18 results about "4d imaging" patented technology

The invention relates to a tower crane operation environment sensing method based on multi-scale and multi-modal feature fusion decoding, belongs to the technical field of intelligent construction, and specifically comprises the following steps: mainly based on sparse point cloud data acquired by a 4D imaging radar and video image data acquired by a monitoring camera; fusion feature extraction of two modal data is realized through twice Transform architecture based on a deformable attention mechanism, and the feature extraction process is repeated after down-sampling is performed on the two modal data, so that fusion feature information of multi-modal data is perfected from different scales. And finally, multi-scale decoding is performed on the fusion feature information of different scales, so that a final tower crane environment sensing result is obtained, and the recognition efficiency and accuracy of the tower crane operation environment sensing problem are remarkably improved by performing multi-modal fusion analysis of different scales on the 4D sparse point cloud data and the video monitoring image data.

The ultrasound imaging apparatus according to an embodiment includes: a display configured to display an ultrasound image; an ultrasound probe configured to transmit an ultrasound signal to an object and receive an ultrasound echo signal; and a controller configured to obtain a 4D image of a heart at a first position of the object by processing the ultrasound echo signal, obtain a biplane image of the heart in a second position different from the first position, when an artifact is detected in the biplane image, extract a second cross-sectional image corresponding to a first cross-sectional image in which the artifact is detected among the biplane images from the 4D image and control the display to display the second cross-sectional image.

The application discloses a kind of 4D imaging millimeter wave radar stereo traffic dataset construction method and related equipment, comprising: obtaining the multi-source original data collected by data acquisition platform, which is equipped with 4D imaging millimeter wave radar, laser radar, high-definition camera and positioning system etc., and the multi-source original data contains the above-mentioned each sensor data and is collected in the target scene of preset scene library, each sensor data is aligned under unified space-time reference after time synchronization and space calibration;Multi-source original data is analyzed and processed, point cloud is obtained and quality verification is carried out;4D imaging millimeter wave radar point cloud and laser radar point cloud are fused, visual reference is provided according to image data, motion compensation is provided by positioning data, and multi-modal sensing data is formed;Multi-modal sensing data is labeled, and dataset is obtained.The application constructs multi-modal high-quality dataset with 4D imaging millimeter wave radar as core, cooperates multiple sensors, covers multiple stereo traffic scenes, and provides high-precision labeled information with time sequence continuity.

The invention discloses a 4D imaging millimeter wave radar pitch angle self-calibration processing method, system and platform based on ground and high-altitude targets. The simple and reliable vehicle-mounted 4D imaging millimeter wave radar pitch angle self-calibration method is realized by using common flat road surfaces and high-altitude markers in vehicle driving as references, the mounting angle deviation caused by vibration and jolt can be automatically compensated in the vehicle life cycle, the industrial problem of inaccurate radar height measurement is effectively solved, and the vehicle-mounted 4D imaging millimeter wave radar pitch angle self-calibration method is suitable for popularization and application. And the sensing precision and decision reliability of the advanced driving assistance system are obviously improved.

The invention relates to the technical field of cockpit images, and discloses a cockpit 4D image generation system based on end-cloud collaboration. The system comprises an end side data acquisition module, a cloud side processing module and an end side image generation module. The end-side data acquisition module is provided with a multi-sensor fusion unit, so that multi-source cabin data can be formed; after the cloud side processing module receives the data, an image prediction unit outputs an image prediction signal and a risk early warning signal, an image optimization unit processes the data and the prediction signal to obtain an optimal rendering signal, and a rendering control unit defines constraint conditions and outputs rendering parameters. In the end side image generation module, a self-adaptive rendering execution unit adjusts parameters according to the optimal rendering signal, a cabin equipment control unit adjusts equipment according to the parameters and multi-source data and receives a real-time state signal, and a user interaction module processes an early warning and prediction signal and outputs a feedback index. According to the system, by means of cloud cooperation and multi-source data fusion, the cockpit 4D image generation effect and intelligent experience are optimized.

The present disclosure provides systems and methods for fetal monitoring. The methods can include obtaining ultrasound data related to a fetus collected by an ultrasound imaging device; generating a 4D image of the fetus based on the ultrasound data; instructing a display component of an extended reality device to display the 4D image to an operator; detecting a motion of the fetus based on the ultrasound data; and instructing a haptic component of the extended reality device to provide haptic feedback to the operator regarding the motion.

The invention belongs to the technical field of medical image sequence registration, and provides a self-adaptive medical image sequence registration method and system based on space-time collaborative coding, and the method comprises the steps: obtaining 4D image sequence data, defining each element in the 4D image sequence data as a 3D image corresponding to a corresponding moment, registering the 4D image sequence data by using a pre-trained deep neural network model to obtain a registration result; the deep neural network model comprises a feed-forward encoder and a reconstruction decoder which both adopt a multi-stage hierarchical design, and the feed-forward encoder fuses time sequence dependence and space context information in an image sequence; the reconstruction decoder performs step-by-step up-sampling and accurate reconstruction on the features output by the encoder, and constructs a feature compensation path through jump connection between layers so as to fuse shallow spatial information and deep semantic features. According to the invention, the accuracy of registration is improved.

The application relates to the technical field of sensor calibration, in particular to a 4D imaging millimeter wave radar-camera external parameter calibration method and device. 4D imaging millimeter wave radar point cloud and camera images are acquired and preprocessed, an initial external parameter matrix of the 4D imaging millimeter wave radar-camera and a camera internal parameter matrix are initialized; point cloud features and image features under multiple scales are extracted by using an improved PointNet++ network and multiple residual network blocks, the improved PointNet++ network synchronously encodes spatial, velocity and intensity information of the point cloud; based on the point cloud features, the image features, the initial external parameter matrix and the camera internal parameter matrix, a point cloud-image fusion feature under multiple scales is acquired by using a Transformer module; the external parameter of the 4D imaging millimeter wave radar-camera is estimated by using a coarse-to-precise iterative refinement mode. Compared with the prior art, the application has the advantages that the 4D imaging millimeter wave radar and the camera external parameter online calibration can be quickly, timely and accurately performed without being affected by the environment.

The present disclosure provides an ultrasonic transducer, an ICE probe and a four-dimensional imaging device for 4D imaging. The ultrasonic transducer for 4D imaging comprises a control assembly, a linear array and a reflection structure provided with a rotating reflection inclined surface connected with the control assembly and oppositely arranged; the linear array comprises a plurality of array element structures arranged in different preset directions and independently working; the control assembly is used to drive the rotating reflection inclined surface to rotate; the control assembly is also used to drive a target array element structure matched with a target azimuth of the rotating reflection inclined surface to emit and receive ultrasonic signals according to the target azimuth at different acquisition time instants, so as to generate a corresponding cross-sectional image at each acquisition time instant, and the cross-sectional images at different acquisition time instants are synthesized to obtain a four-dimensional dynamic ultrasonic image; wherein different array element structures correspond to different azimuth ranges of the rotating reflection inclined surface. The four-dimensional dynamic ultrasonic image generated by the present disclosure can meet the medical needs of accurate examination of heart cavities.

The invention provides a production line EOL calibration method of a vehicle-mounted millimeter wave radar, and belongs to the technical field of vehicle-mounted millimeter wave radar calibration. Comprising the steps that a rear radar calibration metal plate is installed on the rear side of a four-wheel positioning station, the width of the rear radar calibration metal plate is made to be larger than that of a calibration object, and the rear radar calibration metal plate serves as a rear side radar calibration target of the distributed millimeter wave radar; and the width of the front radar calibration metal plate is widened to be greater than the width of the calibration object, so that the front radar calibration metal plate is used as a front side radar calibration target of the distributed millimeter wave radar. By setting a calibration working mode and properly reducing the number of working array elements, the effective aperture of the radar is reduced, the existing production line station is reused to the maximum extent, the method is not only suitable for a traditional 3D radar, but also suitable for a 4D imaging radar, meanwhile, an OTA wireless communication scheme is used for replacing a wired communication scheme of a diagnostic instrument and an OBD interface, and the cost of calibration equipment is reduced.

The application relates to the technical field of intelligent traffic and road safety monitoring, and discloses a slope deformation monitoring and identification method based on 4D imaging millimeter wave radar, which comprises the following steps: acquiring continuous point clouds; modeling voxels of the point clouds in a three-dimensional space; selecting three continuous frames of point clouds, identifying mutant voxels by calculating the point number change of each voxel in adjacent frames; performing spatial clustering on the mutant voxels to obtain an obstacle region; extracting features of the obstacle region, wherein the extracted features include a height difference, an average reflection intensity and a centroid drift of the obstacle region; performing linear weighted fusion on the extracted features to construct a landslide mutation index; determining whether the obstacle region contains an obstacle target according to a preset condition, and performing risk classification identification according to the landslide mutation index. The application realizes all-weather, structured and high-reliability perception of landslide / rockfall traffic major safety hazards, and provides a new basic capability for a traffic safety system.

The present application relates to a tower crane operating environment perception method based on multi-scale multi-modal feature fusion decoding, belonging to the technical field of intelligent construction, specifically comprising that the method is mainly based on sparse point cloud data collected by 4D imaging radar and video image data collected by monitoring camera, through twice feature extraction of fusion of two modal data based on deformable attention mechanism Transformer architecture, while the two modal data are down-sampled, the above feature extraction process is repeated to realize the fusion feature information of multi-modal data from different scales, and finally the multi-scale decoding of the fusion feature information of different scales is carried out, so that the final tower crane environment perception result is obtained, the present application carries out multi-modal fusion analysis of 4D sparse point cloud data and video monitoring image data in different scales, and then the recognition efficiency and accuracy of tower crane operating environment perception problem are significantly improved.

The application discloses a 4D multi-frame spectral three-dimensional imaging method based on aperture coding and digital image correlation, adopts a 4D imaging system, and tightly couples and cooperatively images two different mechanisms of spectral imaging and three-dimensional imaging. In the system, a mask in an aperture coding spectral imaging module is removed, a target object is actively illuminated with an aperture coding pattern, and then an image after spatial light intensity modulation is obtained, so that the effect of the mask is achieved. The application combines active coded aperture snapshot spectral imaging with digital image correlation (DIC), creatively combines a digital speckle image used for 3D imaging and a random code required for spectral imaging, and can synchronously perform spectral reconstruction and three-dimensional reconstruction, so that the system speed is greatly improved. Since the active CASSI scheme is adopted to realize spectral imaging, and no mechanical motion structure and mask are contained, the device structure is stable and fast sampling can be achieved.

This application belongs to the field of computer vision and 3D reconstruction technology, and relates to a method, device, electronic device, and storage medium for single-image vehicle 4D reconstruction. The method includes: performing frequency domain decomposition processing on a single vehicle image to be processed using a wavelet basis to obtain image transformation components; processing the image transformation components using an image feature network to obtain a static 3D Gaussian ellipsoid set; performing temporal deformation processing based on the static 3D Gaussian ellipsoid set, time parameters, and the vehicle motion type corresponding to the time parameters, combined with an implicit deformation field network, to obtain a 4D Gaussian ellipsoid set; expanding the 4D Gaussian ellipsoid set with specified parameters to obtain an expanded 4D Gaussian ellipsoid set; and obtaining a single-image vehicle 4D image based on the expanded 4D Gaussian ellipsoid set, the spherical harmonic coefficient vector of the ambient illumination distribution, and the viewing angle direction. This achieves single-image vehicle 4D reconstruction under heavy illumination conditions.

The invention discloses a cleavage-stage embryo medical image quality detection method and system, and relates to the technical field of medical image detection.The cleavage-stage embryo medical image quality detection method comprises the following steps that S1, a cleavage-stage embryo is placed in a matched agarose culture dish, and the refractive index of the agarose culture dish is consistent with that of an embryo culture solution; s2, constructing a 4D imaging model, performing continuous dynamic imaging on the cleavage stage embryo, and collecting 4D original image data of the cleavage stage embryo within a preset time range; s3, constructing a preprocessing model, carrying out refraction correction on the 4D original image data, identifying an embryo contour and cell distribution, judging an embryo body position, and forming preprocessed image data; the agarose culture dish with the refractive index consistent with that of the embryo culture solution is adopted and matched with the exclusive refraction correction sub-module for light refraction deviation compensation, refraction deviation is eliminated from the source and post-processing two dimensions, the problems of image blurring and distortion are effectively solved, and the basic quality of images is improved.

This invention relates to the field of cockpit imaging technology and discloses a cockpit 4D image generation system based on edge-cloud collaboration. The system comprises three main modules: edge-side data acquisition, cloud-side processing, and edge-side image generation. The edge-side data acquisition module includes a multi-sensor fusion unit that can generate multi-source cockpit data. After receiving this data, the cloud-side processing module outputs image prediction signals and risk warning signals through an image prediction unit. An image optimization unit processes the data and prediction signals to obtain the optimal rendering signal, and a rendering control unit defines constraints and outputs rendering parameters. In the edge-side image generation module, an adaptive rendering execution unit adjusts parameters according to the optimal rendering signal, the cockpit equipment control unit adjusts equipment based on parameters and multi-source data, and receives real-time status signals. A user interaction module processes warning and prediction signals and outputs a feedback index. This system optimizes the cockpit 4D image generation effect and intelligent experience through edge-cloud collaboration and multi-source data fusion.

The invention discloses a 4D imaging millimeter wave radar pitch angle dynamic self-calibration processing method, system and platform based on a road guardrail, and the method comprises the steps: employing a common road guardrail at the side of a vehicle as a calibration object, analyzing the height change rule of a guardrail point cloud detected by a radar in real time, employing an intelligent iteration compensation algorithm, and achieving the dynamic self-calibration of the pitch angle of a 4D imaging millimeter wave radar. On-line calibration of the pitch angle deviation of the 4D imaging millimeter wave radar can be automatically and accurately completed in the vehicle driving process, the problem that height measurement is not accurate due to the change of the radar installation angle is effectively solved, the recognition reliability of an advanced driving assistance system on air and ground targets is greatly improved, no extra calibration facility is needed, and the cost is reduced. The maintenance cost is obviously reduced; according to the method, a metal guardrail which is common on a road and easy to recognize by a radar is used as a calibration object, a pitch angle deviation compensation value is automatically calculated in an iterative compensation mode by analyzing a height change rule of a guardrail point cloud detected by the radar, complex calculation and special tools are not needed, and the method can be automatically completed in a vehicle driving process.

A system and method of automated segmentation of computed tomography (CT) imaging for predictive modeling of therapeutic agent response using deep learning analysis. The method includes acquiring a single CT scan of one or more regions of a patient. The method includes segmenting the single CT scan to generate one or more volumetric segmentation (VS) masks. The method includes combining the single CT scan and the one or more VS masks to generate a 4D image. The method includes providing the 4D image to one or more predictive models trained to predict therapeutic agent responses based on the 4D image. The method includes generating, by a processing device, a predicted treatment response score to a treatment for the patient based on the 4D image and the one or more predictive models.