公开(公告)号：US12026881B2

公开(公告)日：2024-07-02

申请号：US17567458

申请日：2022-01-03

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Bin Kong ,  Youbing Yin ,  Xin Wang ,  Yi Lu ,  Haoyu Yang ,  Junjie Bai ,  Qi Song

IPC: G06T7/12 ,  G06F18/213 ,  G06F18/214 ,  G06T7/00 ,  G06T7/73 ,  G06V10/44

CPC classification number: G06T7/0012 ,  G06F18/213 ,  G06F18/214 ,  G06T7/75 ,  G06V10/44 ,  G06T2207/20081 ,  G06T2207/30104 ,  G06V2201/03

Abstract: Embodiments of the disclosure provide methods and systems for joint abnormality detection and physiological condition estimation from a medical image. The exemplary method may include receiving, by at least one processor, the medical image acquired by an image acquisition device. The medical image includes an anatomical structure. The method may further include applying, by the at least one processor, a joint learning model to determine an abnormality condition and a physiological parameter of the anatomical structure jointly based on the medical image. The joint learning model satisfies a predetermined constraint relationship between the abnormality condition and the physiological parameter.

公开(公告)号：US11847547B2

公开(公告)日：2023-12-19

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: G06T15/00 ,  G06N3/006 ,  G06N3/08 ,  G06T19/00 ,  G06V10/42 ,  G06F18/21 ,  G06V10/776

CPC classification number: G06N3/006 ,  G06F18/217 ,  G06N3/08 ,  G06T19/00 ,  G06V10/42 ,  G06V10/776

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：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.

公开(公告)号：US11574122B2

公开(公告)日：2023-02-07

申请号：US16544837

申请日：2019-08-19

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Feng Gao ,  Changsheng Liu ,  Yue Pan ,  Youbing Yin ,  Kunlin Cao ,  Qi Song

IPC: G06F40/295 ,  G06N3/08 ,  G16H10/60

Abstract: Embodiments of the disclosure provide systems and methods for processing unstructured texts in a medical record. A disclosed system includes at least one processor configured to determine a plurality of word representations of an unstructured text and tag entities in the unstructured text by performing a named entity recognition task on the plurality of word representations. The at least one processor is further configured to determine position embeddings based on positions of words in the unstructured text relative to positions of the tagged entities and concatenate the plurality of word representations with the position embeddings. The at least one processor is also configured to determine relation labels between pairs of tagged entities by performing a relationship extraction task on the concatenated word representations and position embeddings.

公开(公告)号：US20220091568A1

公开(公告)日：2022-03-24

申请号：US17468040

申请日：2021-09-07

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

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

IPC: G05B13/04 ,  G05B13/02

Abstract: The disclosure relates to a method and device for predicting a physical parameter based on input physical information, and medium. The method may include predicting, by a processor, an intermediate variable based on the input physical information with an intermediate sub-model, which incorporates a constraint on the intermediate variable according to prior information of the physical parameter. The method may also include transforming, by the processor, the intermediate variable predicted by the intermediate sub-model to the physical parameter with a transformation sub-model.

公开(公告)号：US20210082580A1

公开(公告)日：2021-03-18

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

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：US10937549B2

公开(公告)日：2021-03-02

申请号：US16048272

申请日：2018-07-28

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

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

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

Abstract: The present disclosure is directed to a method and device for automatically predicting FFR based on images of vessel. The method for automatically predicting FFR based on images of a vessel. The method comprises a step of receiving the images of a vessel acquired by an imaging device. Then, a sequence of flow speeds at a sequence of positions on a centerline of the vessel is acquired by a processor. A sequence of first features at the sequence of positions on a centerline of the vessel are acquired by the processor, by fusing structure-related features and flow speeds and using a convolutional neural network. Then, a sequence of FFR at the sequence of positions is determined by the processor through using a sequence-to-sequence neural network on the basis of the sequence of first features.

公开(公告)号：US10430949B1

公开(公告)日：2019-10-01

申请号：US16392516

申请日：2019-04-23

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

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

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

Abstract: Embodiments of the disclosure provide systems and methods for segmenting a biomedical image including at least one tree structure object. The system includes a communication interface configured to receive the biomedical image and a learning model. The biomedical image is acquired by an image acquisition device. The system further includes at least one processor configured to extract a plurality of image patches from the biomedical image and apply the learning model to the plurality of image patches to segment the biomedical image. The learning model includes a convolutional network configured to process the plurality of image patches to construct respective feature maps and a tree structure network configured to process the feature maps collectively to obtain a segmentation mask for the tree structure object. The tree structure network models a spatial constraint of the plurality of image patches.

公开(公告)号：US12062198B2

公开(公告)日：2024-08-13

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 ,  A61B6/00 ,  A61B8/08 ,  G06T7/00 ,  G06T7/73 ,  G06T11/00 ,  G06T17/00 ,  G06T19/20 ,  A61B5/00 ,  A61B5/055 ,  A61B6/03 ,  A61B8/12

CPC classification number: G06T7/344 ,  A61B6/5247 ,  A61B8/5261 ,  G06T7/0012 ,  G06T7/75 ,  G06T11/00 ,  G06T17/00 ,  G06T19/20 ,  A61B5/0066 ,  A61B5/055 ,  A61B6/032 ,  A61B8/12 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/10101 ,  G06T2207/10132 ,  G06T2207/20221 ,  G06T2207/30096 ,  G06T2207/30101 ,  G06T2210/41 ,  G06T2219/2004

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.

公开(公告)号：US20230097133A1

公开(公告)日：2023-03-30

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

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.