公开(公告)号：US12045961B2

公开(公告)日：2024-07-23

申请号：US18489876

申请日：2023-10-19

申请人： ZHEJIANG LAB

发明人： Jingsong Li ,  Jinnan Hu ,  Peijun Hu ,  Yu Tian ,  Tianshu Zhou

IPC分类号： G06T5/70 ,  G06T5/10

CPC分类号： G06T5/70 ,  G06T5/10 ,  G06T2207/20064 ,  G06T2207/20081 ,  G06T2207/20084

摘要： Disclosed is an image denoising method and apparatus based on wavelet high-frequency channel synthesis. Image data are expanded to a plurality of frequency-domain channels, a plurality of “less-noise” channels and a plurality of “more-noise” channels are grouped through a noise-sort algorithm, and a denoising submodule and a synthesis submodule based on style transfer are combined to form a generative network. A discriminative network is established to add a constraint to the global loss function. After iteratively training the GAN model described above, the denoised image data can be obtained through wavelet inverse transformation. The disclosed algorithm can effectively solve the problem of “blurring” and “loss of details” introduced by traditional filtering or CNN-based deep learning methods, which is especially suitable for noise-overwhelmed image data or high dimensional image data.

公开(公告)号：US11562491B2

公开(公告)日：2023-01-24

申请号：US17541271

申请日：2021-12-03

申请人： ZHEJIANG LAB

发明人： Jingsong Li ,  Peijun Hu ,  Yu Tian ,  Tianshu Zhou

IPC分类号： G06T7/11 ,  G06V10/82 ,  G06N3/08

摘要： The present invention discloses an automatic pancreas CT segmentation method based on a saliency-aware densely connected dilated convolutional neural network. Under a coarse-to-fine two-step segmentation framework, the method uses a densely connected dilated convolutional neural network as a basis network architecture to obtain multi-scale image feature expression of the target. An initial segmentation probability map of the pancreas is predicted in the coarse segmentation stage. A saliency map is then calculated through saliency transformation based on a geodesic distance transformation. A saliency-aware module is introduced into the feature extraction layer of the densely connected dilated convolutional neural network, and the saliency-aware densely connected dilated convolutional neural network is constructed as the fine segmentation network model. A coarse segmentation model and the fine segmentation model are trained using a training set, respectively.

公开(公告)号：US12106404B2

公开(公告)日：2024-10-01

申请号：US18363703

申请日：2023-08-01

申请人： ZHEJIANG LAB

发明人： Jingsong Li ,  Yiwei Gao ,  Peijun Hu ,  Tianshu Zhou ,  Yu Tian

IPC分类号： G06T11/00 ,  G06T3/4053 ,  G06T5/70 ,  G16H30/40

CPC分类号： G06T11/006 ,  G06T3/4053 ,  G06T5/70 ,  G06T11/005 ,  G16H30/40 ,  G06T2207/10081 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30004 ,  G06T2207/30168 ,  G06T2211/441

摘要： The present application discloses a label-free adaptive CT super-resolution reconstruction method, device and system based on a generative network, which comprises the following modules: an acquisition module configured for acquiring low-resolution original CT image data; a preprocessing module configured for performing super-resolution reconstruction on original CT images based on total variation to obtain an initial value; and a super-resolution reconstruction module configured for performing high-resolution reconstruction on the initial value. According to the present application, a parameter fine-tuning method is adopted, and a CT reconstruction network which is not suitable for a certain patient is adjusted into a network which is suitable for the patient's situation on the premise of not using a large number of data sets for training; only the low-resolution CT data of the patient is used in this process, and the corresponding high-resolution CT data is not needed as a label.

公开(公告)号：US12094484B2

公开(公告)日：2024-09-17

申请号：US18360838

申请日：2023-07-28

申请人： ZHEJIANG LAB

发明人： Jingsong Li ,  Zhenchuan Zhang ,  Tianshu Zhou ,  Yu Tian

IPC分类号： G10L21/0232 ,  G10L17/02 ,  G10L17/04 ,  G10L25/30

CPC分类号： G10L21/0232 ,  G10L17/02 ,  G10L17/04 ,  G10L25/30

摘要： The present disclosure discloses a general speech enhancement method and apparatus using multi-source auxiliary information. The method includes following steps: S1: building a training data set; S2: using the training data set to learn network parameters of a model, and building a speech enhancement model; S3: building a sound source information database in a pre-collection or on-site collection mode; S4: acquiring an input of the speech enhancement model; and S5: taking a noisy original signal as a main input of the speech enhancement model, taking auxiliary sound signals of a target source group and auxiliary sound signals of an interference source group as side inputs of the speech enhancement model for speech enhancement, and obtaining an enhanced speech signal.

公开(公告)号：US12119108B2

公开(公告)日：2024-10-15

申请号：US18363701

申请日：2023-08-01

申请人： ZHEJIANG LAB

发明人： Jingsong Li ,  Wenchao Xiang ,  Guangyuan Deng ,  Tianshu Zhou ,  Yu Tian

IPC分类号： G06F16/25 ,  G06F9/48 ,  G16H10/60 ,  G16H40/20

CPC分类号： G16H40/20 ,  G06F9/4881 ,  G06F16/254 ,  G16H10/60

摘要： The present disclosure discloses a medical ETL task dispatching method, system and apparatus based on multiple centers. The method includes following steps: step S1: testing and verifying ETL tasks; step S2: deploying the ETL tasks to a hospital center, and dispatching the ETL tasks to a plurality of executors for execution; step S3: screening an executor set meeting resource demands of ETL tasks to be dispatched; step S4: calculating a current task load of each executor in the executor set; step S5: selecting the executor with a minimum current task load to execute the ETL tasks; and step S6: selecting, by the dispatching machine, the ETL tasks from executor active queues according to a priority for execution. The present disclosure selects the most suitable executor by analyzing a serving index as a task to be dispatched on a current dispatching machine.

公开(公告)号：US11989883B2

公开(公告)日：2024-05-21

申请号：US18360796

申请日：2023-07-27

申请人： ZHEJIANG LAB

发明人： Jingsong Li ,  Jun Li ,  Baochen Wang ,  Zhuoxin Li ,  Yu Tian ,  Tianshu Zhou

IPC分类号： G06T7/11 ,  G06T7/00

CPC分类号： G06T7/0014 ,  G06T2207/10088 ,  G06T2207/30016

摘要： The present application discloses a system and a device for functional connectivity matrix processing based on feature selection using a filtering method, which comprises the following steps: acquiring a preprocessed resting state brain functional magnetic resonance image of a subject; extracting time series; calculating a Pearson correlation coefficient to obtain a Pearson correlation coefficient matrix; vectorizing the Pearson correlation coefficient matrix; calculating quantitative correlation indices using a filtering method, and selecting a quantitative correlation index based on a preset threshold; performing weighting processing a selected functional connectivity feature by using the corresponding quantitative correlation index with high correlation with a disease diagnosis result to obtain a functional connectivity matrix; and obtaining a prediction result from the functional connectivity matrix.

公开(公告)号：US11521751B2

公开(公告)日：2022-12-06

申请号：US17553832

申请日：2021-12-17

申请人： ZHEJIANG LAB

发明人： Jingsong Li ,  Shiqiang Zhu ,  Tianshu Zhou ,  Yu Tian

IPC分类号： G16H50/50 ,  G16H10/60 ,  G16H50/30 ,  G16H50/70 ,  G16H50/20 ,  G16H70/20 ,  G06K9/62 ,  G06N5/00

摘要： Provided is a patient data visualization method and system for assisting decision making in chronic diseases. According to the present application, a management data model diagram of a patient on a hyperplane is constructed by constructing a chronic disease knowledge graph, and combining static data and dynamic data of the patient, and then the management data model diagram is projected onto a two-dimensional plane. The difference of the Euclidean distance between features of a patient information model on a two-dimensional plane graph from the distance of standard features is compared, and a management plan is generated and recommended in combination with path node concepts and an attribute relationship between the concepts.

公开(公告)号：US12086534B2

公开(公告)日：2024-09-10

申请号：US18360794

申请日：2023-07-27

申请人： ZHEJIANG LAB

发明人： Tianshu Zhou ,  Xin Gao ,  Jingsong Li ,  Yu Tian

IPC分类号： G06F40/14 ,  G10L15/22

CPC分类号： G06F40/14 ,  G10L15/22 ,  G10L2015/223

摘要： The present disclosure discloses a multi-component abstract association and fusion method and apparatus in page design. The method includes the following steps: step S1: a construction demand is acquired, and the construction demand is analyzed through a speech recognition method to obtain a natural language text; step S2: an abstract model is constructed by predefining a component library, a rule library and a relationship library, and the abstract model performs components fusion to obtain a JSON structure of a fused component; step S3: the JSON structure of the fused component is escaped into a virtual DOM by using a rendering function, and attributes and events of a virtual DOM node are mapped to obtain a fused component drawing result; and step S4: a real DOM structure is created and interpolated into a real DOM node, so as to realize display of the fused component on a view.

公开(公告)号：US11907390B2

公开(公告)日：2024-02-20

申请号：US18336053

申请日：2023-06-16

申请人： ZHEJIANG LAB

发明人： Jingsong Li ,  Guangyuan Deng ,  Tianshu Zhou ,  Yu Tian

IPC分类号： H04L29/06 ,  G06F21/62 ,  H04L9/30 ,  G06F21/60 ,  G06F16/901

CPC分类号： G06F21/6218 ,  G06F16/9024 ,  G06F21/602 ,  H04L9/3006

摘要： Discloses a method and an apparatus for visual construction of a knowledge graph system. In the present disclosure, data permission of a distributed client is determined through a central server. The central server obtains a master template of a knowledge graph system and sends it to the distributed client. The distributed client receives a natural language inputted by a user and parses to generate an abstract syntax tree. The user completes customization of a subtemplate of the knowledge graph system through visual operation. The distributed client encrypts the subtemplate and then sends it to the central server. When the knowledge graph system is to be used, any knowledge concept is inputted, the central server calls and decrypts the subtemplate and then searches a database, and a tree structure knowledge graph is generated and sent to the distributed client.

公开(公告)号：US11735321B2

公开(公告)日：2023-08-22

申请号：US17543736

申请日：2021-12-07

申请人： ZHEJIANG LAB

发明人： Jingsong Li ,  Tianshu Zhou ,  Chengkai Wu ,  Ying Zhang

IPC分类号： G16H50/20 ,  G16H10/60 ,  G16H40/20 ,  A61B5/00

CPC分类号： G16H50/20 ,  G16H10/60 ,  A61B5/7267 ,  G16H40/20

摘要： Provided is a system for the prognostics of the chronic diseases after the medical examination based on the multi-label learning, including a data acquisition module, a data preprocessing module, a basic predicting model constructing module, and a local predicting module. The data acquisition module is configured to acquire physical examination data of a physical examination user. The basic predicting model constructing module is configured to construct a multi-label learning model for a physical examination scenario. The local predicting module includes a local model training unit and a predicting unit. The local model training unit adjusts the basic predicting model into a local predicting model, and solidifies the local predicting model into the local predicting module. The predicting unit outputs a predicted prognostic index for an occurrence of a plurality of chronic diseases, and finally acquires a future expected occurrence time of the chronic diseases.