272 results about "Rapid imaging" patented technology

Provided herein is a tunnel electromagnetic joint scanning detection method and a system thereof. It introduces a new tunnel electromagnetic detection system called TEJS, realizes three-dimensional joint inversion of multi-component, time domain and frequency domain signals, and forms tunnel joint scanning imaging. This method adopts the mode of surface transmission, underground reception, multi-source transmission and multi-component reception. Based on an observation system, a large number of stochastic models are constructed and numerically simulated, and a large number of training data sets are constructed by using the simulated data to complete the training of UNet model. This model can realize real-time and fast imaging of the position of the low-resistance anomalous body in three-dimensional space. An algorithm forms a dual checking mechanism through surface imaging and underground imaging, which constrains the three-dimensional spatial position of anomalous body together to prevent misjudgment.

The invention discloses a rapid imaging method and system for a multi-time-sequence magnetic resonance image group, particularly relates to the technical field of multi-time-sequence magnetic resonance image processing, and is used for solving the problems of low imaging speed and poor time sequence consistency. According to the method, sampling reference distribution is constructed in a frequency domain, the reconstruction difficulty is predicted by using graph convolution, a multi-scale under-sampling mask is generated, and sampling is distributed according to channel sensitivity, so that high information priority and sparse controllability are realized; sending the registered sparse data into a space-time-parameter three-domain network, extracting structural, dynamic and parameter characteristics, and obtaining an image group with a clear structure and a stable time sequence through cross-domain fusion, non-rigid body registration and wavelet domain artifact suppression; and forming a comprehensive score by using four indexes output by the quality scoring network, performing reinforcement learning feedback, adaptive adjustment of a sampling rate, a mask, a reconstruction parameter and closed-loop optimization, and finally outputting the comprehensive score together with a sequence parameter, a timestamp and a score, and generating a structure comparison diagram and a time curve to facilitate quality control and presentation.

The invention provides a rapid Marchenko imaging method for undulating surface conditions, and the method comprises the following steps: S1, inputting an earthquake shot record of a fixed surface and a depth domain undulating migration surface, and correcting the earthquake shot record to the migration surface through a static correction method; s2, inputting a depth domain seismic velocity model, and constructing an initial downlink focusing function from an underground target area imaging point to an undulating surface migration surface through a ray tracing algorithm; and S3, taking the shot record on the fluctuating offset surface and the initial downlink focusing function as input, and calculating uplink and downlink Green functions from the underground imaging point to the ground through an iterative method. And S4, applying an energy normalization cross-correlation imaging condition to the reconstructed uplink and downlink Green functions to obtain a Marchenko imaging result. According to the Marchenko imaging method, the problems that conventional Marchenko imaging is low in calculation efficiency and undulating surface conditions cannot be processed are solved, and the Marchenko imaging quality under the undulating surface conditions is ensured while the calculation efficiency is improved.

The utility model discloses a rapid imaging camera, which comprises a camera body, and is characterized in that the camera body is internally provided with a printing bin for storing thermosensitive printing paper, and the camera body is provided with a mounting position; the lens comprises a lens body, and the lens body is accommodated in the mounting position and is used for receiving light; the imaging device is arranged in the camera body, and the light passing through the lens body is transmitted into the imaging device to form an image signal; the thermal printing head is arranged in the machine body, and the thermal printing head can receive the image signal so as to print and present the corresponding content on the thermal printing paper; wherein the camera body is provided with a first connecting part, the first connecting part is arranged corresponding to the mounting position, the lens further comprises a second connecting part arranged on the lens body, and the second connecting part can be in butt joint with the first connecting part, so that the lens is detachably connected to the camera body. According to the rapid imaging camera provided by the invention, detachable connection of the lens and the camera body can be realized, so that a proper lens can be replaced according to user requirements, and the user experience is improved.

The invention discloses an aviation composite material-oriented ultrasonic guided wave damage rapid imaging method, which relates to the field of nondestructive testing, and comprises the following steps: calculating a frequency dispersion curve according to material parameters of a carbon fiber composite material plate, and obtaining an ultrasonic optimal excitation angle and an ultrasonic guided wave propagation mode; scanning and collecting two groups of ultrasonic guided wave signals in the orthogonal direction in sequence; decomposing the guided wave signal, and obtaining a reconstructed ultrasonic guided wave signal after extracting a target component according to the size of an energy entropy value; calculating time-frequency information and energy of the signal, and estimating the damage probability in the scanning path by combining a damage index; embedding the expansion kernel convolution and the double probability distribution function into the damage index curve to respectively realize the reinforcement of the damage index and the sharpening of the edge; and expanding the two groups of damage index curves in the orthogonal direction into a two-dimensional damage matrix, and imaging according to a composite path cross imaging method, thereby finally realizing damage positioning imaging of the carbon fiber composite material plate.

Systems and methods for producing an ultrafast functional photoacoustic microscopy system are disclosed herein. Such systems are configured to enable the imaging of microvasculature and functional dynamics of tissue samples with a broad field of view and high spatial resolution. According to several disclosed embodiments, a combination of a Raman path and a polygon scanner in water immersion and air immersion environments enables rapid imaging of target materials.

The invention discloses an aviation electromagnetic rapid imaging method and device based on a GAF-CNN, and belongs to the technical field of processing and interpretation of aviation electromagnetic (AEM) data. The method comprises the following steps: acquiring aviation electromagnetic original data and carrying out data preprocessing; mapping the preprocessed data to a spatial domain based on a Gram matrix, and generating a Gramian angle summation field and a Gramian angle difference field; designing a deep convolutional neural network, wherein the network comprises four groups of convolutional layers and two full connection layers which are in communication connection in sequence; and inputting the preprocessed data, the Gramian angle summation field data and the Gramian angle difference field data into a trained deep convolutional neural network to obtain an underground resistivity model. According to the method, through innovative feature representation and deep learning network architecture, the time sequence characteristics and the space characteristics of the electromagnetic data are organically combined, and the inversion precision and the calculation efficiency are remarkably improved.

The invention discloses a hyperspectral fast imaging method and system based on spectral difference depth matrix decomposition, and aims at low signal-to-noise ratio data under a limit imaging condition to realize high-quality image recovery through structural modeling of an average spectrum chart and a spectral difference chart. The method comprises the following steps: firstly, quickly collecting and splicing hyperspectral data to form a three-dimensional tensor, and constructing a forward observation model under a weak light condition; decomposing into an average spectrum chart, a spectrum difference chart and a noise item; rearranging the spectral difference graph into a two-dimensional low-rank matrix, and obtaining a space and spectral principal component matrix by adopting PCA decomposition; an unsupervised dual-path optimization network is innovatively constructed; a 2D jump network is used to optimize a spatial principal component so as to model structural information, and a 1D jump network is used to optimize a spectral principal component so as to fit detail changes; and finally, outputting an optimized spectrum difference graph by the network after joint training, and fusing the optimized spectrum difference graph with the average spectrum graph to complete reconstruction. High-fidelity image reconstruction is realized under single-frame and unsupervised conditions, and the reconstruction quality and robustness are significantly improved.

The utility model relates to a rapid imaging camera, and belongs to the technical field of photography and camera shooting equipment. The 3D printer comprises a printer body, at least two printing heads and at least two paper storage bins, the printer body comprises a lens and an optical imaging module, the lens is used for collecting optical images and transmitting the optical images to the optical imaging module, and a first mounting cavity and a second mounting cavity are formed in the printer body; the printing head is detachably connected with the printing cavity, and the printing head is electrically connected with the optical imaging module, so that the printing head can receive an image signal transmitted by the optical imaging module and print an image; each paper storage bin can be arranged in the corresponding second mounting cavity; each paper storage bin is provided with a containing chamber for containing and limiting printing paper, and the sizes of the printing paper contained in the containing chambers of different paper storage bins are different; printing paper in the paper storage bin passes through the printing head and then is output out of the machine body; therefore, the rapid imaging camera can print different types of photos, and the application range of the camera is expanded.

The invention discloses a method for measuring the thickness of an oil film on the surface of a bearing bush and pressure distribution based on ultrasonic guided waves. The method comprises the following specific steps: step 1, embedding a piezoelectric plate array in the back of a to-be-measured bearing bush; step 2, acquiring a reference signal, changing oil film pressure and film thickness, and acquiring a guided wave signal; step 3, acquiring a noise signal, and performing trend noise fitting on the noise signal; 4, after trend noise fitting is completed, a segmented RMS index is established, and pressure and film thickness features are extracted; and 5, importing the extracted guided wave data into a convolutional neural network in deep learning to decouple coupling features, and imaging the surface of the bearing bush by using an RAPID imaging algorithm based on a probability damage imaging principle to complete measurement. According to the bearing bush surface oil film thickness and pressure distribution measuring method based on the ultrasonic guided waves, the thickness of the oil film can be accurately calculated, and the pressure of the oil film can be calculated.

The invention discloses a marine geological profile rapid imaging and stratigraphic structure inversion system and a marine geological profile rapid imaging and stratigraphic structure inversion method. Comprising a multi-source marine geological data synchronous acquisition module, an acquisition signal noise reduction and space-time registration module, a stratum interface initial positioning and feature enhancement module, a multi-scale geological section rapid imaging module, a stratum physical parameter inversion initialization module, a constraint stratum structure inversion optimization module and an inversion result verification and visual output module. According to the invention, through GPS and Beidou synchronization and Kalman registration, the problem of spatial-temporal dislocation of multi-source data is solved, and deep fusion of sound wave, gravity and magnetic survey data is realized; based on self-adaptive wavelet threshold noise reduction, effective signals are reserved, and meanwhile, marine environment noise interference is greatly reduced; the multi-scale fusion algorithm gives consideration to shallow details and deep structures, and meets the requirements of different exploration targets.

The invention provides a high-throughput multi-view automatic positioning light sheet microscopic imaging method. The method comprises the following steps: automatically identifying the size of a sample, presetting parameters, and carrying out preliminary scanning; splicing imaging data in real time; globally and automatically positioning a sample area; planning a shooting path; and multi-target area high-throughput shooting parameters are optimized. A microscope large-view high-flux rapid imaging method based on a real-time image automatic splicing and positioning technology is combined with a real-time splicing function of shot imaging data and an automatic positioning function of a sample position in an image to rapidly search specific position area information of a sample; and shooting imaging and data storage of the experimental sample are realized by automatically optimizing shooting configuration parameters. The invention further provides a high-throughput multi-view automatic positioning light sheet microscopic imaging system adopting the method, and shooting imaging and data processing can be rapidly and accurately carried out on a target large sample.

The invention provides a resistivity imaging method and a resistivity imaging device based on remote detection electromagnetic wave logging, which are used for realizing rapid imaging of a medium around a shaft and providing a basis for drilling guidance and stratum evaluation. Comprising the steps of obtaining a remote detection electromagnetic wave logging response measured value of a target well section; segmenting the response measured value, dispersing the stratum corresponding to the segmented response measured value into an initial grid, and obtaining a corresponding network topology structure; constructing an apparent resistivity model based on the stratum prior information of the target well section; selecting a discrete wave number, and obtaining a wave number domain far exploration electromagnetic wave logging response corresponding to the resistivity grid model; obtaining a posterior error, and judging whether the posterior error is smaller than a first threshold value or not; if yes, obtaining a remote detection electromagnetic wave logging response simulation value based on a wavenumber domain remote detection electromagnetic wave logging response; obtaining a data fitting difference based on the remote detection electromagnetic wave logging response simulation value and the remote detection electromagnetic wave logging response actual measurement value; judging whether the data fitting difference is smaller than a second threshold value or not; and if yes, outputting a network topology structure and a resistivity model.

The invention provides a combustion temperature and component concentration rapid imaging measurement method based on frame rate increase, a high-frame-rate laser-induced fluorescence image is obtained by using a deep learning model, and high-speed imaging of combustion temperature and component concentration is realized by fusing laser absorption spectrum data. A flame turbulence image is obtained according to fluid mechanics simulation, a fluorescence image frame interpolation model is obtained through training, and a high-frame-rate fluorescence image is generated through low-speed laser-induced fluorescence data. Obtaining temperature distribution of a combustion field by using laser absorption spectrum data, and substituting the temperature distribution into a fluorescence model satisfied by fluorescent molecules / free radical groups to obtain high-frame-rate gas molecule / free radical group concentration distribution; the concentrations of other products are solved according to a reaction kinetic equation, and the combustion field temperature and a multi-component concentration image are solved through iterative calculation. The frame rate of low-speed fluorescence data is increased according to turbulence motion estimation, the response speed of temperature and concentration distribution imaging is increased, and the method has wide application prospects in the field of combustion reaction monitoring research.

The utility model relates to a rapid imaging camera, which belongs to the technical field of photographic equipment and comprises a camera body, more than one printing head and a separation blade connected in the camera body in a sliding manner. The machine body comprises a lens and an optical imaging module, and the lens is used for collecting optical images and transmitting the optical images to the optical imaging module; a printing cavity and a paper storage bin used for storing printing paper are arranged in the machine body. The printing head can be selectively installed in the printing cavity, the printing head is detachably connected with the printing cavity, and the printing head is in signal connection with the optical imaging module so that a corresponding image can be printed on printing paper. The blocking piece is movably connected into the paper storage bin and used for limiting the printing paper in the paper storage bin. The blocking piece can move in the axis direction of the paper storage bin, so that the blocking piece can abut against and be fixed to the end faces of the printing paper of different sizes, the printing paper of different sizes is fixed in the paper storage bin, and printing of photos of different sizes is achieved.

To provide methods and systems suitable for evaluating image data from a patient on a real time or substantially real time basis using machine learning methods and systems.SOLUTION: There are provided systems and methods for improving diagnostic tools for end users such as cardiologists and imaging specialists using machine learning techniques applied to specific problems associated with intravascular images that have polar representations. Further, given the use of rotating probes to obtain image data for OCT, IVUS, and other imaging data, dealing with the two coordinate systems associated therewith creates challenges. The present disclosure addresses these and numerous other challenges relating to solving the problem of quickly imaging and diagnosing a patient such that stenting and other procedures may be applied during a single session in the catheter lab.SELECTED DRAWING: Figure 1C

The invention relates to geological three-dimensional reconstruction, in particular to a self-adaptive parameter optimization and rapid imaging method in complex geological body three-dimensional modeling, which comprises the following steps of: integrating multi-source geological data to generate an initial three-dimensional geological model; determining an objective function and constraint conditions of adaptive parameter optimization of the three-dimensional modeling of the complex geologic body, and constructing an adaptive parameter optimization model; solving the adaptive parameter optimization model by adopting an improved crocodile ambush optimization algorithm to obtain an optimal parameter combination; substituting the optimal parameter combination into the initial three-dimensional geologic model, and generating a final three-dimensional geologic model through curved surface reconstruction; according to the technical scheme provided by the invention, the optimal parameter combination is substituted into the initial three-dimensional geologic model, and the final three-dimensional geologic model is generated through curved surface reconstruction.

The invention discloses a step frequency continuous wave ground penetrating radar imaging device and a rapid imaging method, and belongs to the technical field of microwave ground penetrating imaging. The vector network analyzer is adopted, the radio frequency power amplifier is carried, the ultra-wideband directional antenna is combined, signals of a step frequency continuous wave system are adopted, the frequency range is 700 MHz to 3 GHz, the bandwidth is large, meanwhile, the large transmitting power can be achieved, and meanwhile the requirements for the detection depth and the detection resolution are met; according to the method, direct wave interference is eliminated by adopting a singular value decomposition algorithm, then the effective signal strength is improved based on an automatic gain algorithm, and finally clutter interference is eliminated by adopting a block matching algorithm, so that the signal-to-noise ratio is improved; according to the method, an F-K migration imaging algorithm is developed, processed data are converted to a frequency wavenumber domain through Fourier transform, wavenumber domain data are filled before fast inverse Fourier transform, and the transverse space sampling rate and the imaging speed are increased.

The invention relates to a terahertz frequency band space target three-dimensional rapid imaging method, device and equipment. The method comprises the following steps: acquiring a two-dimensional ISAR image sequence; based on the two-dimensional ISAR image sequence, constructing a projection relation from a three-dimensional space to a two-dimensional imaging plane; randomly selecting an initial candidate point of the space target, taking the initial candidate point as a starting point, performing first expansion according to a mode of diverging from inside to outside, and generating a plurality of first candidate points; based on the projection relation from the three-dimensional space to the two-dimensional imaging plane, the maximum energy projection criterion is adopted to calculate the projection energy of each first candidate point, a second candidate point with the maximum projection energy is screened out, and the second candidate point is reserved as a real three-dimensional point of the space target; and taking the second candidate point as a starting point, carrying out second expansion according to a mode of diverging from inside to outside until a termination condition is reached, and obtaining a final space target three-dimensional imaging result. According to the invention, three-dimensional imaging can be realized quickly, and the body characteristics of a real target can be reflected better.

The invention relates to the technical field of magnetic field measurement error compensation, in particular to a single-axis Hall surface magnetic rapid imaging analysis system, which is characterized in that a magnetic field gradient real-time analysis unit calculates a magnetic field gradient change rate through a sliding window weighted difference algorithm, identifies a magnetic pole transition region and analyzes the magnetic field gradient change rate. The multi-source error coupling modeling unit synchronizes Hall probe spacing fluctuation, inclination angle and magnetic field gradient data and constructs a composite compensation function, the adaptive compensation unit corrects and counteracts spacing attenuation and projection errors through two-stage assembly lines, and the nonlinear trigger control unit generates an adaptive encryption trigger signal, so that the sampling spacing decreases progressively along with the gradient change rate, and the error compensation is realized. And the magnetic field distribution reconstruction unit fuses the compensation data and the sampling sequence, reconstructs a continuous magnetic field distribution curve by adopting gradient constraint cubic spline interpolation, accurately outputs a magnetic pole boundary position and a surface magnetic field intensity quantification result, and improves the surface magnetic imaging precision and efficiency.

The invention provides a rapid magneto-acoustic-electric tomography method without mechanical rotation and scanning. In order to solve the problems of low speed, poor stability, low imaging precision and the like of rotary scanning measurement in the existing magnetoacoustic-electric tomography (MAET), a magnetoacoustic-electric measurement theory suitable for annular sound source excitation and electrode detection is provided on the basis of sound radiation and a magnetoacoustic-electric coupling mechanism. An MAET imaging method based on annular multi-sound-source cyclic excitation and multi-electrode synchronous measurement is developed. The minimum configuration requirement of the MAET system is obtained based on the influence of the annular sound source, the number of electrodes and the positions of the electrodes on the imaging quality, and an optimal configuration scheme of rapid MAET imaging is provided. According to the invention, mechanical scanning without a transducer or phased scanning measurement of an array sound source is utilized, mechanical rotation of an object is not needed, sound source circulation excitation and multi-electrode synchronous measurement are realized through electronic control, and the imaging speed and stability are improved. The device is easy to be fused with a commercial ultrasonic CT system, and cross-scale multi-modal imaging combining ultrasonic and electrical impedance is realized.

The invention discloses an intelligent detection and analysis system for biological evaluation data of a medical instrument, and relates to the technical field of data processing, and the system comprises an image acquisition module which carries out the rapid imaging of the initial physical planking state of cells in a microwell plate; the image processing and feature quantification module is used for identifying the cell object and extracting a plurality of physical operation quality (POQ) feature parameters representing a population space distribution mode of the cell object; the quality evaluation and early warning module is used for comparing the POQ fingerprint with a preset quality baseline in real time and generating an early warning signal when the deviation exceeds a threshold value; and the data management and trend analysis module is used for continuously recording and analyzing POQ fingerprint historical data associated with the automatic pipetting equipment. According to the method, the physical operation quality is monitored at the experiment starting point, so that the accuracy, the reliability and the experiment efficiency of biological evaluation data of medical instruments are improved, the resource waste and the failure risk caused by initial inoculation errors are effectively reduced, and a way is provided for intelligent management of automatic equipment.

The invention provides a magnetic resonance free respiration data extraction method based on a respiratory wave extraction algorithm, and relates to the technical field of respiration acquisition, and the method comprises the following steps: obtaining a rapid imaging sequence, and extracting a complex number sampling value of a center k space line of the rapid imaging sequence in a z direction as an initial input signal; performing z-direction IFFT interpolation processing on the initial input signal to output a high-resolution z-t signal matrix; performing time dimension signal smoothing processing on the high-resolution z-t signal matrix; performing normalization processing on the z-axis signal at each time point based on a smoothing processing result; the z-axis signals of all the channels are spliced along the longitudinal axis according to the normalization processing result to form a unified matrix; the unified matrix is subjected to standard PCA decomposition, and principal components of the unified matrix are extracted to obtain respiratory wave data; according to the method, the breathing signal waveform can be stably extracted from the MRI original k space in the free breathing state without depending on the breath holding condition, and the structure consistency and time synchronism of breathing waves are improved.

The invention belongs to the technical field of pulsed eddy current nondestructive testing, and particularly discloses a ferromagnetic component pulsed eddy current detection imaging method and system, and the detection imaging method comprises the following steps: collecting a pulsed eddy current signal of a ferromagnetic component, carrying out logarithmic processing on the pulsed eddy current signal, and then carrying out secondary filtering processing; carrying out dimension reduction processing on the signal after the secondary filtering processing; calculating an amplitude standard deviation of the signal after dimension reduction processing of each time dimension, and selecting an effective imaging interval based on the amplitude standard deviation; performing Min-Max standardization processing on the data in the effective imaging interval; and calculating a pixel value based on a processing result obtained by Min-Max standardization, and carrying out homogenization processing on the pixel value to obtain a pulsed eddy current image. According to the invention, rapid imaging can be realized aiming at the pulsed eddy current detection signal of the ferromagnetic component, so that defects can be identified and preliminarily positioned.

The invention discloses a deep learning-based ultrasonic power Doppler image filtering method, which comprises the steps of 1, constructing input sample data, including data acquisition and preprocessing; 2, a generative adversarial network model based on U-net is constructed, the generative adversarial network model comprises a generator G and a discriminator D, the generator G comprises a coding module, an intermediate module and a decoding module, and the discriminator D comprises a series of convolution modules; and 3, constructing a loss function to train the model and update model parameters to obtain an optimal ultrasonic power Doppler image filtering model. According to the method, an ultrasonic power Doppler image obtained through traditional SVD imaging can be subjected to deep neural network and filtering to obtain a high-quality image comparable with an RAPID imaging method, so that high-efficiency imaging of ultrasonic power Doppler can be realized, and the integrity and smoothness of a blood flow structure of the Doppler image are improved to a certain extent.

The utility model relates to an imaging auxiliary device and a laser imaging system.The imaging auxiliary device comprises a sample bearing device and a position measuring device for measuring the sample bearing device in the z-axis direction, and when the sample bearing device compresses a biological tissue sample in the z-axis direction, the position measuring device measures the position of the sample bearing device in the z-axis direction; the position measuring device can be used for measuring the position of the cover glass at the bottom of the sample bearing device to obtain the position parameter of the biological tissue sample in the z-axis direction, so that the position parameter is used for controlling the laser imaging system to quickly focus the biological tissue sample in the z-axis direction in the imaging process. According to the technical scheme, rapid focusing on the biological tissue sample is facilitated, and the deformation quantity of the cover glass at the bottom of the sample bearing device in the z-axis direction can be obtained in real time, so that the biological tissue sample is indicated to be pressed, the imaging effect is greatly improved, rapid imaging of the laser imaging system is achieved, and the imaging efficiency is improved.

The invention discloses an offshore field two-dimensional seismic data rapid imaging method, and relates to the technical field of seismic exploration data processing, and the method comprises the steps: obtaining SEGD format original seismic data of a target region from a seismic collection system, combining the data of each shot of each measuring line, decoding the data into internal available data, and obtaining a to-be-processed data body; and loading an observation system and assigning seismic trace header parameters according to actual acquisition parameters based on the decompiled to-be-processed data volume. According to the invention, through a multi-stage denoising and signal protection strategy, effective suppression of various sea interferences is realized, a frequency division multi-channel statistical abnormal amplitude suppression technology is adopted, zero-phase high-pass filtering is combined, low-frequency effective signals are protected while low-frequency strong-energy background noise is removed, and the noise suppression effect is improved. The direct wave cutting step further eliminates strong energy interference under a long cable condition, highlights an effective reflection signal of middle and far offset data, forms a progressive signal-to-noise ratio improvement mechanism from original data to final imaging, and improves the interpretability of seismic data.

Disclosed in the present invention are a conical optical illumination-based reflective scanning super-resolution optical microscopy system and method. The system comprises a sample displacement module, an optical microscopic imaging module, an annular focused beam generation module, a beam scanning module, a super-resolution focused illumination and collection module, a super-resolution optical imaging module and a computer. By means of using the advantages of annular focused beam illumination, high focusing efficiency of traditional lenses, and high beam scanning speed, high-efficiency super-resolution focused illumination with an extended depth of focus is achieved, and further traditional optical lenses can be used to achieve fast super-resolution optical microscopic imaging; fast label-free far-field super-resolution two-dimensional microscopic imaging is implemented by means of two-dimensional beam scanning; by means of performing label-free far-field super-resolution two-dimensional microscopic imaging on samples at different axial positions, super-resolution two-dimensional microscopic images of different cross sections of samples are obtained, thereby achieving three-dimensional tomography. The present invention can be applied to fast label-free super-resolution microscopic imaging of biological samples, and can also be applied to other fields such as industrial super-resolution microscopic inspection.

The invention provides a single-array-element super-resolution ultrasonic imaging system based on deep learning, and the system is characterized in that the system comprises an ultrasonic collection module which comprises a single-array-element ultrasonic probe and is used for collecting a plurality of microbubble echo signals of an imaging target tissue at a single imaging angle; the system measurement matrix storage module is used for storing a corresponding system measurement matrix of the single array element ultrasonic probe at a single imaging angle; the microbubble reconstruction module is used for performing image reconstruction on each microbubble echo signal through a Moore-Penrose pseudo-inverse method according to the system measurement matrix to obtain a corresponding reconstructed microbubble image; the microbubble positioning module comprises a trained microbubble positioning network and is used for obtaining a corresponding microbubble positioning image according to the reconstructed microbubble image; and the image reconstruction module is used for carrying out superposition processing on all the microbubble positioning images to obtain a super-resolution ultrasonic microscopic image. In conclusion, the method can realize rapid imaging based on simple imaging equipment and has high imaging quality at the same time.

The invention discloses a metal internal defect rapid imaging detection method based on frequency domain interpolation and laser ultrasound, and belongs to the field of laser ultrasound nondestructive testing. The method comprises the following steps: firstly, carrying out large-interval rapid scanning on a local area of the surface of a tested piece by utilizing laser ultrasound, obtaining a group of ultrasonic body wave time domain signals with the number of x at different positions of the surface of a material, and then carrying out two-dimensional Fourier transform on the obtained time domain signals to obtain a frequency-wave number two-dimensional signal matrix; zero filling is carried out on a high-frequency part in the frequency domain, and then two-dimensional inverse Fourier transform is carried out to obtain interpolation to obtain a group of n time domain signal matrixes (n is gt; and finally, carrying out synthetic aperture imaging processing on the interpolated time domain signal to obtain a high-resolution synthetic aperture imaging result. According to the invention, for metal internal defect detection and imaging, the problems of long time consumption, large required data volume and the like of traditional laser ultrasonic synthetic aperture detection can be effectively solved, and the laser ultrasonic synthetic aperture detection efficiency and the imaging resolution are greatly improved.