公开(公告)号：US20210279906A1

公开(公告)日：2021-09-09

申请号：US17330557

申请日：2021-05-26

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Junjie Bai ,  Zhihui Guo ,  Youbing Yin ,  Xin Wang ,  Yi Lu ,  Kunlin Cao ,  Qi Song ,  Xiaoyang Xu ,  Bin Ouyang

IPC: G06T7/68 ,  G06N3/04 ,  G06N3/08

Abstract: Systems and methods for generating a centerline for an object in an image are provided. An exemplary method includes receiving an image containing the object. The method also includes detecting at least one bifurcation of the object using a trained bifurcation learning network based on the image. The method further includes extracting the centerline of the object based on a constraint condition that the centerline passes through the detected bifurcation.

公开(公告)号：US11069078B2

公开(公告)日：2021-07-20

申请号：US16550093

申请日：2019-08-23

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Junjie Bai ,  Zhihui Guo ,  Youbing Yin ,  Xin Wang ,  Yi Lu ,  Kunlin Cao ,  Qi Song ,  Xiaoyang Xu ,  Bin Ouyang

IPC: G06K9/00 ,  G06T7/68 ,  G06N3/04 ,  G06N3/08

Abstract: Systems and methods for generating a centerline for an object in an image are provided. An exemplary method includes receiving an image containing the object. The method also includes generating a distance cost image using a trained first learning network based on the image. The method further includes detecting end points of the object using a trained second learning network based on the image. Moreover, the method includes extracting the centerline of the object based on the distance cost image and the end points of the object.

公开(公告)号：US10980502B2

公开(公告)日：2021-04-20

申请号：US16689048

申请日：2019-11-19

Applicant: Shenzhen Keya Medical Technology Corporation

Inventor： Qi Song ,  Ying Xuan Zhi ,  Xiaoxiao Liu ,  Shubao Liu ,  Youbing Yin ,  Yuwei Li ,  Kunlin Cao

IPC: A61B6/00 ,  G06T7/20 ,  G06T7/277 ,  G06T7/00 ,  G06T7/269 ,  G06F16/50

Abstract: The present disclosure relates to a method, storage medium, and system for analyzing an image sequence of a periodic physiological activity. In one implementation, the method includes receiving the image sequence acquired by an imaging device, the image sequence having a plurality of frames, and identifying a feature point in a first frame. The method further includes determining motion vectors for the feature point in the frames of the image sequence. Each motion vector for the feature point is determined based on respective locations of corresponding feature points in frames adjacent to the first frame. The method also includes determining a motion magnitude profile based on the determined motion vectors and determining a phase of each frame in the image sequence based on the motion magnitude profile.

公开(公告)号：US10573005B2

公开(公告)日：2020-02-25

申请号：US16529769

申请日：2019-08-01

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

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

IPC: G06T7/11 ,  G06N20/00 ,  G06N3/08 ,  G06T7/174 ,  G06T7/00

Abstract: Embodiments of the disclosure provide systems and methods for analyzing a biomedical image including at least one tree structure object. The system includes a communication interface configured to receive a learning model and a plurality of model inputs derived from the biomedical image. The biomedical image is acquired by an image acquisition device. The system further includes at least one processor configured to apply the learning model to the plurality of model inputs to analyze the biomedical image. The learning model includes a first network configured to process the plurality of model inputs to construct respective feature maps and a second network configured to process the feature maps collectively. The second network is a tree structure network that models a spatial constraint of the tree structure object.

公开(公告)号：US11748902B2

公开(公告)日：2023-09-05

申请号：US17330557

申请日：2021-05-26

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Junjie Bai ,  Zhihui Guo ,  Youbing Yin ,  Xin Wang ,  Yi Lu ,  Kunlin Cao ,  Qi Song ,  Xiaoyang Xu ,  Bin Ouyang

IPC: G06K9/00 ,  G06T7/68 ,  G06N3/08 ,  G06N3/045

CPC classification number: G06T7/68 ,  G06N3/045 ,  G06N3/08 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30101 ,  G06T2207/30172

Abstract: Systems and methods for generating a centerline for an object in an image are provided. An exemplary method includes receiving an image containing the object. The method also includes detecting at least one bifurcation of the object using a trained bifurcation learning network based on the image. The method further includes extracting the centerline of the object based on a constraint condition that the centerline passes through the detected bifurcation.

公开(公告)号：US20230177677A1

公开(公告)日：2023-06-08

申请号：US17741654

申请日：2022-05-11

Applicant: Shenzhen Keya Medical Technology Corporation

Inventor： Shaofeng Yuan ,  Xiaomeng Huang ,  Tong Zheng ,  Yuwei Li ,  Kunlin Cao ,  Liwei Wang

IPC: G06T7/00 ,  G06T7/11 ,  G06T7/60 ,  G16H30/40 ,  G16H40/63

CPC classification number: G06T7/0012 ,  G06T7/11 ,  G06T7/60 ,  G16H30/40 ,  G16H40/63 ,  G06T2207/20021 ,  G06T2207/30101 ,  G06T2207/20081 ,  G06T2207/20132 ,  G06T2207/30008 ,  G06T2207/10012 ,  G06T2200/04 ,  G06T2207/10072 ,  G06T2207/30061 ,  G06T2207/20084

Abstract: The present disclosure relates to a method, a device and a medium for performing vessel segmentation in a medical image. The method may comprise acquiring a medical image for vessel segmentation containing multiple parts, each of which contains vessels with different structural attributes. The method may comprise dividing the medical image into sub-medical images according to the parts by using a processor. The method may comprise determining individual vessel segmentation result for each part by means of using the vessel segmentation model corresponding to the part based on the sub-medical image of the part by using the processor. The method may comprise obtaining a vessel segmentation result of the medical image by means of fusing the individual vessel segmentation results of the sub-medical images of the parts by the processor. By applying the method and the device, vessel segmentation models are adapted differentially for the individual parts so as to segment the vessels of the individual parts respectively, so that the entire vessel segmentation process is fast, effective, and accurate.

公开(公告)号：US20220198226A1

公开(公告)日：2022-06-23

申请号：US17692337

申请日：2022-03-11

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 ,  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 a processor, using a reinforcement learning network configured to predict movement of a virtual agent that traces the centerline in the image. The reinforcement learning network is further configured to perform at least one auxiliary task that detects a bifurcation in a trajectory of the object. The reinforcement learning network is trained by maximizing a cumulative reward and minimizing an auxiliary loss of the at least one auxiliary task. Additionally, the method includes displaying the centerline of the object.

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.

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.

公开(公告)号：US20200065989A1

公开(公告)日：2020-02-27

申请号：US16550093

申请日：2019-08-23

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Junjie Bai ,  Zhihui Guo ,  Youbing Yin ,  Xin Wang ,  Yi Lu ,  Kunlin Cao ,  Qi Song ,  Xiaoyang Xu ,  Bin Ouyang

IPC: G06T7/68 ,  G06N3/04 ,  G06N3/08

Abstract: Systems and methods for generating a centerline for an object in an image are provided. An exemplary method includes receiving an image containing the object. The method also includes generating a distance cost image using a trained first learning network based on the image. The method further includes detecting end points of the object using a trained second learning network based on the image. Moreover, the method includes extracting the centerline of the object based on the distance cost image and the end points of the object.