38 results about "Tomographic reconstruction" patented technology

The invention relates to the technical field of CT detection, and discloses a plane CT fan-beam projection filtering back projection reconstruction method and CT detection device.The method comprises the steps that S1, tilt geometric configuration parameters are determined according to the distance from a detector to a rotation center and a tilt angle, a sample rotating table is controlled to rotate, and the detector is triggered at each rotation angle to collect first projection data; s2, calculating a global three-dimensional coordinate of a detector pixel point under each rotation angle, and generating second projection data; s3, performing frequency domain filtering according to the thickness of the sample and the second projection data to obtain third projection data; and S4, calculating a ray intersection point coordinate from a reconstructed slice pixel point to a detector plane, and reconstructing the third projection data according to the ray intersection point coordinate to obtain a tomographic reconstruction image.According to the method, high-frequency detail features are reserved while noise is suppressed, the problem that a traditional fixed filtering kernel parameter is poor in adaptability to different samples is avoided, and the method is suitable for being applied to the field of image reconstruction. Therefore, high-precision three-dimensional imaging is realized.

The invention relates to the technical field of marine cable monitoring, in particular to a marine cable life prediction and health management method and system based on multi-source data fusion, and the method comprises the steps: constructing an electrochemical impedance spectroscopy and optical fiber humidity sensor array, and synchronously collecting multi-source signals in a coupling environment; performing dynamic compensation on the signal by combining a marine environment and working condition parameters, and eliminating interference to generate a state feature set; constructing a space corrosion-aging distribution diagram by using an electro-chemical coupling field chromatography reconstruction algorithm; real defects are determined through space-time adaptive segmentation and defect dynamics screening; and finally, calculating the corrosion depth and the aging rate by adopting a hyperbolic tangent-power law attenuation combined model to realize risk assessment. According to the invention, the accuracy of defect identification and life prediction of the marine cable in a complex environment is improved.

The present application belongs to the field of CT tomographic reconstruction technology and artificial intelligence, and discloses a limited-angle CT reconstruction artifact suppression method based on a multi-domain feature fusion network. In view of the problem that the reconstruction result of traditional CT scanning under limited-angle conditions is prone to artifacts and structural distortion, thereby affecting the image quality and defect detection accuracy, the present application constructs a multi-domain feature fusion artifact suppression network, takes the limited-angle reconstruction result as input, and realizes artifact suppression and detail recovery through the synergistic effect of the encoder part, the decoder part, the feature enhancement part and the feature conversion part. The present application can obtain high-quality tomographic images under limited-angle conditions, effectively reduces the scanning angle and time of industrial CT detection, improves the imaging clarity and reliability without increasing the radiation dose, is suitable for industrial detection of complex structure workpieces, and has important industrial application value.

The present application relates to the field of optical sensing technology, and provides a transparent tomographic imaging method based on an edge convex lens array, which receives an incident light source at a first end face to generate a first light signal, and the first light signal is transmitted along the first end face to a circumferential side face. The first light signal is encoded by a convex lens array structure arranged at the circumferential side face, and at least one group of second light signals is obtained after encoding. The second light signal is sensed by at least one optical detection module. The optical detection module transmits the second light signal to a signal reconstruction module for tomographic reconstruction to obtain a third light signal. The present application also discloses a sensing device. The method and the sensing device can transfer the sampling and encoding process of the light signal from a plane to an edge region of an imaging plane, realize angle-related optical encoding of the in-plane propagating light signal, and obtain an imaging result through tomographic reconstruction. Thus, the technical problems of limited transparency and limited resolution in the existing transparent imaging scheme are overcome.

The invention discloses an air inlet channel flow field panoramic measurement system based on multiple cameras and background schlieren. The measurement system comprises a multi-camera imaging module, a pulse illumination module, a synchronization system and a computing platform. And a plurality of cameras in the multi-camera imaging module synchronously collect background plate images and output the background plate images to the computing platform. And the calculation platform performs cross-correlation calculation on the two frames of background images with / without flow field disturbance to obtain a displacement field, and performs two-dimensional flow field chromatography reconstruction on the multi-camera view angle displacement field based on the calibrated imaging parameters to obtain a density gradient field of the flow field in the binary supersonic air inlet. A miniature background schlieren system is adopted to replace a single-point measurement pressure measurement system, large-view two-dimensional reconstruction of a flow field in an air inlet channel is achieved, the system is simple in structure, high in reliability and high in expansibility, and a plurality of cameras are arranged in an optical access channel so that measurement of flow in a larger range of the flow field can be achieved.

The application discloses a fluorescence tomography reconstruction imaging method based on a physical model depth network, acquires tissue surface light intensity information through a CCD camera, performs mesh partitioning on a phantom by using Amira software, respectively partitions two meshes with different precisions, respectively solves corresponding system matrices and adjacent matrices of mesh nodes by using the mesh after partitioning and optical parameters of each region in the phantom through a finite element method, sets a transfer matrix corresponding to the power density of different meshes, then transmits surface light intensity data into a depth network, solves in a coarse mesh, and demarcates a feasible area for solving a fine mesh according to the solving result of the coarse mesh, and solves in the feasible area, so that the norm of the obtained solution is small, the result is relatively sparse, the error of the norm and the result forward and the real surface light intensity is considered during solving, the position of a fluorescent group in the tissue can be positioned more accurately, and the application has important significance for studying tumors and early diagnosis of tumors.

The application belongs to the field of CT tomographic reconstruction and the field of artificial intelligence, and discloses an industrial battery CT image super-resolution method based on deep learning. The method takes a low-resolution tomographic image as input, constructs an end-to-end battery CT image super-resolution network, and outputs a high-resolution tomographic image. The network uses multi-scale attention module (MSA) and enhanced grouping module (EGM) for parallel calculation, adopts hybrid channel attention feed-forward module (HCFB) for nonlinear enhancement, and combines a frequency modulation module for frequency domain feature modeling. The method can obtain a battery CT tomographic reconstruction result with clearer boundaries, more coherent layer structures and fewer artifacts, and provides a more stable and reliable data basis for subsequent defect detection, structure segmentation and three-dimensional analysis.

A method is provided for correcting a reconstruction artefact of a three-dimensional tomographic image. The method includes the steps of providing an acquired three-dimensional tomographic image from a cell group, and applying the image to a neural network trained in advance to determine a corrected tomographic image.

This invention provides a dual-aperture multi-pinhole collimator, comprising: a collimator plate; and multiple pinholes of two different apertures spaced apart on the collimator plate. During a single imaging process, radioactive rays passing through the imaging fields of different apertures simultaneously form corresponding and non-overlapping projection responses on the detector. Of the two apertures, the first aperture is smaller than the second aperture. The first aperture is determined based on the desired system spatial resolution, and the second aperture is determined based on the desired detection efficiency. This invention also proposes a SPECT imaging system based on the aforementioned multi-pinhole collimator. Its imaging module obtains imaging results from the data required for tomographic reconstruction using an improved MLEM iterative algorithm. The improved MLEM iterative algorithm introduces weighting factors into the original MLEM iterative algorithm, weighting the projection data of the dual-aperture pinholes and the corresponding system transmission matrix elements respectively. This invention improves detection sensitivity while maintaining spatial resolution.

This invention provides a non-destructive testing device and method for nut quality based on a fully automated micro-CT scanner. The method includes: S1, using a transport mechanism to transport the nuts to a rotating platform; S2, keeping the micro-focal spot X-ray source and the flat panel detector stationary, and controlling the rotating platform to rotate intermittently via a PLC controller to achieve full-angle irradiation of the nuts by the micro-focal spot X-ray source; S3, during the intermittent stops of the rotating platform, acquiring planar array images of the nuts from various angles using the flat panel detector to obtain a full-angle planar array image of the nuts, and transmitting it to a computer; S4, the computer performs tomographic reconstruction and image processing based on the full-angle planar array image to obtain the quality trait parameters of the nuts. This invention enables non-destructive testing of nut quality trait parameters through visual recognition technology, significantly improving testing accuracy and efficiency compared to manual trait testing methods and traditional culture methods for detecting mold infection.

The invention provides an electromagnetic chromatography evaluation method for aging damage of a metal material, which is used for establishing a relationship between the electromagnetic property of the material and the aging damage degree in order to solve the problem of the electromagnetic property of the material caused by environment and load action in the early stage of long-term service of the conductive metal material. A broadband electromagnetic response signal is obtained through pulsed eddy current excitation, equivalent multi-frequency information is extracted through spectral analysis, an electromagnetic field positive problem model under the multi-frequency condition is constructed, and chromatographic reconstruction of the internal conductivity of the material in the depth direction is achieved. And introducing a prior constraint that the conductivity changes in a quadratic function along the depth, and reconstructing a stable conductivity distribution profile by adopting a nonlinear least square inversion method. On the basis, local aging damage degree and weighted aging damage evaluation indexes are constructed, and quantitative evaluation of aging damage distribution of the material in the depth direction and the overall aging damage degree is achieved.

The present application belongs to the technical field of image analysis, and discloses a kind of vehicle lamp thick wall piece image defect intelligent detection system;Including emitting depth direction time coding laser pulse sequence to vehicle lamp thick wall piece, so that different depth defects are excited in turn to generate photoacoustic shock wave, and the photoacoustic shock wave is collected in space-time combination, and multiple layer original correlation intensity matrix is generated;Tomographic reconstruction is executed to multiple layer original correlation intensity matrix, and the complete three-dimensional photoacoustic density field of thick wall piece is generated;Three-dimensional photoacoustic density field is carried out voxel grid division and executes three-dimensional connected domain marking, and all independent defect bodies are obtained;The geometric feature and topological feature of the voxel set of each independent defect body are calculated, and the defect feature vector set is used as input, and the defect type and three-dimensional center coordinates are output through the pre-trained defect mapping model;According to defect type and three-dimensional center coordinates, mechanical hand is controlled to execute sorting or marking;Vehicle lamp thick wall piece image defect intelligent detection is realized.

The invention discloses a self-adaptive temperature field measuring device and method for a dynamic arc. The device comprises an arc generating mechanism, an image collecting device, a reflecting mirror set, an angle reference component and a processing unit. The angle reference component is installed on the arc generation mechanism, the central axis is coaxial with the geometric installation axis of the arc generation mechanism, and an angle scale structure is arranged on the surface and used for establishing the mapping relation between the pixel position and the observation angle. The reflector group is arranged on the side of the arc generation mechanism and is used for reflecting radiation light from different directions of the dynamic arc to the same image acquisition device so as to realize multi-view imaging; the processing unit determines the projection angle of each visual angle in real time in the dynamic discharge process, performs tomography reconstruction based on multi-visual-angle radiation information, obtains emission coefficient distribution of an arc section, adaptively distinguishes a high-temperature region from a low-temperature region according to isoline topological characteristics, performs temperature mapping, and realizes accurate reconstruction of a dynamic arc temperature field. And the stability and reliability of measurement under the dynamic working condition are improved.

Methods, systems, and apparatus for performing scanning spectral tomographic reconstruction of an object. The imaging system includes a power source that is configured to provide an alternating high voltage. The imaging system includes an X-ray source. The X-ray source includes an array of X-ray emitters that allow fast switching “ON” and “OFF” using a grid electrode. The source is configured to generate an X-ray beam with an energy spectrum based on the alternating high voltage and uses X-ray filters. The imaging system includes a controller configured to operate synchronously with the alternating high voltage. The controller is also configured to drive an actuator to position the X-ray source with respect to an object and drive the source in a pre-defined trajectory about the object. At each position in the trajectory, the controller is configured to control the exposure timing of the emitters based on a predefined firing pattern.

The invention belongs to the field of CT (Computed Tomography) tomography reconstruction and the field of artificial intelligence, and discloses an industrial battery CT image super-resolution method based on deep learning. According to the method, a low-resolution cross-sectional image is used as input, and an end-to-end battery CT image super-resolution network is constructed to output a high-resolution cross-sectional image. The network uses a multi-scale attention module MSA and an enhanced packet Mama module EGM to carry out parallel computing, uses a mixed channel attention feedforward module HCFB to carry out nonlinear enhancement, and combines a frequency modulation module to carry out frequency domain feature modeling. According to the method, a battery CT fault reconstruction result with clearer boundary, more coherent layered structure and fewer artifacts can be obtained, and a more stable and reliable data basis is provided for subsequent defect detection, structure segmentation and three-dimensional analysis.

A computer-implemented process for electromagnetic imaging, the process including the steps of: accessing scattering data representing at least a two-dimensional array of measurements of electromagnetic wave scattering by internal features of an object, wherein each said measurement represents scattering of electromagnetic waves emitted by a corresponding antenna of an array of antennas disposed about the object as measured by a corresponding antenna of the array of antennas; and processing the scattering data to generate image data representing a spatial distribution of internal features of the object, wherein the generation of the image data does not involve tomographic reconstruction but is in accordance with a weighted mapping to directly map the measurements of electromagnetic wave scattering to a corresponding spatial distribution of electromagnetic wave scattering by the internal features of the object that corresponds to the physical shape of the object to enable the detection, localization, size estimation, shape estimation and classification of one or more features of interest of the object.

The application discloses a kind of based on neural network's quick inversion method and device of filter visible light camera image, belong to image tomographic reconstruction technical field, this method includes: constructing preliminary data set;According to preliminary data set, select the area mainly reflecting neutral particle and impurity radiation, and cut fixed size as real data set;In the case where assuming tokamak plasma is circumferentially symmetric, weight matrix is calculated;Real data set is divided into training set, verification set and test set;Training set is put into ViT model and is trained, and the output of ViT model is the neutral particle and impurity radiation distribution obtained by inversion;Then according to the relationship between camera image and the radiation distribution of neutral particle and impurity, the radiation distribution of neutral particle and impurity is multiplied by weight matrix to obtain simulated camera image, and ViT neural network is trained according to the overall loss of network.The application realizes that radiation distribution is obtained once calculation, and operation resource is saved.

The invention provides a beam light field quasi-periodic reconstruction system and method for discharge oscillation of an electric thruster. The method comprises the steps that after the electric thruster is started, beam plasma is sprayed out of the vacuum bin; the monitoring and modulation system monitors the discharge current, can send an image acquisition trigger signal to the shooting and processing system, or modulates the voltage input into the electric thruster to obtain the modulated discharge current, and returns to the step of monitoring the discharge current of the electric thruster; and the shooting and processing system is used for carrying out image acquisition on the beam plasma based on the image acquisition trigger signal to obtain a beam circumferential projection drawing time sequence after the current rotation of a preset angle, and processing the beam circumferential projection drawing time sequences at different angles according to a three-dimensional chromatography reconstruction algorithm to obtain a beam three-dimensional light intensity field time sequence. According to the method, low-cost and high-synchronization-precision dynamic reconstruction of the time sequence of the three-dimensional light field of the beam is realized.

The application relates to the technical field of image recognition, and discloses a 3D printing defect identification method and system based on OCT and deep learning, the method comprising the following steps: performing coherence gating benchmarking calibration on an OCT acquisition device to obtain a standardized image acquisition benchmark; based on the standardized image acquisition benchmark, performing coherence volume data tomographic reconstruction on real-time acquired OCT interference signals to obtain a coherent tomographic volume image; performing feature contrast enhancement on the coherent tomographic volume image to obtain a feature enhanced image; performing multi-scale feature discrimination on the feature enhanced image to obtain a defect identification result; performing three-dimensional geometric reconstruction on the defect identification result and the coherent tomographic volume image to obtain three-dimensional geometric representation data, and performing spatial configuration analysis on the three-dimensional geometric representation data to obtain a spatial topological atlas; and performing defect root cause tracing on a printer to obtain a process parameter adjustment strategy; the application can improve the efficiency of a 3D printing defect identification method based on OCT and deep learning.

The present application relates to the technical field of marine cable monitoring, and particularly relates to a marine cable life prediction and health management method and system based on multi-source data fusion, which constructs an electrochemical impedance spectrum and a fiber-optic humidity sensor array to synchronously collect multi-source signals under a coupled environment; combines marine environment and working condition parameters to dynamically compensate the signals, eliminate interference and generate a state feature set; uses an electro-chemical coupling field tomographic reconstruction algorithm to construct a spatial corrosion-aging distribution map; determines real defects through spatio-temporal adaptive segmentation and defect dynamics screening; and finally uses a hyperbolic tangent-power law attenuation joint model to calculate corrosion depth and aging rate to realize risk assessment. The present application improves the accuracy of marine cable defect identification and life prediction under complex environments.

The invention relates to the technical field of plastic defect detection, in particular to an engineering plastic product internal bubble defect detection method based on laser scattering chromatography, which comprises the following steps of: acquiring a time domain scattering signal through a multi-angle scattering light receiving array, and performing dynamic compensation in combination with material thickness and environment temperature parameters; and the refractive index interference caused by temperature is eliminated. And based on the compensated scattering characteristic parameter set, constructing a three-dimensional scattering coefficient distribution diagram by adopting a chromatography reconstruction algorithm, visually displaying the internal density gradient change, and presenting a local high scattering coefficient value in a bubble defect area. And through adaptive threshold segmentation and bubble morphological feature screening, accurate identification and authenticity discrimination of a defect area are realized. And finally, a hyperboloid fitting model is adopted to quantify the bubble volume radius, geometric center and distribution density parameters, the product structural integrity is judged according to a preset safety threshold, and the detection precision and reliability are remarkably improved.

A system for processing ultrasound images utilizes a trained orientation neural network to provide orientation information for a multiplicity of images captured around a body part, orienting each image with respect to a canonical view. In one aspect, the system includes a set creator and a generative neural network. The set creator generates sets of images and their associated transformations over time. The generative neural network then produces a summary canonical view set from these sets, showing changes during a body part cycle. In another aspect, the system includes a volume reconstructer. The volume reconstructer uses the orientation information to generate a volume representation of the body part from the oriented images using tomographic reconstruction, and to generate a canonical image from that volume representation.

This application provides an image data processing method and apparatus. Specifically, it involves acquiring an image to be processed; the image to be processed includes multiple projected images, each of which is obtained by scanning a target object using SPECT within a sparse angular range at a first interval angle; the first interval angle is greater than a second interval angle for scanning the target object across the entire angular range; denoising the image to be processed is performed to obtain a denoised image; tomographic reconstruction is performed on the denoised image to obtain image domain volume data; denoising is performed on the image domain volume data to obtain denoised image domain volume data; super-resolution processing is performed on the denoised image domain volume data to obtain a target image; the resolution of the target image is higher than the resolution of the image to be processed. In other words, the image data processing method provided by this application can improve scanning speed and reduce scanning time while ensuring image quality.

This invention relates to the field of non-destructive testing (NDT) technology in building engineering, specifically a method and system for NDT of internal defects in building structures. The method includes: simultaneously acquiring ultrasonic pulse echo, X-ray projection, and infrared thermography sequences of the target area; extracting signal features through time-frequency joint analysis; generating an internal three-dimensional density field through tomographic reconstruction and density inversion; identifying thermal resistance anomalies through transient thermal conduction analysis; fusing the above multi-physics field features and inputting them into a pre-trained deep network model to directly output the defect type, precise geometric parameters, and quantified hazard level; and automatically generating a spatial location map of the defect and a damage evolution trend prediction report based on these features. This invention achieves deep fusion and intelligent analysis of multi-source information, improves the accuracy of defect identification and quantitative assessment, and enables predictive assessment of defect development trends.

This invention discloses a joint spatiotemporal decorrelation suppression method for TomoSAR. First, multi-temporal SLC images are registered and de-skewed to generate an initial complex covariance matrix. Then, homogeneous pixels are identified based on likelihood ratio, and a high-precision complex covariance matrix is ​​obtained through weighted summation. A joint model is constructed by fusing interferometric observations and phase priors, linearized using Taylor expansion, and the phase of the SLC complex image is inverted using iterative weighted least squares. Finally, the decorrelation-suppressed SLC complex image is output, and 3D tomographic reconstruction is completed by combining compressed sensing. This method effectively suppresses spatiotemporal decorrelation noise, accurately recovers complex images, and improves the point cloud density and elevation accuracy of TomoSAR 3D reconstruction, providing a technical reference for application in multi-temporal, multi-baseline TomoSAR.

A system for monitoring the corrosion of a metallic structure using guided ultrasonic waves, employing a multi-element magnetostrictive probe forming an array of independent transmitting / receiving transducers on either side of an area to be inspected in the structure, comprising: switching means (70) for sequentially controlling the excitation of each transmitting transducer in the transmitting transducer array (Ei = 1, ..., Ne), and acquisition means (80) for sequentially controlling the acquisition of the detection signal delivered by each receiving transducer in the receiving transducer array (Rj = 1, ...Nr), in response to the signal generated by each transmitting transducer, means for recording a detection matrix corresponding to all acquired detection signals, means for processing said matrix by a tomographic reconstruction algorithm intended to provide a distribution of the thickness variation at any point in the area to be inspected. Figure to be published with the abbreviation: Fig. 5.

The invention relates to a comprehensive method for preoperative focus identification and intraoperative guidance, and belongs to the technical field of preoperative focus identification and intraoperative guidance. According to the invention, a joint acquisition mode of the OCT image and the microscope image is adopted, and a registration strategy of a tomography reconstruction algorithm and luminosity correction is combined, so that the space consistency among different modal images is realized. Through the joint optimization method based on the feature points and the surface curvature, deep tissue and surface texture information can be effectively aligned, so that the registration precision and the spatial integrity of the multi-modal image are remarkably improved, and a reliable data basis is provided for subsequent focus recognition.

The present application relates to the technical field of neutron imaging and tomographic reconstruction, and particularly relates to a three-dimensional reconstruction method, system and device for low-yield and few-angle neutron imaging and a storage medium. The technical scheme comprises obtaining neutron imaging projection data of a sample to be measured at multiple rotation angles to form a projection sequence; preprocessing the projection sequence, wherein the preprocessing comprises normalization, angle uniform sampling, spatial clipping and resolution uniform resampling to obtain standardized projection data; calculating an artifact evaluation index based on the standardized projection data, and adaptively suppressing artifacts of the standardized projection data according to the artifact evaluation index to obtain corrected projection data. Through the organic combination of preprocessing, adaptive artifact suppression, DiffNeuVox voxel optimization reconstruction, ROI constraint and post-processing, the structural clarity, noise resistance and usability of the three-dimensional reconstruction result of low-yield and few-angle neutron imaging are significantly improved.

This application discloses an integrated system and method for adaptive enteral nutrition infusion and in vivo physiological parameter monitoring, belonging to the field of medical monitoring technology. The method includes: acquiring a raw voltage dataset; validating the raw voltage dataset to obtain an effective voltage dataset when the raw voltage dataset is valid; based on the effective voltage dataset, reconstructing a conductivity distribution matrix characterizing the conductivity distribution within the region where the sensor probe is located using a preset tomographic reconstruction algorithm; performing image segmentation and interpretation on the conductivity distribution matrix to extract at least one quantitative parameter characterizing the state of gastric residue; and generating an infusion command for controlling the enteral nutrition pump based on at least one quantitative parameter. This application solves the technical problems of invasiveness, discontinuity, and low information dimensionality in existing gastric residue monitoring technologies.