利索-全球专利检索

  1. 登录
  2. 注册

搜索结果

17 条记录 (耗时 0.016 秒)

    SYSTEMS AND METHODS FOR USING AI TO IDENTIFY REGIONS OF INTEREST IN MEDICAL IMAGES
    13.
    发明申请
    SYSTEMS AND METHODS FOR USING AI TO IDENTIFY REGIONS OF INTEREST IN MEDICAL IMAGES 有权

    公开(公告)号：US20220164951A1

    公开(公告)日：2022-05-26

    申请号：US17531177

    申请日：2021-11-19

    申请人： Hologic, Inc.

    发明人： Haili Chui ,  Nikolaos Gkanatsios ,  Zhenxue Jing ,  Ashwini Kshirsagar ,  Samir Parikh ,  Venky Vaddineni

    IPC分类号： G06T7/00 ,  G06T7/11 ,  G06K9/62

    摘要： Examples of the present disclosure describe systems and methods for using AI to identify regions of interest (ROI) in medical images. In aspects, medical reports and images may be provided to a first environment. The first environment may use the medical report data/medical images to train a natural language processing (NLP)-based algorithm to identify the location in images of ROI described in the medical report data. The output of the NLP-based algorithm may be stored in an ROI repository in the first environment. After the NLP-based algorithm has been trained, a request to train a user-specific model may be received in a second environment. Data objects for the requested user-specific model may be provided to the first environment, which uses the ROI repository to train the model. The trained model may be provided to the second environment, where the trained user-specific model/algorithm may be tested and stored.

    SYSTEMS AND METHODS FOR USING AI TO IDENTIFY REGIONS OF INTEREST IN MEDICAL IMAGES
    14.
    发明申请
    SYSTEMS AND METHODS FOR USING AI TO IDENTIFY REGIONS OF INTEREST IN MEDICAL IMAGES 有权

    公开(公告)号：US20220164586A1

    公开(公告)日：2022-05-26

    申请号：US17532286

    申请日：2021-11-22

    申请人： Hologic, Inc.

    发明人： Haili Chui ,  Nikolaos Gkanatsios ,  Zhenxue Jing ,  Ashwini Kshirsagar ,  Samir Parikh ,  Venky Vaddineni

    IPC分类号： G06K9/20 ,  G06F40/40 ,  G06T7/00 ,  G06F21/62

    摘要： Examples of the present disclosure describe systems and methods for using AI to identify regions of interest (ROI) in medical images. In aspects, medical reports and images may be provided to a second environment. The second environment may use the medical report data/medical images to train a natural language processing (NLP)-based algorithm to identify the location in images of ROI described in the medical report data. The output of the NLP-based algorithm may be stored in an ROI repository in the second environment. After the NLP-based algorithm has been trained, a request to train a user-specific model may be received in a first environment. Data objects for the requested user-specific model may be provided to the second environment, which uses the ROI repository to train the model. The trained model may be provided to the first environment, where the trained user-specific model/algorithm may be tested and stored.

    MOTION, COMPRESSION, AND POSITIONING CORRECTIONS IN MEDICAL IMAGING
    15.
    发明申请
    MOTION, COMPRESSION, AND POSITIONING CORRECTIONS IN MEDICAL IMAGING 审中-公开

    公开(公告)号：US20200178926A1

    公开(公告)日：2020-06-11

    申请号：US16779178

    申请日：2020-01-31

    申请人： Hologic, Inc.

    发明人： Ashwini Kshirsagar ,  Nikolaos Gkanatsios ,  John Laviola

    IPC分类号： A61B8/08 ,  A61B6/00 ,  A61B8/13 ,  A61B8/00

    摘要： Methods and systems for imaging. For example, a system may include a breast compression paddle, an imaging detector, at least one sensor incorporated into at least one of the breast compression paddle or the imaging detector. The system performs operations including generating, at a first time point, first spatial data of the breast based on data captured by the at least one sensor; generating, at a second time point, second spatial data of the breast based on data captured by the at least one sensor; based on the first spatial data and the second spatial data, determining an amount of motion of the breast that occurred; and based on the determined amount of motion performing at least one of: generating a motion map for the breast; discarding one or more acquired projections for use in generating a tomosynthesis reconstruction; or correcting a medical image acquired the second time point.