41 results about "Cone beam ct" patented technology

The invention provides a cervical cancer self-adaptive radiotherapy assessment decision method and device, and relates to the technical field of medical artificial intelligence, and the method comprises the steps: obtaining a cone beam CT image and a plan CT image before radiotherapy of a patient to be subjected to radiotherapy on the day of radiotherapy, and extracting the structural quantitative features of the images; the method comprises the following steps: calculating a difference value of structured quantitative characteristics between a cone beam CT image on the day of radiotherapy and a plan CT image before radiotherapy to obtain multi-dimensional geometric change characteristics; and inputting the multi-dimensional geometric change features, the vectorized representation of the predetermined key region of the cone beam CT image and the clinical text information into a pre-trained clinical large language model, and outputting a self-adaptive radiotherapy demand tag. The problem that the prior art depends on manual analysis, and it is difficult to compare the change characteristics of the CT image between the radiotherapy day and the plan before radiotherapy to automatically analyze whether self-adaptive radiotherapy is executed on the radiotherapy day is solved.

The invention discloses a four-dimensional cone beam CT (Computed Tomography) reconstruction method based on an anatomical prior constraint diffusion model, which mainly solves the problem of poor quality of a reconstructed image in the prior art, and adopts the implementation scheme that the method comprises the following steps: acquiring CT original full-projection data of a batch of patients, and carrying out sparse sampling on the CT original full-projection data; performing data set division and reconstruction on the original full projection data and the sparse projection data to obtain a reference true value and a low-quality CT image containing a large number of artifacts; preliminarily enhancing the CT image containing a large number of artifacts by using the pre-trained ResViT network to obtain a CT image without artifacts; segmenting the CT image without artifacts by using a body segmentation network to obtain anatomical information of each organ; constructing a four-dimensional cone beam CT motion compensation reconstruction model based on anatomical prior constraints, and training and verifying the four-dimensional cone beam CT motion compensation reconstruction model; and inputting the tested data into the trained reconstruction diffusion model to obtain a reconstruction result. According to the method, artifacts of sparse cone beam CT in a specific organ area can be thoroughly eliminated, the reconstructed image is clear in details, and the method can be used for tracking and positioning tumor movement caused by respiration.

The invention discloses a four-dimensional dynamic image guided dose optimization system for tumor radiotherapy, and belongs to the technical field of medical imaging and radiotherapy. The system comprises a real-time image acquisition module, a dynamic anatomical model construction module, an organ deformation prediction module, a motion compensation engine, a four-dimensional dose accumulation calculation module, a self-adaptive treatment plan generation module and a dose delivery control module. A patient-specific four-dimensional dynamic anatomical model is constructed based on a deep neural network, an autoregression algorithm is adopted to predict organ motion trails, motion compensation parameters are calculated in real time, cumulative dose distribution considering tissue deformation is accurately calculated, a treatment plan is automatically adjusted, and dose delivery with millimeter-level precision is achieved. According to the system, the target area coverage deviation is reduced by 62%, the normal tissue irradiation dose is reduced by 37%, and the precision and safety of thoracic and abdominal tumor radiotherapy are remarkably improved.

Based on the traditional calibration method, a phantom method for calibrating the rotation center and SOD of the cone beam CT with high precision is provided, which is simple and efficient to improve the calibration precision of the parameters, the CT geometric parameters are calibrated by using the traditional method initially, after the calibration is completed, the steel needle phantom is used for CT scanning, image reconstruction, and the reconstructed image is post-processed, the rotation center and the distance from the ray source to the rotation center (SOD parameter) are fine-tuned, so that the imaging section of the steel needle obtained is small, the steel needle section characteristics are met, the center area is not distorted, and the distance between the steel needles meets the actual steel needle spacing.

The present invention relates to an apparatus (10) for estimation of Hounsfield unit values for voxels of a 3D cone beam CT image, the apparatus comprising: —a processing unit (20); and —an output unit (30). A 3D cone beam CT image comprises voxels with associated attenuation coefficient values. The processing unit is configured to calculate a histogram of at least some of the voxels of the 3D cone beam CT image representing a number of voxels having specific attenuation coefficient values or specific ranges of attenuation coefficient values. The processing unit is configured to identify a specific attenuation coefficient value or specific range of attenuation coefficient values associated with a first feature representative of a part of the 3D cone beam CT image, wherein the first feature is air or soft tissue or bone, and wherein the identification comprises utilization of the histogram. The processing unit is configured to determine an attenuation value to Hounsfield Unit converter, wherein the determination of the attenuation value to Hounsfield Unit converter comprises utilization of a correlation between the specific attenuation coefficient value or specific range of attenuation coefficient values associated with the first feature with a Hounsfield Unit for the first feature. The processing unit is configured to transform attenuation coefficient values of voxels in the 3D cone beam CT image to Hounsfield Units based on the attenuation value to Hounsfield Unit converter. The output unit is configured to output information relating to Hounsfield units of voxels of the 3D cone beam CT image.

The invention discloses an image reconstruction method, electronic equipment, a storage medium and a product, relates to the technical field of medical treatment, and is used for optimizing an image reconstruction effect and reducing the influence of shielding artifacts. The method comprises the following steps: acquiring a cone beam CT projection image shielded by a light beam blocking array; light beam blocking substances on the light beam blocking array are asymmetrically arranged about the first axis; the first axis is parallel to a rotating shaft of the cone beam CT and passes through a beam center in a cone beam CT projection image; reconstructing the cone beam CT projection image based on the symmetric projection points and the shadow points in the cone beam CT projection image to obtain a reconstructed image; the symmetric projection points are symmetric points of shadow points in the cone beam CT projection image.

The invention relates to a head positioning device and an oral cavity cone beam CT system, and relates to the technical field of medical instruments. The device comprises a forehead structure used for supporting the forehead of a patient and serving as a reference for connecting the device with an external frame; the supporting structure is connected to the forehead structure and used for providing vertical supporting and adjusting functions; the locking structure is mounted at the top of the supporting structure and used for applying constraining force to the head of the patient from the upper portion or the side portion; wherein the forehead gear structure, the supporting structure and the locking structure work together to achieve adjustable fixing of the head of a patient. Through cooperative work of the three parts of structures, multi-dimensional adjustment and precise fixation of the head of a patient can be achieved, pressure is effectively dispersed, local indentation and discomfort are avoided, meanwhile, the stability of a positioning reference is ensured, and the image quality is improved.

The invention relates to a geometric parameter estimation method for cone-beam CT, belongs to the technical field of cone-beam computed tomography, and solves the problems of high cost and low efficiency of a technical scheme for determining geometric parameters of cone-beam CT in the prior art. The geometric parameter estimation method comprises the following steps: extracting same preset sampling lines from projection images at all projection angles to obtain sinograms corresponding to all the preset sampling lines; determining a first transverse offset of each preset sampling line according to the sinogram corresponding to each preset sampling line, and performing linear fitting based on the first transverse offset of each preset sampling line to obtain a torsion angle of the cone beam CT; and performing rotation correction on the projection images at each projection angle by using the torsion angle of the cone beam CT, extracting a sinogram corresponding to the center line from the projection images at each projection angle after rotation correction, and taking the transverse offset of the center line as the transverse offset estimation value of the cone beam CT. And the geometric parameters of the cone beam CT can be quickly estimated.

The application provides an orthodontic tooth movement monitoring method and system based on wax occlusion records, which comprises the following steps: obtaining an intraoral scanning model and a cone beam CT tooth model at time T0, superimposing the two models to obtain a complete model of each tooth containing a tooth crown and a tooth root; obtaining a wax occlusion record at time T N , optically scanning the wax occlusion record to obtain a three-dimensional digital model of the occlusion record and uploading the three-dimensional digital model; matching the occlusion pits of the digital model of the occlusion record with the occlusal surfaces of the complete model of each tooth to restore a tooth position model at time T N ; superimposing the tooth position models at times T0 and T N , and establishing a local three-dimensional coordinate system for each tooth; calculating three-dimensional movement data of the teeth; and a doctor remotely monitors the tooth movement of a patient with high accuracy by obtaining accurate three-dimensional data of the tooth position changes, provides reliable data for subsequent correction, and guides the next treatment of the patient.

The invention provides a glioma image segmentation method and system based on multi-feature fusion, and relates to the technical field of medical image processing, and the method comprises the steps: carrying out the preprocessing of multi-modal image data, and obtaining the spatial alignment multi-modal image data; based on the spatially aligned multi-modal image data, respectively extracting texture and metabolism characteristics of a preoperative image, gray gradient and morphological characteristics of an intra-operative cone beam CT image and micro texture characteristics of an intra-operative optical coherence tomography image; fusing the morphological characteristics of the intra-operative cone beam CT image and the microscopic texture characteristics of the intra-operative optical coherence tomography image, and constructing a multi-modal spatial characteristic field; based on the multi-modal spatial feature field, determining a spatial assessment origin, a main assessment axis and an auxiliary assessment axis, and defining a dynamic spatial assessment sector accordingly; and arranging a series of spatial feature observation points in the dynamic space evaluation sector. According to the method, feature reliability quantification can be realized, so that adaptive precise feature fusion is completed, and the glioma subregion segmentation precision is improved.

The invention discloses a cone-beam CT arterial phase automatic scanning method and system based on forward projection, and relates to the technical field of medical image.The method comprises the steps that low-dose cone-beam CT pre-scanning is conducted on a target area when a contrast agent is not injected, a three-dimensional image is reconstructed, a to-be-monitored anatomical structure is selected on the three-dimensional image to form a three-dimensional area of interest, and the three-dimensional area of interest is obtained; the method comprises the following steps of: performing forward projection on a three-dimensional region of interest based on cone beam CT geometric parameters to obtain a two-dimensional monitoring region template corresponding to each rack angle, acquiring a real-time perspective image sequence in a contrast agent injection process, calling the corresponding two-dimensional monitoring region template for each frame of image to calculate a monitoring signal, acquiring a baseline value before contrast, calculating a difference value, and acquiring a real-time perspective image sequence; when the difference value reaches a preset threshold value, a trigger signal is output to start arterial phase cone beam CT scanning. Through three-dimensional pre-scanning targeted forward projection and real-time threshold monitoring, the arrival of a target focus contrast agent is accurately judged, the accuracy of the imaging opportunity in the arterial phase is improved, and the radiation dose is reduced.

The invention discloses an oral cavity cone beam CT-oriented central incisor and nasal palate neural tube structure pair segmentation method, which is applied to the technical fields of medical image processing, artificial intelligence and oral medicine, and aims at solving the problem that in the prior art, when a typical large-structure and small-tubular structure pair task of'central incisor and nasal palate neural tube 'is carried out, the segmentation efficiency is high. And a systematic method for joint segmentation, structure-to-geometric relationship constraint and structure-to-evaluation indexes is lacked. According to the method, a decoder and a boundary enhancement decoding branch are shared, and when the central incisor and the nasal palate neural tube are segmented, geometric constraints and special indexes oriented to structural pairs of the central incisor and the nasal palate neural tube are introduced; while the segmentation precision of the central incisor tooth is kept, the segmentation quality of the nasal palate neural tube is remarkably improved, the geometric consistency of the central incisor tooth and the nasal palate neural tube in a three-dimensional space is enhanced, and clinical indexes such as the safe distance between the root tip and the neural tube calculated based on the segmentation result are more reliable.

The application discloses a cone beam CT geometry correction method suitable for irregular tracks, adopts a new optimization constraint iteration method based on a back projection model to solve geometry parameters under each projection view, and most of existing correction methods all assume that the internal geometry relation of a reference point in a phantom is accurate and known, and rarely deeply study whether the phantom precision is suitable for the correction model. Through the disclosure of the application scheme, the correction method is a high-noise robust correction method, and high-precision correction can be realized even when the resolution of a system to be calibrated is twice that of a phantom measurement system.

The application discloses a kind of based on optical flat panel cone beam CT imaging component precision installation and method, including horizontal plate, the upper and lower ends of the inside of the horizontal plate are fixedly installed with mark card plate, the right end of the inside of the horizontal plate is fixedly installed with fixed plate, the upper and lower ends of the inside of the fixed plate are fixedly installed with driving rod, the inside of the driving rod is fixedly installed with light projector, the left end of the fixed plate is fixedly installed with detection plate, the upper and lower ends of the inside of the detection plate are fixedly installed with electric capacity device.One kind of based on optical flat panel cone beam CT imaging component precision installation and method, by being fixedly installed in the inside of fixed plate before installation and adjustment with light projector, then again fixedly installing detection plate in the inside of horizontal plate, finally cooperate with the light of light projector and judge whether it can be from one end of detection plate to the other end, to judge whether light projector is located on the center line of horizontal plate, to reach the effect of convenient adjustment level.

The application discloses a kind of upper and lower jaw alveolar arch coordination analysis method based on oral cone beam CT, specific steps are as follows: collecting patient cone beam examination data, it is exported as DICOM format, three-dimensional reconstruction is carried out using software;Head position calibration is carried out in software, and three-dimensional reference plane is established;Four quadrant of dental arch is positioned and marked, and four quadrant first molar impedance center point is positioned;Determine alveolar arch measurement plane;Determine four quadrant alveolar arch width measurement mark point;Mark point is projected to the same coronal reference plane, and is connected to form upper and lower jaw alveolar arch width coordination angle respectively, and the angle of upper and lower jaw alveolar arch width coordination angle is measured respectively;According to the angle of upper and lower jaw alveolar arch width coordination angle, whether the upper and lower jaw alveolar arch coordination is judged.The angle of measured double jaw alveolar arch width coordination angle can more accurately reflect the position relationship of upper and lower jaw first molar alveolar arch in horizontal direction;It has guiding significance to judge whether left and right alveolar arch is symmetrical.

The invention relates to the technical field of medical image processing, provides a target focus identification method and system based on a medical image, and solves the problem that focus identification precision is limited and unstable. The method comprises the following steps: acquiring a cone beam CT image and reference grayscale data of a mandible before an oral implantation operation; enhancement processing is carried out through a self-adaptive histogram equalization algorithm with metal artifact reduction and contrast limitation, and an enhanced image is obtained; extracting a three-dimensional gray histogram of the implanted target area to calculate gray skewness and gray kurtosis, and extracting a texture feature set; performing principal component analysis on the texture feature set to obtain principal component features, and splicing the principal component features with gray skewness and gray kurtosis into a fusion feature vector; and analyzing the vector by adopting a density peak value clustering algorithm, mapping a result to an anatomical partition, and performing Z-score inspection in combination with reference gray data to identify a bone focus area. According to the invention, accurate and automatic positioning of the focus can be realized.

The present invention provides a method of matching data, which is performed by an apparatus for matching data, the method including synchronizing acquisition time points of cone beam computed tomography (CBCT) data and 3D scan data, conforming coordinate systems of the CBCT data and the 3D scan data, constructing a 3D scan image in which a motion is corrected by matching depth maps created each time the 3D scan data are acquired, and constructing a CBCT 3D image in which the motion is corrected from the CBCT data by applying motion information acquired by matching the depth maps.

The application discloses a kind of for the correction method and device of cone beam CT system geometry parameter error, method includes: acquisition projection image projected on flat panel detector;Obtain the geometry parameter error of cone beam CT system;By the translation error of transverse and longitudinal of the plane where flat panel detector is, correct projection image, obtain first correction image;The normal rotation error of the plane where flat panel detector is and the distance error between flat panel detector and ray source are corrected to first correction image, obtain second correction image;For second correction image, respectively correct along the rotation error of transverse and longitudinal of the plane where flat panel detector is, obtain third correction image;The distance error of third correction image's rotating table and ray source is corrected, obtain the ideal image of geometry parameter error correction.By geometry parameter error correction projection image, without adjusting the position of cone beam CT system device, it is easy to calculate, effectively eliminate the influence of system error on image three-dimensional reconstruction.

The application relates to the technical field of medical image processing, and provides a target lesion identification method and system based on medical images, which solves the problems of limited and unstable lesion identification precision. The method comprises the following steps: acquiring a cone beam CT image of a mandible before oral implantation and reference gray data; performing metal artifact reduction and adaptive histogram equalization algorithm enhancement processing with limited contrast to obtain an enhanced image; extracting a three-dimensional gray histogram of an implant target area to calculate gray skewness and gray kurtosis, and extracting a texture feature set; performing principal component analysis on the texture feature set to obtain principal component features, and splicing the principal component features with the gray skewness and the gray kurtosis into a fusion feature vector; analyzing the vector by using a density peak value clustering algorithm, and mapping the result to an anatomical partition, and performing Z-score testing in combination with the reference gray data to identify a bone lesion area. The application can realize accurate and automatic positioning of a lesion.

This invention relates to the field of image processing technology and discloses a method and apparatus for processing projection data in cone-beam CT half-fan scanning. The method includes: acquiring raw projection data obtained from cone-beam CT half-fan scanning; inputting a first diagonal projection data pair from the raw projection data into a pre-trained artificial intelligence model to obtain a pair of synthetic projection data, wherein the size of the pair of synthetic projection data is larger than the raw projection data and equivalent to the projection data obtained from full-fan scanning. This invention, through AI, learns complete projection data from two basic diagonal (approximately 180° interval) projection data, obtaining projection data equivalent to that acquired by a large-size detector, thereby increasing the scanning field of view of cone-beam CT.

The invention discloses an industrial cone beam CT scattering correction method, and relates to the technical field of image processing, and the method comprises the steps: processing a correction plate for scattering correction; placing the correction plate in an industrial cone beam CT system, placing the correction plate between an X-ray source and a rotary table, starting the system and carrying out 360-degree scanning to obtain a group of complete projection images with correction plate information; based on the collected projection information, processing information of a correction plate shielding area in the projection image, and extracting a scattering signal set; processing the information of the area which is not shielded by the correction plate to obtain an original projection image set; the corrected image is used, a step-by-step reconstruction and image fusion method based on an Fdk reconstruction algorithm is used for reconstruction, data changes introduced by the positions of the lead bars on the left side and the right side are compensated, and a corrected CT image is obtained; according to the method, the collection time is shortened by half, the scattering correction efficiency is improved, and the reconstructed image quality of the scattering correction result is effectively improved.

The invention discloses a cone-beam CT image multi-segment registration and splicing method and device, complete anatomical images of organs can be acquired, and the method comprises the following steps: acquiring volume data of a plurality of cone-beam CTs through movement of a bed body; searching a reference image layer corresponding to registration of the previous data body; determining a to-be-registered image layer of the next data body; calculating a transformation matrix between the to-be-registered image layer and the reference image layer; performing mapping correspondence on the next data body according to the obtained transformation matrix; combining adjacent sequences; and so on, a final splicing sequence is obtained. Cone beam CT acquisition is adopted, a plurality of cone beam CT reconstruction sequences can be set, a bed body can be automatically translated, the adjacent cone beam CT sequences are subjected to registration and splicing processing, the CT scanning width is expanded, and the completeness and continuity of cone beam CT reconstruction organs are guaranteed. Aiming at the problem that the scanning range of traditional cone beam CT equipment is limited, the cone beam CT scanning width is expanded, and the completeness and continuity of CBCT reconstruction organs are guaranteed.

The invention relates to the technical field of CT image reconstruction, and discloses a cone beam CT scanning image rapid reconstruction system and method based on deep learning, and the system comprises a dual-ray generation module, a scanning module, a deep learning reconstruction module, and a result output module. The dual-ray generation module comprises two ray generators, a beam outlet of one ray generator is provided with a 0.1 mm low atomic number material aluminum to filter an X-ray ultra-low energy part, and the other beam outlet is provided with a 0.1 mm high atomic number material copper to attenuate the X-ray low energy part. According to the method, the dual-energy-spectrum projection data is obtained through the dual-ray generator, the tissue linear attenuation coefficient is solved through fitting by taking PMMA and aluminum as base materials, background interference is corrected in combination with air reference data, the error of the reconstructed CT value in the soft tissue area is smaller than or equal to + / -10 HU, the error of the reconstructed CT value in the cortical bone area is smaller than or equal to + / -30 HU, and compared with traditional CBCT, the method is more accurate, and a reliable foundation is laid for preventing power ratio calculation.

The application discloses an orthodontic scheme design auxiliary method based on tooth movement digital twin, relates to the technical field of orthodontic auxiliary, and comprises the following steps: acquiring patient oral cone beam CT data and tooth crown surface three-dimensional point cloud data, and constructing a three-dimensional geometric model of teeth-periodontal membrane-alveolar bone; discretizing the three-dimensional geometric model into a finite element grid, respectively giving periodontal membrane viscoelastic parameters, alveolar bone gray-mechanical mapping parameters and tooth linear elastic constants according to patient age, periodontal biotype and CT gray value, and forming an individualized tooth movement digital twin; determining a target displacement vector in the individualized tooth movement digital twin, calculating a correction force vector and a support requirement index, and assisting orthodontic scheme design according to the support requirement index. The application can effectively improve the accuracy, predictability and individualization level of orthodontic scheme design, reduce experience dependence and optimize overall correction effect.

The application provides a prior image constraint-based adaptive step cone-beam CT limited-angle reconstruction algorithm, effectively removes limited-angle artifacts in a cone-beam CT image under a small-angle scanning range, and meets the image-guided registration task in a radiotherapy plan. The application first generates simulated projections of a planning CT according to the same scanning range, then reconstructs a planning CT limited-angle image and a cone-beam CT limited-angle image by using a FDK algorithm, then obtains a transformation matrix of the planning CT by using rigid registration, applies the transformation matrix to the planning CT to obtain a prior image, and finally reconstructs the cone-beam CT image by combining a total variation iteration with a mean square error of the cone-beam CT image and the prior image as a regularization term. The application greatly shortens the cone-beam CT scanning angle of the registration task and improves the registration efficiency.

The invention relates to the technical field of oral rehabilitation, in particular to an abutment crown integrated manufacturing method which comprises the following steps: acquiring intraoral scanning data and cone beam CT data, performing registration to obtain a unified patient coordinate system, and calculating a target soft tissue curved surface and a tolerance parameter set based on an alveolar ridge form, mucous membrane thickness and an implant attitude; solving an abutment main body, a crown body and a plastic neck section at the same time under the same coordinate system, dividing plastic neck section patches, and setting a propelling direction, an allowable propelling amount and a limiting groove for each patch; an integrated main body piece with a limiting groove and a plastic neck sleeve are machined, and propelling information is marked; after installation, the face sheet is shaped or retreated in a staged and directional upheaval mode according to marks, so that the gingival margin and the gingival papilla are gradually shaped, a neck margin closed contact band is established, and controllable individualized soft tissue shaping is achieved.

This invention relates to the field of geometry and drift correction technology for cone-beam CT systems, specifically providing a device and method for synchronously correcting the geometric position and focus drift of a cone-beam CT system. The device includes a correction phantom, a radiation source unit, a moving unit, and a detection unit. The phantom consists of a transparent pressure plate and positioning steel balls, positioning steel bars, and a cross steel bar sandwiched between them. The positioning steel balls are arranged in a square area, with a pair of vertical sides arranged at equal and non-equal intervals to provide angular identification features. The positioning steel bars are located in the middle of the horizontal sides, and the cross steel bar is located at the center of the area, with the intersection point serving as the drift measurement reference. This invention, through its integrated phantom design, can simultaneously complete geometric parameter calibration and focus drift measurement in a single scan without moving or replacing the phantom. The correction method integrates algorithms such as elliptical trajectory fitting, feature point matching, and bicubic spline interpolation, enabling efficient and accurate calculation of the dynamic curves of detector position, attitude, and focus drift.

The invention discloses a cone beam CT image reconstruction method and device, equipment and a storage medium. The method comprises the following steps: acquiring limited angle projection data and geometric parameters; inputting the three-dimensional Gaussian kernel parameter into a pre-trained generative model to obtain an initial Gaussian kernel parameter of the three-dimensional Gaussian scene; taking the initial scene as a starting point, carrying out iterative optimization under the constraint of a micro-cone beam CT forward projection model, obtaining a synthetic projection through micro-rendering in each iteration, calculating an error between the synthetic projection and a real projection, updating Gaussian kernel parameters according to the error, and adaptively adjusting the density distribution of Gaussian kernels; and finally, converting the optimized scene into three-dimensional volume data and outputting the three-dimensional volume data. According to the method, strong structure prior initialization is provided through the generative model, and high-quality and high-efficiency reconstruction under the condition of serious data missing is realized in combination with iterative optimization constrained by the physical model and adaptive structure adjustment, so that artifacts are remarkably inhibited, and a clear anatomical structure is recovered.

The invention relates to an image reconstruction method based on cone-beam CT, belongs to the technical field of cone-beam computed tomography, and solves the problem of low quality of a reconstructed image reconstructed according to a projection image of the cone-beam CT in the prior art. The image reconstruction method comprises the following steps: extracting a sinogram corresponding to each preset sampling line; determining a first transverse offset of each preset sampling line according to the sinogram corresponding to each preset sampling line, and performing linear fitting based on the first transverse offset of each preset sampling line to obtain a torsion angle of the cone beam CT; using the torsion angle of the cone beam CT to perform rotation correction on the projection image at each projection angle, and taking the transverse offset of the center line as the transverse offset of the cone beam CT; and reconstructing the target object by combining the projection images of the target object at each projection angle according to the torsion angle and the transverse offset of the cone beam CT to obtain a target reconstruction image. And the quality of the target reconstruction image is improved.

The invention relates to the technical field of cone beam CT system geometry and drift correction, and particularly provides a cone beam CT system geometric position and focus drift synchronous correction device and a measurement method thereof. The device comprises a correction phantom, a ray source unit, a moving unit and a detection unit, the positioning steel balls, the positioning steel bars and the cross-shaped steel bars are clamped between the transparent pressing plates, the positioning steel balls are arranged to form a square area, a pair of vertical edges are arranged at equal intervals and non-equal intervals so as to provide angle identification characteristics, the positioning steel bars are arranged in the middles of transverse edges, and the cross-shaped steel bars are arranged in the middle of the transparent pressing plates. The cross-shaped steel bar is located in the center of the area and takes a cross point as a drift measurement reference. Through the integrated phantom design, geometric parameter calibration and focus drift distance measurement can be synchronously completed in single scanning, and the phantom does not need to be moved or replaced; according to the correction method, elliptic trajectory fitting, feature point matching, bicubic spline interpolation and other algorithms are fused, and the dynamic curve of the position, attitude and focus drift of the detector can be efficiently and accurately calculated.