32 results about "Beam hardening" patented technology

The invention discloses a pole piece surface density measurement method based on a double-index model, which comprises the following steps: firstly, starting an X-ray source, and measuring the ray intensity when a pole piece is not placed; secondly, replacing standard to-be-measured pole pieces with different surface densities, and measuring ray intensity; obtaining mass attenuation coefficients corresponding to different coating surface densities according to an attenuation formula, and performing double-index model correction on the mass attenuation coefficients according to the calibration data; and finally, measuring the intensity of rays passing through the pole piece to be measured, and measuring the surface density of the pole piece according to a ray intensity attenuation model and the calibrated mass attenuation coefficient. According to the method, the surface density of the pole piece is measured by using a method for correcting the quality attenuation coefficient of the pole piece through the double-index model, and compared with a method for directly calibrating the measured ray intensity and the standard surface density value, the problem that the measurement of the surface density of the pole piece coating is affected by X-ray beam hardening and Compton scattering is solved; and the surface density measurement precision of the pole piece is improved.

To provide techniques capable of shorting the time required for calibration.SOLUTION: An embodiment comprises: determining an effective voltage value V1 of a high kV on the basis of energy information of X-rays detected in a first sub-region of a detector assembly and energy information of X-rays detected in a second sub-region of the detector assembly, when the high kV is applied to an X-ray tube; determining an effective voltage value V2 of a low kV on the basis of energy information of X-rays detected in the first sub-region of the detector assembly and energy information of X-rays detected in the second sub-region of the detector assembly, when the low kV is applied to the X-ray tube; calculating a correction coefficient required to correct beam hardening on the basis of the effective voltage value V1; and calculating a correction coefficient required to correct beam hardening on the basis of an effective voltage value V2.SELECTED DRAWING: Figure 15

The present invention discloses a method for generating a channel spectrum response difference correction table and a channel spacing correction table, a computer program, a computer readable storage medium and a computer tomography device. The method for generating a channel spectrum response difference correction table and a channel spacing correction table includes using parallel projection P paral (k, r) determines the channel position corresponding to the center of the phantom, and calculates the simulated parallel projection and the ideal projection P accordingly sim (k, r), and finally according to the projection difference diff(k, l, r) and the simulated ideal projection P sim (k, r), calculate the channel spectrum response difference correction table t CCR (k, l) and channel spacing correction table t spacing The method, computer program, computer-readable storage medium, and computer tomography device of the present invention for generating a channel spectrum response difference correction table and a channel spacing correction table are not affected by residual beam hardening and can effectively generate ideal projections.

A deep learning segmentation method for asphalt mixture CT images relates to the technical field of aggregate image segmentation. CT images of asphalt mixtures are collected and voids are removed. Image equalization is performed using a gamma beam hardening correction algorithm. A filter window is selected, and an adaptive bilateral filtering denoising algorithm based on local image information is used to denoise the image. The U-Net model is improved, with the Inception convolution module replacing the standard convolution operation and residual connections replacing skip-layer connections. A spatial attention mechanism is introduced, and a joint loss function is used. Image samples are selected, aggregates are labeled, and data augmentation is used to increase the sample size to form a training set for model training. After training, this set is used to segment other images. By equalizing and denoising CT images and using the improved U-Net model, the method can achieve accurate segmentation of aggregate-mortar boundary information, avoiding aggregate adhesion issues.

The application discloses a kind of simultaneously sparse angle CT reconstruction and metal artifact high-precision correction method, belong to medical imaging field, specifically: simulate the projection data under the influence of beam hardening under sparse angle sampling, obtain sparse sampling and the sinogram of containing metal trace;Interpolation processing is carried out to sparse sinogram, and the sinogram is obtained as the initial sinogram of sinogram domain;According to the additive property of artifact, preliminarily decompose the CT image containing a large number of artifacts, obtain the initial estimated image of image domain and the initial artifact image of artifact domain;A multi-domain optimization model is established, and the constructed multi-domain optimization problem is alternately iterated minimization solution;Iterative update is carried out to sinogram domain, image domain and artifact domain respectively;The high-precision CT image of reconstruction is output.The application can simulate the sinogram containing metal trace and sparse obtained by CT imaging equipment to carry out simultaneously sparse angle CT reconstruction and metal artifact correction, and the reconstruction effect is good and correction precision is high.

The present application relates to a scatter model derivation apparatus, a radiation image processing apparatus, a method thereof, and a storage medium. The apparatus includes: a reference image acquisition unit configured to acquire at least one reference image representing a reference object having different thicknesses, the at least one reference image being obtained by radiographing the reference object with a radiation detector in a state in which the reference object is interposed between the reference object and the radiation detector; a reference object thickness and radiation attenuation coefficient relationship derivation unit configured to derive a relationship between a thickness of the reference object and a radiation attenuation coefficient of the reference object corresponding to an energy characteristic of the radiation and reflecting an influence of beam hardening caused by the reference object and an object; a primary ray component derivation unit configured to derive a primary ray component corresponding to the thickness of the reference object included in the reference image based on the relationship between the thickness of the reference object and the radiation attenuation coefficient of the reference object; a scatter ray component derivation unit configured to derive a scatter ray component corresponding to the thickness of the reference object included in the reference image based on a difference between the reference image and the primary ray component; and a scatter model derivation unit configured to derive a scatter model representing a relationship between the thickness of the reference object and a proportion of the scatter ray component with respect to the primary ray component.

The present invention pertains to a method and system for image reconstruction for computer tomography, in particular for reducing beam hardening effects, wherein image reconstruction is performed based on the generalized Lambert-Beer law for poly-chromatic sources.

The multi-modal imaging apparatus and method include a rotatable gantry system with multiple radiation sources including different energy levels (e.g., kV and MV). Fast slip ring technology and spiral scanning allow data from multiple radiation sources to be combined or utilized to generate improved images and workflows, including improved images and workflows for IGRT. Features include improving the accuracy of spatial registration between corresponding image sets to allow more accurate radiation therapy irradiation, reducing image artifacts (e.g., scatter, metal and beam hardening, image blur, motion, etc.), and utilizing dual energy imaging (e.g., for material separation and quantitative imaging, patient settings, online adaptive IGRT, etc.).

A correction apparatus reduces calculation costs for correcting artifacts due to a beam hardening effect in reconstructing a CT image by correcting an artifact due to a beam hardening effect caused in reconstructing a CT image. The correction apparatus includes processing circuitry configured to acquire an incident X-ray distribution, acquire a linear absorption coefficient model representing an energy dependency of a linear absorption coefficient by a scale factor including a parameter, acquire a projection image, and correct the projection image using the incident X-ray distribution and the linear absorption coefficient model.

The present application relates to an industrial CT beam hardening correction method, comprising: taking the jth row of pixel points in each circumferential DR image to form a projection image; CT reconstruction is carried out on the projection image to obtain a tomographic image; a homogeneous material region in the detected sample is selected in the tomographic image; a function relationship formula corresponding to the minimum standard deviation of all corrected pixel values in the region is obtained, and the obtained function relationship formula is recorded as the optimal function relationship formula; the pixel value of each pixel point in each circumferential DR image is substituted into the optimal function relationship formula to obtain the corrected pixel value of each pixel point, and then the DR image after beam hardening correction is obtained; finally, the DR image after beam hardening correction is reconstructed to obtain the corrected CT image of the detected sample. The method does not need additional processing of contrast test blocks or test samples with known structures, the process is simple, especially for homogeneous material parts, the full-automatic interactive link can be realized, and the image quality and efficiency of industrial CT are improved.

The invention discloses a method for generating a channel spectral response difference correction table and a channel spacing correction table, a computer program, a computer readable storage medium and computed tomography equipment. The method for generating the channel spectral response difference correction table and the channel spacing correction table comprises the following steps: determining a channel position corresponding to the center of a motif by using parallel projection Pparal (k, r), calculating simulation parallel projection # imgabs0 # simulation ideal projection Psim (k, r) according to the channel position, and finally calculating the channel spectral response difference correction table tCCR (k, l) and the channel spacing correction table tspacing (k, l) according to the projection difference diff (k, l, r) and the simulation ideal projection Psim (k, r). According to the method for generating the channel spectral response difference correction table and the channel spacing correction table, the computer program, the computer readable storage medium and the computed tomography equipment, the influence of beam hardening residues is avoided, and the ideal projection can be effectively generated.

The present application belongs to the technical field of printed circuit board manufacturing quality detection, and particularly relates to a PCB hole defect detection method based on 2D line scanning and 3D-X ray fusion. The method drives the to-be-detected PCB board to perform 2D line scanning through a motion platform, obtains the whole-board 2D image and the physical coordinates of each hole site, extracts the hole ring profile matching degree, the hole inner gray scale statistical features and the hole diameter deviation, and determines the to-be-reviewed hole. According to the physical coordinates, the projection image is collected, 3D data is reconstructed after beam hardening correction and material weighted iteration correction, 2D image and 3D data are registered based on the unified coordinates, the material level is distinguished through gray scale-attenuation coefficient conversion, the adaptive threshold edge detection is performed on the hole wall development, the internal defects such as hole wall cracks and copper plating cavities are extracted, the defect classification and quantization are completed by fusing the 2D surface defect attributes and 3D internal defect attributes, the detection result and quality evaluation report are output, and nondestructive detection of the hole site is realized.

The invention discloses a scattering and hardening artifact eliminating method, system, device and equipment for turbine blade CT imaging and a medium, and relates to the field of aero-engine turbine blade CT detection. The method comprises the following steps: acquiring an original multicolor projection image and a scattering correction projection image of the turbine blade before and after placing a grating correction plate by using a cone beam CT (Computed Tomography) system; the aluminum strips arranged on the grating correction plate at intervals have inclined angles; according to the two images, determining a multi-color projection image for scattering removal of the turbine blade, and further utilizing a beam hardening correction model to obtain a single-color projection image of the turbine blade; weighting the monochromatic projection image and the scattering-removed multicolor projection image by adopting a weighted compensation enhancement correction algorithm which introduces a trade-off factor to obtain a projection image of which the cup artifact is eliminated; and finally, performing three-dimensional reconstruction by adopting a filtered back projection algorithm to obtain a projection correction slice image of the turbine blade. The method can effectively eliminate cup-shaped artifacts caused by scattering and hardening, and improves the image reconstruction quality.

A dispersive metal artifact removal method based on an energy spectrum estimation technology belongs to the field of CT imaging technology and artifact removal, and comprises the following steps: initializing an X-ray source target material and element excitation characteristic energy; a step-shaped phantom is placed; starting a ray source, and obtaining step phantom projection data; reversely estimating an X-ray source energy spectrum curve by using a conjugate gradient method; the phantom is removed, and the measured workpiece is scanned; and performing energy spectrum correction on a projected image obtained by scanning, performing reconstruction by using an FDK algorithm, and finally outputting a high-quality CT reconstruction image without metal artifacts. According to the method, the metal artifact phenomenon caused by beam hardening and photon starvation can be effectively reduced, operation is easy and convenient, redundant image post-processing algorithms are not needed, and the CT reconstruction quality can be remarkably improved.

Various systems and methods are provided for an integrated filter assembly including at least one bowtie filter and at least one beam hardening filter mounted on a carriage. In one embodiment, an imaging system may include a first carriage including at least one beam hardening filter and at least one bowtie filter, a second carriage including at least two additional bowtie filters, and a carriage driving system for moving the carriages to selectively position the at least one beam hardening filter and one of the bowtie filters in a path of an X-ray beam. The at least one beam hardening filter may overlap with at least one of the bowtie filters.

Methods and apparatus are described herein to determine an effective voltage value V1 of a high kV on the basis of energy information of X-rays detected in a first sub-region of a detector assembly and energy information of X-rays detected in a second sub-region of the detector assembly, when the high kV is applied to an X-ray tube, determine an effective voltage value of a low kV on the basis of energy information of X-rays detected in the first sub-region of the detector assembly and energy information of X-rays detected in the second sub-region of the detector assembly, when the low kV is applied to the X-ray tube, calculate a correction coefficient required to correct for beam hardening on the basis of an effective voltage value, and calculate a correction coefficient required to correct for beam hardening on the basis of an effective voltage value.

The application provides a kind of industrial CT scattering and beam hardening coupling artifact suppression method based on deep learning, belongs to the field of industrial CT image processing, for the problem that coupled artifacts cannot be accurately separated and corrected in industrial CT imaging, a beam hardening, scattering coupling artifact model based on real CT image artifact features is constructed, a simulated image and an actual image are mixed to construct a data set by a coupled model representation equation, and artifact suppression and image enhancement are completed by a long-short connection, structure doublet improved neural network, effectively removing multiple types of coupled artifacts and noise, this method is suitable for coupled artifact suppression of any complex structure actual CT image, and the practicability and generality of the method are better.

The present application relates to the technical fields of industrial CT measuring machine, especially to a traceable industrial CT forest ball calibrator device, comprising a base and measuring needles, the measuring needles in the device have high rigidity, when the calibrator device is traced by using a coordinate measuring machine, contact measurement is needed for each standard ball of the measuring needles to obtain the spatial coordinates of each standard ball of the calibrator device, the high rigidity of the measuring needles can reduce the deflection change of the measuring needles in the measurement process, which can be ignored compared with the test accuracy, and the reliability and repeatability of the traceability are ensured, and the projection of the standard ball of the first layer of step measuring needles in the front view direction does not overlap with the projection of the third layer of step measuring needle support seats in the same direction; the first layer and the second layer of steps have 8 and 4 threaded holes respectively, the threaded hole positions are staggered by 30°, so as to reduce the stacking number of the calibrator device in the front view direction projection, the rays attenuate on the path, and the beam hardening is reduced.

The present invention pertains to a method and system for image reconstruction for computer tomography, in particular for reducing beam hardening effects, wherein image reconstruction is performed based on the generalized Lambert-Beer law for poly-chromatic sources.

Disclosed herein are methods for reducing beam-hardening artifacts in CT imaging using a mapping operator that comprises a hybrid spectral model that incorporates air scan X-ray intensity data acquired at two different effective mean energies. In one variation, the air scan X-ray intensity data acquired during a calibration session is combined with an ideal spectral model for each X-ray detector to derive the hybrid spectral mode. A mapping operator based on the hybrid spectral model is used to correct beam-hardening artifacts in the acquired CT projection data. In some variations, the mapping operator is a lookup table of monochromatic (corrected) projection values, and the acquired CT projection data is used to calculate the index of the lookup table entry that contains the corrected projection value that corresponds with the acquired CT projection data.

The embodiment of the invention provides a CT scanning system error correction method and device, equipment and a medium. The CT scanning system error correction method comprises the steps that first attenuation data of a target motif based on multi-energy X rays at different rotation angles are determined; determining a measurement attenuation path of the X-ray passing through the target die body at different rotation angles; determining second attenuation data of the single-energy X-ray passing through the target motif at different rotation angles according to a measurement attenuation path and a conversion factor between the attenuation data and the attenuation path under the single-energy X-ray; determining first target attenuation data and second target attenuation data under the target measurement attenuation path according to the first attenuation data and the second attenuation data; and determining a mapping function between the single-energy X-ray attenuation data and the multi-energy X-ray attenuation data in different target measurement attenuation paths according to the first target attenuation data and the second target attenuation data in the target measurement attenuation paths. Beam hardening correction is realized, and detector response consistency correction is also realized.

Nondestructive evaluation (NDE) of objects can elucidate impacts of various process parameters and qualification of the object. Computed tomography (CT) enables rapid NDE and characterization of objects. However, CT presents challenges because of artifacts produced by standard reconstruction algorithms. Beam-hardening artifacts especially complicate and adversely impact the process of detecting defects. By leveraging computer-aided design (CAD) models, CT simulations, and a deep-neutral network high-quality CT reconstructions that are affected by noise and beam-hardening can be simulated and used to improve reconstructions. The systems and methods of the present disclosure can significantly improve the reconstruction quality, thereby enabling better detection of defects compared with the state of the art.

Provided is a technique capable of shortening the time taken for calibration. [Solution] When a high kV is applied to an X-ray tube 104, an effective voltage value V1 of the high kV is determined on the basis of energy information of X-rays detected in a first sub-region 109B of a detector assembly 109 and energy information of X-rays detected in a second sub-region 109A of the detector assembly 109; determining an effective voltage value V2 of the low kV on the basis of the energy information of the X-rays detected in the first sub-region 109B of the detector assembly 109 and the energy information of the X-rays detected in the second sub-region 109A of the detector assembly 109 when the low kV is applied to the X-ray tube 104; calculating a correction coefficient 75 required for beam hardening correction on the basis of the effective voltage value V1; and calculating a correction coefficient 76 required for beam hardening correction on the basis of the effective voltage value V2.

The present invention pertains to a method and system for image reconstruction for computer tomography, in particular for reducing beam hardening effects, wherein image reconstruction is performed based on the generalized Lambert-Beer law for polychromatic sources.

The invention discloses a deep learning segmentation method for an asphalt mixture CT image, and relates to the technical field of aggregate image segmentation. The method comprises the following steps: acquiring a CT image of an asphalt mixture and removing a gap part, completing equalization processing of the image through a gamma beam hardening correction algorithm, selecting a filtering window, performing noise reduction processing on the image by adopting a self-adaptive bilateral filtering noise reduction algorithm based on local information of the image, improving a U-Net model, and replacing standard convolution operation with an Inception convolution module. Layer skipping connection is replaced by residual connection, a space attention mechanism is introduced, a joint loss function is adopted, image samples are selected, aggregates are labeled, the sample size is increased through data enhancement to form a training set, the training set is used for model training, and the trained training set is used for segmenting other images. By performing equalization and noise reduction processing on the CT image and adopting the improved U-Net model, accurate segmentation of aggregate-mucilage boundary information can be realized, and the problem of aggregate adhesion is avoided.

The application discloses a kind of based on double exponential model pole piece surface density measurement method, comprising: first, the X-ray source is started, the ray intensity when not placing pole piece is measured;Second, replace different surface density standard pole piece to be measured, and measure the ray intensity;Again, different coating surface density corresponding mass attenuation coefficient is obtained according to attenuation formula, and mass attenuation coefficient is corrected according to double exponential model calibration data;Finally, the ray intensity after measuring through the pole piece to be measured, according to the ray intensity attenuation model and the mass attenuation coefficient after calibration, the pole piece surface density measurement can be realized.This application uses the method of double exponential model to correct the mass attenuation coefficient of pole piece to realize the measurement of pole piece surface density, compared with the method of directly calibrating the measured ray intensity and standard surface density value, the problem of the influence of X-ray beam hardening and Compton scattering on pole coating surface density measurement is overcome, and the precision of pole piece surface density measurement is improved.

A computer-implemented method of reducing scatter in an X-ray projection image of an object, the method comprising: generating an initial X-ray projection image of an object with an imaging beam produced by an imaging system; based on a first transmission indicator for the object and on a second transmission indicator for at least one element of the imaging system, selecting a kernel for convolution of the initial projection image; convolving the initial X-ray projection image with the kernel to generate a scatter component of the initial X-ray projection image; and generating a corrected X-ray projection image by removing the scatter component from the initial X-ray projection image.

To realize beam hardening correction capable of improving image quality as compared with a conventional one.SOLUTION: A computer tomography imaging data generation method according to the embodiment acquires a reconstructed image data group, and generates radon space data by transforming the reconstructed image data group into a differential of radon space. The radon space data has a radial sampling pattern in the differential of the radon space. The method inputs the radial space data into a first trained machine learning model to resample the radon space data to generate resampled data. The resampled data has a sampling pattern of cone-beam projection geometry in the differential of the radon space.SELECTED DRAWING: Figure 1

Disclosed are techniques for performing CT beam hardening correction. The CT beam hardening correction includes scanning a phantom to obtain measured projection data of the phantom and calculating corrected projection data of a measured object according to a calculated beam hardening correction factor, measured projection data of the measured object, a corrected projection data of the measured object, and a relationship among expected projection data of a scanned object.

The CT scan system error correction method, device, equipment and medium provided by the embodiments of the present disclosure include: determining first attenuation data of a target phantom based on multi-energy X-rays at different rotation angles; determining the measured attenuation paths of X-rays passing through the target phantom at different rotation angles; determining second attenuation data of mono-energy X-rays passing through the target phantom at different rotation angles according to the measured attenuation paths and the conversion factor between the attenuation data and the attenuation paths under mono-energy X-rays; determining first target attenuation data and second target attenuation data under the target measured attenuation path according to the first attenuation data and the second attenuation data; and determining the mapping function between the mono-energy X-ray attenuation data and the multi-energy X-ray attenuation data under different target measured attenuation paths according to the first target attenuation data and the second target attenuation data under the target measured attenuation path. While beam hardening correction is achieved, detector response consistency correction is also achieved.