534 results about "Ct imaging" patented technology

The invention discloses a urinary calculus CT image automatic segmentation method based on deep learning, particularly relates to the technical field of medical image processing, and is used for solving the problem of low geometric fidelity of a segmentation result caused by hardening artifacts when an existing deep learning segmentation method is used for processing a high-density urinary calculus CT image. The method comprises the following steps: acquiring a urinary calculus CT image, performing initial segmentation by using a deep learning model to generate an initial calculus segmentation region, evaluating texture heterogeneity degree and identifying a hardening artifact risk region by analyzing feature value distribution of a structure tensor field, and positioning an artifact-causing source point based on a CT imaging projection geometric principle by reversely tracing a spatial position relation. According to the method, boundary distortion features are identified by analyzing CT value profile curve form distortion features and local boundary curvature singularity features, geometric correction is performed on corresponding boundaries in an initial stone segmentation region according to the boundary distortion features, a final stone segmentation region is obtained, and the geometric accuracy and reliability of a segmentation result are effectively improved.

Embodiments of the present invention relate generally to implant placement into bone. More specifically, embodiments of the invention relate to implant placement across the sacroiliac joint. Placement can be facilitated using various CT imaging views that allow the implants to be placed in bone associated with articular cartilage.

The invention provides a solid-state battery performance testing method and system, and relates to the technical field of battery performance testing. According to the method, pressure is applied to the solid-state battery, the pressure value is gradually changed, in-situ CT imaging detection and electrochemical performance detection are carried out on the solid-state battery in the pressure change process, and coupling analysis is carried out on the pressure value, CT image information and electrochemical parameters; the mutual relation and evolution rule among the pressure value, the CT image information and the electrochemical parameters are summarized, so that the comprehensive performance characterization of the battery under different pressure conditions is realized, and more comprehensive and accurate data support is provided for deeply understanding the performance evolution of the battery in the actual use process; the internal relation between the internal structure change of the battery and the electrochemical performance can be disclosed, and an important theoretical basis and a guidance direction are provided for the optimization design of a battery material and the improvement of the battery performance.

The invention discloses a low-dose 3D spiral CT reconstruction method and system based on a context cold diffusion model, and the method comprises the following steps: converting a linear inverse problem of CT imaging into an optimization problem, and adding a regularization term; based on a near-end gradient descent framework, solving the optimization problem by adopting an iterative shrinkage threshold algorithm, replacing a near-end operator in the near-end gradient descent method with a pre-trained two-dimensional cold diffusion model, and replacing a regularization item with the pre-trained cold diffusion model; when the cold diffusion model is pre-trained, three-dimensional context information formed by a current slice and two adjacent slices is used as the input of the cold diffusion model; taking a low-dose two-dimensional CT image as input, and performing low-dose 3D spiral CT image reconstruction by adopting the trained network; by combining the physical imaging model and the deep learning prior, the reconstruction quality and efficiency of the low-dose CT are remarkably improved, the noise and artifacts in the low-dose CT image are remarkably reduced, and the quality of the low-dose CT image is remarkably improved.

The invention discloses a multi-section type linear array X-ray source static real-time CT imaging system and an imaging method, and the multi-section type linear array X-ray source static real-time CT imaging system is provided with a scanning device and a ray source control unit; the scanning device is provided with a multi-section X-ray source array and a detector, the transmitting end of the multi-section X-ray source array faces the detector, and the multi-section X-ray source array is connected with the ray source control unit. The multi-section X-ray source array has the advantages that the multi-section X-ray source array can freely adjust the length and the included angle of the whole section, and the multi-section X-ray source array is suitable for a large-size measured object; 2, the multi-section X-ray source array can use fewer X-ray sources to realize the same wide view field, the design is more free, and the expansion is easier; 3, the distribution of ray sources can be relatively dispersed, the crossing of ray paths is less, and the interference of scattered signals can be obviously reduced; and 4, the exposure strategy of the scanning device can be controlled through the radiation source control unit, and the radiation dose utilization rate is optimized.

A method and device for accurately locating and surveying hidden active faults. First, through regional geological analysis and geomorphological judgment, potential hidden active faults and geomorphological features are identified using geological data and remote sensing images. Then, shallow exploration trenches are laid in the preliminary judgment area, and the activity and shallow location of hidden active faults are determined by combining chronological analysis and shallow seismic reflection method. Then, magnetotelluric sounding, microseismic monitoring and seismic wave CT imaging are used to detect deep hidden active faults. After that, a three-dimensional geological model is established by integrating multi-source data to intuitively display the information of hidden active faults. Finally, the activity of hidden active faults is evaluated based on the model, the impact of the project is analyzed, and optimization suggestions such as structural reinforcement and avoidance schemes are proposed. The problem that the traditional geological exploration technology is prone to splashing rocks, threatening personnel safety, increasing the difficulty of collection and affecting the exploration accuracy when locating hidden active faults, especially shallow exploration trenches, is solved due to the excavation equipment and sampling methods.

The invention discloses a spring probe system for rapid registration of articular cartilage based on 3D printing, and relates to the technical field of medical imaging and orthopedic surgery navigation. The problem that the joint registration precision is insufficient due to the fact that cartilage cannot be developed in traditional CT imaging is solved. Through personalized customization of the 3D printing guide plate, convenient installation of positioning holes, adjustability of the spring probe assembly and real-time data monitoring, and automatic data processing of the intelligent registration module, manual operation is reduced, the operation efficiency is improved, the spring probe assembly is reasonable in structure and adjustable in elastic force, stable operation of the system in an operation is guaranteed, and the operation safety is improved. Multi-position CT scanning is combined with an advanced image processing and registration technology, an accurate initial model is constructed, a spring probe assembly collects data and is combined with an elastic deformation compensation model to correct registration errors in real time, the registration accuracy is improved, reliable support is provided for orthopedic surgery navigation, the surgery success rate can be improved, and patient wounds and surgery risks are reduced.

Methods and systems are provided to predict an upper threshold and a lower threshold of a heart rate (HR) of a patient of a computed tomography (CT) imaging system using a machine learning (ML) model, based on HR time series data collected over a duration prior to a cardiac scan. The ML model takes as an additional input a desired probabilistic certainty (e.g., statistical confidence level) that the predicted upper and lower HR thresholds will be accurate, provided by an operator of the CT imaging system. Before the start of the imaging scan, the predicted upper and lower HR thresholds are used to set the start exposure and end exposure times, to ensure that the requested cardiac phases are acquired.

The invention provides an ultrasonic transmission CT (Computed Tomography) imaging method and system, a computer and a storage medium, which can be used for quickly reconstructing an ultrasonic transmission image with high resolution and high contrast. The method comprises the following steps: in layer-by-layer scanning of an annular ultrasonic transducer array, calculating a TOF (Time of Flight) matrix containing transmission time of all ultrasonic paths after the annular ultrasonic transducer array rotates by a specific angle each time; after one layer of scanning is completed, the TOF matrixes of different angles are recombined into a three-dimensional matrix according to the spatial relation, and missing data are complemented; discretizing an area to be imaged into two-dimensional grids, making each grid correspond to a pixel point, counting transmission time and path length of all ultrasonic paths penetrating through the pixel point, calculating sound velocity contribution values of the paths, taking an average value as a sound velocity value of the pixel point, and generating a two-dimensional ultrasonic transmission image; a two-dimensional image is converted into a three-dimensional image through a ray casting algorithm, the visual influence of voxels is adjusted by introducing a weight factor based on depth, and the depth perception and semitransparent rendering effect of the image are enhanced.

To perform in-situ imaging and characterization of hydraulic fracture development, a triaxial test assembly is configured to evaluate a core sample obtained from a hydrocarbon formation. The triaxial test assembly is positioned within a Computer Tomography (CT) imaging system. While the triaxial test assembly is positioned within the CT imaging system, a core sample is connected to the triaxial test assembly. The triaxial test assembly is operated to evaluate the core sample. The CT imaging system is operated while evaluating the core sample by operating the test assembly. Properties of the core sample are determined using results of operating the triaxial test assembly and of operating the CT imaging system.

The invention discloses a phosphatidylcholine gold nano CT (Computed Tomography) probe as well as a preparation method and application thereof, and belongs to the technical field of medical materials. The preparation method comprises the following steps: step S1, preparing a phosphatidylcholine ligand NH2-MPC; step S2, synthesis of a gold nanocluster GS-Au25 is carried out; and S3, the GS-Au25 is modified with a PC ligand, and the PC-Au25 is prepared. The ultra-small gold nano CT probe PC-Au25 with an Au25 gold nano cluster as a core and phosphatidylcholine PC as a surface ligand is obtained by optimizing and screening the core size and the surface ligand property of ultra-small gold nano particles. Wherein the 2-methacryloyloxyethyl phosphorylcholine is used as a PC ligand for the first time to modify the surfaces of the ultra-small gold nanoparticles, so that the surface modification of the ultra-small gold nanoparticles is realized, and the ultra-small gold nanoparticles can be efficiently and freely filtered through the kidney. The CT probe can be applied to the determination of the glomerular filtration rate through a CT imaging or blood test method.

The invention relates to the field of temperature control, in particular to a temperature control method and system for an industrial personal computer mainboard. The method comprises the following steps: acquiring a CT imaging structure diagram of a mainboard; performing inter-component physical connection analysis and component spatial topology mining on the mainboard CT imaging structure diagram, and constructing a mainboard three-dimensional topological structure model; calculating a real-time temperature value of each mainboard assembly; carrying out time sequence temperature fluctuation analysis and dynamic temperature distribution rendering on the mainboard three-dimensional topological structure model based on the real-time temperature value of each mainboard assembly so as to construct a dynamic heat distribution twinborn model; obtaining a mainboard state monitoring log; and carrying out load fluctuation trend evolution analysis on the mainboard state monitoring log, and carrying out multi-period periodic association mining so as to generate a multi-time-sequence load fluctuation evolution rule. Through efficient and dynamic temperature cooling control, long-term stability and reliability of mainboard performance are achieved.

The invention relates to the field of biological functional materials, and discloses a preparation method and application of a Cu-doped W18O49 nano-enzyme with near-infrared two-region photoresponse. The specific method is as follows: a solvothermal method is adopted, the Cu-doped W18O49 (xCu-W18O49) nano-enzyme is prepared by regulating and controlling the molar doping amount of a Cu element, taking tungsten chloride as a tungsten source, taking copper chloride dihydrate as a copper source and taking n-propyl alcohol as a reaction solvent. The crystallinity of the nano enzyme is good, and the nano enzyme shows remarkable glutathione oxidase (GSHOx) activity in a tumor microenvironment. Compared with W18O49, Cu doping enables enzyme activity to be remarkably improved, the problem of low activity generally existing in current cancer treatment nano-enzymes is effectively solved, and meanwhile the nano-enzyme has application potential in the aspect of CT imaging.

The present invention provides a method, system and medium for the etiology classification of pneumonia CT images, the method comprising: constructing a training set; performing feature extraction; performing semi-supervised learning training, including supervised learning of labeled images and assigning pseudo labels to unlabeled images based on prediction probability and adaptive confidence threshold; performing contrastive learning training, including self-supervised contrastive learning of the remaining unlabeled images, and jointly performing supervised contrastive learning with labeled images and pseudo-labeled images; constructing a joint loss function and performing back propagation optimization; repeating the steps of feature extraction, semi-supervised learning, contrastive learning and loss function optimization until the training is completed; establishing a classification system based on the trained feature extraction network and classification head, and using the classification system to classify pneumonia CT images. The present invention obtains high-quality pseudo labels through a confidence threshold category-by-category iterative optimization mechanism, and effectively alleviates the category imbalance problem by using dynamic weighted balance loss.

The invention provides an SPECT pinhole collimator imaging truncation artifact filling method and related equipment, and relates to the technical field of CT imaging. The method comprises the following steps: reconstructing real projection data to obtain an original reconstructed image, and determining a high-confidence region in the original reconstructed image; mapping the real projection data to a projection image of an ideal detector radial distance to obtain mapping projection data; predicting projection data outside an effective area of a real acquisition detector and taking the projection data as simulation projection data; carrying out weighted reconstruction on the simulation projection data to obtain a complemented image containing a truncation region; and according to the high-confidence region, fusing the original reconstructed image and the complemented image to obtain a final image. The method aims at solving the problem of truncation artifacts caused by the fact that the probe cannot completely cover the whole human body projection image, negative effects caused by the truncation artifacts can be made up, and the effect of improving the imaging quality and the diagnosis accuracy is achieved.

The invention discloses a navigation method of a surgical instrument, equipment, a medium and a program product, relates to the technical field of surgery, and discloses the navigation method of the surgical instrument, comprising: acquiring a calibration module DR image and a calibration module optical image; based on the imaging position of the mark point in the DR image of the calibration module and the imaging position of the mark point in the optical image of the calibration module, determining a conversion matrix between an optical tracking system coordinate system and a DR imaging plane coordinate system, and recording the conversion matrix as a first conversion matrix; the surgical instrument is tracked through the optical tracking system, the instrument feature points of the surgical instrument are projected to the DR image of the patient based on the first conversion matrix, the actual position of the surgical instrument can be presented in real time in the DR image of the patient on the basis of not depending on three-dimensional CT image equipment, and therefore the surgical precision and the operation convenience of a doctor are improved.

Disclosed is a support frame of a CT imaging system, including: a connection flat plate portion; a support body portion disposed on the connection flat plate portion; an X-ray source installation reference portion disposed on the connection flat plate portion; an electrical installation portion; a cooling component installation portion; and a through hole, wherein the through hole is surrounded by the support body portion, the X-ray source installation reference portion, the electrical installation portion and the cooling component installation portion, and the through hole penetrates the connection flat plate portion. The connection flat plate portion, the support body portion, the X-ray source installation reference portion, the electrical installation portion and the cooling component installation portion are integrally formed.

The invention belongs to the technical field of CT imaging, and relates to a bismuth-based imaging contrast agent and a preparation method thereof. The bismuth-based imaging contrast agent is formed by chelating diethylenetriamine pentaacetic acid (DTPA) modified by sulfamic acid with bismuth ions and then connecting an antibody to the surface. The preparation method comprises the following steps: carrying out first reaction on DTPA and sulfamic acid in the presence of an activating agent to obtain sulfamic acid modified DTPA; carrying out a second reaction with an inorganic bismuth salt in a second solvent, then adjusting the pH value to be neutral, and drying to obtain aminosulfonic acid modified DTPA chelated bismuth ions; and carrying out third reaction on the DTPA chelated bismuth ions modified by sulfamic acid and an antibody, and drying to obtain the product. The CT imaging contrast agent has excellent CT imaging capability, high safety and tumor cell killing capability.

The invention relates to a scatter correction method, a cone beam computed tomography (CBCT) system and a computer storage medium. The method comprises the following steps: performing cone beam CT imaging on a to-be-measured object to obtain a first group of projection data of the to-be-measured object, and performing reconstruction according to the first group of projection data to obtain a first volume image containing scattering artifacts; performing fan-beam CT imaging on a plurality of different heights of the to-be-measured object to obtain a plurality of groups of fan-beam projection data of the to-be-measured object, performing reconstruction according to the plurality of groups of fan-beam projection data to obtain a plurality of fan-beam slice images, and using the plurality of fan-beam slice images as reference images without scattering artifacts; extracting a plurality of cone beam slice images from the first volume image; performing image registration on the plurality of fan-beam slice images and the plurality of cone-beam slice images; and training a scattering correction model based on deep learning by using the plurality of registered image pairs to obtain a trained scattering correction model.

The invention provides a radiation imaging apparatus. The apparatus comprises: a radiation source configured to emit a radiation beam; a detector configured to receive a radiation beam from the radiation source, the radiation source and the detector defining an inspection channel; and at least one grating disposed on the inspection channel between the radiation source and the detector. The at least one grating is in the form of a cambered surface, or in the form of a groove-shaped surface having a plurality of angled planar segments, the cambered surface or groove-shaped surface facing the radiation source.

A method, apparatus, and computer-readable storage medium for controlling X-ray computed tomography (CT) imaging. A first set of projection data is acquired in a first CT scan of an object with a CT imaging apparatus. The first CT image data is reconstructed from the first set of projection data. X-ray tube current modulation information is determined for a second CT scan of the object, based on a noise propagation model between X-ray projection data and CT image data, and using, as inputs, the obtained first set of projection data, information indicating an imaging region-of-interest (ROI) for the second CT scan, and a target image quality level in the imaging ROI. The second CT scan of the object is obtained based on the obtained X-ray tube current modulation information.

The invention relates to a nondestructive walnut grading detection method based on a ray technology, which comprises the following steps: taking walnuts as materials, firstly carrying out CT imaging and shell breaking on different walnuts with shells, then carrying out manual grading marking to obtain a training set, carrying out feature recognition and grading on walnut kernels by using a deep residual network model, and outputting a grading detection result. Training the deep residual network model by minimizing the grading detection result and the actual grade to obtain a trained walnut grading detection model; and performing CT imaging on the walnut kernels with shells by using the trained walnut grading detection model to obtain a grading result. According to the invention, an image identification classification model is constructed through an algorithm, and a confusion matrix graph and an ROC curve are introduced to verify the feasibility and accuracy of the model in a certain range. The non-destructive testing technology is used for grading the walnuts with the shells, and the method has the advantages of cost saving, time saving and convenience.

The invention provides radiation imaging equipment, CT imaging equipment, a radiation imaging method and a CT imaging method. A radiation imaging device includes a radiation source, a detector, and at least one grating disposed between an inspection channel defined by the radiation source and the detector between the radiation source and the detector. And the grating only shields one part of the radiation beam, so that one part of the radiation beam passes through the grating and then is received by the detector.

The invention discloses a peripheral blood and CT-based liver transplantation recipient sarcopenia classification method and device, and the method comprises the steps: carrying out the single-factor COX regression preliminary screening of collected peripheral blood biochemical indexes of liver transplantation recipients, and obtaining potential prediction factors related to sarcopenia; performing LASSO regression screening on the potential predictive factors to obtain core predictive factors related to sarcopenia; multiplying each core predictive factor by a regression coefficient calculated in LASSO regression, performing accumulation calculation to obtain an LASSO + COX model score, and dividing liver transplantation recipients into different risk groups according to the size of the LASSO + COX model score; and carrying out definite diagnosis on sarcopenia according to a risk group division result in combination with a CT image examination result. According to the method, a new strategy of peripheral blood prediction preliminary screening and high-risk CT confirmation is realized, the radiation risk, cost and detection threshold are reduced, and the sarcopenia management efficiency is improved.

The invention discloses an intelligent laser oral implanting robot for clinical application. The intelligent laser oral implanting robot comprises a robot system, a CT imaging system, an optical positioning and tracking system, a supporting device and a control platform. The robot system comprises a base, a fixing frame, a mechanical arm and a laser transmitter, and the laser transmitter is used for drilling holes in bone tissues; the CT imaging system comprises a radiation source and a detector and is used for scanning and collecting oral information of a patient before an operation; the optical positioning and tracking system comprises an infrared emitter, an infrared stereo camera and a dynamic reference frame and is used for dynamically scanning and collecting oral cavity information of a patient in an operation; the control platform receives data information collected by the CT imaging system and the optical positioning and tracking system, and the working state of the robot system is planned and timely adjusted. Advanced image reconstruction, intelligent path planning, dynamic navigation and laser cutting technologies are combined, the accuracy of the laser cutting path can be ensured, and accurate cutting and precision control of the alveolar bone are achieved.

The embodiment of the invention relates to the technical field of tomography, in particular to a medical CT imaging system which comprises a CT imaging system and method, and the CT imaging system comprises a scanning module, a detection module and a reconstruction module; the scanning module comprises a rack, a workbench and an array X-ray light source module; the array X-ray light source module comprises a plurality of groups of light source assemblies which are arranged along the axial direction, each group of light source assembly comprises a plurality of ray source arrays, and the plurality of ray source arrays enclose to form 360 degrees; the ray source array comprises a plurality of ray source units, and rays emitted by each unit cover a part of an imaging object to form a multi-center scanning structure; the detection module comprises a plurality of detectors arranged on the inner side of the rack; and the reconstruction module is used for receiving the projection data, performing image reconstruction and acquiring image internal information. According to the CT imaging system based on the static X-ray source, the imaging object can be scanned under the condition that the light source is static, and the internal structure of the reconstructed object is obtained.

The invention relates to the technical field of small animal imaging, and particularly discloses a bimodal small animal molecular image imaging device which comprises a rack; the rotating bracket is rotationally mounted on the rack; the rotating assembly is installed on the rack and used for driving the rotating support to rotate relative to the rack; the CT imaging assembly is mounted on one side of the rotating bracket; the SPECT imaging assembly is installed on the other side of the rotating support, and the imaging center of the SPECT imaging assembly and the imaging center of the CT imaging assembly are coaxial with the rotating axis of the rotating support; the animal bed assembly is installed on the rack and used for bearing a small animal to be imaged and driving the small animal to be imaged to move towards or away from the rotating support along the rotating shaft of the rotating support; the method can effectively solve the problems of registration error, attenuation correction failure, image fusion quality reduction and quantitative analysis misalignment when the SPECT image and the CT image are fused due to alignment error of the SPECT imaging assembly and the CT imaging assembly.

The invention discloses a low-dose CT (Computed Tomography) imaging method and equipment based on semantic priori knowledge guidance. In order to solve the problems of excessive smoothness of images, detail loss and the like in low-dose CT imaging, semantic prior information is extracted through a pre-trained visual model by utilizing significant differences of different anatomical structures (such as bones, soft tissues, gas regions and the like) on noise levels, so that different tissue types are effectively distinguished, and noise modes of specific regions are captured. Meanwhile, a semantic perception module is provided, detail features concerned by the noise reduction network and high-level anatomical semantic features captured by the semantic network are aligned and fused, and it is ensured that the anatomical structure is perceived more accurately in the denoising process. Further, a segmentation network is introduced behind the noise reduction network, and a multi-task learning strategy is adopted to realize joint optimization of noise reduction and semantic segmentation. According to the design, the denoising performance of the image is improved, key anatomical details are effectively reserved, and clearer image support is provided for clinical diagnosis.

The invention discloses a prediction method for kidney stone prognosis based on CT imaging omics, and relates to the field of medicine. Comprising the following steps that CT images and clinical data are collected, retrieval is conducted through a hospital medical record system, clinical information is collected, and the CT images are scanned through a scanner; cT image processing and feature extraction are carried out, calculus areas are sketched layer by layer on all cross sections of the CT image, information is recorded, and then feature extraction is carried out; and image omics feature screening and model construction: extracting image omics features from each original CT image. According to the method, CT image features and clinical prediction factors are combined, a clinical-image omics model is developed and verified, a repeatable, non-invasive, non-invasive and safe preoperative prediction method is provided, the calculus removal success rate of a kidney stone patient after flexible ureteroscope lithotripsy can be accurately evaluated, and the calculus removal success rate of the kidney stone patient after flexible ureteroscope lithotripsy is improved. And a clinician can be assisted to make a clinical decision and implement precise medical treatment.

Various systems and methods are provided for a system and a computer-implemented method to dynamically configure a collimator aperture of a CT imaging system. The system may be provided to dynamically configure a collimator aperture over a slice coverage of a CT imaging system. The system may, further, provide a processor programmed to select an X-ray dose efficiency based on one or more parameters and dynamically configure a collimator aperture of the system within a reliability range of a calibration curve based on the selected X-ray dose efficiency and flux measured by the X-ray detector.