公开(公告)号：US20220215956A1

公开(公告)日：2022-07-07

申请号：US17567486

申请日：2022-01-03

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Bin Kong ,  Youbing Yin ,  Xin Wang ,  Yi Lu ,  Qi Song

IPC: G16H50/20 ,  G06N5/04 ,  G06V10/774 ,  G06T7/00

Abstract: The disclosure relates to a system and method for predicting physiological-related parameters based on a medical image. The method includes receiving a medical image acquired by an image acquisition device and predicting a sequence of physiological-related parameters at a sequence of positions and simultaneously estimating an uncertainty level of the predicted sequence of physiological parameters from the medical image by using a sequential learning model. The sequential learning model is trained to minimize a loss function associated with the uncertainty level. The method not only provides predictions but also the corresponding uncertainty estimations by using sequential learning model(s), thus improving the transparency and explainability of the sequential learning model.

公开(公告)号：US11357464B2

公开(公告)日：2022-06-14

申请号：US17317487

申请日：2021-05-11

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Xin Wang ,  Youbing Yin ,  Bin Kong ,  Yi Lu ,  Junjie Bai ,  Zhenghan Fang ,  Qi Song

IPC: G06T7/00 ,  A61B6/03 ,  G16H50/20 ,  A61B6/00 ,  A61B5/00 ,  G16H10/60 ,  G06N3/04 ,  G06N3/08 ,  G16H30/40 ,  A61B6/02

Abstract: Embodiments of the disclosure provide methods and systems for determining a disease condition from a 3D image of a patient. The exemplary system may include a communication interface configured to receive the 3D image acquired of the patient by an image acquisition device. The system may further include a processor, configured to determine a 3D region of interest from the 3D image and apply a detection network to the 3D region of interest to determine the disease condition and a severity of the disease condition. The detection network is a multi-task learning network that determines the disease condition based on one or more lesion masks determined from the 3D region of interest and determines the severity of the disease condition from the 3D region of interest. The processor is further configured to provide a diagnostic output based on the disease condition and the severity of the disease condition.

公开(公告)号：US10803583B2

公开(公告)日：2020-10-13

申请号：US16056535

申请日：2018-08-07

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Xin Wang ,  Youbing Yin ,  Kunlin Cao ,  Yuwei Li ,  Junjie Bai ,  Xiaoyang Xu

IPC: G06T7/00 ,  A61B6/00 ,  G06K9/46 ,  G06K9/62 ,  G06T17/00

Abstract: The disclosure relates to systems and methods for determining blood vessel conditions. The method includes receiving a sequence of image patches along a blood vessel path acquired by an image acquisition device. The method also includes predicting a sequence of blood vessel condition parameters on the blood vessel path by applying a trained deep learning model to the acquired sequence of image patches on the blood vessel path. The deep learning model includes a data flow neural network, a recursive neural network and a conditional random field model connected in series. The method further includes determining the blood vessel condition based on the sequence of blood vessel condition parameters. The disclosed systems and methods improve the calculation of the sequence of blood vessel condition parameters through an end-to-end training model, including improving the calculation speed, reducing manual intervention for feature extraction, increasing accuracy, and the like.

公开(公告)号：US20200311485A1

公开(公告)日：2020-10-01

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: G06K9/62 ,  G06K9/52 ,  G06T19/00 ,  G06N3/08

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.

公开(公告)号：US20190050982A1

公开(公告)日：2019-02-14

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

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.

公开(公告)号：US11869142B2

公开(公告)日：2024-01-09

申请号：US17557373

申请日：2021-12-21

Applicant: Shenzhen Keya Medical Technology Corporation

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

IPC: G06T17/00 ,  G06T7/50

CPC classification number: G06T17/00 ,  G06T7/50 ,  G06T2207/10116 ,  G06T2207/30101 ,  G06T2210/41

Abstract: The disclosure provides a method, device and a computer-readable medium for performing three-dimensional blood vessel reconstruction. The device includes an interface configured to receive a single-view two-dimensional image of a blood vessel of a patient, where the single-view two-dimensional image is a projection image acquired in a predetermined projection direction. The device further includes a processor configured to estimate three-dimensional information of the blood vessel from the single-view two-dimensional image using an inference model, and reconstruct a three-dimensional model of the blood vessel based on the three-dimensional information.

公开(公告)号：US11495357B2

公开(公告)日：2022-11-08

申请号：US17107881

申请日：2020-11-30

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Bin Ma ,  Ying Xuan Zhi ,  Xiaoxiao Liu ,  Xin Wang ,  Youbing Yin ,  Qi Song

IPC: G16H50/50 ,  A61B5/0275 ,  A61B5/026 ,  A61B6/00 ,  A61B6/03 ,  G06T7/00 ,  A61B5/02

Abstract: The present disclosure is directed to a method and system for automatically predicting a physiological parameter based on images of vessel. The method includes receiving the images of a vessel acquired by an imaging device. The method further includes determining a sequence of temporal features at a sequence of positions on a centerline of the vessel based on the images of the vessel, and determining a sequence of structure-related features at the sequence of positions on the centerline of the vessel. The method also includes fusing the sequence of structure-related features and the sequence of temporal features at the sequence of positions respectively. The method additionally includes determining the physiological parameter for the vessel at the sequence of positions, by using a sequence-to-sequence neural network configured to capture sequential dependencies among the sequence of fused features.

公开(公告)号：US11494908B2

公开(公告)日：2022-11-08

申请号：US17408321

申请日：2021-08-20

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Ruoping Li ,  Pengfei Zhao ,  Junhuan Li ,  Bin Ouyang ,  Yuwei Li ,  Kunlin Cao ,  Qi Song

IPC: G06K9/00 ,  G06T7/00 ,  G06K9/62 ,  G06F40/20 ,  G16H30/20 ,  G16H10/60 ,  G06N3/08 ,  G06V10/50

Abstract: The present disclosure relates to a medical image analysis method, a medical image analysis device, and a computer-readable storage medium. The medical image analysis method includes receiving a medical image acquired by a medical imaging device; determining a navigation trajectory by performing navigation processing on the medical image based on an analysis requirement, the analysis requirement indicating a disease to be analyzed; extracting an image block set along the navigation trajectory; extracting image features using a first learning network based on the image block set; and determining an analysis result using a second learning network based on the image features and the navigation trajectory.

公开(公告)号：US20220351374A1

公开(公告)日：2022-11-03

申请号：US17725051

申请日：2022-04-20

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Xin WANG ,  Youbing YIN ,  Bin KONG ,  Yi LU ,  Xinyu GUO ,  Hao-Yu YANG ,  Qi SONG

IPC: G06T7/00 ,  G06V10/764 ,  G06V10/82 ,  G06V10/40 ,  G06V10/776 ,  G16H50/20 ,  G16H50/30

Abstract: This disclosure discloses a method for analyzing clinical data. The Method includes extracting a first feature information by applying a neural network to the clinical data; predicting a disease status related parameter by applying a regression model to the extracted first feature information; generating a second feature information based on the extracted first feature information and the disease status related parameter; and predicting a disease status classification result by applying a classification model to the second feature information. The method can improve the prediction accuracy and the diagnosis efficiency of doctors.

公开(公告)号：US20220284571A1

公开(公告)日：2022-09-08

申请号：US17505917

申请日：2021-10-20

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

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

IPC: G06T7/00 ,  G06N20/00 ,  G06N3/08

Abstract: Embodiments of the disclosure provide systems and methods for medical image analysis. A method may include receiving a medical image acquired of a subject by an image acquisition device. The method may also include applying a calcium detection model to detect at least one calcium region relevant in determining a calcium score from the medical image. The method may further include applying a score regression learning model to the at least one calcium region to determine a calcium score for the medical image. The method may additionally include providing the determined calcium score of the medical image for a diagnosis of the subject.