6350 results about "3d image" patented technology

Systems, methods, and devices for using ultrasound for diagnostic and therapeutic procedures are provided. Ultrasound signals may be transmitted and / or received by ultrasound transducers in an ultrasound device positioned within the anatomy of a patient. The ultrasound transducers may be arranged in an array such that a first segment of the array is configured to transmit ultrasound pulses and receive ultrasound echoes for diagnostic procedures and a second segment of the array is configured to transmit ultrasound pulses for therapeutic procedures. The received ultrasound echoes may be used to generate two- or three-dimensional images of the anatomy.

A method of performing Cross-Domain Spatial matching (CDSM) for monocular object detection in 3D free space surrounding a vehicle includes receiving into an image processing network, from a camera of the vehicle, at least one input image, determining from the input image, a set of 2D image features of potential targets in surrounding the vehicle, transforming the set of 2D image features into a set of 3D image features of the potential targets by aligning a lateral axis and a vertical axis of the 2D image features with, respectively, a tensor height axis and a tensor width axis of a 3D birds eye view grid, applying a CDSM aggregation to the 3D image features to extrapolate depth information, and generating a set of aggregated 3D features to the potential targets, and detecting, based on the aggregated 3D features, one or more objects associated with the potential targets.

The invention relates to a method of visualising a dynamic anatomical structure (1), a computer program and a user interface. The method comprises (a) providing a sequence of three-dimensional medical images (M1, M2, M3, . . . MZ) of a dynamic anatomical structure (1) spanning a time period (T), (b) providing a dynamic model (14), in particular surface of the anatomical structure, (c) determining a volume of interest (40) containing an anatomical feature of interest (3) within each of the three-dimensional images, wherein the volume of interest (40) follows the position and / or the shape of the anatomical feature of interest (3) across the time period and wherein the volume of interest (40) is smaller than the complete field of view of the three-dimensional medical images (M1, M2, M3, . . . MZ), and (d) providing a three-dimensional visualisation environment (50, 70), wherein a visualisation (45) corresponding to a particular point in time comprises (i) a volume rendering of the volume of interest (40) of the three-dimensional image; and (ii) a visualisation of the dynamic model (14) in the same coordinate system. Preferably, the three-dimensional visualisation environment (50, 70) allows for displaying the dynamic model (14) and the volume rendered volume of interest (40) for each three-dimensional image across the time period in cine mode.

The invention relates to an image processing method and a puncture guiding system. The method comprises the following steps: acquiring a medical image sequence image and an ultrasonic sequence image of a target object; performing registration based on the ultrasonic sequence image and the medical image sequence image to obtain a registration transformation matrix and a three-dimensional image after registration fusion; displaying a cross section image in the registered and fused three-dimensional image in a first display area, and projecting a puncture point on the puncture plate on a mapping point of the cross section image and an imaging area of a sagittal plane; responding to rotation operation of the ultrasonic probe, and updating imaging areas of the cross section image, the mapping points and the sagittal plane in the first display area in real time according to the rotation operation; when any target mapping point is located in the imaging area of the sagittal plane in the cross section image, the relative position of the target mapping point located in the imaging area of the sagittal plane in the sagittal plane image is displayed in the second display area. Therefore, the same target mapping point can be displayed in the cross section image and the sagittal plane image at the same time.

The invention relates to an underwater environment three-dimensional reconstruction method. The method comprises the following steps: projecting a multi-band structured light pattern in an underwater environment, and capturing an image by using a multispectral camera; fusing images of different wavebands through a spectrum matching algorithm, and extracting depth information to generate three-dimensional reconstruction basic data; a depth error caused by underwater scattering and absorption is corrected by using a depth compensation technology; generating an environment characteristic model by using real-time monitoring environment parameters including illumination, turbidity and temperature of an underwater sensor; adaptively adjusting image acquisition and processing parameters including exposure, contrast and color balance according to the environment characteristic model; detecting a distorted area caused by environment change in the image through an intelligent correction algorithm, and executing local correction and overall optimization; generating a multi-scale image pyramid, and decomposing the structure information of the three-dimensional image layer by layer from coarse to fine; and through an adaptive detail enhancement technology, carrying out refinement processing on the key area to generate an underwater three-dimensional image.

The invention provides a burn area measurement method and system, electronic equipment and a storage medium, and relates to the field of area measurement. The method comprises the following steps: photographing a target part to obtain a multi-modal burn image set, and carrying out image registration; and constructing a global three-dimensional surface model based on the registered image set. Carrying out burn area identification segmentation on the multi-mode burn image, mapping a segmentation result to the global three-dimensional surface model, and obtaining a preliminary burn area three-dimensional surface model; and performing multi-scale feature extraction and fusion on the registered image set, and inputting a depth estimation model to obtain burn depth estimation data. And performing deep layering on the preliminary burn area three-dimensional surface model based on the burn depth estimation data to obtain burn area three-dimensional images of different depth levels. And calculating the actual burn area of each depth level based on the burn area three-dimensional images of different depth levels and the camera focal length information. Through the method, the accuracy of burn area measurement is improved.

The invention discloses a TSV technology-based silicon wafer image defect identification method and system, and the method comprises the steps: synchronously collecting three-dimensional images according to the depth structure characteristics of a TSV silicon wafer, mapping the three-dimensional images of different modes to a unified space coordinate system, and obtaining a three-dimensional fusion image; according to the three-dimensional fusion image, a feature extraction model based on a three-dimensional convolutional neural network is adopted, TSV hole wall morphology, depth deviation and material uniformity features are extracted, and an enhanced multi-dimensional feature tensor is obtained; according to the multi-dimensional feature tensor, modeling in combination with the spatial topological relation of the TSV structure to obtain a spatial topological distribution diagram of the defects; according to the space topology distribution diagram of the defects, the relevance between defect causes and process links is analyzed, a defect cause report and process optimization suggestions are generated, and an interpretable defect diagnosis result is obtained. According to the embodiment of the invention, a comprehensive and accurate silicon wafer image defect identification and process optimization scheme can be provided, and the reliability of a TSV manufacturing process is improved.

To simulate a 3D image of a subsurface below a surface, the system having a memory device for storing an instruction, a processor in communication with the memory device configured to execute the instruction, and a subsurface image capture module in communication with the processor, the subsurface image capture module having one or more wave generating device and one or more sensor affixed to a vehicle to capture a series of digital image datasets of the subsurface with a coordinate reference data, wherein the processor executes an instruction to generate a digital model of the series of digital image datasets of the subsurface while maintaining the coordinate reference data, wherein the processor executes an instruction to determine a depth map of the digital model, and wherein the processor executes an instruction to identify a key subject point in the digital model, where subsurface includes an internal biology, below ground, underwater.

The invention discloses a pipe online defect detection method and system, and relates to the technical field of image detection. The detection method comprises the following steps: placing a to-be-detected pipe in a dark box environment, irradiating the to-be-detected pipe in a rotating state through a light source, displaying a pipe projection on a projection surface, and setting a detection line at the upper end of the projection surface; comparing the detection line with a set reference line in real time, and marking a suspected warping area according to the local offset; performing three-dimensional image reconstruction on the suspected warping area to generate a simulation three-dimensional point cloud model; the method is technically characterized in that preliminary judgment passes through a grading strategy of'rapid screening-precise reinspection ', and the detection speed and precision are balanced; by means of the optical path principle and threshold value comparison, positioning operation of the whole-surface suspected warping area can be rapidly completed, only data of a local area (suspected warping area operation) is analyzed, the hardware cost and energy consumption are greatly reduced, and the high-speed online detection requirement is met.

Presented herein are systems and methods that provide for automated analysis of three-dimensional (3D) medical images of a subject in order to automatically identify specific 3D volumes within the 3D images that correspond to specific anatomical regions (e.g., organs and / or tissue). Notably, the image analysis approaches described herein are not limited to a single particular organ or portion of the body. Instead, they are robust and widely applicable, providing for consistent, efficient, and accurate detection of anatomical regions, including soft tissue organs, in the entire body. In certain embodiments, the accurate identification of one or more such volumes is used to automatically determine quantitative metrics that represent uptake of radiopharmaceuticals in particular organs and / or tissue regions. These uptake metrics can be used to assess disease state in a subject, determine a prognosis for a subject, and / or determine efficacy of a treatment modality.

Presented herein are systems and methods that provide for automated analysis of three-dimensional (3D) medical images of a subject in order to automatically identify specific 3D volumes within the 3D images that correspond to specific anatomical regions (e.g., organs and / or tissue). Notably, the image analysis approaches described herein are not limited to a single particular organ or portion of the body. Instead, they are robust and widely applicable, providing for consistent, efficient, and accurate detection of anatomical regions, including soft tissue organs, in the entire body. In certain embodiments, the accurate identification of one or more such volumes is used to automatically determine quantitative metrics that represent uptake of radiopharmaceuticals in particular organs and / or tissue regions. These uptake metrics can be used to assess disease state in a subject, determine a prognosis for a subject, and / or determine efficacy of a treatment modality.

The invention relates to the technical field of machine vision and detection, in particular to a shoe pattern defect detection system based on the visual technology, which comprises an acquisition processing unit, a three-dimensional model unit, a defect detection unit and a defect processing unit. The three-dimensional model unit reconstructs an accurate shoe pattern three-dimensional model in sequence, the defect detection unit divides the model into a plurality of areas, calculates the average curvature, and accurately analyzes and judges the flatness defect degree by adopting a plane fitting algorithm based on a least square method and a curvature difference algorithm based on a sliding window; and the defect processing unit automatically processes the shoes with serious defects, so that high efficiency, accuracy and automation of shoe pattern defect detection are realized, and the quality detection level of shoe production is powerfully improved.

The invention relates to the field of image recognition, in particular to a wind power construction intelligent safety management method and system based on intelligent AI monitoring. The method comprises the following steps: obtaining an omnibearing real-time image flow of a wind power construction area, carrying out super-resolution deep convolution optimization and operator three-dimensional image segmentation, and extracting an operator three-dimensional image frame; three-dimensional point cloud modeling of the construction area is carried out based on the image flow, real-time image frame position positioning rendering is carried out according to a three-dimensional image frame, and a real-time twinborn model of the construction area is constructed; performing operation dynamic behavior analysis and behavior deviation degree quantitative analysis based on a twin model to obtain the behavior deviation degree of the operator; and according to the behavior deviation degree, carrying out early prediction analysis on illegal behaviors, making an adaptive risk early warning decision, and constructing an operation behavior risk early warning strategy. According to the invention, through real-time operation behavior identification and environmental risk analysis, the intelligence and safety level of wind power construction are improved.

The present invention includes a three-dimensional (3D) image display device and a head-mounted display featuring a light-field image display comprising a display panel with a group of element pixels composed of multiple pixels displaying light field information, and a light shutter array panel capable of forming an aperture by opening and closing multiple light shutters. In the present invention, to address vergence-accommodation conflict (VAC), reduce crosstalk, improve viewing angles, and enhance 3D resolution, the light-field image display has a light field ray group with multiple radiation angles formed by the element pixel group and the aperture, wherein the resolution of the radiation angles of the light field ray group is 0.3° or less. It further comprises a padding pixel group with one or more pixels not displaying light field information around the element pixel group, and the light field ray group is output only within a central viewing angle range, while a two-dimensional image is output in angular ranges outside the central viewing angle.

The invention relates to a small focus segmentation and feature learning method based on Transform and CNN fusion. The method comprises the following steps: preprocessing an input three-dimensional image to obtain original input features, and inputting the original input features into a segmentation network model of an encoder-bottleneck-decoder structure; after passing through an encoder based on channel-Transform fusion, obtaining fusion features through a bottleneck used for expanding a receptive field; wherein the encoder comprises a channel convolution module for local feature capture and a local attention mechanism module for global modeling; the preprocessed input features pass through a channel convolution module and a local attention mechanism module in sequence, and then pass through a bottleneck containing cavity convolution to carry out feature fusion; and inputting the fused features into a decoder based on a jump connection mechanism to gradually restore the low-resolution features to the same size as the input image, and generating a final segmentation result or classification result. According to the method, efficient feature extraction and fine prediction of three-dimensional images such as medical images can be realized.

The invention discloses a multi-angle particle therapy system without a rotating rack and a using method thereof, and relates to the technical field of particle therapy equipment, and the treatment system comprises an accelerator, an irradiation system, a control system, a patient supporting system and an imaging system. The patient supporting system comprises a containing and fixing device, a two-dimensional translation system, a rotating system and a multi-degree-of-freedom mechanical positioning system, the containing and fixing device is connected with the two-dimensional translation system, the two-dimensional translation system is connected with the rotating system, and the two-dimensional translation system controls the relative position of a patient and a rotating center; the rotating system rotates a patient to an appointed angle of a treatment plan or cooperates with the imaging system to obtain a three-dimensional image of the patient, and the irradiation system irradiates a tumor target area; the use method comprises the following steps: generating a treatment plan by reconstructing a three-dimensional CT image, and completing irradiation at different angles according to the treatment plan. According to the treatment system, multi-angle irradiation on a patient can be realized under the condition that a rotating rack is not used, and the manufacturing period and cost of the particle treatment system can be reduced.

The invention discloses a sparse view angle complex outdoor scene three-dimensional reconstruction method, electronic equipment and a storage medium. The method comprises the steps of obtaining camera pose information and initial three-dimensional point cloud information with rich geometric priori through an initialization module; according to the camera pose information and the initial three-dimensional point cloud information, in combination with a self-attention mechanism, a first target image is generated through a new view angle enhancement module, and the first target image is used as a pseudo-supervision signal to supervise an original rendering image; according to the camera pose information and the initial three-dimensional point cloud information, a high-fidelity second target image with transient shielding removed is acquired through a shielding processing module; and optimizing the three-dimensional Gaussian radiation field through a course learning strategy according to the first target image and the second target image, and reconstructing to obtain a three-dimensional image of the complex outdoor scene. The embodiment of the invention can reproduce the landscape scene vividly, provides immersive roaming experience, can improve the reconstruction effect and visual consistency, and can be widely applied to the technical field of computers.

Presented herein are systems and methods for the automated determination of a prostate cancer staging score (e.g., a PRIMARY score) for a subject. In certain embodiments, the systems and methods employ a machine learning model (e.g., one or more convolutional neural networks, CNNs) to analyze three-dimensional (3D) images obtained via both a functional imaging modality and an anatomical imaging modality. In addition to identifying regions of PSMA binding agent uptake (hotspots), the techniques described herein are able to accurately and automatically associate specific prostate zones to each hotspot and use this information in the determination of the staging score.

An in-situ fretting corrosion fatigue testing machine based on synchrotron radiation diffraction and three-dimensional (3D) imaging includes an axial fatigue loading system, a fretting loading system, and a corrosion environment control system, where the axial fatigue loading system includes a driving device, a load control device, and a load sensing device; the load sensing device is configured to measure an axial force and a normal force in real time; the driving device is configured to drive the load control device, thereby achieving axial displacement of the load control device; the load control device is configured to carry out axial fatigue loading of a specimen; and the fretting loading system includes a fretting wear device. The testing machine achieves real-time 3D imaging characterization of wear spot and crack morphology of a material in a fretting corrosion environment, as well as characterization of a residual stress evolution law.

The invention relates to the technical field of mining scraper conveyor equipment, in particular to a scraper conveyor chain breakage monitoring method and device based on machine vision. The method comprises the following steps: acquiring a real-time three-dimensional image when a chain moves through a stereo camera; obtaining real-time state data of the chain according to the real-time three-dimensional image; and comparing the real-time state data with standard data, and if the real-time state data does not meet a preset threshold value, determining that the chain has a chain breakage risk. According to the method, the real-time three-dimensional image of the chain during movement is obtained through the stereo camera, the real-time state data of the chain is obtained according to the real-time three-dimensional image, whether the chain breakage risk exists or not is determined by comparing the real-time state data with the standard data, and the chain state can be accurately monitored in real time.

An electronic device includes: a projector; a camera; one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the electronic device to: control the projector to display a projected image on a screen, wherein the screen includes surfaces; control the camera to obtain a captured image including the surfaces and the projected image; identify, based on the captured image, shapes of the surfaces and areas of the projected image projected onto the surfaces; and correct the projected image, based on the shapes of the surfaces and the areas of the projected image, by transforming the projected image into one from among a three-dimensional image and a flat image.

The invention belongs to the technical field of visual inspection, and particularly relates to a PCB defect detection method and device based on 2D and 3D image visual combination, and the method comprises the steps: collecting the 2D information and 3D information of a PCB, and carrying out the defect marking; the 2D information subjected to defect labeling serves as a training set to be input into a pre-constructed yolov10 target detection network, and a yolov10 model is obtained after training is conducted through a training strategy of double label distribution and consistent matching measurement; converting the 3D information subjected to defect marking into voxel features and coordinates by using a pre-constructed seond target detection network, performing feature extraction on the voxel features and coordinates by using a sparse convolutional neural network, and classifying object directions to obtain a trained seond model; and determining the defect type of the target PCB according to the yov10 model and the seond model. By adopting the deep learning algorithm and the 3D vision technology, the detection accuracy and efficiency can be greatly improved, the maintenance cost is reduced, and the detection robustness and stability are improved.

The invention discloses a self-adaptive gravity center adjustment method and system for a transfer robot, and relates to the technical field of robot control, and the method comprises the steps: respectively collecting the three-dimensional information and contact force distribution information of an article and the contact force information between the robot and the article through a sensor, integrating the collected information to obtain a multi-modal data set, and carrying out the preprocessing of the multi-modal data set; utilizing a deep learning algorithm to extract visual feature vectors from the three-dimensional image information, and extracting tactile feature vectors from the contact force distribution information and the contact force information; fusing the extracted visual feature vector and the extracted tactile feature vector to obtain a multi-modal feature set; constructing a motion state model based on a deep learning algorithm, inputting the motion state model by using the historical multi-modal feature set, and outputting a control strategy; a control algorithm and a control strategy are optimized by using real-time feedback information; the invention provides a self-adaptive gravity center adjustment method by collecting multi-modal sensor data and combining a deep learning algorithm to perform feature extraction and fusion.

A deep learning network can perform three-dimensional (3D) image reconstruction of a scene from multi-view calibrated two-dimensional (2D) images. The network can include a convolutional neural network that performs feature extraction to generate feature pyramids corresponding to features at different levels of resolution. The feature pyramids can be used to compute a respective cost volume for each feature pyramid at each level of resolution, with the cost volume incorporating a learnable parameter that corresponds to a weight allocated to the “reference” feature pyramid relative to other feature pyramids. A depth map for each input image can be generated based at least in part on the cost volume.

The invention relates to the technical field of three-dimensional image reconstruction, in particular to a VR-based three-dimensional reconstruction method and system for textile culture heritage, and the method comprises the steps: obtaining a multi-view image collection sequence of the textile culture heritage, carrying out the geometric topological feature extraction of the multi-view image collection sequence, generating a three-dimensional point cloud geometric model, and carrying out the reconstruction of the three-dimensional point cloud geometric model. Performing multi-resolution texture feature mapping processing on the three-dimensional point cloud geometric model to generate an initial three-dimensional model fusing geometric topological features and multi-resolution texture features; performing dynamic geometric optimization processing on the initial three-dimensional model based on preset VR display parameters to generate a target three-dimensional model after surface continuity correction; and performing dynamic matching processing on the target three-dimensional model and a preset VR interaction algorithm to generate a VR visual model with a multi-dimensional interaction attribute, and transmitting the VR visual model to a VR display terminal to perform three-dimensional space rendering, so that the three-dimensional reconstruction and interaction intelligence degree of the textile culture heritage can be improved in combination with a VR technology.

The invention discloses a quality detection system and method for a glue injection laser contour, and belongs to the technical field of quality detection, and the method comprises the steps: obtaining a reflection point cloud signal of a glue injection finished product, constructing a point cloud data stream, setting an image reconstruction method, constructing a glue layer three-dimensional model, synchronously generating a pseudo-color grey-scale map, and achieving the visual representation of the surface texture of a glue layer. A three-layer feature extractor is constructed, a quality primary judgment method is set, features of different scales are fused in a cross-layer mode, the problem of missing detection of complex defects in traditional single-feature detection is solved, basic defects are automatically recognized, and a quality primary judgment result is output; and performing defect judgment on the glue-injected finished product which is unqualified in primary judgment, setting a defect fine judgment method, performing voxel-level segmentation on the three-dimensional image, calculating defect characteristics, and judging whether the defects affect the use performance of the product or not so as to generate a fine judgment result, so that accurate positioning of complex defects is realized, and the defect type identification accuracy is improved.

The invention discloses a device and a method for intelligently investigating types and quantity of fishes. The device comprises a self-adaptive sonar detection module, a three-dimensional image acquisition module, an image preprocessing module, a fish detection module, a main body segmentation module and an identification and classification module. The sonar module is integrated with a three-frequency-band transducer, can dynamically switch frequency according to fish school depth, and realizes target tracking counting and quantity estimation in combination with an algorithm; the image acquisition module constructs a fish school three-dimensional image model by combining a depth camera with a light attenuation compensation algorithm; the preprocessing module fuses acoustic and optical features and expands a data set; the detection and segmentation module is used for accurately positioning fishes and removing impurities; the identification and classification module realizes type identification based on transfer learning and supports incremental learning of new fingerlings. According to the method, through cooperation of multiple modules, the problems of insufficient detection precision, poor image quality and the like in traditional investigation are solved, efficient and accurate investigation of fish species and quantity is realized, and technical support is provided for fishery resource management and ecological protection.

The invention relates to a three-dimensional semantic scene completion method and device, a storage medium and computer equipment, and the method comprises the steps: inputting a two-dimensional image and a depth image into a three-dimensional semantic scene completion model, carrying out the feature extraction through a feature extraction module, extracting a two-dimensional semantic feature in the two-dimensional image, and extracting a depth feature in the depth image; carrying out feature fusion on the two-dimensional semantic features and the depth features to obtain a fused feature map; inputting the fused feature map into a feature enhancement module for feature enhancement to obtain an enhanced fused feature map; inputting the enhanced fusion feature map into a down-sampling module for down-sampling to obtain a down-sampled feature map; inputting the down-sampling feature map into an attention enhancement module for attention enhancement processing, and outputting a three-dimensional image of the scene to be complemented; the adaptive capacity to complex scenes is enhanced, and the accuracy of three-dimensional semantic scene completion is improved.

The invention provides a high-imaging-resolution method for identifying a lead sealing defect part of a cable, and relates to the field of nondestructive testing. Comprising the steps that a linear array probe array is utilized, a plurality of array elements emit ultrasonic waves to a to-be-detected defect part at the same time, and a received echo signal reflects the waveform shape and the waveform phase of the defect. A two-dimensional image is preprocessed through a synthetic aperture focusing technology, a combined image is reprocessed through a phase coherence technology, the quality and accuracy of the image are further improved, and a high-resolution three-dimensional image is constructed in combination with an imaging synthetic aperture focusing technology. The ultrasonic phased array technology, the SAFT technology, the phase coherence technology and the synthetic aperture focusing technology are combined, the imaging resolution is effectively improved, the method has remarkable advantages especially when defect parts in complex structures such as cable lead seals are recognized, the imaging quality is optimized, a two-dimensional image is converted into a high-resolution three-dimensional image, and finally an accurate defect recognition result is obtained.

The invention discloses an immersive robot teleoperation method and system, and belongs to the technical field of robot teleoperation. An existing teleoperation scheme lacks an effective and timely feedback mechanism, is poor in operation intuition and low in control precision, and is difficult to compete with complex and fine operation tasks. According to the immersive robot teleoperation method, by constructing the first person mapping model, the interaction data acquisition model, the teleoperation processing model, the execution perception model and the immersive visual angle simulation model, real-time mapping can be performed on posture actions of an operator, and a real-time response three-dimensional image capable of being displayed in VR equipment is generated; an effective and timely immersive feedback mechanism from a first person perspective is formed, an operator can execute a task as like being personally on the scene, and the immersion, intuition and naturalness of interaction are improved, so that the control capability and the task execution effect can be remarkably improved, the operation efficiency and precision are improved, and then the operator can competent for complex and fine operation tasks.