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    Method and system for disease quantification of anatomical structures
    41.
    发明授权
    Method and system for disease quantification of anatomical structures 有权

    公开(公告)号：US12119117B2

    公开(公告)日：2024-10-15

    申请号：US17726307

    申请日：2022-04-21

    Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

    Inventor： Xin Wang ,  Youbing Yin ,  Bin Kong ,  Yi Lu ,  Hao-Yu Yang ,  Xinyu Guo ,  Qi Song

    IPC: G16H50/30 ,  G06N3/045 ,  G06T7/00 ,  G06V10/42 ,  G06V10/44 ,  G06V10/82 ,  G16H30/40

    CPC classification number: G16H50/30 ,  G06N3/045 ,  G06T7/0012 ,  G06V10/42 ,  G06V10/44 ,  G06V10/82 ,  G16H30/40

    Abstract: This disclosure discloses a method and system for predicting disease quantification parameters for an anatomical structure. The method includes extracting a centerline structure based on a medical image. The method further includes predicting the disease quantification parameter for each sampling point on the extracted centerline structure by using a GNN, with each node corresponds to a sampling point on the extracted centerline structure and each edge corresponds to a spatial constraint relationship between the sampling points. For each node, a local feature is extracted based on the image patch for the corresponding sampling point by using a local feature encoder, and a global feature is extracted by using a global feature encoder based on a set of image patches for a set of sampling points, which include the corresponding sampling point and have a spatial constraint relationship defined by the centerline structure. Then, an embed feature is obtained based on both the local feature and the global feature and input into to the node. The method is able to integrate local and global consideration factors of the sampling points into the GNN to improve the prediction accuracy.

    Method and system for anatomical labels generation
    42.
    发明授权
    Method and system for anatomical labels generation 有权

    公开(公告)号：US12094596B2

    公开(公告)日：2024-09-17

    申请号：US17726039

    申请日：2022-04-21

    Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

    Inventor： Xin Wang ,  Youbing Yin ,  Bin Kong ,  Yi Lu ,  Xinyu Guo ,  Hao-Yu Yang ,  Junjie Bai ,  Qi Song

    IPC: G06V10/82 ,  G06N3/045 ,  G06V20/70 ,  G16H30/40

    CPC classification number: G16H30/40 ,  G06N3/045 ,  G06V10/82 ,  G06V20/70

    Abstract: The present disclosure relates to a method and a system for generating anatomical labels of an anatomical structure. The method includes receiving an anatomical structure with an extracted centerline, or a medical image containing the anatomical structure with the extracted centerline; and predicting the anatomical labels of the anatomical structure based on the centerline of the anatomical structure, by utilizing a trained deep learning network. The deep learning network includes a branched network, a Graph Neural Network, a Recurrent Neural Network and a Probability Graph Model, which are connected sequentially in series. The branched network includes at least two branch networks in parallel. The method in the disclosure can automatically generate the anatomical labels of the whole anatomical structure in medical image end to end and provide high prediction accuracy and reliability.

    Methods and systems for computer-assisted medical image analysis using sequential model
    43.
    发明授权
    Methods and systems for computer-assisted medical image analysis using sequential model 有权

    公开(公告)号：US12086981B2

    公开(公告)日：2024-09-10

    申请号：US17557449

    申请日：2021-12-21

    Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

    Inventor： Junjie Bai ,  Hao-Yu Yang ,  Youbing Yin ,  Qi Song

    IPC: G06T7/00 ,  G06T7/11

    CPC classification number: G06T7/0012 ,  G06T7/11 ,  G06T2207/20092 ,  G06T2207/30096 ,  G06T2207/30101 ,  G06T2207/30172

    Abstract: Embodiments of the disclosure provide systems and methods for analyzing a medical image containing a vessel structure using a sequential model. An exemplary system includes a communication interface configured to receive the medical image and the sequential model. The sequential model includes a vessel extraction sub-model and a lesion analysis sub-model. The vessel extraction sub-model and the lesion analysis sub-model are independently or jointly trained. The exemplary system also includes at least one processor configured to apply the vessel extraction sub-model on the received medical image to extract location information of the vessel structure. The at least one processor also applies the lesion analysis sub-model on the received medical image and the location information extracted by the vessel extraction sub-model to obtain a lesion analysis result of the vessel structure. The at least one processor further outputs the lesion analysis result of the vessel structure.

    SYSTEM AND METHOD FOR PROGNOSIS MANAGEMENT BASED ON MEDICAL INFORMATION OF PATIENT
    45.
    发明申请
    SYSTEM AND METHOD FOR PROGNOSIS MANAGEMENT BASED ON MEDICAL INFORMATION OF PATIENT 有权

    公开(公告)号：US20230099284A1

    公开(公告)日：2023-03-30

    申请号：US17501041

    申请日：2021-10-14

    Applicant: Shenzhen Keya Medical Technology Corporation

    Inventor： Feng Gao ,  Hao-Yu Yang ,  Yue Pan ,  Youbing Yin ,  Qi Song

    IPC: G16H30/20 ,  G16H50/30 ,  G16H50/50 ,  G16H30/40 ,  G16H10/60 ,  G16H50/20 ,  G06N20/00 ,  G06T7/00 ,  A61B5/00 ,  A61B5/021

    Abstract: The disclosure relates to a method, a system, and a computer-readable medium for prognosis management based on medical information of a patient. The method may include receiving the medical information including at least a medical image of the patient reflecting a morphology of an object associated with the patient at a first time, The method may further include predicting a progression condition of the object at a second time based on the medical information of the first time, where the progression condition is indicative of a prognosis risk, and the second time is after the first time. The method may also include generating a prognosis image at the second time reflecting the morphology of the object at the second time based on the medical information of the first time. The method may additionally include providing the progression condition of the object at the second time and the prognosis image at the second time to an information management system for presentation to a user.

    METHODS AND SYSTEMS FOR TRAINING LEARNING NETWORK FOR MEDICAL IMAGE ANALYSIS
    46.
    发明申请
    METHODS AND SYSTEMS FOR TRAINING LEARNING NETWORK FOR MEDICAL IMAGE ANALYSIS 有权

    公开(公告)号：US20220366679A1

    公开(公告)日：2022-11-17

    申请号：US17565274

    申请日：2021-12-29

    Applicant: Shenzhen Keya Medical Technology Corporation

    Inventor： Junhuan Li ,  Ruoping LI ,  Ling Hou ,  Pengfei Zhao ,  Yuwei Li ,  Kunlin Cao ,  Qi Song

    IPC: G06V10/774 ,  G06V10/776 ,  G06T7/00 ,  G06V10/82

    Abstract: The present disclosure relates to a training method and a training system for training a learning network for medical image analysis. The training method includes: acquiring an original training data set for a learning network with a predetermined structure; performing, by a processor, a pre-training on the learning network using the original training data set to obtain a pre-trained learning network; evaluating, by the processor, the pre-trained learning network to determine whether the pre-trained learning network has an evaluation defect; when the pre-trained learning network has the evaluation defect, performing, by the processor, a data augmentation on the original training data set for the existing evaluation defect; and performing, by the processor, a refined training on the pre-trained learning network using a data augmented training data set. The present disclosure can evaluate and train the learning network in stages, therefore, the complexity of medical image processing is reduced, and the efficiency and accuracy of medical image analysis are improved.

    METHODS AND SYSTEMS FOR COMPUTER-ASSISTED MEDICAL IMAGE ANALYSIS USING SEQUENTIAL MODEL
    48.
    发明申请
    METHODS AND SYSTEMS FOR COMPUTER-ASSISTED MEDICAL IMAGE ANALYSIS USING SEQUENTIAL MODEL 有权

    公开(公告)号：US20220215534A1

    公开(公告)日：2022-07-07

    申请号：US17557449

    申请日：2021-12-21

    Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

    Inventor： Junjie Bai ,  Hao-Yu Yang ,  Youbing Yin ,  Qi Song

    IPC: G06T7/00 ,  G06T7/11

    Abstract: Embodiments of the disclosure provide systems and methods for analyzing a medical image containing a vessel structure using a sequential model. An exemplary system includes a communication interface configured to receive the medical image and the sequential model. The sequential model includes a vessel extraction sub-model and a lesion analysis sub-model. The vessel extraction sub-model and the lesion analysis sub-model are independently or jointly trained. The exemplary system also includes at least one processor configured to apply the vessel extraction sub-model on the received medical image to extract location information of the vessel structure. The at least one processor also applies the lesion analysis sub-model on the received medical image and the location information extracted by the vessel extraction sub-model to obtain a lesion analysis result of the vessel structure. The at least one processor further outputs the lesion analysis result of the vessel structure.

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