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61.发明申请公开(公告)号：US20190206052A1
公开(公告)日：2019-07-04
申请号：US16236366
申请日：2018-12-29
Inventor： Qingmao Hu , Liyilei Su , Xiaodong Zhang , Xianjun Fu
Abstract: The present application relates to the technical field of image recognition, and provides a carpal segmentation and recognition method, including: performing threshold segmentation on a carpal region of interest on a child orthotopic wrist X-ray image based on an adaptive threshold segmentation manner of variable threshold segmentation windows, and extracting edge information of the carpal region of interest based on an edge detection manner; combining a binarized image obtained by performing the threshold segmentation with the extracted edge information to obtain an initial segmentation image; performing carpal recognition on the initial segmentation image by using a carpal anatomy priori model to obtain an initial recognition image including information of each carpal bone; and performing boundary optimization on the initial recognition image, and outputting a carpal recognition image obtained after the boundary optimization is performed.
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公开(公告)号：US10280425B2
公开(公告)日：2019-05-07
申请号：US14909060
申请日：2014-08-05
Applicant: Shenzhen Institutes of Advanced Technology , Shenzhen Hornetcorn Biotechnology Company, Ltd.
Inventor： Zhiying Chen , Fei Ma , Chengyi He
Abstract: Provided are a minicircle DNA recombinant parental plasmid having a genetically engineered antibody gene expression cassette and a preparation method for the plasmid, a minicircle DNA having the genetically engineered antibody gene expression cassette, a preparation method for the DNA, and applications thereof, and, a host cell having the minicircle DNA, a preparation method for the cell, and applications thereof. Also provided are a genetically engineered antibody, a preparation method for same, and applications thereof.
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公开(公告)号：US20190011515A1
公开(公告)日：2019-01-10
申请号：US16067204
申请日：2015-12-30
Inventor： Hairong Zheng , Xin Liu , Chuanli Cheng , Chao Zou
IPC: G01R33/48 , G01R33/565 , G01R33/485 , G01R33/46 , A61B5/055 , G01R33/44 , G01R33/56
Abstract: Provided are a magnetic resonance chemical-shift-encoded imaging method, apparatus, and device, belonging to the technical field of magnetic resonance imaging. The method comprises: in a phasor-error plot established on the basis of a two-point magnetic resonance signal model, determining to be an initial seed point a pixel having a unique phasor and causing said plot to reach a minimal local value; according to the initial seed point, estimating the phasor value of a to-be-estimated pixel to obtain a field map; mapping and merging the field map at the highest resolution to obtain a reconstructed field map; determining a reconstructed seed point from the reconstructed field map, and estimating the reconstructed seed point to obtain the phasor value of the reconstructed to-be-estimated pixel; according to the reconstructed seed point and the phasor value of the reconstructed to-be-estimated pixel, obtaining two separate images having predetermined components. In the method, a region simultaneously containing two components is identified as a seed point, eliminating the deviation caused by phasor-value jump at high resolution and ensuring the correctness of the seed point ultimately selected.
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公开(公告)号：US10121283B2
公开(公告)日：2018-11-06
申请号：US15371148
申请日：2016-12-06
Inventor： Hui Huang , Kangxue Yin , Daniel Cohen-Or
Abstract: A method for reconstructing surface from a point cloud includes following steps: (a) extracting skeletal curves from an input point cloud; (b) editing the extracted skeletal curves, and assigning sweeping path; (c) obtaining sliced point clouds along the edited skeletal curves, and fitting a closed NURBS curve according to the sliced point clouds; (d) reconstructing the point cloud to get generalized cylinders along the assigned sweeping path, according to the closed NURBS curves; (e) merging the generalized cylinders into a single surface, and smoothing intersections of the generalized cylinders so as to reconstruct surface from the point cloud. The invention further relates to a system for reconstructing surface from a point cloud. The invention can reconstruct the surface with high accuracy by the minimum interactions, and can deal with point cloud data having missing region caused by occlusion. In addition, the invention can achieve high reconstruction quality and fine controllability.
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65.发明授权公开(公告)号：US10089781B2
公开(公告)日：2018-10-02
申请号：US15389959
申请日：2016-12-23
Inventor： Hui Huang , Shihao Wu , Minglun Gong , Matthias Zwicker , Daniel Cohen-Or
Abstract: The present disclosure provides a three-dimensional point cloud model reconstruction method and a device. The method comprises: 1) sampling and WLPO-consolidating an input point set to generate an initial surface point set, copying the initial surface point set as an initial position of an interior skeleton point set, to establish a correspondence relation between surface points and skeleton points; 2) moving points in the interior skeleton point set inwards along a direction opposite to a normal vector thereof, to generate interior points; 3) using a self-adaptive anisotropic neighborhood as a regularization term to perform an optimization of the interior points, and generating skeleton points; 4) performing a consolidation and completion of the initial surface point set using the skeleton points, to generate consolidated surface points; 5) reconstructing a three-dimensional point cloud model according to the skeleton points, the surface points and the correspondence relation between the surface points and the skeleton points.
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Patent Agency Ranking
66.发明申请公开(公告)号：US20170363702A1
公开(公告)日：2017-12-21
申请号：US15618979
申请日：2017-06-09
Inventor： Xi PENG , Dong LIANG , Xin LIU , Hairong ZHENG
IPC: G01R33/563 , G01R33/56
CPC classification number: G01R33/56341 , A61B5/055 , A61B5/7203 , G01R33/5602 , G06T5/002 , G06T2207/10092
Abstract: The application provides a method, apparatus and computer program product for denoising a magnetic resonance diffusion tensor, wherein the method comprises: collecting data of K space; calculating a maximum likelihood estimator of a diffusion tensor according to the collected data of K space; calculating a maximum posterior probability estimator of the diffusion tensor by using sparsity of the diffusion tensor and sparsity of a diffusion parameter and taking the calculating maximum likelihood estimator as an initial value; and calculating the diffusion parameter according to the calculated maximum posterior probability estimator. The application solves the technical problem in the prior art of how to realize high precision denoising of diffusion tensor while not increasing scanning time and affecting spatial resolution, achieves the technical effects of effectively suppressing noises in the diffusion tensor and improving the estimation accuracy of the diffusion tensor.
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公开(公告)号：US20170296639A1
公开(公告)日：2017-10-19
申请号：US15312976
申请日：2015-05-20
Inventor： Yifan MA , Xiangjun ZHOU , Shang CHEN , Lintao CAI , Ce WANG , Peng LIU
IPC: A61K39/00 , C12N7/00 , A61K39/29 , C12N5/0784
CPC classification number: A61K39/0011 , A61K39/12 , A61K39/292 , A61K2039/5154 , A61K2039/55555 , C12N5/0639 , C12N7/00 , C12N2500/90 , C12N2501/05 , C12N2501/22 , C12N2501/2304 , C12N2730/10134
Abstract: The present invention provides a method for preparing dendritic cell loaded with antigen, the method comprising the steps of adding serum-free cell culture medium containing granulocyte-macrophage colony-stimulating factor (GM-CSF) and inter-leukin (IL)-4 into mononuclear cells, culturing in an incubator at 37° C. under 5% carbon dioxide for 5 days, adding target antigen wrapped cationic liposome and culturing for 8-24 hours to obtain target antigen loaded dendritic cell.
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68.发明申请公开(公告)号：US20170193692A1
公开(公告)日：2017-07-06
申请号：US15389959
申请日：2016-12-23
Inventor： Hui HUANG , Shihao WU , Minglun GONG , Matthias ZWICKER , Daniel COHEN-OR
CPC classification number: G06T17/00 , G06T5/002 , G06T7/20 , G06T7/60 , G06T13/40 , G06T2207/10028 , G06T2210/56
Abstract: The present disclosure provides a three-dimensional point cloud model reconstruction method, a computer readable storage medium and a device. The method comprises: 1) sampling and WLOP-consolidating an input point set to generate an initial surface point set, copying the initial surface point set as an initial position of an interior skeleton point set, to establish a correspondence relation between surface points and skeleton points; 2) moving points in the interior skeleton point set inwards along a direction opposite to a normal vector thereof, to generate interior points; 3) using a self-adaptive anisotropic neighborhood as a regularization term to perform an optimization of the interior points, and generating skeleton points; 4) performing a consolidation and completion of the initial surface point set using the skeleton points, to generate consolidated surface points; 5) reconstructing a three-dimensional point cloud model according to the skeleton points, the surface points and the correspondence relation between the surface points and the skeleton points.
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69.发明申请公开(公告)号：US20170132793A1
公开(公告)日：2017-05-11
申请号：US15412838
申请日：2017-01-23
Applicant: Shenzhen Institutes of Advanced Technology
Inventor： Qingmao HU , Tianqiao ZHANG
CPC classification number: G06T7/12 , G06T5/20 , G06T7/0012 , G06T7/11 , G06T7/149 , G06T2207/10101 , G06T2207/20016 , G06T2207/20024 , G06T2207/20104 , G06T2207/20116 , G06T2207/30041
Abstract: The present disclosure provides a method for acquiring a retina structure from an optical coherence tomographic image and a system thereof. The method comprises: calculating a region of interest (ROI) image of a source image; performing a Gaussian filtering of the ROI image; calculating a first estimated boundary position of a first layer boundary and a second estimated boundary position of a second layer boundary using a multi-resolution method; refining the first layer boundary and the second layer boundary respectively using a simplified active contour model according to the first estimated boundary position and the second estimated boundary position, to obtain a first initial boundary position of the first layer boundary and a second initial boundary position of the second layer boundary; smoothing the first initial boundary position and the second initial boundary position using a filtering method; acquiring segmentation positions of rest layer boundaries in the ROI image according to a segmented position of the first layer boundary and a segmented position of the second layer boundary. The present disclosure can improve the calculation speed and reduce the calculation complexity while maintaining high location accuracy.
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公开(公告)号：US20170109465A1
公开(公告)日：2017-04-20
申请号：US15392688
申请日：2016-12-28
Inventor： Bin WANG , Hui HUANG , Longhua WU
CPC classification number: G06F17/5018 , G06F17/11 , G06F17/16 , G06F2217/16 , G06T13/00
Abstract: The present disclosure discloses a method and a device for elastic object deformation modeling. The method comprises: acquiring a static point cloud of the elastic object and dynamic point cloud sequences; establishing a simulation tetrahedral mesh model; driving the simulation tetrahedral mesh model to track the dynamic point cloud sequences, to obtain track deformation sequences; iteratively estimating material property coefficients and corresponding reference shapes of the elastic object; performing the following operations in each iteration: obtaining a reference shape corresponding to a current material property coefficient; driving the simulation tetrahedral mesh model to simulate the deformation from the same initial deformation according to the coefficient and the reference shape to obtain a simulation deformation sequences; calculating a positional deviation between the simulation deformation sequences and the track deformation sequences; and updating the material property coefficients in a direction in which the positional deviation is decreased; establishing an elastic object deformation model according to a material property coefficient under a minimum positional deviation and corresponding reference shape. The technical solution can establish a vivid elastic object deformation model.
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