors. The feature model parameters are updated based on the comparison with the feature health values with ground truth health scores.

公开(公告)号：US11734911B2

公开(公告)日：2023-08-22

申请号：US17129133

申请日：2020-12-21

Applicant: Imago Systems, Inc.

Inventor： Thomas E. Ramsay ,  Eugene B. Ramsay

IPC: G06K9/46 ,  G06V10/54 ,  A61B8/08 ,  A61B6/00 ,  G06T7/00 ,  G06T7/48 ,  G06V10/56 ,  G06V10/46 ,  G06T7/11 ,  G06T7/174 ,  A61B5/00 ,  G06T11/00 ,  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：US11730364B2

公开(公告)日：2023-08-22

申请号：US17145389

申请日：2021-01-10

Applicant: XAIMED Co., Ltd.

Inventor： Sang Min Park ,  Joo Young Chang ,  Choong Hee Lee ,  Il Hyung Shin

IPC: A61B3/12 ,  A61B3/00 ,  G06T7/00 ,  G06T5/00 ,  G06T3/40 ,  G06T7/73 ,  G06N20/00 ,  G16H30/20 ,  G16H50/20 ,  G06V10/764 ,  G06V10/82 ,  G06V10/44

CPC classification number: A61B3/12 ,  A61B3/005 ,  A61B3/0025 ,  G06N20/00 ,  G06T3/40 ,  G06T5/002 ,  G06T7/0012 ,  G06T7/73 ,  G06V10/454 ,  G06V10/764 ,  G06V10/82 ,  G16H30/20 ,  G16H50/20 ,  G06T2207/30041 ,  G06V2201/03

Abstract: Provided are apparatuses, a non-transitory computer-readable medium or media, and methods for supporting reading of a fundus image of a subject. In certain aspects, disclosed a method including the steps of: extracting a first feature information from a first fundus image of the subject based on a machine learning model; generating a second fundus image having a second feature information by mapping an adversarial factor to the first fundus image so that the first feature information is changed; and displaying the first fundus image having the first feature information and the second fundus image having the second feature information on a display device.

公开(公告)号：US20230260258A1

公开(公告)日：2023-08-17

申请号：US18167480

申请日：2023-02-10

Applicant: Konica Minolta, Inc

Inventor： Nodoka IIDA

IPC: G06V10/774 ,  G06T7/00 ,  G06V10/82

CPC classification number: G06V10/774 ,  G06T7/0012 ,  G06V10/82 ,  G06T2207/30096 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06V2201/03 ,  G06V2201/07

Abstract: A medical image learning method includes: pre-task learning in which a model performs self-supervised learning, based on first medical image data; and target-task learning in which the model that has learned in the pre-task learning learns to detect a lesion, based on second medical image data that has a correct answer. The first medical image data includes original image data on which predetermined image processing is not performed and/or processed image data on which the predetermined image processing has been performed. The second medical image data includes the original image data.

公开(公告)号：US20230255468A1

公开(公告)日：2023-08-17

申请号：US18165180

申请日：2023-02-06

Applicant: COSMO ARTIFICIAL INTELLIGENCE-AI LIMITED

Inventor： NHAN NGO DINH ,  GIULIO EVANGELISTI ,  FLAVIO NAVARI

IPC: A61B1/31 ,  G06T7/70 ,  G16H30/20 ,  G06N3/08 ,  G06T7/00 ,  G06T11/00 ,  G06T11/60 ,  G06T11/20 ,  A61B1/00 ,  A61B5/00 ,  G06V20/40 ,  G06V10/82 ,  G06F18/214 ,  G06N3/045 ,  G06V10/25 ,  G06V10/20

CPC classification number: A61B1/31 ,  G06T7/70 ,  G16H30/20 ,  G06N3/08 ,  G06T7/0012 ,  G06T11/001 ,  G06T11/60 ,  G06T11/203 ,  A61B1/00055 ,  A61B5/7264 ,  G06V20/49 ,  A61B1/000096 ,  A61B5/7267 ,  G06V10/82 ,  A61B1/000094 ,  A61B1/000095 ,  G06F18/214 ,  G06N3/045 ,  G06V20/40 ,  G06V10/25 ,  G06V10/255 ,  G06T2207/10016 ,  G06T2207/20084 ,  G06T2207/30032 ,  G06T2207/30096 ,  G06T2207/10068 ,  G06V2201/03 ,  G06V2201/032 ,  G06T2207/30004 ,  G06T2207/30064

Abstract: The present disclosure relates to systems and methods for processing real-time video and detecting objects in the video. In one implementation, a system is provided that includes an input port for receiving real-time video obtained from a medical image device, a first bus for transferring the received real-time video, and at least one processor configured to receive the real-time video from the first bus, perform object detection by applying a trained neural network on frames of the received real-time video, and overlay a border indicating a location of at least one detected object in the frames. The system also includes a second bus for receiving the video with the overlaid border, an output port for outputting the video with the overlaid border from the second bus to an external display, and a third bus for directly transmitting the received real-time video to the output port.

公开(公告)号：US11727699B2

公开(公告)日：2023-08-15

申请号：US16753667

申请日：2018-10-04

Applicant: BECTON DICKINSON AND COMPANY

Inventor： Michael A. Brasch ,  Curtis M. Gosnell ,  Timothy M. Wiles ,  Raphael Rodolphe Marcelpoil ,  Bas Nieuwenhuis ,  Trienko Marten Van Der Kaap ,  Michael Bois

IPC: G06K9/00 ,  G06V20/69 ,  G06F16/58 ,  C12M1/34 ,  G06T7/00 ,  G06N7/01

CPC classification number: G06V20/698 ,  C12M1/3446 ,  C12M41/36 ,  G06F16/5866 ,  G06N7/01 ,  G06T7/0016 ,  G06T2207/10056 ,  G06T2207/30024 ,  G06V2201/03

Abstract: A system and method for developing applications (Apps) for automated assessment and analysis of processed biological samples. Such samples are obtained, combined with nutrient media and incubated. The incubated samples are imaged and the image information is classified according to predetermined criteria. The classified image information is then evaluated according to Apps derived from classified historical image information in a data base. The classified historical image information is compared with the classified image information to provide guidance on further processing of the biological sample through Apps tailored to process provide sample process guidance tailored to the classifications assigned to the image information.

公开(公告)号：US11727087B2

公开(公告)日：2023-08-15

申请号：US17221860

申请日：2021-04-05

Applicant: Nano-X AI Ltd.

Inventor： Raouf Muhamedrahimov ,  Amir Bar

IPC: G06T7/00 ,  G06F18/214 ,  G06N3/08 ,  A61B6/00 ,  G06F18/23 ,  G06F18/213 ,  G06N3/045

CPC classification number: G06F18/2148 ,  A61B6/481 ,  A61B6/484 ,  G06F18/213 ,  G06F18/2155 ,  G06F18/23 ,  G06N3/045 ,  G06N3/08 ,  G06T7/0012 ,  G06T2207/10081 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30004 ,  G06V2201/03

Abstract: There is provided a method, comprising: accessing medical images of subjects, depicting contrast phases of contrast administered to the respective subject, accessing for a first subset of the medical images, metadata indicating a respective contrast phase, wherein a second subset of the medical images are unassociated with metadata, mapping each respective contrast phase of the contrast phases to a respective time interval indicating estimated amount of time from a start of contrast administration to time of capture of the respective medical image, creating a training dataset, by labelling images of the first subset with a label indicating the respective time interval, and including the second subset as non-labelled images, and training the ML model using the training dataset for generating an outcome of a target time interval indicating estimated amount of time from the start of contrast administration, in response to an input of a target medical image.

公开(公告)号：US20230245478A1

公开(公告)日：2023-08-03

申请号：US18010545

申请日：2021-06-11

Applicant: HAMAMATSU PHOTONICS K.K. ,  NATIONAL UNIVERSITY CORPORATION HAMAMATSU UNIVERSITY SCHOOL OF MEDICINE

Inventor： Fumio HASHIMOTO ,  Kibo OTE ,  Hidenao YAMADA ,  Hirotoshi KIKUCHI ,  Amane HIROTSU ,  Shigetoshi OKAZAKI

IPC: G06V20/69 ,  G06V10/40

CPC classification number: G06V20/698 ,  G06V10/40 ,  G06V2201/03

Abstract: A discrimination device is a device that discriminates whether or not a discrimination target object is a blood cell based on an image of the discrimination target object, and includes a blood cell feature extraction unit that acquires an image of a blood cell and extracts a feature of the blood cell from the acquired image, a discrimination target object feature extraction unit that acquires the image of the discrimination target object and extracts a feature of the discrimination target object from the acquired image, and a discrimination unit that discriminates whether or not the discrimination target object is a blood cell through anomaly detection based on the extracted feature of the blood cell and the feature of the discrimination target object.

公开(公告)号：US11710290B2

公开(公告)日：2023-07-25

申请号：US16379313

申请日：2019-04-09

Applicant: FUJIFILM Corporation

Inventor： Kazuhiro Hirota ,  Kaku Irisawa ,  Dai Murakoshi ,  Yoshiro Imai ,  Tsuyoshi Matsumoto

IPC: A61B5/00 ,  G06V10/143 ,  A61B5/02 ,  G06T7/00 ,  G06T7/33 ,  G06T7/11 ,  G01N29/24 ,  G06T7/149 ,  A61B8/13 ,  A61B8/06 ,  G06F18/22 ,  G06V10/74 ,  G06V40/14

CPC classification number: G06V10/143 ,  A61B5/0095 ,  A61B5/02007 ,  A61B5/7425 ,  A61B8/06 ,  A61B8/13 ,  G01N29/2418 ,  G06F18/22 ,  G06T7/0016 ,  G06T7/11 ,  G06T7/149 ,  G06T7/337 ,  G06V10/761 ,  G01N2291/02466 ,  G06T2207/10132 ,  G06T2207/20024 ,  G06T2207/20221 ,  G06V40/14 ,  G06V2201/03 ,  G06V2201/031

Abstract: A photoacoustic image evaluation apparatus includes a processor configured to acquire a first photoacoustic image generated at a first point in time and a second photoacoustic image generated at a second point in time before the first point in time, the first and second photoacoustic images being photoacoustic images generated by detecting photoacoustic waves generated inside a subject, who has been subjected to blood vessel regeneration treatment, by emission of light into the subject; acquire a blood vessel regeneration index, which indicates a state of a blood vessel by the regeneration treatment, based on a difference between a blood vessel included in the first photoacoustic image and a blood vessel included in the second photoacoustic image; and display the blood vessel regeneration index on a display.