23 results about "Morphological model" patented technology

The invention provides a cortical bone screw automatic planning method and device based on a statistical morphology model. The method comprises the following steps: acquiring CT image data of any object; based on the CT image data, segmenting point cloud information of a vertebral body to be subjected to screw placement; acquiring a statistical shape model and cortical bone screw planning information corresponding to the serial number; and registering the statistical shape model to the point cloud information, and determining a cortical bone screw plan of the vertebral body to be subjected to screw placement. In the application, the preset screw placement planning of the cortical bone screw is performed through the statistical shape model, and the preset screw placement planning is mapped to the current spinal column three-dimensional model through registration, so that the preset screw placement planning only needs to be performed on the statistical shape model, and a screw placement model is not needed, thereby solving the problem that a large number of cases need to be collected to realize the screw placement model; therefore, the problem of nail placement of the cortical bone can be solved.

The present invention relates to the field of computer vision, and more particularly to an OCR recognition method based on adaptive mapping and perceptual adjustment. The method extracts the original feature map of the OCR image through a neural network. Next, by comparing the original feature map with a morphological model, the deviation is calculated to adjust the offset of the convolution kernel, thereby accurately locating feature points. When recognizing text regions, the text density and average spacing between characters in each region are calculated, and the size and shape of the receptive field are dynamically determined based on this. A target feature map is generated through this adaptive convolution process. Finally, the neural network model is trained specifically based on the target feature map and text density and spacing information to obtain an optimized OCR recognition model. By conducting in-depth analysis of text features, the present invention significantly improves the recognition accuracy and adaptability of OCR technology when processing diverse and complex documents.

The invention relates to the field of computer vision, in particular to an OCR (Optical Character Recognition) method based on adaptive mapping and perceptual adjustment, which comprises the following steps of: extracting an original feature map of an OCR image through a neural network, comparing the original feature map with a morphological model, and calculating deviation so as to adjust the offset of a convolution kernel, so that feature points are accurately positioned; when text regions are recognized, the text density of each region and the average spacing between characters are calculated, the size and the shape of a receptive field are dynamically determined accordingly, a target feature map is generated through the self-adaptive convolution process, and finally, a neural network model is subjected to targeted training in combination with the target feature map and text density and spacing information, so that the recognition accuracy of the text regions is improved. And thus, an optimized OCR recognition model is obtained. According to the method, the text features are deeply analyzed, so that the recognition precision and adaptability of the OCR technology in processing diversified and complex documents are remarkably improved.

The invention provides a method and a device for establishing and applying a whole-spine morphological model based on a medical image, and relates to the technical field of medical images. The method comprises the following steps: acquiring morphological characteristics and medical image data of the whole spine of a patient, and constructing a whole spine three-dimensional morphological architecture; generating a full-spine morphological model based on the full-spine three-dimensional morphological architecture; obtaining a personalized correction demand of a patient, and generating morphological difference information based on the personalized correction demand; generating a morphological matching chain according to the morphological difference information and the whole spine morphological model; generating a personalized correction model of the patient according to the morphological matching chain; generating a resource allocation strategy of the patient based on the personalized correction model and the whole spine morphological model; wherein the resource allocation strategy is used for allocating three-dimensional modeling nodes and data processing resources for the personalized correction requirements. According to the method, the precise modeling and personalized correction of the whole spine can be realized, and the scientificity of spinal disease diagnosis and treatment and the resource utilization efficiency are improved.

The invention provides a spinal surgery planning method and device based on a statistical morphological model. The method comprises the following steps: acquiring CT image data of any object; inputting the CT image data into the improved segmentation network to obtain a segmented spine three-dimensional model; based on the spine three-dimensional model, determining a cortical bone screw plan of a vertebral body; and based on cortical bone screw planning of the vertebral body, determining spinal surgery planning information and guide plate planning information. According to the method, the spine three-dimensional model is constructed through the CT image data, and the cortical bone screw planning and the spine operation planning are performed through the spine three-dimensional model, so that the spine operation planning based on the cortical bone screw is realized.

The application provides a virtual organ simulation method and system based on three-dimensional stacked spatial transcriptome data, which comprises the following steps: constructing a spatial adjacency network according to the coordinate information of a plurality of spatial transcriptome slice data; using a graph attention autoencoder to perform expression embedding representation learning on each point in the spatial adjacency network; voxelizing the three-dimensional coordinates of each slice, constructing a continuum through Gaussian smoothing, and generating a three-dimensional morphological model; training a latent space diffusion model to generate a latent expression of the spatial transcriptome data; for a given coordinate and condition, sampling an embedding vector from the trained latent space diffusion model, and inputting the embedding vector into the graph attention autoencoder to obtain the gene expression profile of the corresponding point. The advantage of the application lies in that the spatial transcriptome of the whole organ or even the cross-tissue region is uniformly modeled and expressed, which breaks through the small-scale modeling capability of the existing method which is limited to a local region or a single slice.

The invention provides a lingual surface three-dimensional shape reconstruction method and system based on deep learning, and relates to the technical field of three-dimensional reconstruction, and the method comprises the steps: activating an image collection array based on a light source illumination parameter to carry out the multi-angle two-dimensional sensing of a target tongue part, and obtaining an original lingual surface image sequence; performing visual cutting, extracting a plurality of lingual surface target images, performing deep learning, and constructing a lingual surface depth map; performing three-dimensional shape analysis, constructing lingual surface three-dimensional point cloud coordinates, mapping the coordinates to a plurality of lingual surface target images for identification, and performing comparative analysis on an identification result and a standard image library to generate a comparative parameter set; and performing correction, performing three-dimensional reconstruction on the target tongue according to a correction result, and constructing a three-dimensional morphological model. The technical problems that a lingual surface analysis method in the prior art mostly depends on two-dimensional images or manual observation, subjectivity is often high, information loss is serious, and the real three-dimensional form of the lingual surface is difficult to obtain are solved.

A method and apparatus for generating an actual morphological model of an aorta root, the method comprising: setting a plurality of first control points on a structural contour of an ultrasonic image according to a first rule, and setting a plurality of second control points on a structural contour of a section shape according to a second rule, the plurality of sub-anatomical structures of the second rule are in one-to-one correspondence with the plurality of sub-anatomical structures of the first rule, and the control point generation rules associated with the two corresponding sub-anatomical structures in the first rule and the second rule are the same; therefore, the plurality of first control points and the plurality of second control points form a one-to-one correspondence relationship about matching of the aorta root on the anatomical structure position point. Therefore, corresponding point positions of the same sub-anatomical structure are limited on the ultrasonic image and on the section shape corresponding to the three-dimensional template model, and deformation of the three-dimensional template model needs to be restrained by one-to-one superposition, and under the constraint, the three-dimensional template model can be closer to a real model shape of a current patient about a target part after deformation.

The present invention relates to a method for obtaining a theoretical spectrum, a method for measuring morphological parameters, and an apparatus. A periodic structure includes a plurality of periodic units, and the method comprises: dividing the morphological model into a plurality of lamellae along a direction Z from the bottom to the top of the periodic structure; obtaining a continuous function of the dielectric constant of the corresponding lamellae along the periodic direction based on the dielectric distribution of each lamellae in the direction Z; then calculating the Fourier coefficient of the dielectric constant of each lamellae; and finally, using a rigorous coupled wave analysis algorithm to calculate the theoretical spectrum of the periodic structure. The present invention avoids approximating the side profiles of the lamellae divided by the model, making the processing of the morphological model in the RCWA calculation more consistent with the actual morphological model of the sample, obtaining a continuous function of the dielectric constant of each lamellae, improving the calculation accuracy of the Fourier coefficient of the dielectric constant, and improving the calculation accuracy and efficiency of the theoretical spectrum.

This invention discloses an omnidirectional morphological scanning device suitable for large-size rock specimens, comprising a support platform, a hydraulic lifting system, a scanning system, and a computer system. The hydraulic lifting system includes a first set of lifting devices and a second set of lifting devices. The scanning system includes scanning devices mounted on the support platform and arranged around the rock specimen, and scanning devices arranged to the sides of the rock specimen. Each scanning device includes a hyperspectral camera, a high-definition camera, and a vertical angle adjustment device. The computer system controls the first and second sets of lifting devices to simultaneously or alternately lift the rock specimen. The computer system receives data captured by the hyperspectral camera, matches it with a built-in mineral spectral library to determine mineral types, and analyzes the mineral composition of the rock specimen surface. Data captured by the high-definition camera is preprocessed and aligned with multiple perspectives to complete model reconstruction and analyze the morphology of the rock specimen surface. This invention optimizes the structure of the morphological scanning device and improves the accuracy of morphological model stitching.

The present disclosure relates to the technical field of three-dimensional model construction, and provides a method and apparatus for reconstructing a three-dimensional model, which may solve the problems of the structure being complex and modeling efficiency being low for existing three-dimensional models. The method for reconstructing a three-dimensional model of the present disclosure comprises: according to data features of a group of initial three-dimensional models, acquiring point cloud data of each initial model; selecting one model in the group of initial three-dimensional models as a standard three-dimensional model, and acquiring a plurality of discrete deformation fields by using difference values between points in the standard three-dimensional model and points in the other initial three-dimensional models; converting the plurality of discrete deformation fields into a statistical morphological model by using a multi-dimensional Gaussian process; and resampling the statistical morphological model, and acquiring a target three-dimensional model.

This invention discloses a method for quantitatively evaluating the morphology of aggregates based on frequency analysis, comprising the following steps: performing three-dimensional laser scanning on aggregate particles and removing noise to obtain the boundary pixel coordinates of the aggregate particles; calculating the centroid coordinates and centered coordinates of the aggregate particles' outlines, and constructing a complex sequence of each pixel point in the aggregate particles based on the centered coordinates; performing a discrete Fourier transform on the complex sequence to calculate the Fourier coefficients and amplitude spectrum of the complex sequence; extracting feature values ​​of different morphological parameters according to a preset set of contribution frequencies, and constructing a morphological model of each morphological parameter based on the feature values; substituting the amplitude spectrum of the aggregate particles into the morphological model to quantify each morphological parameter of the aggregate particles. This invention also discloses a system for quantitatively evaluating the morphology of aggregates based on frequency analysis. This invention solves the technical problem of how to accurately and quickly determine the morphology of aggregate particles.

The invention discloses a novel anti-bias-fixation chip preparation method, and relates to the technical field of semiconductor chip preparation, and the method comprises the steps: generating a growth column target morphological model based on target geometric parameters; preparing a growth column in the electrode area; comparing the three-dimensional contour information of the growth column with the target morphological model of the growth column to generate a morphological error matrix; correcting the etching track by using the morphological error matrix, and constructing an infiltration energy level gradient which is gradually increased from the center to the edge at the top end of the growth column; calculating thermodynamic stability values of the growth columns based on the infiltration energy level gradient, screening out qualified growth columns based on the thermodynamic stability values, and constructing a growth column array; and based on the growth column array, generating a self-alignment liquid bridge restoring force in a solid crystal melting stage, and inducing the chip to perform self-alignment posture correction to obtain the flip LED chip. According to the invention, active pose correction and high-precision anti-deviation preparation of the flip LED chip are realized.

The invention discloses a method and system for measuring cracks in a mountain, and the method comprises the steps: obtaining crack distribution features according to the topographic features of a cave region where the cracks in the mountain are located, so as to determine a crack measurement region in the cave region; the method comprises the following steps: acquiring point cloud data of a crack measurement area, dividing the point cloud data into first point cloud data of a cave channel and second point cloud data of a cave top crack, establishing a three-dimensional morphological model of the cave channel and a three-dimensional morphological model of the cave top crack, and then obtaining spatial morphological distribution characteristics of each cave top crack by cutting the three-dimensional morphological model of the cave top crack; and according to the derivative model diagram of the three-dimensional morphological model of the cave top crack, in combination with the spatial morphological distribution characteristics of each cave top crack, obtaining morphological characteristics and crack parameters of each cave top crack, and further in combination with the derivative model diagram of the three-dimensional morphological model of the cave channel, obtaining a crack measurement result. According to the invention, complete and accurate measurement of the cracks in the mountain is realized.

The invention belongs to the field of oil and gas exploitation, particularly relates to a casing deformation prediction method, system and equipment, and aims to solve the problem that a method for predicting casing deformation caused by sand production is not scientific and accurate enough. The method comprises the following steps: determining a sand production cavity form model of an oil and gas well and parameters of the sand production cavity form model; based on the parameters, the sand production condition and the perforation condition of the oil and gas well are combined, and the axial pressure borne by the sleeve at the sand production cavity of the oil and gas well is calculated through a sleeve stress geometry and mathematical model and a sand production cavity volume calculation formula of the oil and gas well; determining the residual wall thickness of the sleeve; calculating the critical stress of the casing according to the type and the residual wall thickness of the casing; calculating the deformation critical force of the casing pipe of the oil and gas well based on the critical stress in combination with the compression area of the casing pipe; if the axial pressure borne by the casing pipe is larger than the deformation critical force, the casing pipe deforms. According to the invention, accurate prediction of casing deformation is realized.

The invention discloses a three-dimensional dynamic biological simulation method based on formulation modeling, which comprises the following steps of: initializing a three-dimensional simulation space and initial position, speed and morphological parameters of an organism to construct a parameterized biological morphological model; dynamically updating the two-dimensional form reference of the organism and the position and posture of the organism in the three-dimensional space based on the form modulation parameters and the movement speed; the method comprises the following steps of: converting a two-dimensional form into a three-dimensional entity structure with symmetry or randomness by adopting a differentiation strategy such as equal-angle slicing or random direction generation aiming at different structure parts of a living body, and performing linear interpolation to enhance continuity; and finally, rendering the three-dimensional entity structure into volume data, performing superposition intensity projection along a preset direction, generating continuous frame images, and outputting multi-page TIFF format simulation data after a preset frame number is reached.

The invention relates to the technical field of remote monitoring, and discloses a management method and system applied to protection and rejuvenation of ancient and famous trees, and the method comprises the steps: generating basic information, physiological and biochemical indexes, growth environment parameters, and dynamic baseline data of pest and disease damage and safety inspection data; establishing a three-dimensional shape model of the ancient and famous trees to analyze the growth stages of the ancient and famous trees; analyzing the ancient tree health index of the ancient and famous tree in the growth stage by using a preset ancient tree health analysis model; analyzing health key influence factors of the ancient and famous trees, and when the health index of the ancient trees is lower than a preset health threshold value of the ancient trees, establishing an etiological traceability map of the ancient and famous trees through the key influence factors; and analyzing a personalized rejuvenation path of the ancient and famous trees through the etiological traceability map to generate a rejuvenation task work order of the ancient and famous trees, and performing protection and rejuvenation of the ancient and famous trees based on the rejuvenation task work order. The scientific, refined and sustainable management efficiency of large-scale ancient tree groups can be improved.

The invention belongs to the technical field of geological data modeling, and particularly relates to a seismic geological data model building method and device and a storage medium, and the method comprises the steps: S1, building an overall model which is not filled with data information, and carrying out the grid division of the overall model according to a seismic horizon; s2, performing geological data filling on the grids; s3, storing the filled geological data; and S4, splicing and sorting different grids, and establishing a geological data model. According to the method, the overall model is subjected to grid splitting according to the seismic horizon, models of different forms are established for data between different horizon positions at the same time, the data models of each layer are combined, the overall seismic geologic model is rapidly constructed, rapid establishment of the seismic geologic numerical model in the complex area is achieved, the geologic data modeling efficiency is improved, and the seismic geologic data modeling efficiency is improved. And meanwhile, grid splicing of different ranks can be realized according to different requirements, so that different geologic models can be quickly established.

The application discloses a three-dimensional dynamic biological simulation method based on formula modeling, and the method comprises the following steps: initializing a three-dimensional simulation space and initial positions, velocities and morphological parameters of a biological body, and constructing a parameterized biological morphological model; dynamically updating a two-dimensional morphological reference of the biological body and positions and postures of the biological body in a three-dimensional space based on morphological modulation parameters and motion velocities; for different structural parts of the biological body, an equal-angle slicing or random-direction generation equal-difference strategy is adopted to convert the two-dimensional morphological reference into a three-dimensional entity structure with symmetry or randomness, and linear interpolation is performed to enhance continuity; finally, the three-dimensional entity structure is rendered into volume data, superimposed intensity projection is performed along a preset direction, continuous frame images are generated, and the continuous frame images are output as multi-page TIFF format simulation data after a preset number of frames is reached.

The invention provides a unicondylar replacement guiding and positioning equipment design method and related equipment. The design method comprises the following steps: acquiring historical medical data of a unicondylar osteotomy object; generating a knee joint statistical morphology model based on the historical medical data; and generating a predetermined unicompartmental knee arthroplasty guiding and positioning device based on the knee joint statistical morphology model. According to the method, the knee joint statistical morphology model is generated through the historical medical data, and then the unicompartmental knee arthroplasty guiding and positioning equipment is generated based on the statistical morphology model, so that the generated unicompartmental knee arthroplasty guiding and positioning equipment is matched with an individual, and the osteotomy precision and the operation effect of unicompartmental knee arthroplasty are improved.

The invention provides a virtual organ simulation method and system based on three-dimensional stacked space transcriptome data. The method comprises the steps that a space adjacency network is constructed according to coordinate information of multiple pieces of space transcriptome slice data; performing expression embedding expression learning on each point location in the spatial adjacency network by adopting a graph attention auto-encoder; voxelization processing is carried out on the three-dimensional coordinates of all the slices, a continuum is constructed through Gaussian smoothing, and a three-dimensional morphological model is generated; training the potential spatial diffusion model to generate a potential expression of the spatial transcriptome data; and for given coordinates and conditions, sampling from the trained potential spatial diffusion model to generate an embedded vector, and inputting the embedded vector into a graph attention auto-encoder to obtain a gene expression profile of a corresponding point location. The method has the advantages that unified modeling and expression generation are carried out on the space transcriptome of the whole organ or even a cross-tissue region, and the small-scale modeling capability that an existing method is only limited to a local region or a single slice is broken through.

This invention discloses a method, device, storage medium, and apparatus for tree identification using a drone. The invention preprocesses remote sensing image information acquired by the drone, segments the remote sensing tree images based on an improved Mask-R-CNN model, and identifies tree species based on a preset tree species model and tree image information, obtaining image sets corresponding to each tree species type. Based on a preset morphological model and the image sets of each tree species type, the invention predicts the growth trend of trees within a target area, and determines the perceived growth status of trees in the target area based on the prediction results. This invention segments the preprocessed remote sensing tree images using an improved Mask-R-CNN model and identifies tree species based on a preset tree species model, thereby determining the growth status of each type of tree. This invention achieves accurate vegetation identification and precise prediction of tree growth status using a drone, improving data accuracy.

This invention relates to the field of artificial intelligence technology and discloses a method and system for real-time 3D paleontological reconstruction based on artificial intelligence and multimodal interaction. It aims to solve the problems of fragmented multi-source data, low automation, limited interaction methods, and lack of intelligent reasoning capabilities in existing technologies, which lead to strong subjectivity and difficulty in dynamic verification. The method includes: constructing a four-dimensional unified representation framework integrating fossil point clouds, stratigraphy, isotopes, and extant analog data, and generating a structured knowledge graph; using conditional generative adversarial networks to complete missing structures under biomechanical and evolutionary rules constraints, generating an anatomically consistent 3D morphological model; deploying natural language and virtual reality interfaces to achieve multimodal human-computer collaborative interaction; and triggering incremental learning based on user feedback and new evidence to complete real-time iterative optimization. This system integrates the above modules and scientific verification mechanisms, enabling high-fidelity, interactive, verifiable, and continuously evolving 3D dynamic paleontological reconstruction.