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    METHOD AND SYSTEM FOR MULTI-MODALITY JOINT ANALYSIS OF VASCULAR IMAGES
    3.
    发明申请
    METHOD AND SYSTEM FOR MULTI-MODALITY JOINT ANALYSIS OF VASCULAR IMAGES 有权

    公开(公告)号：US20230095242A1

    公开(公告)日：2023-03-30

    申请号：US17723863

    申请日：2022-04-19

    Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

    Inventor： Shubao Liu ,  Junjie Bai ,  Youbing Yin ,  Feng Gao ,  Yue Pan ,  Qi Song

    IPC: G06T7/33 ,  G06T17/00 ,  G06T7/00 ,  G06T7/73 ,  G06T11/00 ,  G06T19/20 ,  A61B6/00 ,  A61B8/08

    Abstract: Embodiments of the disclosure provide methods and systems for multi-modality joint analysis of a plurality of vascular images. The exemplary system may include a communication interface configured to receive the plurality of vascular images acquired using a plurality of imaging modalities. The system may further include at least one processor, configured to extract a plurality of vessel models for a vessel of interest from the plurality of vascular images. The plurality of vessel models are associated with the plurality of imaging modalities, respectively. The at least one processor is also configured to fuse the plurality of vessel models associated with the plurality of imaging modalities to generate a fused model for the vessel of interest. The at least one processor is further configured to provide a diagnostic analysis result based on the fused model of the vessel of interest.

    System and method for automatically detecting a physiological condition from a medical image of a patient
    7.
    发明授权
    System and method for automatically detecting a physiological condition from a medical image of a patient 有权

    公开(公告)号：US11341631B2

    公开(公告)日：2022-05-24

    申请号：US16028389

    申请日：2018-07-05

    Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

    Inventor： Qi Song ,  Shanhui Sun ,  Feng Gao ,  Junjie Bai ,  Hanbo Chen ,  Youbing Yin

    IPC: G06T7/00 ,  G06T7/70 ,  G06K9/62 ,  G06V10/44

    Abstract: The present disclosure is directed to a method and system for automatically detecting a physiological condition from a medical image of a patient. The method may include receiving the medical image acquired by an imaging device. The method may further include detecting, by a processor, target objects and obtaining the corresponding target object patches from the received medical image. And the method may further include determining, by the processor, a first parameter using a first learning network for each target object patch. The first parameter represents the physiological condition level of the corresponding target object, and the first learning network is trained by adding one or more auxiliary classification layers. This method can quickly, accurately, and automatically predict target object level and/or image (patient) level physiological condition from a medical image of a patient by means of a learning network, such as 3D learning network.

    Method and system for generating a centerline for an object, and computer readable medium
    8.
    发明授权
    Method and system for generating a centerline for an object, and computer readable medium 有权

    公开(公告)号：US11308362B2

    公开(公告)日：2022-04-19

    申请号：US16827613

    申请日：2020-03-23

    Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

    Inventor： Xin Wang ,  Youbing Yin ,  Qi Song ,  Junjie Bai ,  Yi Lu ,  Yi Wu ,  Feng Gao ,  Kunlin Cao

    IPC: G06T15/00 ,  G06K9/62 ,  G06N3/08 ,  G06T19/00 ,  G06V10/42

    Abstract: Methods and Systems for generating a centerline for an object in an image and computer readable medium are provided. The method includes receiving an image containing the object. The method also includes generating the centerline of the object by tracing a sequence of patches with a virtual agent. For each patch other than the initial patch, the method determines a current patch based on the position and action of the virtual agent at a previous patch. The method further determines a policy function and a value function based on the current patch using a trained learning network, which includes an encoder followed by a first learning network and a second learning network. The learning network is trained by maximizing a cumulative reward. The method also determines the action of the virtual agent at the current patch. Additionally, the method displays the centerline of the object.

    SYSTEMS AND METHODS FOR VESSEL PLAQUE ANALYSIS
    9.
    发明申请
    SYSTEMS AND METHODS FOR VESSEL PLAQUE ANALYSIS 有权

    公开(公告)号：US20210374950A1

    公开(公告)日：2021-12-02

    申请号：US17121595

    申请日：2020-12-14

    Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

    Inventor： Feng Gao ,  Zhenghan Fang ,  Yue Pan ,  Junjie Bai ,  Youbing Yin ,  Hao-Yu Yang ,  Kunlin Cao ,  Qi Song

    IPC: G06T7/00 ,  G06K9/62 ,  G06T3/40 ,  G06T7/70 ,  A61B6/03 ,  A61B6/00

    Abstract: The disclosure relates to systems and methods for vessel image analysis. The method includes receiving a set of images along a vessel acquired by a medical imaging device, and determining a sequence of centerline points along the vessel and a sequence of image patches at the respective centerline points based on the set of images. The method further includes detecting plaques based on the sequence of image patches using a first learning network. The first learning network includes an encoder configured to extract feature maps based on the sequence of image patches and a plaque range generator configured to generate a start position and an end position of each plaque based on the extracted feature maps. The method also includes classifying each detected plaque and determining a stenosis degree for the detected plaque, using a second learning network reusing at least part of the parameters of the first learning network and the extracted feature maps.

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