61 results about "4d imaging" patented technology

There is provided a method for analysing medical image data (34) in a virtual multi-user collaboration, wherein the medical image data (34) is analysed by at least two users (A, N, C, S), each user having his / her own workspace (30), wherein the workspace is a VR- and / or AR- and / or MR-workspace, the method including the steps of providing medical image data (34) including 3D or 4D image information, loading the medical image data (34) into the workspace (30) of each user so as to simultaneously display a visualization of the medical image data (34) to each user, allowing each user to individually and independently from each other change the visualization of the medical image data (34), so as to obtain an individual visualization of the medical image data (34) in each workspace (30) pertaining to each user, allowing at least one user to execute an analysing process of the medical image data (34) in his / her workspace, displaying the result of the analysing process in the workspace (30) in which the analysing process was carried out, and synchronizing the result of the analysing process in real-time with the at least one other workspace (30) such that each workspace (30) displays the result of the analysing process in the respective individual visualization of the medical image data (34). Further, there is provided a computer program relating to the above method. In addition, a user interface and a system used during execution of the above method are provided.

An apparatus comprises an interface and a processor. The interface may be configured to receive pixel data representing a first field of view of a camera and four-dimensional (4D) point cloud data representing a second field of view of a 4D imaging radar sensor. The first field of view of the camera and the second field of view of the 4D imaging radar sensor generally overlap. The processor may be configured to process the pixel data and the 4D point cloud data arranged as video frames and perform an extrinsic parameter calibration for the 4D imaging radar sensor and the camera based on adaptive projection error. The extrinsic parameter calibration may comprise applying a pose calibration process to the video frames. The pose calibration process may use (i) a respective translate vector and a respective rotation matrix for each of the 4D imaging radar sensor and the camera and (ii) a radar corner reflector to obtain configuration parameters for the first field of view of the camera and the second field of view of the 4D imaging radar sensor. The pose calibration process generally comprises capturing data for a plurality of positions of the radar corner reflector between a near-distance value and a long-distance value, and modifying a scale of a projection error of the radar corner reflector based on a size of the radar corner reflector in an image captured by the camera.

The invention relates to the technical field of intelligent traffic and road safety monitoring, and discloses a 4D imaging millimeter wave radar-based slope deformation monitoring and identification method, which comprises the following steps of: acquiring a continuous point cloud; carrying out voxel modeling on the point cloud in a three-dimensional space; selecting three continuous frames of point clouds, and identifying mutant voxels by calculating the point number variation of each voxel in adjacent frames; performing spatial clustering on the mutant voxels to obtain an obstacle region; performing feature extraction on the obstacle area, wherein the extracted features comprise the height difference, the average reflection intensity and the centroid drift of the obstacle area; carrying out linear weighted fusion on the extracted features, and constructing a landslide mutation index; and judging whether an obstacle target exists in an obstacle area or not according to a preset condition, and performing risk grading identification according to the landslide sudden change index. According to the invention, all-weather, structured and high-reliability perception of major traffic potential safety hazards such as landslide / rockfall is realized, and a new basic capability is provided for a traffic safety system.

The invention belongs to the technical field of medical treatment, and discloses a radiotherapy protection system for reducing normal tissue damage, and the system comprises a real-time imaging and monitoring module which employs high-speed CT or MRI equipment to obtain 4D images of a target region and surrounding tissues of a patient in real time in a treatment process; the dynamic protection dose distribution module is used for dynamically calculating dose distribution of each radiation according to the real-time imaging data, optimizing an irradiation path and reducing the stress of normal tissues; the intelligent feedback control module is used for detecting the accumulated dose of a target region and normal tissues in real time and dynamically adjusting an irradiation strategy; inputting the real-time image and the dose monitoring data into a treatment planning system, and updating an irradiation plan; the user interaction module provides a radiotherapy real-time display interface; patient physiological data is monitored in real time. According to the invention, through dynamic real-time monitoring, dose distribution optimization and intelligent feedback control, the limitation of the traditional radiotherapy technology on real-time performance and protection effect is broken through. The system significantly reduces damage to normal tissues, improves treatment precision and patient experience, and has wide clinical application value.

The invention discloses a method for evaluating the dynamic change of the open form of an aortic valve based on 4D radiography, and the method comprises the following steps: 1, carrying out the three-dimensional modeling of the aortic valve based on a clinical image; 2, under the condition that it is guaranteed that morphological information of the three-dimensional model is not lost, the opening area AVA of the aortic valve under different time phases is obtained through a 4D image or the three-dimensional model; 3, according to the obtained AVA values in different time phases, drawing a systolic period AVA curve for describing open form change characteristics of the aortic valve in the systolic period, confirming an AV stable open period, and obtaining the average open area, the maximum open area and the minimum open area of the aortic valve in the AV stable open period; 4, calculating mutual differences according to the obtained average open area, the minimum open area and the maximum open area of the aortic valve in the AV stable open period; calculating the ratio of the open area to the maximum open area of the aortic valve under different time phases; 5, according to the result of the step 4, evaluating the opening degree change condition of the aortic valve in the systolic period.

The invention relates to the technical field of sensor calibration, in particular to a 4D imaging millimeter wave radar-camera external parameter calibration method and device. Obtaining and preprocessing a 4D imaging millimeter wave radar point cloud and a camera image, and initializing an initial external reference matrix and a camera internal reference matrix of a 4D imaging millimeter wave radar-camera; extracting point cloud features and image features under multiple scales by using an improved PointNet + + network and a plurality of residual network blocks, wherein the improved PointNet + + network performs synchronous coding on space, speed and intensity information of the point cloud; based on the point cloud features, the image features, the initial external reference matrix and the camera internal reference matrix, obtaining point cloud-image fusion features under multiple scales by using a Transform module; and estimating the external parameters of the 4D imaging millimeter wave radar-camera in a coarse-to-fine iterative refining mode. Compared with the prior art, the method has the advantages that on-line calibration of the external parameters of the 4D imaging millimeter-wave radar and the camera can be rapidly and accurately carried out in real time under the condition that the method is not influenced by the environment, and the like.

A computer-implemented method of correcting motion in respiratory four-dimensional computed tomography (4DCT) images of a subject in radiation planning is provided. The method includes receiving respiratory 4DCT images, wherein the respiratory 4DCT images were acquired while a subject was free breathing. The method also includes receiving cardiac four dimensional (4D) images of the subject, wherein the cardiac 4D images were acquired while the subject was in breath hold. The method further includes deriving a cardiac motion model based on the cardiac 4D images, wherein the cardiac motion model includes frames of images of the subject, each frame corresponding to a cardiac phase in a cardiac cycle, each frame of images including motion fields at the cardiac phase. The method further includes correcting motion in the respiratory 4DCT images using the cardiac motion model, and outputting the corrected respiratory 4DCT images.

The embodiment of the invention provides a radar system, a target detection method and unmanned equipment, and relates to the technical field of radars. A signal processing module of the radar system alternately works in a first mode and a second mode, a radio frequency module is controlled to gate a transmitting antenna in a first mode in the first mode, and the radar system performs target detection based on a 4D imaging technology; in the second mode, the radio frequency module is controlled to gate the transmitting antenna in a second mode, and the radar system carries out target detection based on the phased array technology; the radio frequency module processes the echo signal received by the receiving antenna; and the signal processing module obtains target detection data according to a processing result of the echo signal. As the radar system can alternately work in the first mode and the second mode, target detection is carried out based on the 4D imaging technology in the first mode, and accurate measurement of a close-range target is realized; and in the second mode, target detection is carried out based on a phased array technology, and remote target detection is realized, so that various working scene requirements are met.

The invention discloses a liver cancer focus segmentation method and system based on dynamic feature fusion, and relates to the technical field of liver cancer diagnosis assistance, and the method comprises the steps of multi-source data collection, feature extraction, dynamic fusion, segmentation output and result verification. A 4D image, a multi-posture liver image and a synchronous physiological signal are obtained through the multi-source data acquisition module, features are extracted through the static and dynamic feature extraction module, weights are distributed through the dynamic fusion module, and then processing is conducted through the segmentation output and result verification module. Through cooperative processing of the multi-source data acquisition module, the feature extraction module and the like, a real focus boundary and a motion artifact can be accurately distinguished, and the missing detection condition of a tiny focus caused by fuzzy boundary is effectively reduced; meanwhile, the omission ratio caused by the atypical single posture feature is greatly reduced, the identification accuracy is improved by capturing the stability difference of benign and malignant lesions, finally precise segmentation of the liver cancer focus is achieved, and a reliable basis is provided for clinical diagnosis and treatment decision making.

The invention provides an ultrahigh-temperature infinite rotation 4D imaging system, and relates to a 4D imaging system, the ultrahigh-temperature infinite rotation 4D imaging system comprises a system body installed on a CT rotary table, the system body comprises a water slip ring unit, a driving and electric slip ring unit, a high-temperature bearing barrel unit and a water and electricity slip ring unit, and a sample is positioned in the high-temperature bearing barrel unit; the high-temperature bearing barrel unit is used for realizing ultrahigh-temperature heating and driving, the electric slip ring unit is used for applying a drawing force, a compressing force or a twisting force to a sample and can also perform n * 360-degree infinite rotation along with the water slip ring unit at the bottom, and the water slip ring unit is positioned at the top of the high-temperature bearing barrel unit; the water slip ring unit and the water slip ring unit are jointly used for providing cooling liquid for a system body rotating during a high-temperature test so as to prevent the system body from being damaged due to excessive heating, the water slip ring unit is used for stretching, compression and torsion tests of a material under a ray field at an ultrahigh temperature, and an n * 360-degree infinite rotation test system can be realized; and the winding problem of the cable and the water cooling pipe is effectively avoided.

The present disclosure provides a system and method for fetus monitoring. The method may include obtaining ultrasound data relating to a fetus collected by an ultrasound imaging device; generating a 4D image of the fetus based on the ultrasound data; directing a display component of a virtual reality (VR) device to display the 4D image to an operator; detecting motion of the fetus based on the ultrasound data; and directing a haptic component of the VR device to provide haptic feedback with respect to the motion to the operator.

The invention provides a system for image registration and volumetric imaging of a patient, the system comprising: a first interface adapted to receive 3D and / or 4D images of the patient; a second interface adapted to receive 2D images during a procedure carried out on the patient; and a processing unit wherein the processing unit is adapted to carry out a method comprising the steps of a method for image registration and volumetric imaging.

The invention provides an ultrasonic transducer for 4D imaging, an ICE probe and four-dimensional imaging equipment. The ultrasonic transducer for 4D imaging comprises a control assembly, a linear array connected with the control assembly and arranged oppositely, and a reflection structure provided with a rotary reflection slope. The linear array comprises a plurality of array element structures which are arranged according to different preset directions and work independently; the control assembly is used for driving the rotary reflection slope to rotate; the control assembly is further used for driving a target array element structure matched with a target orientation to transmit and receive an ultrasonic signal according to the target orientation of the rotary reflection inclined plane at different acquisition moments so as to generate a corresponding section image at each acquisition moment, and the section images at different acquisition moments are synthesized to obtain a four-dimensional dynamic ultrasonic image; wherein different array element structures correspond to different azimuth ranges of the rotary reflection inclined plane. The generated four-dimensional dynamic ultrasonic image can meet the medical requirement of accurate examination of the heart cavity.

The invention belongs to the technical field of intelligent sensors, and particularly relates to a high-precision area array 4D imaging optical method and system based on coherent detection. The method specifically comprises the following steps of: generating a step frequency signal by using an arbitrary waveform generator, loading the step frequency signal on an electro-optical modulator, and modulating a light beam output by a laser; the modulated laser is divided into reflected light and reference light, and the reflected light is reflected by an object to be detected and then enters the area array optical imaging device together with the reference light; the area array optical imaging device comprises a space bridge and a CCD (Charge Coupled Device) photosensitive area, the space bridge splits incident light into four paths through beam splitting control, and the space bridge regulates and controls the polarization state of the incident light, so that a phase difference exists between reference light and reflected light in each path of light beam; coherent processing is carried out on multiple frames of voltage data in each pixel, and the linear frequency modulation rate is calculated; and calculating the speed and position of each pixel target based on the linear frequency modulation rate to realize 4D high-precision imaging of the target.

A four-dimensional (4D) light-detection-and-ranging sensor using frequency modulated continuous wave is provided with an ultra-high velocity resolution. At a transmitting terminal, the hybrid waveform of a driving laser is used to minimize the phase noise generated by a distributed-feedback laser during wavelength scanning. The hybrid waveform is obtained by combining direct-current signal (not modulated) and alternating-current (AC) signal. The AC signal is a predistorted triangle or AC waveform for extracting location. The continuous wave (CW) extracts velocity. At a receiving terminal, a radar radio-frequency receiver is combined with an avalanche photodiode (APD) with multiple layers accumulated in series to obtain excellent responsivity and saturated current. The mixed waveform coordinated with the APD prevents Doppler shift frequency from being contaminated by low-frequency flicker noise. Thus, a good-quality 4D image is provided; and the use of the APD improves the pixel contrast between the object and background.

The application discloses a liver cancer lesion segmentation method based on dynamic feature fusion, relates to the technical field of liver cancer diagnosis assistance, and comprises the steps of multi-source data acquisition, feature extraction, dynamic fusion, segmentation output and result verification. 4D images, multi-posture liver images and synchronous physiological signals are acquired through a multi-source data acquisition module, features are extracted through static and dynamic feature extraction modules, weights are allocated by a dynamic fusion module, and then the segmentation output and result verification module is processed. Through the cooperative processing of the above-mentioned multi-source data acquisition, feature extraction and other modules, the application can accurately distinguish the real lesion boundary from the motion artifact, effectively reduces the missed detection situation caused by the fuzzy boundary of the micro lesion, greatly reduces the missed detection rate caused by the atypical single posture feature, improves the identification accuracy by capturing the difference in the morphological stability of benign and malignant lesions, and finally realizes the accurate segmentation of the liver cancer lesion, thereby providing a reliable basis for clinical diagnosis and treatment decision.

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 invention relates to the technical field of radar data processing, and particularly discloses a self-adaptive grid division method based on 4D imaging millimeter wave radar point clouds, which comprises the following steps: step S11, acquiring multiple pieces of dimension information of target point clouds around a vehicle; s12, establishing a grid map according to the current dimension information of the target point cloud around the vehicle; s13, distributing the target point clouds around the vehicle to the corresponding minimum grids on the grid map according to the current dimension information of the target point clouds, and calculating the density of the target point clouds in each minimum grid; step S14, according to the target point cloud density in each minimum grid, merging the plurality of minimum grids in the grid map to form a plurality of merged grids; and the step S12 to the step S14 are repeated until all the grid maps established by all the dimension information of the target point cloud around the vehicle are subjected to grid combination. According to the invention, through adaptive grid division, redundant grids are reduced, and a basis is provided for a subsequent rasterization clustering algorithm.

The present invention provides a method and device for assisting breast cancer identification based on multi-parameter MRI images. The method comprises: respectively acquiring breast MRI images I1 and I2 of a DWI-ADC sequence and a T1 dynamic enhancement sequence of the same patient; extracting a 3D image block I from I1 1‑3D ; Extract 3D image blocks from I2 and stitch them together in time order to form 4D image blocks I containing time information 2‑4D ; Use 3D convolutional neural network module to respectively analyze 3D image blocks I 1‑3D , 4D image block I 2‑4D Feature extraction is performed to obtain features F1 and F2; features F1 and F2 are fused, and the fused features are input into a benign and malignant classifier to obtain the benign and malignant nature of the breast lesion. The present invention improves the recognition accuracy of breast cancer by extracting and fusing features of two different sequences of MRI images.

The invention discloses a self-adaptive PET (positron emission tomography) real-time imaging method based on a fine system matrix. The self-adaptive PET real-time imaging method comprises the following steps: 1) simulating and generating the fine system matrix of a PET system; 2) based on coincidence data acquired by the PET system and the fine system matrix, performing image reconstruction by adopting an ordered subset maximum expected value method; wherein in the iteration process of image reconstruction, subset division and iteration updating are carried out on the coincidence data, the step length of each iteration updating is controlled according to a relaxation factor alpha (t) which adaptively changes along with time or a relaxation factor alpha (n) which adaptively changes along with activity, and image reconstruction is carried out according to each subset after each iteration updating. According to the invention, the distribution of the radiopharmaceutical in the scanned object can be observed in real time, a PET real-time imaging image is directly obtained, and a 4D imaging image is generated after scanning is finished.

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.

A system and method for presenting a rotational preview of an object depicted in a volume rendering of 3D image data and / or 4D image data is provided. The method includes presenting a volume rendering of an object having an initial view at a display system. The method includes presenting a volume rendering preview at the display system. Each of the volume rendering previews provides a different rotational view of the object, and each of the volume rendering previews is positioned on the display system relative to the volume rendering at a position associated with a direction indication of a user input device. The method includes receiving a direction indication from the user input device. The method includes presenting an updated volume rendering of the object at the display system. The updated volume rendering includes an updated view of the object rotated from the initial view based on the direction indication from the user input device.

The invention discloses a fuzzy speed processing method and system applied to a vehicle-mounted 4D imaging millimeter wave radar, and the method comprises the steps: obtaining first data corresponding to a view field region of the vehicle-mounted 4D imaging millimeter wave radar, and carrying out the filtering processing of the first data; based on the first data, creating a first target point subset and a second target point subset corresponding to the first target point subset, and generating third data corresponding to the first data in combination with vehicle speed data; matching and processing target point data in a target point subset for at least two times according to the third data in combination with historical frame data and current frame data; clustering the target points moving at the same speed, generating fourth data corresponding to the target points moving at the same speed, and generating corresponding fifth data based on the fourth data; according to the system, the platform and the storage medium corresponding to the method, the fuzzy speed is effectively solved, the computing power resource is remarkably saved, and the radar processing frame period is shortened.

The application discloses a kind of based on fine system matrix adaptive PET real-time imaging method, its steps include: 1) simulating generation PET system fine system matrix;2) based on the coincidence data and the fine system matrix that the PET system acquisition, using ordered subset maximum expectation value method carries out image reconstruction;Wherein in the iteration process of image reconstruction, the coincidence data is subsetted and iteratively updated, according to the relaxation factor α (t) that changes with time or the relaxation factor α (n) that changes with activity adaptively controls each iteration update step, according to each subset after each iteration update respectively carries out image reconstruction.The application can observe the distribution of radiopharmaceutical in the scanned object in real time, directly obtain PET real-time imaging image, and generate 4D imaging image after scanning.

Training an unsupervised Machine Learning model to reduce noise in a reconstructed 4D image can comprise obtaining a projection set comprising a plurality of 2D projections of a training patient volume, wherein the 2D projections represent a plurality of phases of a respiratory cycle of the training patient and comprise measurement noise, repeating, for a plurality of iterations, selecting two non-empty, mutually disjoint subsets that form a partition of the projection set, wherein each of the two selected subsets contains 2D projections that are respiratory uncorrelated for each of the two selected subsets, using a linear reconstruction algorithm to reconstruct a volumetric image of the training patient from the 2D projections contained in the subset, adding the reconstructed volumetric images to a training data set as an input volume and corresponding target output volume training pair, and using training pairs from the training data set to update values of trainable parameters of the ML model.

The invention provides a 4D imaging millimeter wave radar point cloud data thickening method and device, and the method comprises the steps: carrying out the voxelization processing of the point cloud data of a 4D imaging millimeter wave radar, and obtaining a plurality of voxels which at least comprise one point; converting the central point of each voxel into a camera coordinate system to obtain a pixel corresponding to each voxel; performing semantic segmentation on the RGB image to obtain a foreground image and a background image; determining a plurality of foreground voxels according to the pixels corresponding to the voxels; sampling pixels in the foreground image to obtain a plurality of foreground pixels, and generating a plurality of empty voxels of each foreground pixel in the point cloud coordinate system; processing the foreground pixels and the plurality of corresponding empty voxels by using a processing model to obtain a score of each empty voxel, and taking the empty voxels with the scores exceeding a preset threshold as virtual foreground voxels; and screening the virtual foreground voxels by using the foreground voxels, and taking a screening result as a thickened point cloud data set. According to the invention, the thickened point cloud data contains more target information.

The invention relates to the technical field of intelligent driving, and particularly discloses a real-time clustering method based on a 4D imaging millimeter wave radar point cloud, which comprises the following steps: acquiring all target point cloud information of a vehicle surrounding environment acquired by a 4D imaging millimeter wave radar; rasterizing and dividing all the target point clouds of the surrounding environment of the vehicle so as to divide all the target point clouds of the surrounding environment of the vehicle into corresponding grids; calculating the target point cloud density in each grid, and screening out candidate grids of which the target point cloud density reaches a standard value from all grids; combining all the screened candidate grids to obtain a plurality of combined grids, and generating a corresponding point cluster for all the target point clouds in each combined grid; and screening out reasonable point clusters from the plurality of generated point clusters, and outputting a clustering result of each reasonable point cluster. According to the invention, clustering attributes can be provided for a subsequent target tracking algorithm and a target classification algorithm, and the subsequent algorithm is simplified.

1. Name of the product under this design: Millimeter-wave radar (4D imaging CAR‑A300). 2. Purpose of this design product: This design product is used for a long-range millimeter-wave radar that uses millimeter waves to detect targets. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

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.