65results about How to "Reduce artifacts" patented technology

The invention relates to a Mama-based seismic image super-resolution reconstruction method, which comprises the step of constructing a local feature extraction module, a global feature extraction module and a high-quality seismic section reconstruction module so as to solve the problem of insufficient resolution caused by high-frequency attenuation and sparse acquisition. According to the invention, a Mama model is introduced, and a novel super-resolution reconstruction network is constructed. The local feature extraction module extracts shallow feature information through a convolutional layer; the global feature extraction module obtains global features through the multi-stage residual state space block; and the high-quality seismic image reconstruction module realizes reconstruction of a high-resolution seismic image through pixel recombination and convolution operation. In addition, a Charbonnier loss function is adopted, the gradient disappearance problem is effectively avoided, and the loss function of traditional Mamba is improved. According to the method, the seismic image resolution can be improved, and meanwhile, the calculation complexity and the time cost are remarkably reduced.

The invention relates to the field of image enhancement, in particular to an image enhancement method and system of a vehicle-mounted image sensor. The method comprises the following steps: acquiring driving record images of a vehicle at multiple angles; dynamic scene self-adaptive exposure adjustment is carried out on the driving record images of the vehicle at the multiple angles, so that multiple self-adaptive exposure driving images are obtained; carrying out deep network noise identification on the plurality of adaptive exposure driving images, and carrying out dynamic filtering and noise reduction on sub-images one by one so as to generate a plurality of filtering and noise reduction optimized images; carrying out image texture analysis on the plurality of exposure sub-images, and carrying out texture distortion reconstruction to construct a plurality of texture reconstruction images; and road object visual identification is carried out on the plurality of texture reconstruction images, and adaptive contrast enhancement processing is carried out, so that a plurality of detail contrast enhancement images are constructed. According to the invention, a high-definition and stable panoramic vehicle-mounted image is realized.

The invention provides a multi-degraded image restoration method based on self-adaptive prompt. The method comprises a two-stage hidden space diffusion model, and various degraded images can be flexibly processed. Specifically, the model generates a degradation cue by learning the difference between a degraded image and a clean image, and encodes the cue information in a hidden space. In the first stage, a degradation prompt is obtained through a degradation adaptive prompt learning mechanism as a key feature for guiding the diffusion model in the second stage to carry out image restoration. Finally, prompt information is integrated into a Fourier transform restoration network, and accurate restoration of different types of degraded images can be realized. The method not only improves the accuracy of image restoration, but also significantly reduces the calculation complexity, and is suitable for image restoration tasks in various real world scenes, including denoising, deblurring, defogging, rain removing, snow removing, raindrop removing and low illumination enhancement.

The invention belongs to the field of CT image processing, and particularly relates to a CT image reconstruction method and device for improving 3D Gaussian splashing and a CT system. The method comprises the following steps: acquiring multiple frames of two-dimensional X-ray images; performing three-dimensional reconstruction on each frame of two-dimensional X-ray image to generate three-dimensional point cloud data and camera position information; according to the three-dimensional point cloud data of each frame of two-dimensional X-ray image and the camera position information, generating a two-dimensional plane of each frame of two-dimensional X-ray image by using 3D Gaussian splashing; performing adaptive rasterization processing on the data projected to the two-dimensional plane to generate two-dimensional image data; and performing adaptive rendering processing on the rasterized two-dimensional image data to generate a CT reconstructed image. The method does not need to carry out depth sorting, does not need to depend on a large-scale annotation data set, can effectively suppress noise, reduce artifacts and maintain the edge and detail definition of the image, has efficient reconstruction performance, and is suitable for rapid and high-quality reconstruction of low-dose CT imaging.

The invention belongs to the technical field of medical imaging, and particularly relates to an MRI (Magnetic Resonance Imaging) condition reconstruction method based on coil calibration image control, which comprises the following steps of: acquiring a coil calibration image and undersampled MRI image data; inputting the coil calibration image into a condition control module to estimate a coil sensitivity distribution map; taking the coil calibration image as condition input, and reconstructing undersampled MRI image data in combination with a diffusion model; wherein the diffusion model comprises a forward diffusion process and a reverse diffusion process, image reconstruction is realized by gradually adding and removing noise, and detail reduction and definition of a reconstructed image are remarkably improved by combining the forward and reverse noise removal processes of the diffusion model with a condition control mechanism of a coil calibration image; the condition control module dynamically adjusts the influence of the coil calibration image on the reconstructed image, thereby effectively reducing the noise and artifacts in the image, and enabling the reconstructed image to be clearer and more accurate.

The invention discloses a rapid magnetic resonance imaging reconstruction and segmentation method and system, a medium and a product, and relates to the technical field of image processing. The method comprises the following steps: decomposing original three-dimensional magnetic resonance data into a plurality of independent two-dimensional magnetic resonance data slices along a slice sequence; image reconstruction is carried out on the two-dimensional magnetic resonance data slices through a pre-trained forward generator in the frequency domain Schrodinger bridge diffusion model so as to generate a two-dimensional magnetic resonance image, and the forward generator integrates a Fourier convolution module and is used for carrying out frequency domain transformation and feature enhancement processing on feature mapping in the image reconstruction process; inputting each two-dimensional magnetic resonance image into a pre-trained segmentation model in sequence, performing segmentation of a target region and a preset dangerous organ, and generating a corresponding two-dimensional segmentation mask; all the two-dimensional segmentation masks are rearranged and stacked according to the slicing sequence, and a three-dimensional segmentation result is generated through three-dimensional fusion operation. By implementing the technical scheme, magnetic resonance imaging reconstruction and segmentation can be quickly and accurately carried out.

An embodiment of the present invention provides an imaging method of a CT imaging system, which relates to the field of radiation scanning technology. The CT imaging system includes: an imaging channel; M distributed ray sources, at least one of which includes q target points; N detectors; the q target points included in at least one of the M distributed ray sources are arranged at intervals along a first straight line, and the first straight line is arranged obliquely relative to a first direction. The imaging method includes: placing an object to be imaged in an imaging channel; controlling the q target points of at least one distributed ray source to emit a ray beam to form an imaging area; using at least one detector to detect rays emitted from at least one distributed ray source and passing through the object to be imaged, and generating projection data based on the detected rays; generating a computerized tomography image of the object to be imaged based on the projection data. The beam emission time interval is determined based on the inclination angle of the extension direction of the first straight line relative to the first direction.

This invention relates to the field of image processing technology, providing a three-dimensional scene reconstruction method, electronic device, and storage medium. The method includes: inputting a real image and a corresponding rendered image of the scene to be reconstructed into a motion-static separation module of a three-dimensional reconstruction model; obtaining a dynamic mask, a dynamic 3D point cloud representation, and a static 3D point cloud representation generated by the motion-static separation module based on the feature similarity between the real image and the rendered image, and the semantic segmentation result of the real image; inputting the dynamic mask, the dynamic 3D point cloud representation, and the static 3D point cloud representation into a hybrid rendering module of the three-dimensional reconstruction model; and obtaining a three-dimensional reconstructed scene generated by the hybrid rendering module based on the dynamic mask, the dynamic 3D point cloud representation, and the static 3D point cloud representation. This invention achieves high-precision motion-static separation, obtains a dynamic mask, and performs hybrid rendering of the dynamic 3D point cloud representation and the static 3D point cloud representation using the dynamic mask, significantly reducing artifacts in dynamic scenes.

The invention discloses a portable X-ray machine for measuring osteoporosis, and relates to the technical field of medical equipment.The X-ray machine adopts 18-26 V wide-range low-voltage power supply, primary boosting is performed through a full-bridge inverter circuit and a high-voltage transformer, secondary boosting is performed through a single-side CW voltage doubling rectifying circuit, the output voltage ranges from 30 kV to 80 kV, and the tube current ranges from 0.1 mA to 1 mA. A pseudo dual-energy imaging technology is introduced, low-energy and high-energy X-rays are used for imaging respectively, artifacts are reduced through continuous multi-image taking and contrast synthesis, and the imaging quality is improved. And the overexposure risk of the CCD camera is reduced by adopting an accurate dose control and delayed exposure technology. And a glue sealing insulation design and a split type structure are adopted, so that the equipment volume is reduced, and the portability is improved. Through integration of multiple technologies, the portable X-ray machine which is efficient, safe, capable of reducing measurement errors and radiation cost is provided, and the portable X-ray machine is suitable for osteoporosis detection.

The present invention provides a method and system for generating high-frame-rate and high-resolution videos based on synchronous spatiotemporal super-resolution. The method comprises: extracting frames of a video file one by one to form a video frame sequence; extracting features from each pair of adjacent frames to obtain feature vectors, and obtaining inter-frame motion representation vectors through an inter-frame motion alignment network; using RBPN to super-resolve the adjacent frames to obtain high-resolution frame vectors and low-resolution frame vectors corresponding to the adjacent frames; using a spatiotemporal super-resolution network to generate high-resolution frame vectors and low-resolution frame vectors corresponding to inserted frames; optimizing the high-resolution frame vectors corresponding to the adjacent frames and the inserted frames to obtain target high-resolution vectors corresponding to the adjacent frames and the inserted frames and generating three target video frames by upsampling; and re-encoding the generated target video frames into high-frame-rate and high-resolution videos.

This invention provides a cathode-unitized X-ray source, a static CT imaging system, and an image enhancement method, comprising: a vacuum tube; a cathode end for emitting electron beams, the cathode end including an exposure control module and multiple electron emission units arranged in a matrix on the same side of the exposure control module, all electron emission units being independent and electrically connected to the exposure control module; an anode target bombarded by the electron beam, the anode target including an anode body and a target surface formed on the anode body, the target surface being located on the emission path of the electron emission units; when the exposure control module receives an external control signal, it establishes a voltage line between the selected electron emission unit and the exposure control module, the electron emission units emitting electrons one by one or row by row toward the target surface, and the target surface reflecting X-rays to a window under the bombardment of electrons. This invention can increase the scanning range, improve the image quality of static CT, and extend the lifespan of the X-ray source.

The present invention discloses a method for reconstructing simultaneous multi-layer imaging signals. The reconstruction method comprises: generating virtual automatic calibration signals of multiple layers according to the acquired automatic calibration signals of multiple layers, wherein the automatic calibration signals of multiple layers and the virtual automatic calibration signals are both complex data of k-space; generating a training data set according to the automatic calibration signals of multiple layers and the virtual automatic calibration signals; training a neural network model using the training data set; inputting the acquired original aliased data of multiple layers into the trained neural network model to obtain corresponding network output data; obtaining complete reconstruction data of k-space according to the fusion of the original aliased data and the network output data; and generating a reconstructed image according to the complete reconstruction data. The phase information of the virtual automatic calibration signal is fully utilized to more fully train the neural network model, and the virtual signal is used as another training data set to obtain a higher quality reconstructed image without increasing the extra scanning time.

The present invention provides a method for three-dimensional dynamic imaging of fluid based on multi-channel OPT and neural network, comprising the following steps: using laser to provide illumination, emitting laser to biological samples, the biological samples will scatter light and form sample images, continuously collecting sample images of n angles of the biological samples, and obtaining a number of original data graphs; using neural networks to train the collected sample images with spatiotemporal characteristics to obtain a network model; using the network model to predict the original image; obtaining a two-dimensional sample feature distribution map, and using OPT technology to reconstruct three-dimensional images of these two-dimensional sample feature distribution maps to obtain dynamic three-dimensional images. The present invention also provides an imaging device. The present invention improves the accuracy of image feature recognition, has good imaging quality, and can quickly obtain three-dimensional dynamic images.

The application provides a cloud image efficient synthesis method, belonging to the field of image processing, comprising the following steps: calculating the edge distance transform of the mask of the foreground image to generate a multi-level boundary information graph; converting the background image and the foreground image to the Lab color space, and inputting the Lab channel, the mask and the multi-level boundary information graph into a generator network to output a preliminary fusion image in the Lab color space; using a brightness discriminator and a chroma discriminator to respectively judge the local texture consistency of the preliminary fusion image and a real fusion image in the L channel, and the global color harmony of the preliminary fusion image and the real fusion image in the a and b channels; performing the adversarial training of the generator network and the discriminator based on a total loss function until the network model converges, and using the converged generator network to generate a final fusion image. The application can guarantee the high realism and consistency of the fusion image in the details and the overall color tone.

The utility model relates to the technical field of diode production, in particular to an automatic picking and detecting device for formed axial diodes, which is characterized in that a circular vibration disc is arranged on the left side of a workbench, the right side of the circular vibration disc is connected with a vibration feeding rail through a circular vibration disc guide rail, and a defective product picking and detecting device is arranged on the vibration feeding rail; the defective product picking and detecting device feeds defective products into the defective product guide rail, a defective product receiving box is arranged at the tail end of the defective product guide rail, the tail end of the vibration feeding rail is connected with the discharging rail, and a receiving box is arranged at the tail end of the discharging rail. According to the utility model, defective products generated after the formed axial diode is bent and formed can be screened out, the problem of manual reinspection is solved, the production efficiency is improved, and manual finished products are reduced. And a solution is provided for applications with special requirements.

The present disclosure provides a data reconstruction method based on Radon domain sparse representation and related equipment, relating to the technical field of communication. The method comprises: obtaining low-resolution Radon coefficients; inputting the low-resolution Radon coefficients into a neural network of an encoding-decoding structure to obtain first high-resolution Radon coefficients; and increasing the sparsity of the first high-resolution Radon coefficients through an adaptive soft threshold function cascaded at the back end of the neural network to obtain second high-resolution Radon coefficients. The method can reduce the data size, operation time, and operation cost of time-domain inversion of reduced-time variable Radon transform, and improve the stability and resolution of reconstructed data.

A physiological mechanical signal monitoring system and method utilizing motion state to suppress artifacts, belonging to the field of biomedical signal monitoring and processing technology, aims to improve the existing distributed multi-node vibration and physiological signal acquisition systems, which suffer from severe crosstalk between multiple channels, signal aliasing caused by artifacts, and feature distortion, failing to meet the requirements of high-fidelity, multimodal dynamic acquisition. Key technical points: The signal monitoring system includes a multi-point distributed acquisition module, a motion state recognition module, an artifact detection and adaptive filtering module, and a main control and signal fusion module. The main control and signal fusion module is used to fuse and reconstruct the multi-channel physiological mechanical signals after artifact suppression processing, outputting high-fidelity physiological signals. This invention significantly reduces the coupling effect between different channels caused by environmental vibration, body motion impact, and matrix resonance through independent support of multiple spatial nodes and isolation of mechanical paths, significantly improving the spatial discrimination ability and original independence of the signals. This invention achieves multi-point physical isolation at the structural level, and then combines vector superposition to achieve preliminary noise reduction, effectively reducing artifacts caused by non-target actions and environmental disturbances.

The present disclosure provides an image enhancement processing method, device, equipment and storage medium, which relates to the field of artificial intelligence technology, and in particular to the field of cloud computing technology. The specific implementation scheme is: in response to the read input image, the color space corresponding to the input image and all color pixels of at least one color component in the color space are obtained; the sharpened pixel values ​​corresponding to the pixel positions of all color pixels are determined; based on the sharpened pixel values ​​corresponding to the pixel positions of all color pixels, the smoothed sharpened pixel values ​​corresponding to all pixel positions are determined; according to the smoothed sharpened pixel values ​​corresponding to all pixel positions, the image to be encoded corresponding to the input image is obtained.

According to the multi-input hierarchical infrared image super-resolution reconstruction method based on the collaborative CNN and Transform, through ingenious combination of the advantages of the CNN and the Transform, clearer detail information and edge structures can be reconstructed in a reconstruction task of an infrared image super-resolution image, the contrast ratio and definition are improved to a certain degree, and the reconstruction efficiency of the infrared image super-resolution image is improved. Unnecessary artifacts and noise are reduced, a clearer appearance is kept while high-precision textures and structures are recovered, and a good visual effect is achieved.

The present invention discloses a cervical fusion device, which is made of porous tantalum; the structure of the cervical fusion device is a box-type structure; the upper surface of the cervical fusion device is convex, and the lower surface is straight; the cervical fusion device includes a central part and a peripheral wall, the central part is arranged in the middle of the cervical fusion device, and the peripheral wall is arranged around the central part; the peripheral wall is made of porous tantalum with a porosity of 20%-30%; the central part is made of porous tantalum with a porosity of 70%-80%; the central part of the cervical fusion device is provided with vertically retractable barbs. The cervical fusion device provided by the present invention does not require bone grafting, has no bone grafting area, and avoids complications related to bone grafting; it is made of porous tantalum material. Porous tantalum, also known as trabecular metal, has a three-dimensional structure with interconnected pores similar to human cancellous bone, has a high porosity, can promote the exchange of nutrients in the pores, is more conducive to bone ingrowth, promotes bone integration, and increases the fusion rate.

The invention discloses an air coupling photoacoustic imaging system and method based on a finite aperture model, and belongs to the field of biomedical imaging. The system comprises a lens assembly, a reflector assembly, a focusing lens assembly, a three-axis mobile station, a rotating motor, a self-made ultrasonic transducer clamp, an ultrasonic transducer, a self-made sample clamp, a signal amplifier, a data acquisition card and an imaging processing terminal. Compared with the prior art, traditional water immersion or gel coupling is improved into the mode that air is adopted as a coupling medium, a finite aperture model is introduced to improve the finite aperture effect caused by point source mismatching in the imaging process, the imaging effect is further improved, and compared with other imaging methods in the photoacoustic imaging field, the imaging method has the advantages that the imaging efficiency is improved; a reconstructed image with higher resolution can be obtained, artifacts far away from a rotation center are reduced, and the imaging quality is improved.

The invention discloses a laminated imaging method, device and equipment, a medium and a product, and the method comprises the steps: collecting all diffraction sub-graphs of a to-be-recovered sample based on a circular probe; respectively guessing the light intensity distribution of the to-be-recovered sample and the circular probe to obtain a guessed object field image and a guessed circular probe; according to the current random order, each diffraction sub-graph is recovered according to the guessed object field image and the guessed circular probe, and an initial recovery image is obtained; the current random order is a recovery order of updating all diffraction sub-graphs once; according to a preset threshold value and the guessed radius of the circular probe, error information of the edge area of each initial recovery image is eliminated, and each target recovery image is obtained; and according to each target recovery image, determining a recovery image of the to-be-recovered sample. And the convergence speed and the imaging quality of laminated imaging can be improved.

This invention relates to a video object removal method based on a text-based video model and learnable negative tokens, comprising: acquiring the original video to be processed and a specified target to be removed; segmenting the target to be removed using a video segmentation model to generate a corresponding video mask sequence; preprocessing the original video and the video mask sequence to obtain masked video latent features and mask latent features; constructing an object removal model based on a text-based video model, wherein the object removal model retains the cross-attention module of the pre-trained text-based video model; setting the text prompt input to empty and introducing learnable negative tokens; inputting the masked video latent features, mask latent features, and negative tokens into the object removal model; the object removal model processes the negative tokens through the cross-attention module, suppressing object generation features within the mask region, and generating filling content based on video background information; and outputting the video after removing the specified target.

This invention relates to the field of bearing processing equipment technology, and provides a belt feeding device for conveying bearing races, including a base and a plate conveyor belt. A bracket is fixedly connected to the top of the base, and rollers are fixedly installed on both the top and bottom of the bracket. The plate conveyor belt is fixedly connected to the outside of the rollers, and a left support plate is fixedly connected to one side of the plate conveyor belt. A limit mechanism is provided inside the left support plate. By setting the limit mechanism, this invention allows the bearing to be conveyed upwards by the plate conveyor belt. When it rotates to the electromagnetic groove, the conductive head is squeezed and pushes the conductive column into the right electromagnetic attraction block. Current is transmitted through the conductive column to the left and right electromagnetic attraction blocks, causing them to open and attract the bearing onto the left and right support plates. This achieves the function of fixing the bearing races during the conveying process of the belt feeding device for conveying bearing races, preventing the bearings from falling off midway due to vibration, and improving the working efficiency of the equipment.

The invention discloses a novel breast tissue marker, and relates to the technical field of medical instruments, the novel breast tissue marker comprises a metal core and a marker shell wrapping the outer surface of the metal core, the metal core is a non-magnetic metal core, and the marker shell has a compressed state when not absorbing water and an expanded state when being expanded after absorbing water. The marker shell is of a hard structure in a compressed state, and the marker shell is made of a flexible material in an expanded state. According to the arrangement, the metal characteristic of the metal core ensures that the marker is easy to find under X-ray; due to the non-magnetic characteristic of the metal core, noise generated during magnetic resonance is reduced, the developing property of magnetic resonance is improved, and the marker can be easily found during magnetic resonance; the marker shell has an expansion state of expanding after absorbing water, and can absorb body fluid after the whole marker is implanted into a human body, so that the marker shell absorbs water to expand, the volume of the marker shell is expanded, the developing performance of an ultrasonic image is improved, and the marker shell can be found more easily during ultrasonic examination.

The invention belongs to the technical field of image processing, and discloses an event camera-based image processing method and device, equipment and a medium. The method comprises the following steps: acquiring event data of a blurred image collected by an event camera; constructing an initial PINN model, and embedding an event generation equation in the initial PINN model; inputting the event data into the PINN model to obtain a predicted brightness value, performing time derivative self-supervision based on the predicted brightness value and an actual brightness value, introducing Tikhonov regularization constraint conditions to optimize the PINN model, and determining an optimized PINN model; inputting event data of an image to be processed into the optimized PINN model to obtain logarithmic brightness values of three color channels of the image to be processed; the logarithmic luminance values are converted into reconstructed image frames using tone mapping. Noise and artifacts of a reconstructed image can be reduced, and the quality of a model reconstructed image is improved.

The application provides a fluid bulk modulus parameter extraction method, a fluid identification method, equipment and a medium, wherein the parameter extraction method comprises the following steps: dividing a seismic gather into at least three angle intervals, selecting a typical angle for each interval, and obtaining a corresponding partial stack for each interval; obtaining an elastic impedance curve and a curve of K f , f m and p for each typical angle from well logging data; performing elastic impedance inversion on the elastic impedance curve and the partial stack to obtain elastic impedance data of the typical angle; extracting wellside elastic impedance data from the corresponding elastic impedance data body by well logging; constructing a calculation relationship by using the curve of K f , f m and p and the elastic impedance curve of each typical angle, and bringing the curve of K f , f m and p and the wellside elastic impedance data into the calculation relationship to extract fluid bulk modulus. The technical scheme of the application can improve the resolution of the elastic impedance data body, reduce fluid identification artifacts, and improve the drilling rate of fluid inversion.

The present invention provides a magnetic resonance compatible robot system, which belongs to the technical field of medical robots. The robot system comprises a robot body, a control cabinet and cables, the control cabinet is used for controlling the operation of the robot body via the cables, and the robot body comprises motors and encoders, each of which is externally provided with an insulation film, a metal shielding layer and an insulation shell in sequence. The processing scheme of the present disclosure can improve the compatibility of the robot system with the MRI system and greatly reduce noise and artifacts on MRI images, so as to realize real-time image-guided interventional surgery.

The invention relates to a microcosmic electron microscope image processing method and system based on multi-scale zooming, and the method comprises the steps: obtaining an image of a target object through a microcosmic electron microscope, storing the obtained microcosmic electron microscope image in a file, carrying out the bilinear difference value down-sampling processing of the image, and obtaining a microcosmic electron microscope image; storing the image subjected to bilinear difference downsampling processing as a low-resolution image LR; the low-resolution image LR is rotated, scaled and overturned, brightness and contrast are adjusted, random noise is added, and therefore additional variants are generated; obtaining a microscopic image data set; and a multi-scale scaling microscopic electron microscope image super-resolution MS-MESR network model is constructed. According to the method, flexible zoom multiple control can be realized, more selective results of zoom multiple are realized, and the resolution and quality of the microscopic electron microscope image and the applicability under different zoom factors are remarkably improved.

The present application relates to a magnetic field enhancement component and a magnetic field enhancement device. The magnetic field enhancement component includes a first dielectric layer, a first electrode layer, a second electrode layer, a third electrode layer, a fourth electrode layer and a seventh control circuit. The first electrode layer and the second electrode layer are arranged on the first surface of the first dielectric layer. The third electrode layer and the fourth electrode layer are arranged on the second surface of the first dielectric layer. The first electrode layer and the third electrode layer constitute a second structural capacitor. The second electrode layer and the fourth electrode layer constitute a third structural capacitor. The seventh control circuit is connected between the first electrode layer and the second electrode layer, and includes a third capacitor, a first inductor and a first switching circuit. The circuit after the first inductor and the first switching circuit are connected in series is connected in parallel with the third capacitor. The first switching circuit is disconnected in the radio frequency transmission stage, so that the loop where the magnetic field enhancement component is located resonates with the detection part to increase the magnetic field. The first switching circuit is turned on in the radio frequency transmission stage and cannot enhance the magnetic field.