公开(公告)号：US20230290514A1

公开(公告)日：2023-09-14

申请号：US18129754

申请日：2023-03-31

Applicant: ZHEJIANG LAB

Inventor： Yu ZHANG ,  Jun LI ,  Chaoliang SUN ,  Huan ZHANG ,  Zhichao WANG ,  Jingsong LI

IPC: G16H50/30 ,  G06T7/00 ,  G06V10/62 ,  G06F17/16

CPC classification number: G16H50/30 ,  G06T7/0012 ,  G06V10/62 ,  G06F17/16 ,  G06T2207/10088 ,  G06T2207/30016

Abstract: Disclosed are a disease prediction method, system and apparatus based on a multi-relation functional connectivity matrix. A Pearson correlation coefficient matrix and a DTW distance matrix are respectively calculated according to resting state functional magnetic resonance time series extracted from a brain atlas, the DTW distance matrix is converted in combination with the Pearson correlation coefficient matrix into a DTW′ matrix which includes correlation degree and correlation direction information and whose numerical range is equivalent to the value range of a Pearson coefficient, and a functional connectivity matrix is obtained after weighted combination. The present disclosure combines DTW distance information to weaken the dynamic change of functional connectivity and the influence of asynchrony of functional signals in different brain regions on the functional connectivity matrix, so that the calculated functional connectivity matrix can better reflect the correlation between the functional signals in different brain regions.

公开(公告)号：US11715562B2

公开(公告)日：2023-08-01

申请号：US17775873

申请日：2021-01-23

Applicant: ZHEJIANG LAB ,  MINFOUND MEDICAL SYSTEMS CO., LTD

Inventor： Ling Chen ,  Wentao Zhu ,  Bao Yang ,  Fan Rao ,  Hongwei Ye ,  Yaofa Wang

IPC: G06V10/77 ,  G06V10/84 ,  G06V10/82 ,  G06V10/774 ,  G16H50/20 ,  G06V10/766

CPC classification number: G16H50/20 ,  G06V10/766 ,  G06V10/774 ,  G06V10/7715 ,  G06V10/82 ,  G06V10/84 ,  G06V2201/03

Abstract: Disclosed is a method for multi-center effect compensation based on a PET/CT intelligent diagnosis system. The method includes the following steps: estimating multi-center effect parameters of a test center B relative to a training center A by implementing a nonparametric mathematical method for data of the training center A and the test center B based on a location-scale model about additive and multiplicative multi-center effect parameters, and using the parameters to compensate the data of the test center B to eliminate a multi-center effect between the test center B and the training center A. According to the present disclosure, the multi-center effect between the training center A and the test center B can be compensated, so that the compensated data of the test center B can be used in the model trained by the training center A, and the generalization ability of the model is indirectly improved.

公开(公告)号：US11664966B2

公开(公告)日：2023-05-30

申请号：US18075430

申请日：2022-12-06

Applicant: ZHEJIANG LAB

Inventor： Changming Zhang ,  Xianbin Yu ,  Xuemin Li ,  Jie Shen

IPC: H04L5/14

CPC classification number: H04L5/1461

Abstract: A co-frequency co-time full duplex (CCFD) signal receiving method includes: taking the sent baseband signal as the self-interference reference signal, reconstructing self-interference, and then performing primary self-interference cancellation on the received signal; processing, by using a timing synchronization loop, the signal after the primary self-interference cancellation, realizing timing recovery at the optimal sampling point of the useful signal through resampling a, and controlling resampling b1 and resampling b2 after performing low-pass filtering on the timing error signal in the timing synchronization loop, to recover the optimal sampling points of the self-interference reference signal and the received signal respectively; and performing joint self-interference cancellation and equalization on the resampled self-interference reference signal and the resampled received signal, and receiving the useful signal through signal demodulation. The above method can significantly enhance the self-interference cancellation capability of CCFD technology and improve the receiving performance of the useful signal.

公开(公告)号：US20230122343A1

公开(公告)日：2023-04-20

申请号：US17896055

申请日：2022-08-25

Applicant: ZHEJIANG LAB

Inventor： Wei HUA ,  Yechi MA ,  Shun ZHANG

IPC: G06V10/74 ,  G06V10/82

Abstract: An efficient across-camera target re-identification method based on similarity, which obtains a plurality of matching pairs and similarity scores thereof through two groups of targets to be matched; wherein for the matching pairs that are not matched by both parties, only a part of the matching pairs with higher similarity scores are selected each time, and the matching pairs are traversed according to the order of the similarity scores thereof from large to small, and the matching pairs and the similarity scores thereof are output as a matching result; when any target to be matched in a matching pair already appears in the matching result, the target cannot be output as the matching result; unmatched matching pairs are repeated traversed until the matching result reaches the expectation. The method firstly solves the multi-target matching problem based on similarity, and greatly reduces the time complexity and improves the efficiency.

公开(公告)号：US20230121358A1

公开(公告)日：2023-04-20

申请号：US17766204

申请日：2021-01-23

Applicant: ZHEJIANG LAB ,  MINFOUND MEDICAL SYSTEMS CO., LTD

Inventor： Fan RAO ,  Wentao ZHU ,  Bao YANG ,  Ling CHEN ,  Hongwei YE

IPC: G06T7/00

Abstract: Disclosed is a CT image generation method for attenuation correction of PET images. According to the method, a CT image and a PET image at T1 and a PET image at T2 are acquired and input into a trained deep learning network to obtain a CT image at T2; the CT image can be applied to the attenuation correction of the PET image, thereby obtaining more an accurate PET AC (Attenuation Correction) image. According to the CT image generation method for attenuation correction of PET images, the dosage of X-rays received by a patient in the whole image acquisition stage can be reduced, and physiological and psychological pressure of the patient is relieved. In addition, the later image acquisition only needs a PET imaging device, without the need of PET/CT device, cost of imaging resource distribution can be reduced, and the imaging expense of the whole stage is reduced.

公开(公告)号：US20230082598A1

公开(公告)日：2023-03-16

申请号：US17740349

申请日：2022-05-10

Applicant: ZHEJIANG LAB

Inventor： Wentao ZHU ,  Hui SHEN ,  Ling CHEN ,  Yuan JIN ,  Hailiang HUANG

IPC: G06T7/00 ,  A61B6/00 ,  G06T7/11 ,  G06V10/44 ,  G06V10/764

Abstract: Disclosed is a diagnostic apparatus for a chronic obstructive pulmonary disease (COPD) based on prior knowledge CT subregion radiomics, belonging to the field of medical imaging. The diagnostic apparatus comprises: a subregion partitioning module based on prior knowledge configured for partitioning a CT lung image of a patient into three subregions based on the CT values of the interior of the lung, wherein the CT value of the interior of the lung of a subregion 1 is in the range of (−1024, −950), the CT value of the interior of the lung of a subregion 2 is in the range of (−190, 110), and the CT value of the interior of the lung of a subregion 3 is in the range of (−950, −190); a feature extraction module configured for extracting the radiomics features of the three subregions, respectively, and obtaining the LAA-950I features.

公开(公告)号：US20230080337A1

公开(公告)日：2023-03-16

申请号：US17701692

申请日：2022-03-23

Applicant: ZHEJIANG LAB

Inventor： Wentao ZHU ,  Mengfan XUE ,  Shaojie LI ,  Defu YANG

IPC: G06T7/00 ,  G06T7/11 ,  G06T7/194 ,  G06T7/90

Abstract: Disclosed is a method for automatic classification of pathological images based on a staining intensity matrix. This method directly extracts the staining intensity matrix irrelevant to a stain ratio, a staining platform, a scanning platform and some human factors in the pathological image as the feature information of classification, without restoring normalized stained images, while retaining all impurity-free information related to diagnosis. It avoids the phenomenon that the diagnostic effect of the existing computer-aided diagnosis method of pathological images based on the traditional color normalization method changes with the changes of the selected standard pathological sections. Moreover, it avoids the error introduced by the need to restore the stained image, and has a higher diagnostic accuracy and a more stable diagnostic effect. At the same time, the method can realize the diagnosis of pathological images in a shorter time, which is easy to realize and more practical.

公开(公告)号：US11568996B2

公开(公告)日：2023-01-31

申请号：US17541301

申请日：2021-12-03

Applicant: ZHEJIANG LAB

Inventor： Jingsong Li ,  Yu Tian ,  Yong Shang ,  Ran Xin

IPC: G16H10/60 ,  G16H50/50 ,  G16H50/20

Abstract: Provided is a cross-departmental decision support system for early diagnosis of a chronic kidney disease based on knowledge graph, which comprises a patient information model building module, a patient information model library storage module, a knowledge graph association module, a knowledge graph inference module and a decision support feedback module. According to the present application, by constructing a patient information model and utilizing an OMOP CDM standard terminology system, patient electronic medical record data is constructed into a patient information model with unified concept coding and unified semantic structure; making full use the advantages of semantic technology in data interactivity and scalability, so that the system has better adaptability and scalability to heterogeneous data in different hospitals.

公开(公告)号：US20220415534A1

公开(公告)日：2022-12-29

申请号：US17902215

申请日：2022-09-02

Applicant: Zhejiang Lab ,  Zhejiang University

Inventor： Cuihong Li ,  Yuanyuan Ma ,  Yizhou Zhang ,  Xiaowen Gao ,  Shaochong Zhu ,  Huizhu Hu

IPC: G21K1/00 ,  H05B3/00

Abstract: A method for enhancing vacuum tolerance of optical levitation particles includes steps of: (1) turning on a trapping laser to form an optical trap, loading the particles to an effective capture region of the optical trap, and collecting scattered light signals; (2) turning on the preheating laser, and directing a preheating laser beam to the captured particles; (3) adjusting a power of the preheating laser until a particle heating rate is larger than a heat dissipation rate; (4) turning on the vacuum pump, and stopping evacuating when a vacuum degree is greater than a vacuum inflection point of a first reduction of the effective capture region of the optical trap; and (5) turning off the preheating laser when the scattered light signals collected by the photodetector no longer changes. The present invention improves a stable capture probability of the particles in high vacuum environment.

公开(公告)号：US20220399119A1

公开(公告)日：2022-12-15

申请号：US17775873

申请日：2021-01-23

Applicant: ZHEJIANG LAB ,  MINFOUND MEDICAL SYSTEMS CO., LTD

Inventor： Ling CHEN ,  Wentao ZHU ,  Bao YANG ,  Fan RAO ,  Hongwei YE ,  Yaofa WANG

IPC: G16H50/20 ,  G06V10/82 ,  G06V10/774 ,  G06V10/77 ,  G06V10/766 ,  G06V10/84

Abstract: Disclosed is a method for multi-center effect compensation based on a PET/CT intelligent diagnosis system. The method includes the following steps: estimating multi-center effect parameters of a test center B relative to a training center A by implementing a nonparametric mathematical method for data of the training center A and the test center B based on a location-scale model about additive and multiplicative multi-center effect parameters, and using the parameters to compensate the data of the test center B to eliminate a multi-center effect between the test center B and the training center A. According to the present disclosure, the multi-center effect between the training center A and the test center B can be compensated, so that the compensated data of the test center B can be used in the model trained by the training center A, and the generalization ability of the model is indirectly improved.