31 results about "Marching cubes" patented technology

Systems and methods for tracking a wireless device are disclosed. According to one aspect, the wireless device includes a hybrid global positioning system (GPS) and wireless local area network (WLAN) circuit board for seamless indoor and outdoor tracking. In embodiments, GPS and WLAN data are combined to obtain a position estimate of the device. In other embodiments, the circuit board automatically switches between WLAN and GPS data for indoor and outdoor environments. A Location Based Services (LBS) algorithm for determining the position of a wireless device using WLAN and/or GPS signals is also disclosed. The LBS algorithm is implemented by way of method steps including: sensing GPS and/or WLAN signals, measuring and/or converting the sensed signals to obtain distance data, fusing the distance data, and applying one or more approximation algorithms to the distance data to obtain a position estimate of the wireless device. A method for rendering position data using a Marching Cubes algorithm is further disclosed.

The invention discloses a medical image based segmentation and 3D reconstruction method and a 3D printing system. The method comprises segmenting a medical image and carrying out 3D reconstruction. The 3D printing system carries out 3D printing on a reconstruction model by utilizing a fused decomposition modeling (FDM) method. In the image segmentation part, a unique segmentation algorithm based on medical image (DICOM) preprocessing is provided, and a segmentation task is completed effectively. In the reconstruction part, an MC (Marching Cubes) algorithm is optimized, and the model in the invention is improved greatly. In an interactive interface, a visualization tool enables interaction between a user and the model to certain extent. Finally, a 3D printer prints the obtained model and obtains a simulated entity of bones, and doctors can touch and make interaction with the simulated entity.

A method for the problem of reconstructing a watertight surface defined by an implicit equation from a finite set of oriented points. As in other surface reconstruction approaches disctretizations of this continuous formulation reduce to the solution of sparse least-squares problems. Rather than forcing the implicit function to approximate the indicator function of the volume bounded by the surface, in the present formulation the implicit function is a smooth approximation of the signed distance function to the surface. Then solution thus introduced is a very simple hybrid FE/FD discretization, which together with an octree partitioning of space, and the Dual Marching Cubes algorithm produces accurate and adaptive meshes.

The invention relates to a core fracture identification method based on three-dimensional image information processing, belonging to the technical field of image segmentation. The method comprises the following steps of: scanning a core to be processed by using a CT (computerized tomography) machine, storing a scanned core CT sequence image in a computer, reading the well scanned core CT sequence image by using core three-dimensional image fracture identification software, performing three-dimensional image reconstruction on the core CT sequence image by utilizing a marching cubes algorithm, and performing a series of calculation, getting and screening processed by utilizing the differences among pores, random noise and fracture in morphological features in a three-dimensional data field to achieve the purpose of identifying a core fracture. According to the method provided by the invention, the core fracture can be fast and accurately identified; and the problems of causing error and even mistake due to negligence of communication information of the core fracture between layers in the existing isolate analysis of each core CT sequence image can be solved.

The invention relates to a micro-CT technology-based reservoir core three-dimensional entity model reconstruction method. The method includes the following steps that: a micro-CT technology is utilized to scan a reservoir core, so that a sectional scanning image of the reservoir core can be obtained, so that a CT image of a real reservoir core can be obtained, and a watershed algorithm is adopted to perform image segmentation on the CT image, so that the three-dimensional data of the image can be obtained; a Marching Cubes algorithm is adopted to generate a three-dimensional surface model of the reservoir core; and with the three-dimensional surface model of the reservoir core adopted as constraints, a constrained Delaunay tetrahedralization algorithm is utilized to generate the three-dimensional entity model of the reservoir core. According to the method of the invention, the three-dimensional entity model of the real reservoir core is established based on the sectional scanning image of the reservoir core, so that the obtained three-dimensional entity model of the reservoir core is more approximate to the structure of a real reservoir core. The method of the invention has the advantages of high accuracy and high efficiency. With the method adopted, defects of poor accuracy and low efficiency in the reconstruction of the three-dimensional entity model of a reservoir core in the prior art can be eliminated, and an effective guarantee can be provided for reservoir core simulation characteristic research.

The invention relates to an acceleration improvement algorithm based on cube edge sharing an equivalent point which comprises the following steps of: (1) storing related information of each edge of a cube by using a global array variable; (2) calculating equivalent point coordinates: before the equivalent point is calculated, firstly judging whether the edge is provided with the equivalent point or not , if so, extracting data stored in an array, wherein the data are used for calculating a triangular patch; if not, calculating coordinates and a normal vector of the equivalent point through linear interpolation; and recording the equivalent point of the edge of a current voxel, and giving an assignment for the equivalent point of the edge of other voxels sharing the edge; and (3) calculating the triangular patch by using a Marching Cubes algorithm, and processing the generated triangular patch through GPU (Ground Power Unit) acceleration image processing software to obtain a three-dimensional graph. By utilizing the method of the cube edges sharing the equivalent point, the algorithm efficiency can be improved and the three-dimensional reconstruction problem of medical images is effectively solved.

The invention discloses an adaptive hierarchical chest large data display implementation method, which comprises the following steps: dividing a CT (computed tomography) sectional image into a target layer image sequence and a background layer image sequence; performing interlayer cubic convolution interpolation on the divided target layer image sequence to form volume data of which each axial resolution is appropriate; making a clear surface drawing by a marching cubes algorithm; performing intraformational and interlayer sampling on the data of the background layer sequence to obtain uninteresting region data of which the resolution is reduced; making a rough body drawing for the data by a ray casting algorithm; displaying the drawing results of the clear surface drawing and the rough body drawing at the same time, and performing hybrid three-dimensional visualization. By the method, the local resolution in the interesting region is increased, and the anisotropic resolution of the uninteresting region is reduced, so that a user is facilitated to know the structure information of a local interesting region, the data volume is decreased and drawing can be implemented on an ordinary computer.

The invention discloses a fluid animation generation method and device of deep learning and an SPH framework. The method includes: constructing a deep-learning model, and carrying out training on fluid simulation data to generate a data drive item based on the neural network; constructing a neural network model according to features of a data set, setting relevant hyperparameters, then reading thedata set for preprocessing, and carrying out training of the network model; importing the trained neural network model into the SPH fluid simulation framework to replace a pressure item in a fluid simulation step with the same as the data drive item; importing the data drive item into low-precision fluid scene data, and then carrying out SPH fluid simulation calculation; and using a Marching Cubes algorithm to construct a fluid surface model, extracting a fluid surface mesh, outputting the same, storing a fluid mesh of each frame as a data file, and using the same for offline rendering. High-detail showing of fluid under a low-precision SPH simulation scene is realized, and calculation efficiency of a large-scale fluid simulation scene is improved.

The invention discloses a vertebra CT image three-dimensional visualization method and belongs to the medical field. In order to solve the problem that a large quantity of voxels and equivalent pointsare processed in the process of performing three-dimensional reconstruction visualization through a traditional Marching Cubes algorithm, the vertebra CT image three-dimensional visualization methodmakes improvement on the theoretical basis of the traditional Marching Cubes algorithm, wherein when subdivision configuration of triangular patches in the voxels is determined, a golden section method is utilized to calculate intersection points of an isosurface and voxel edges, the triangular patches are fitted into the isosurface, normal vectors of the triangular patches are calculated, a central difference method is adopted to solve gradient values of eight vertexes inside the voxels, and display, rotation, scaling and other interactive operation are completed through a VTK (VisualizationToolkit). In this way, transparent and semi-transparent visual function setting is realized, it is convenient for doctors and researchers to perform observation and analysis from arbitrary angles, andthe method provides a theoretical basis and technical support for observation of vertebra internal and external structure information and treatment and research in a later period.

The invention discloses a fast three-dimensional reconstruction method for a spinal CT image, belongs to the medical field, and aims at solving problems that a spinal model is long in three-dimensional reconstruction time and is not sufficient in smoothness in the actual operation and teaching and research of the clinical medicine, especially in a screw implantation operation of vertebral pedicle.The invention provides the fast three-dimensional reconstruction method for the spinal CT image, and the method comprises the steps: performing preprocessing according to a three-dimensional reconstruction surface drawing theory through employing a characteristic selection bilateral filtering denoising algorithm, performing the improvement on the basis of a conventional MC (Marching Cubes) algorithm, selecting a seed voxel, extracting all voxels comprising a contour surface through the regional growth idea, determining a triangulation configuration of the contour surface in the voxels, carrying out the parallel processing through a visualization toolkit VTK and Open GL with the help of a GPU, and completing the fast and precise three-dimensional reconstruction of the spinal CT image. Themethod is of great significance to the analysis, research, actual operation and operation scheme formulating of spinal diseases.

A method for quantitatively analyzing the hippocampal shape in magnetic resonance image includes such steps as acquiring the data of magnetic resonance image, pre-processing, manually dividing the hippocampus, extracting the coordinates of the dots on the hippocampal surface by marching cube method, creating a parameterized curved surface model of hippocampus, finding out the central axis of hippocampus, using the area of relative parallel coil for registration to the central axis to obtain better tissue correspondency, and significant statistical analyzing by arranging-testing method.

The invention relates to the technical field of multi-scale house detection vector diagrams, in particular to a method for generating a multi-scale house detection vector diagram, which comprises the following steps of: 1, classifying earth surface targets by utilizing an earth surface coverage segmentation network, and performing network jump connection by utilizing skip-connection; 2, generating a house vector diagram by using a house vector diagram generation network, and processing training data according to different scale proportions in order to implicitly learn multi-scale information; 3, carrying out polygon extraction and shape simplification of the house vector diagram by using a Marching Cubes algorithm and a Regulation Building Footprint module provided in an arcpy library of ArcGIS10.4, and meanwhile, solving the problems that corners of a building are incomplete and opposite sides are not parallel. According to the method, multi-scale processing can be carried out on an existing map, multi-scale information is implicitly learned through the neural network, and a multi-scale vector diagram with a good effect is obtained.

System that generates the solvent-excluded surface (SES) of a molecule using a parallel algorithm that may execute on a GPU. Parallel execution allows a SES to be created in seconds even for a large protein, or to be recreated rapidly when exploring modifications to molecular structure. The algorithm calculates a spatial field that represents a signed distance between an atom-facing surface of a probe and each point in 3D grid. Spatial field calculations for different grid points may be performed in parallel. The SES is then obtained as the zero isosurface of the spatial field, using for example marching cubes. Atoms and probes may be placed into spatial buckets and indexed by bucket to improve efficiency by limiting calculations to atoms and probes in the proximity of a point.

The present invention provides an angiocarpy image reconstruction method and system based on an implicit deformable model. The method comprises the steps of: obtaining a human body heart three-dimensional image, and employing the parameters of the human body heart three-dimensional image to construct a nested function partial differential equation; employing a combination mode of a fast marching method and a collision forward method to initialize angiocarpy aorta images and coronary artery images, perform swelling, smoothing and convection processing, solve the nested function partial differential equation and obtain a reconstructed angiocarpy three-dimensional image; and employing marching cubes to perform processing of the reconstructed angiocarpy three-dimensional image to obtain an angiocarpy three-dimensional model. The method and the system solve the problem that the calculation stability is poor in a current angiocarpy image reconstruction method, achieve rapidly and accuratelysegment required areas on the premise of ensuring the calculation result stability, are simple to operate and facilitate later calculation of the hydromechanics analysis.