453 results about "Tomographic image" patented technology

The invention discloses a control method, system and equipment of an intelligent throat surgical robot and a medium. According to the scheme, a three-dimensional tissue model is constructed according to visual image data, laser imaging data and tomography image data; determining lesion data according to the historical lesion data and the tomography image data, superposing the lesion data and the three-dimensional tissue model, and determining a target operation model; determining prediction trajectory data according to the tomography image data and the physiological motion data; planning a path according to the predicted trajectory data, the target operation model and the constraint condition, and controlling the operation robot to perform an operation according to the planned path; through multi-modal data fusion, a three-dimensional tissue model is established to improve the surgical accuracy; the data are analyzed to determine the lesion direction, the motion trail of the organ tissue is predicted, the three-dimensional tissue model is integrated for path planning, the interference of physiological activities of the organ tissue on the operation is avoided, and the safety of the operation is improved. The embodiment of the invention can be widely applied to the field of intelligent robots.

The invention discloses an optical coherence tomography device for optimizing aberration digital compensation and an imaging method, the device comprises an optical coherence tomography device and an image processing module, and the optical coherence tomography device comprises an illumination module, an interference module, an area array detection module and a synchronous control module. The imaging method comprises the following steps: setting device light source parameters according to coherent gating, and determining a sampling matching relation of the area array detection module according to a sampling theorem; selecting a frequency sweeping mode or a time domain mode, electrifying to activate a corresponding light source and a synchronous time sequence, and adjusting the position of a reference mirror; collecting a full-field interference sequence of the area-array camera, performing digital aberration compensation, performing compensation and denoising on volume data of different depths, and exporting a three-dimensional diffraction limit image; and outputting a three-dimensional tomographic image with transverse diffraction limit and axial micron-level resolution. According to the invention, the imaging resolution and the imaging speed of optical coherence tomography are improved under the conditions that the camera specification is reduced, the GPU dependence is reduced and the system cost is reduced.

The invention belongs to the technical field of discrete element simulation, and particularly relates to a digital twinborn discrete element model construction method based on CT (Computed Tomography) scanning, which comprises the following three steps of: in a CT scanning stage, acquiring a high-resolution cross-sectional image by optimizing scanning parameters, and carrying out image noise reduction and feature enhancement processing; in the structural analysis stage, a segmentation model is constructed based on a deep convolutional neural network, and automatic annotation of a scanned image and intelligent prediction of a three-dimensional space topological relation are realized; in the discrete element modeling stage, the reconstructed three-dimensional grid model is converted into a discrete element model with real physical attributes through parameter calibration, and discrete element simulation is achieved. According to the method, the non-destructive detection advantage of industrial CT and the feature extraction capacity of deep learning are combined, microstructure characterization is converted into macroscopic performance prediction, and a reliable simulation analysis method is provided for performance optimization of the composite material.

A computer cuts out, from a tomographic image obtained by imaging the inside of a human body, a plurality of partial images, which include the same position in the tomographic image and have different sizes, calculates a probability of each of the plurality of partial images being a region of a specified lesion, calculates an integrated value by integrating the probabilities calculated from the plurality of partial images using a calculation that increases a contribution of probabilities calculated from partial images corresponding to at least an intermediate size out of the plurality of partial images, and identifies the same position as a region of the specified lesion when the integrated value exceeds a predetermined threshold.

This invention discloses a method for transport of intensity diffraction tomography based on non-interferometric synthetic aperture. By acquiring through-focus intensity stacks under different illumination angles and performing three-dimensional Fourier domain half-space filtering (or 3D Hilbert transform equivalently) on the measured intensity stack, further combining with non-interferometric synthetic aperture, the 3D refractive index tomographic imaging in a non-interferometric manner without the need to meet matched illumination condition can be achieved. Leveraging the inherent advantage of synthetic aperture, the imaging resolution reaches the incoherent diffraction limit, resulting in high-resolution imaging results. The non-interferometric nature of TIDT-NSA offers a simple imaging optical setup, delivers speckle-free imaging quality, and is compatible with an off-the-shelf bright-field microscope.

The invention discloses a tunnel cross-sectional image analysis method based on image processing, and aims to solve the problems that a surface image is not clear in correspondence with a transient seismic wave method, a geological radar and a resistivity imaging section space, and anomalies at a certain distance in front are difficult to map to a tunnel face. According to the method, anisotropic reforming is carried out by adopting a Fourier neural operator, cross-modal Transform registration of a micro attention mask based on sector geometry, curve mileage and section polar coordinate position coding is combined, analytic geometry mapping and uncertainty propagation are matched, tunnel face structure traces and water seepage texture evidences are fused, and the tunnel face structure traces and the water seepage texture evidences are combined. The technical effects of accurate positioning of abnormity on the tunnel face, position confidence range estimation, risk grading early warning, stripe artifact suppression, abnormal boundary reservation and output of structured results of mileage stake numbers, azimuth angles, distance intervals and the like are achieved.

The invention provides a micro-damage tomography method based on a nonlinear ultrasonic static component damage index, and particularly relates to the technical field of material monitoring. The method specifically comprises the following steps: S1, arranging sensors on the surface of a to-be-detected component; s2, setting a signal excitation end and a signal receiving end; s3, signal emission is carried out on the signal excitation end, a receiving signal of the signal receiving end is collected, and error preprocessing is carried out on the collected signal; s4, carrying out fast Fourier transform analysis and obtaining a static component energy value; s5, calculating a nonlinear damage index; s6, based on a detection grid formed by a circular array or an orthogonal scanning type array, a nonlinear damage index is used as a parameter to be embedded into an RAPID ellipse positioning algorithm, pixel values of the detection grid in an imaging area are calculated and filled, and a micro-damage tomographic image is generated. According to the method, millimeter-level positioning imaging of microcracks, layering defects and the like in the to-be-monitored structure can be realized by combining the nonlinear damage index with the RAPID ellipse chromatography algorithm.

A mark that identifies a lesion site is displayed on a tomographic image. A two-dimensional map and a graph are displayed regardless of whether or not the mark is displayed. The two-dimensional map represents lesion site probability distribution. The graph represents temporal change of lesion site probabilities.

The invention belongs to the field of train structure health monitoring, and discloses a bogie tube plate structure welding seam detection method and device, and the method comprises the steps: obtaining a Lamb wave signal of a to-be-detected tube plate structure welding seam region, and carrying out the preprocessing, and obtaining a preprocessed Lamb wave signal; on the basis of the preprocessed Lamb wave signal, the position of the weld crack defect of the to-be-detected tube plate structure is predicted through the RAPID tomography technology, and a weld crack defect positioning detection result is obtained; inputting the preprocessed Lamb wave signal sequence into a bogie tube plate structure welding seam detection model to obtain a welding seam crack defect quantitative detection result; outputting a welding seam crack defect positioning detection result and a quantitative detection result as welding seam detection results; according to the invention, the positioning and quantitative detection result of the welding seam damage of the bogie tube plate structure can be quickly and accurately obtained, the high-precision detection requirement of the welding seam of the bogie tube plate structure is met, and the safe operation of a rail transit vehicle is ensured.

The invention discloses a terahertz polyethylene pipeline defect detection method based on an improved MASK-R-CNN network, and the method comprises the following steps: 1, automatically obtaining a detection image through a terahertz tomography method, dividing the image into a training set, a verification set and a test set according to a proportion of 5: 2: 3, and converting the data set into a standard COCO format through Label-Image and Label Me tools; and step 2, inputting the tomographic image into an improved MASK-R-CNN network for training. The terahertz polyethylene pipeline defect detection method based on the improved MASK-R-CNN network disclosed by the invention has the beneficial effects that accurate detection and identification of PE pipeline hot melting joint defects are realized under complex background noise interference by constructing an improved MASK-R-CNN polyethylene pipeline defect identification model based on CBAM.

The invention discloses a glass-based circuit board defect detection method and system, and relates to the technical field of glass substrate defect detection.The method comprises the steps that an optical coherence tomography system with the fixed scanning resolution of 320 * 320 is used for collecting a tomographic image of a target area, three-dimensional reconstruction is conducted on the tomographic image, and a three-dimensional body data model is obtained; extracting a plurality of three-dimensional morphological characteristics such as defect depth, transverse distribution profile and defect internal refractive index unevenness from the model; and inputting the features into a defect classifier constructed based on a three-dimensional convolutional neural network for identification, and performing spatial position verification in combination with a known design layout to generate a final detection report. According to the method, the standardization of the detection process is realized through the fixed scanning resolution, and the efficiency and the result consistency are improved; by quantifying the refractive index non-uniformity in the defect, the optical property variation type defect in the material is effectively identified, and the detection depth and accuracy are enhanced.

The invention relates to a semi-quantitative fluid inclusion analysis method based on three-dimensional CT (Computed Tomography) scanning, which is applied to the technical field of geological mineral detection and comprises the following steps: acquiring sample data of a sample to be analyzed; performing sample preparation on the to-be-analyzed sample based on the sample data to generate a target sample; performing three-dimensional CT scanning processing on the target sample to generate three-dimensional cross-sectional image data; performing image preprocessing on the three-dimensional cross-sectional image data to generate processed three-dimensional data; extracting a three-dimensional structure of the fluid inclusion based on the processed three-dimensional data to obtain three-dimensional data of the fluid inclusion; performing parameter calculation and semi-quantitative analysis on the three-dimensional data of the fluid inclusion to generate calculation and analysis data; and generating a fluid inclusion analysis result based on the fluid inclusion three-dimensional data and the computational analysis data. The method has the effect of comprehensively and accurately analyzing the fluid inclusion.

The invention relates to a navigation method and device of a bronchoscope and a storage medium. The navigation method relates to the technical field of medical information processing. The mapping library is constructed based on the dynamic tomographic image, and the target bifurcation point identifier corresponding to the target bifurcation point is determined based on matching of the multi-modal data of the target bifurcation point and the mapping library in the process that the bronchoscope advances along the initial path. And then, determining a target AR mark corresponding to the target bifurcation point identifier based on the mapping library, and superposing the target AR mark in the visual field of the bronchoscope through AR display equipment, so as to intuitively present the position mark, the feature mark, the risk mark, the path mark and other multi-modal parameters of the bifurcation point. And finally, on the basis of a position deviation value between the mark position of the target AR mark monitored in real time and the positioning data, updating the target multi-modal feature corresponding to the target bifurcation point identifier in the mapping library in real time. In conclusion, the accuracy and safety of bronchoscope navigation are improved.

The invention provides a medical treatment suggestion auxiliary decision-making method for a calculus patient and a related device, and the method comprises the steps: obtaining the medical image data of the calculus patient, and the medical image data comprise a tomography image and ultrasonic echo data; according to the medical image data, stone position data, stone morphological characteristic data and stone density distribution data are determined; performing component analysis on the calculus according to the calculus density distribution data to obtain a calculus component analysis result; determining a stone displacement index and a volume growth rate according to the stone position data and the stone morphological characteristic data; according to the stone component analysis result, the stone displacement index and the volume growth rate, constructing a stone risk assessment coefficient; according to the calculus risk assessment coefficient and a preset risk threshold value, the treatment suggestion of the calculus patient is determined, treatment opportunity delay caused by observation delay can be effectively avoided, and the timeliness of urinary calculus clinical management is improved.

Provided are a medical image processing device, a medical image processing method, and a program that reduce a load on a user in a case of designating a three-dimensional region and improve an interpretation accuracy and efficiency of the three-dimensional region. A first image, which is a tomographic image or cross-sectional image orthogonal to a first direction of three-dimensional medical image data, is displayed on a display device, a rectangular region designated in the displayed first image is received, a length of a normal line of the first image is determined based on the rectangular region, a three-dimensional region surrounded by a rectangular parallelepiped defined by the rectangular region and the normal line in the three-dimensional medical image data is determined, image processing is performed on the determined three-dimensional region, and a result of the image processing is displayed on the display device.

The present invention relates to an artificial intelligence-based device and method for determining amyloid PET positivity, wherein a normal-appearing white matter dominance ratio is used and amyloid PET positivity is automatically determined based on machine learning, thereby improving the accuracy and sensitivity of amyloid PET positivity determination. The device comprises: an image acquisition unit for acquiring PET and MRI images of the brain of a diagnostic subject administered with a contrast agent, the images being acquired through tomographic scanning; a segmentation unit for segmenting normal-appearing white matter (NAWM) and white matter hyperintensity (WMH) from a fluid attenuated inversion recovery (FLAIR) image obtained from the MRI image; a standardized uptake value ratio (SUVR) calculation unit for calculating a global standardized uptake value ratio (SUVR) and a standardized uptake value ratio in normal-appearing white matter (NAWM SUVR), on the basis of the PET image and the NAWM region segmented by the segmentation unit; and an amyloid PET positivity determination unit for determining amyloid PET positivity by inputting the global SUVR and the NAWM dominance ratio (NDR) into a pre-trained prediction model, wherein the NDR is a value obtained by dividing the global SUVR by the NAWM SUVR.

The invention relates to the technical field of medical instrument manufacturing, and discloses a method for instantly forming an individualized child tracheal catheter through a 3D printing technology. The method comprises the following steps: acquiring CT (Computed Tomography) or MRI (Magnetic Resonance Imaging) body layer image data of neck and chest areas of a target child patient, wherein the data is used for reflecting anatomical structures of a throat and a trachea; importing the image data into three-dimensional reconstruction software, executing structure identification and segmentation operation, and constructing a three-dimensional model of the throat and trachea of the child patient; performing parameter modeling according to the model, and designing an individualized tracheal catheter model which is fit with the inner diameter of a target airway and is matched with the target airway in length and curvature; the model is converted into a printing data file matched with 3D printing equipment; and a biocompatible 3D printing device is called, the catheter model is printed through a medical implant material, and the solid catheter meeting the size requirement is obtained. The pediatric intubation system improves the matching degree and safety of pediatric intubation, and has good clinical practical value.

The invention relates to the technical field of image reconstruction, in particular to a compressed sensing driven terahertz tomography reconstruction method based on an adaptive strategy. According to the technical scheme, the method comprises the following steps that a terahertz continuous wave imaging system is used for collecting intensity data P of a corresponding view angle at equal-interval sparse angles, and a sinogram of a sparse sampling view angle is obtained; performing data preprocessing on the intensity data to unify the data scale; relevant parameters of the algorithm are initialized, wherein the relevant parameters comprise step length and regularization parameters; through a core parameter dynamic adjustment mechanism, cooperative improvement of imaging quality, reconstruction efficiency and environmental adaptability is successfully realized, clearer and more accurate terahertz tomographic images can be obtained, reconstruction can be completed at a faster calculation speed, and the method is suitable for wider practical application scenes and has good application prospects. And the comprehensive performance is obviously superior to that of a traditional non-adaptive method.

The invention discloses an X-ray tomography in-situ testing device and method suitable for a seawater high-pressure environment. The X-ray tomography in-situ testing device comprises an X-ray source, a collimator, a flat panel detector, a seawater pressure cabin and a seawater pressure control device. During detection, the X-ray source is started, the sample is started to move spirally, the flat panel detector collects projection data, then a cross-sectional image is reconstructed through an existing method, and the X-ray tomography in-situ test of the sample in the seawater high-pressure environment is achieved. In order to solve the problems that a seawater in-situ detection device in the prior art is insufficient in penetrating power, low in resolution ratio, limited in sample movement freedom degree and poor in high-pressure environment adaptability, the invention discloses an X-ray tomography device and method, and in-situ dynamic imaging can be carried out on a large component in a seawater high-pressure environment. In-situ observation of micron-sized damage and defects (100-200 microns) is realized, and meanwhile, an imaging view field is expanded through a multi-degree-of-freedom sample table and a spiral scanning method, so that the detection efficiency is improved.

A tomographic imaging system, methods to visualize tomographic images, and a ‎stereoscopic calibration procedure for obtaining two-dimensional cross-sectional ‎and three-dimensional volumetric images over the entire anterior eye. The optical ‎system combines stereoscopic imaging with patterned illumination (e.g., slit-‎scanning or array of slits). The captured cross-sectional images can be viewed ‎individually or as a fly-through video. The calibration and reconstruction methods ‎determine the true spatial location of imaged features and record a 3D volumetric ‎representation of the anterior eye. The system can image the entire anterior ‎chamber and contiguous structures, including the corneal limbus, sclera and ‎eyelids. Furthermore, the system can obtain corneal topography. ‎

A method and system for correcting detector defects in an X-ray microscope system based on deep learning. Normal geometry projections and offset geometry projections are collected for a given detector, mappings between defective regions and healthy regions are created, and a machine learning system is trained using these projections. The trained neural network system is then used to correct the tomographic projection dataset, thereby improving the image quality of the resulting reconstructed tomographic image volume set.

An image processing device includes a processor, in which the processor is configured to: input at least one processing target tomographic image to a derivation model constructed by contrastive learning using a plurality of tomographic images acquired by imaging an interior of a body such that a specific anatomical structure is included, the derivation model being constructed by the contrastive learning so as to derive a normalized relative position in the interior of the body based on a relative reference position, which is determined in advance for the specific anatomical structure, in the interior of the body; and derive a normalized relative position of the at least one processing target tomographic image in the interior of the body via the derivation model.

The application provides a human transcranial ultrasound irradiation method, device, electronic equipment and storage medium. The target head sagittal plane tomographic image and the transverse plane tomographic image are acquired; a vertical coordinate system is established based on the sagittal plane tomographic image, and the target point coordinates of the insula in the vertical coordinate system are determined; based on the transverse plane tomographic image, the horizontal distance from the insula to the target head brain midline is measured; the world coordinate point of the insula is mapped in the world coordinate system according to the target point coordinates and the horizontal distance; and the ultrasound transducer is controlled to irradiate the real position of the insula, so that accurate targeted irradiation can be realized, the use cost of the low-intensity focused ultrasound technology is effectively reduced, and the operation is simpler.

An optical tomography device includes a sample optical path system for injecting light, scanned from a light source, into a sample corresponding to biological tissue; a reference optical path system for collecting the light scanned from the light source; and a detection unit for detecting a tomography image of the sample by interfering with sample light, transmitted from the sample optical path system and reflected from the sample, and reference light transmitted from the reference optical path system. The detection unit comprises: a nonlinear crystal which receives the sample light and the reference light and generates nonlinear light having a different wavelength than the sample light and the reference light; and an image sensor which detects a depth direction signal from the nonlinear light.

An image alignment apparatus includes at least one processor, and the processor derives, for each of first and second three-dimensional images each including a plurality of tomographic images and a common structure, first and second three-dimensional coordinate information that define an end part of the structure in a direction intersecting the tomographic image. The processor aligns the first three-dimensional image and the second three-dimensional image by using the first and second three-dimensional coordinate information to align the common structure included in each of the first three-dimensional image and the second three-dimensional image at least in the direction intersecting the tomographic image.

A medical image processing apparatus includes a catheter including a sensor and insertable into a blood vessel, a display, and a processor configured to: control the catheter to acquire tomographic images of the vessel, input the images into a model and acquire information indicating a condition of a part of the blood vessel, generate a histogram of a plaque area ratio in the vessel, acquire a length of a stent to be placed or a lesion to be treated, calculate a threshold for the ratio using the first histogram and the length, generate a graph indicating the ratio at each part of the blood vessel, and control the display to display the graph and the threshold in an overlapping manner.

The invention provides a textile composite material impact energy absorption simulation method, system and device and a medium, and the method comprises the steps: carrying out the connected domain analysis of a tomography image, and determining the equivalent diameter distribution characteristics of pore defects in a textile composite material; performing stochastic simulation based on the equivalent diameter distribution characteristics in combination with a mesoscopic geometric model of the textile composite material to obtain stochastic pore space distribution of the textile composite material in the resin enrichment area; geometric difference is carried out on the random pore space distribution and the mesoscopic geometric model, and then a mesoscopic finite element model containing pore defects is constructed; and endowing the mesoscopic finite element model with material attributes and carrying out explicit kinetic analysis on impact load, and further determining the impact energy absorption performance of the textile composite material prepared in the batch according to an analysis result. By adopting the scheme of the invention, systematic deviation of impact energy absorption performance prediction caused by model idealization can be reduced.

A system is provided that includes one or more sources used to irradiate one or more solids extracted from a reservoir with an energy source and one or more detectors used to acquire one or more transmission images, wherein the one or more transmission images comprise one or more scans. The system also includes a processing circuitry and a memory, accessible by the processing circuitry, the memory storing instructions that, when executed by the processing circuitry cause the processing circuitry to perform operations. The operations may include collecting one or more scans of the one or more solids moving through an imaging zone, reconstructing one or more tomographic images of the one or more solids based on the one or more scans, and extracting one or more physical properties of the solids based on the one or more tomographic images.

Provided are a radiography system, an image processing device, an image processing method, and an image processing program that prevent an image of a correction marker from being included in a reconstructed region of a tomographic image obtained by reconstructing a plurality of projection images. A radiography system includes a correction marker that is used to obtain a marker image included in at least one of a plurality of projection images obtained by tomosynthesis imaging, is provided in an irradiation path of radiation in a radiation emitting unit, and is disposed at the position where the marker image is included in a region other than a reconstructed region in the projection image, the reconstructed region being a region used in a case in which the tomographic image is reconstructed from the plurality of projection images among the regions included in the plurality of projection images.

The present application belongs to the field of CT tomographic reconstruction technology and artificial intelligence, and discloses a limited-angle CT reconstruction artifact suppression method based on a multi-domain feature fusion network. In view of the problem that the reconstruction result of traditional CT scanning under limited-angle conditions is prone to artifacts and structural distortion, thereby affecting the image quality and defect detection accuracy, the present application constructs a multi-domain feature fusion artifact suppression network, takes the limited-angle reconstruction result as input, and realizes artifact suppression and detail recovery through the synergistic effect of the encoder part, the decoder part, the feature enhancement part and the feature conversion part. The present application can obtain high-quality tomographic images under limited-angle conditions, effectively reduces the scanning angle and time of industrial CT detection, improves the imaging clarity and reliability without increasing the radiation dose, is suitable for industrial detection of complex structure workpieces, and has important industrial application value.