知搜-全球专利检索

  1. Login
  2. Sign Up

Search Results

137 records (took 0.018 seconds)

    METHOD FOR TRAINING NEURAL NETWORK AND DEVICE THEREOF
    41.
    发明申请
    METHOD FOR TRAINING NEURAL NETWORK AND DEVICE THEREOF 有权

    公开(公告)号：US20210125074A1

    公开(公告)日：2021-04-29

    申请号：US16842435

    申请日：2020-04-07

    Applicant: Lunit Inc.

    Inventor： HyunJae LEE ,  Hyo-Eun KIM ,  Weonsuk LEE

    IPC: G06N3/08 ,  G06N3/04 ,  G06N20/20 ,  G06T5/50

    Abstract: Provided is a method for training a neural network and a device thereof. The method may train a neural network with three-dimensional (3D) training image data including a plurality of two-dimensional (2D) training image data. The method may include training, at a processor, a first convolutional neural network (CNN) with the plurality of 2D training image data, wherein the first convolutional neural network comprises 2D convolutional layers. The method may further include training, at the processor, a second convolutional neural network with the 3D training image data, wherein the second convolutional neural network comprises the 2D convolutional layers and 3D convolutional layers configured to receive an output of the 2D convolutional layers as an input.

    APPARATUS FOR QUALITY MANAGEMENT OF MEDICAL IMAGE INTERPRETATION USING MACHINE LEARNING, AND METHOD THEREOF
    42.
    发明申请
    APPARATUS FOR QUALITY MANAGEMENT OF MEDICAL IMAGE INTERPRETATION USING MACHINE LEARNING, AND METHOD THEREOF 有权

    公开(公告)号：US20210073990A1

    公开(公告)日：2021-03-11

    申请号：US17073065

    申请日：2020-10-16

    Applicant: Lunit Inc.

    Inventor： Nayoung JEONG ,  Ki Hwan KIM ,  Minhong JANG

    IPC: G06T7/00 ,  G16H30/40 ,  G06N3/08 ,  G16H30/20 ,  G06N3/04 ,  G06N20/00

    Abstract: Provided are a computerized image interpretation method and a device for analyzing a medical image. The image interpretation method may include receiving, at a processor, a medical image, and receiving report information including a healthcare worker's judgement result of the medical image. The method may also include generating, at the processor, result information representing correspondence between first lesion information, which is related to a lesion in the medical image acquired on the basis of the medical image, and second lesion information, which is related to a lesion in the medical image acquired on the basis of the report information, by applying the first lesion information and the second lesion information to a third analysis model. The method may further include outputting, at the processor, the result information.

    APPARATUS FOR PREDICTING METADATA OF MEDICAL IMAGE AND METHOD THEREOF
    43.
    发明申请
    APPARATUS FOR PREDICTING METADATA OF MEDICAL IMAGE AND METHOD THEREOF 审中-公开

    公开(公告)号：US20200372299A1

    公开(公告)日：2020-11-26

    申请号：US16708205

    申请日：2019-12-09

    Applicant: Lunit Inc.

    Inventor： Jongchan PARK ,  Donggeun YOO

    IPC: G06K9/62 ,  G06T7/00 ,  G06T7/70

    Abstract: This disclosure relates to a computerized method to perform a machine learning on a relationship between medical images and metadata using a neural network and acquiring metadata by applying a machine learning model to medical images, and a method thereof. The apparatus and method may include training a prediction model for predicting metadata of medical images based on multiple medical images for learning and metadata matched with each of multiple medical images and predicting metadata of input medical image.

    METHOD FOR MANAGING ANNOTATION JOB, APPARATUS AND SYSTEM SUPPORTING THE SAME
    44.
    发明申请
    METHOD FOR MANAGING ANNOTATION JOB, APPARATUS AND SYSTEM SUPPORTING THE SAME 审中-公开

    公开(公告)号：US20200210926A1

    公开(公告)日：2020-07-02

    申请号：US16814131

    申请日：2020-03-10

    Applicant: Lunit Inc.

    Inventor： Kyoung Won Lee ,  Kyung Hyun Paeng

    IPC: G06Q10/06 ,  G06T7/00 ,  G16H30/20 ,  G16H30/40 ,  G16H40/20 ,  G16H10/40

    Abstract: A computing device obtains information about a medical slide image, and determines a dataset type of the medical slide image and a panel of the medical slide image. The computing device assigns to an annotator account, an annotation job defined by at least the medical slide image, the determined dataset type, an annotation task, and a patch that is a partial area of the medical slide image. The annotation task includes the determined panel, and the panel is designated as one of a plurality of panels including a cell panel, a tissue panel, and a structure panel. The dataset type indicates a use of the medical slide image and is designated as one of a plurality of uses including a training use of a medical learning model and a validation use of the machine learning model.

    METHOD AND APPARATUS FOR MACHINE LEARNING
    45.
    发明申请
    METHOD AND APPARATUS FOR MACHINE LEARNING 审中-公开

    公开(公告)号：US20200151613A1

    公开(公告)日：2020-05-14

    申请号：US16684627

    申请日：2019-11-15

    Applicant: Lunit Inc.

    Inventor： Dong Geun YOO ,  Kyung Hyun Paeng ,  Sung Gyun Park

    IPC: G06N20/20 ,  G06F17/18 ,  G06F11/34

    Abstract: A machine learning method that may reduce an annotation cost and may improve performance of a target model is provided. Some embodiments of the present disclosure may provide a machine learning method performed by a computing device, including: acquiring a training dataset of a first model including a plurality of data samples to which label information is not given; calculating a miss-prediction probability of the first model on the plurality of data samples; configuring a first data sample group by selecting at least one data sample from the plurality of data samples based on the calculated miss-prediction probability; acquiring first label information on the first data sample group; and performing first learning on the first model by using the first data sample group and the first label information.

    Method and system for parallel processing for medical image
    47.
    发明授权
    Method and system for parallel processing for medical image 有权

    公开(公告)号：US12236591B2

    公开(公告)日：2025-02-25

    申请号：US17885611

    申请日：2022-08-11

    Applicant: LUNIT INC.

    Inventor： Donggeun Yoo

    IPC: G16H70/60 ,  G06T7/00 ,  G06V10/22 ,  G06V10/774 ,  G16H30/40

    Abstract: A method for parallel processing a digitally scanned pathology image is performed by a plurality of processors and includes performing, by a first processor, a first operation of generating a first batch from a first set of patches extracted from a digitally scanned pathology image and providing the generated first batch to a second processor, performing, by the first processor, a second operation of generating a second batch from a second set of patches extracted from the digitally scanned pathology image and providing the generated second batch to the second processor, and performing, by the second processor, a third operation of outputting a first analysis result from the first batch by using a machine learning model, with at least part of time frame for the second operation performed by the first processor overlapping at least part of time frame for the third operation performed by the second processor.

    METHOD AND APPARATUS FOR ANALYZING PATHOLOGICAL SLIDE IMAGE
    48.
    发明申请
    METHOD AND APPARATUS FOR ANALYZING PATHOLOGICAL SLIDE IMAGE 有权

    公开(公告)号：US20250054142A1

    公开(公告)日：2025-02-13

    申请号：US18799341

    申请日：2024-08-09

    Applicant: Lunit Inc.

    Inventor： Suk Jun KIM ,  Heon Song ,  Won Kyung Jung ,  Soo lck Cho

    IPC: G06T7/00

    Abstract: A computing device includes at least one memory and at least one processor. The at least one processor is configured to detect a plurality of tumor cells included in one or more tumor areas (cancer areas) from a pathological slide image, determine a cell expression class of the plurality of tumor cells, based on a biomarker expression degree of the plurality of tumor cells, and generate a heatmap image for the pathological slide image, based on a result of the determining.

Patent Agency Ranking