CN115980104A - Multi-angle scanning coded hole X-ray diffraction tomography system and imaging method - Google Patents
Multi-angle scanning coded hole X-ray diffraction tomography system and imaging method Download PDFInfo
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Abstract
The application discloses multi-angle scanning coded hole X-ray diffraction tomography system and imaging method, an X-ray source generates cone beam incident X-rays, a slit collimator is utilized to form fan beam incident X-rays, original diffraction X-rays are generated after an object to be imaged is irradiated, then coded diffraction X-rays are formed after a coded hole template, an energy dispersion photon counting detector detects coded diffraction detection signals corresponding to the object to be imaged under a plurality of imaging angles, and an image reconstruction module reconstructs the multi-angle coded diffraction detection signals by utilizing an imaging system accurate model to obtain a diffraction tomography reconstruction result of the object to be imaged. Therefore, the advantage of high spatial resolution of the rotational scanning X-ray diffraction tomography system is combined with the advantage of accelerated acquisition of coded hole imaging, the spatial resolution of X-ray diffraction tomography is improved, the data acquisition time is reduced, and the application of the X-ray diffraction tomography technology in clinical medical diagnosis and material sample analysis is met.
Description
Technical Field
The application relates to the technical field of radiation imaging, in particular to a multi-angle scanning coded hole X-ray diffraction tomography system and an imaging method.
Background
In the past decades, conventional X-ray attenuation imaging has been widely used in medical, security, industrial injury detection, and other fields. The X-ray attenuation imaging has high sensitivity to the atomic number and electron density properties of the material, and can effectively distinguish light materials from heavy materials. However, for different materials with similar elemental compositions, the X-ray attenuation signals are less distinguishable. In 1912, laue proposed that the crystal face of the crystal material can be used as a grating to generate diffraction effect on X-ray, and since then, X-ray diffraction (XRD) has attracted much attention as a material molecule arrangement rule analysis tool. The commercial powder X-ray diffractometer is based on the principle of angular dispersive X-ray diffraction (ADXRD), and is applied to tasks such as quantitative analysis of crystal components. In security inspection scenarios, energy dispersive X-ray diffraction (EDXRD) based security inspection machines have played an important role in flammable liquid detection, explosive crystal powder detection tasks. In recent years, a large number of experiments indicate that XRD has important value in biological sample detection application, and the material indication of XRD has outstanding advantages in the tasks of breast cancer detection, calculus component analysis and meat lean meat percentage analysis.
Despite the powerful material discrimination capabilities of XRD techniques, existing commercial XRD systems do not focus on the spatial distribution information of the diffraction signals and do not maximize the utilization of XRD techniques. In the well-established commercial powder diffractometers, the diffraction signal measured by the system is derived from the full sample area irradiated by incident X-rays, and has no diffraction signal spatial resolution capability. The security inspection EDXRD system is used for parallelly measuring diffraction signals at different spatial positions by matching the front porous collimator and the rear porous collimator, so that material distribution information at different spatial positions is obtained, and the security inspection EDXRD system has preliminary spatial resolution capability. The X-ray diffraction tomography (XRDT) technology refers to a technology for measuring diffraction spectrum at each position in a two-dimensional tomography plane, and is an extension of the XRD technology in a two-dimensional space. The EDXRD system for security inspection adopts a front and a rear multi-pinhole collimators to be matched and positioned, is a primary XRDT system, and has poor spatial resolution which is usually larger than 1cm due to the geometric effect of a small diffraction angle. Meanwhile, a plurality of pinholes of the rear collimator used in the safety inspection EDXRD system block a large amount of Rayleigh scattered photons, the signal utilization rate is low, and the acquisition time is long. Subsequently, an encoding hole technology is introduced into the EDXRD system, and an encoding hole XRDT (CAXRDT) is based on a compressed sensing data acquisition principle, and replaces a multi-pin hole rear collimator of EDXRD with the encoding hole, so that the signal utilization rate is improved by one order of magnitude, the sampling time is also shortened from one hundred second order to tens of seconds, and the spatial resolution of the encoding hole XRDT in the transmission direction is still low. On the other hand, the XRDT system of the rotary scanning adopts the traditional pen beam or fan beam CT scanning mode, and the highest diffraction imaging spatial resolution is realized at present on the basis of Radon transformation theory, and the level of 1mm is easy to achieve. However, in an XRDT system with pen beam rotational scanning, the pen beam translational scanning motion is still required at each rotational view angle, with an overall imaging time in the order of hours. The XRDT system of fan beam rotation scanning adopts a slit collimator to form fan beam illumination, and a rasterized collimator is added, so that translation scanning at each rotation angle is not needed, the mechanical motion complexity is simplified, but because the rasterized collimator blocks scattered photons, the acceptance rate of the scattered photons is not obviously improved, and the scanning still needs hours. Long imaging times are one of the most significant problems with XRDT systems for rotational scanning.
The bottleneck of the spatial resolution or the data acquisition time of the conventional XRDT system becomes a main bottleneck of the application of the XRDT technology in a refined sample detection task.
Disclosure of Invention
The application provides a multi-angle scanning coded hole X-ray diffraction tomography system and an imaging method, which aim to solve the problems of low X-ray diffraction tomography spatial resolution, long data acquisition time and the like in the related art.
The embodiment of the first aspect of the present application provides a multi-angle scanning coded aperture X-ray diffraction tomography, including: an X-ray source for generating cone beam incident X-rays of a continuous energy spectrum; the slit collimator is arranged on a propagation path of the cone beam incident X-ray so that the cone beam incident X-ray forms a fan beam incident X-ray after passing through the slit collimator; the object stage is used for placing an object to be imaged, and the object stage is arranged on a propagation path of the fan beam incident X-ray so that the object to be imaged is irradiated by the fan beam incident X-ray to generate an original diffraction X-ray; the coding hole template is arranged on a propagation path of the original diffraction X-ray so that the original diffraction X-ray forms a coding diffraction X-ray after passing through the coding hole template; the ray blocker is arranged between the object stage and the coding hole template and is used for absorbing fan-beam transmission X rays penetrating through the object to be imaged; the energy dispersion photon counting detector is arranged on a propagation path of the coded diffraction X-ray and is used for detecting the coded diffraction X-ray corresponding to the object to be imaged under a plurality of imaging angles to obtain a multi-angle coded diffraction detection signal; and the image reconstruction module is used for reconstructing the multi-angle coding diffraction detection signal by using an imaging system accurate model to obtain a diffraction fault reconstruction result of the object to be imaged.
Optionally, in an embodiment of the present application, the method further includes: a mechanical motion module for controlling the object to be imaged to move so as to change an imaging angle of the object to be imaged relative to the X-ray source and the energy dispersive photon counting detector.
Optionally, in an embodiment of the present application, the method further includes: and the model calculation module is used for calculating a general physical model of the imaging system according to the actual calibration parameters of the imaging system to obtain an accurate model of the imaging system, wherein the general physical model of the imaging system is a physical relationship between the multi-angle coded diffraction detection signal and the diffraction fault reconstruction result.
Optionally, in an embodiment of the present application, the method further includes: and the calibration module is used for calibrating the energy response matrix of the detector, the spectrum shape of the incident X-ray of the fan beam and the geometric parameters of the imaging system to obtain the actual calibration parameters of the imaging system.
Optionally, in an embodiment of the present application, the image reconstruction module is further configured to construct an iterative optimization objective function according to the accurate imaging system model, and obtain a diffraction tomographic reconstruction result of the object to be imaged by optimizing the iterative optimization objective function.
Optionally, in an embodiment of the application, the image reconstructing module is further configured to train a deep neural network by using multi-angle scanning coded aperture X-ray diffraction tomography data based on the accurate imaging system model, and reconstruct the multi-angle coded diffraction detection signal through the trained deep neural network, so as to obtain a diffraction tomography reconstruction result of the object to be imaged.
The embodiment of the second aspect of the present application provides a multi-angle scanning coded aperture X-ray diffraction tomography method, and the multi-angle scanning coded aperture X-ray diffraction tomography system using the above embodiment includes the following steps: controlling the object to be imaged to move such that the object to be imaged forms a plurality of imaging angles with respect to the X-ray source and the energy-dispersive photon counting detector; collecting multi-angle coded diffraction detection signals corresponding to the object to be imaged under a plurality of imaging angles; and reconstructing the multi-angle coding diffraction detection signal by using an imaging system accurate model to obtain a diffraction fault reconstruction result of the object to be imaged.
Optionally, in an embodiment of the present application, before reconstructing the multi-angle encoded diffraction detection signal by using an accurate imaging system model, the method further includes: and calculating a general physical model of the imaging system according to the actual calibration parameters of the imaging system to obtain an accurate model of the imaging system, wherein the general physical model of the imaging system is a physical relation between the multi-angle coded diffraction detection signal and the diffraction fault reconstruction result.
Optionally, in an embodiment of the present application, reconstructing the multi-angle encoded diffraction detection signal by using an accurate imaging system model to obtain a diffraction fault reconstruction result of the object to be imaged, includes: and constructing an iterative optimization objective function according to the imaging system accurate model, and optimizing the iterative optimization objective function to obtain a diffraction fault reconstruction result of the object to be imaged.
Optionally, in an embodiment of the present application, reconstructing the multi-angle coded diffraction detection signal by using an accurate imaging system model to obtain a diffraction fault reconstruction result of the object to be imaged, includes: based on the imaging system accurate model, a deep neural network is trained by utilizing multi-angle scanning coded hole X-ray diffraction tomography imaging data, and the multi-angle coded diffraction detection signal is reconstructed through the trained deep neural network to obtain a diffraction tomography reconstruction result of the object to be imaged.
The multi-angle scanning coded hole X-ray diffraction tomography system and the imaging method combine the advantage of high spatial resolution of rotary scanning XRDT with the advantage of accelerated acquisition of coded hole imaging, provide a novel high spatial resolution rapid XRDT system, are defined as a multi-angle scanning coded hole X-ray diffraction tomography system (multi-angle scanning CAXRDT), and can effectively meet the application of XRDT technology in clinical medical diagnosis and material sample analysis.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The above and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic structural diagram of a multi-angle scanning coded aperture X-ray diffraction tomography system according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a code hole template provided according to an embodiment of the present application;
FIG. 3 is a schematic diagram of an alcohol sample provided according to an embodiment of the present application;
FIG. 4 is a schematic diagram of encoded diffraction detection signals of an alcohol sample according to an embodiment of the present application;
FIG. 5 is a schematic diagram of the reconstruction results of an alcohol sample at different scattering vectors according to an embodiment of the present application;
FIG. 6 is a flowchart of a multi-angle scanning code hole X-ray diffraction tomography method according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative and intended to explain the present application and should not be construed as limiting the present application.
The XRD signal is a macroscopic embodiment of Rayleigh scattering of X-ray photons and substances, and the XRD signal reflects the intermolecular structure information of the substances and has extremely strong material indication. In recent years, the application value of the XRD technology in medical treatment and security inspection becomes a hot point of technical attention, and XRDT is an inevitable technical direction of development of XRD detection towards refinement and visualization. However, the spatial resolution of the existing security inspection EDXRD and snapshot CAXRDT system in the transmission direction is larger than 1cm, and the partial volume effect is serious when a sample with a high-frequency space structure exists in the system. On the other hand, the rotary scanning XRDT can realize high-spatial-resolution sample detection, but the scanning time is as long as several hours, so that the practical application requirements are difficult to meet. The embodiment of the application aims to combine the isotropic high spatial resolution advantage of a rotary scanning method and the rapid parallel advantage of code hole compressed sensing data acquisition, and provides a novel fine XRDT system suitable for practical application scanning time, which is called a multi-angle scanning code hole X-ray diffraction tomography imaging system (multi-angle scanning CAXRDT), so that the requirements of clinical medical diagnosis and material sample analysis application on imaging speed and imaging spatial precision are met.
The following describes a multi-angle scanning coded aperture X-ray diffraction tomography system according to an embodiment of the present application with reference to the drawings.
FIG. 1 is a schematic structural diagram of a multi-angle scanning coded aperture X-ray diffraction tomography system according to an embodiment of the present application.
As shown in FIG. 1, the multi-angle scanning coded aperture X-ray diffraction tomography system comprises: an X-ray source commonly used for medical treatment or security inspection, a slit collimator, a stage for placing a sample/object, a ray blocker, a coded hole template and an energy dispersion photon counting detector.
During the imaging process of the multi-angle scanning CAXRDT system, an X-ray source generates cone beam incident X-rays with continuous energy spectrum. The slit collimator is arranged on a transmission path of cone beam incident X-rays, and the cone beam incident X-rays form fan beam incident X-rays after passing through the slit collimator. The objective table is arranged on a propagation path of the incident X-ray of the fan beam, and the object to be imaged is irradiated by the incident X-ray of the fan beam to generate original diffraction X-ray. The coding hole template is arranged on a propagation path of original diffraction X-rays, and the original diffraction X-rays form coding diffraction X-rays after passing through the coding hole template. The ray stopper is arranged between the object stage and the coding hole template, and the part of the fan beam incident X-ray directly penetrating through the object is absorbed by the ray stopper. The energy dispersion photon counting detector is arranged on a propagation path of the coded diffraction X-ray and used for detecting the coded diffraction X-ray corresponding to the object to be imaged under a plurality of imaging angles to obtain a multi-angle coded diffraction detection signal. And the image reconstruction module is used for reconstructing the multi-angle coded diffraction detection signal by using the imaging system accurate model to obtain a diffraction fault reconstruction result of the object to be imaged.
At the angle of imaging
The encoded diffraction detection signal detected by the energy dispersive photon counting detector is
Where u, v are the coordinates of the pixel position of the two-dimensional detector and E isThe detector energy channel.
Optionally, in an embodiment of the present application, the multi-angle scanning coded aperture X-ray diffraction tomography system further includes a mechanical motion module. The mechanical motion module is used for controlling the object to be imaged to move so as to change the imaging angle of the object to be imaged relative to the X-ray source and the energy dispersion photon counting detector.
In the scanning process, the mechanical motion module is controlled to enable an object to be imaged to change imaging angles relative to the X-ray source and the detector, coded diffraction X-rays are collected under each angle, and finally multi-angle coded diffraction detection signals are obtained
Wherein->
Is the total scan angle number.
The image reconstruction module utilizes the imaging system accurate model to encode the diffraction detection signal I at multiple angles XRD Carrying out reconstruction to obtain a diffraction fault reconstruction result
Wherein x and y are two-dimensional space coordinates, and q is a scattering vector.
Optionally, in an embodiment of the present application, the multi-angle scanning coded aperture X-ray diffraction tomography system further includes: and a model calculation module. The model calculation module is used for calculating a general physical model of the imaging system according to actual calibration parameters of the imaging system to obtain an accurate model of the imaging system, wherein the general physical model of the imaging system is a multi-angle coding diffraction detection signal I XRD And the diffraction tomographic reconstruction result f.
Defining the center of the field of view as the origin of coordinates of the global coordinate system, denoted by o, with the axis perpendicular to the detector plane as the X-axis, the Y-axis being parallel to the slit of the slit collimator, the Z-axis being perpendicular to the slit and parallel to the detector plane,
the equivalent rotation angle of the object, i.e. based on the coordinate system of the first viewing angle at different viewing angles, is->
General physical model of imaging system refers to
And f (x, y, q), and the specific expression is as follows: />
Wherein R (E, E') is the energy response matrix of the detector,
is the spectral shape of the fan beam incident X-rays.
For incident attenuation factor, finger->
At an angle, the X-ray photon with energy E' decays from the light source to the object by a ratio of X, y. />
Is a diffraction attenuation factor, finger->
The X-ray photon with energy E' is attenuated from the object at X, y to the detector at u, v. />
Is a code hole factor which indicates whether scattered photons can reach the u and v positions on the detector from the x and y positions on the object through the through holes of the code hole template, is a binary function with the value of 0/1 under the ideal condition, and can be taken under the actual condition [0,1]Within a regionThe value of (c). Make/combine>
The intrinsic relationship model of Rayleigh scattering when the diffraction intensity is not influenced by the code hole template and the attenuation effect is described as a Rayleigh scattering factor. Wherein it is present>
The diffraction solid angle is expressed, and the size of the diffraction solid angle corresponding to a unit area detector from x and y positions on the object to u and v positions on the detector is described. />
Is a Thomson scattering cross section, N A Is the Avogastrol constant, h is the Planck constant, and c is the speed of light. The incidence attenuation factor in equation (1)>
Diffraction attenuation factor->
Diffraction angle theta S And a diffractive cube corner>
Expressed as:
in the formulas (2) and (3), mu (x, y, z, E) is three-dimensional attenuation coefficient distribution of the object to be reconstructed under the energy E, and l { (x) 1 ,y 1 ,z 1 ),(x 2 ,y 2 ,z 2 ) Means a slave point (x) in a three-dimensional coordinate system 1 ,y 1 ,z 1 ) To (x) 2 ,y 2 ,z 2 ) The integration path in between. In the formula (5)<a,b>Representing the angle between the two vectors a, b. S is the distance from the X-ray source to the origin of coordinates o and D is the distance from o to the detector, as shown in FIG. 1. S and D can take different values under different angles, thereby forming multi-angle CAXRDT scanning of the non-circular track.
Optionally, in an embodiment of the present application, the multi-angle scanning coded aperture X-ray diffraction tomography system further includes: and the calibration module is used for calibrating the energy response matrix of the detector, the spectrum shape of the incident X-ray of the fan beam and the geometric parameters of the imaging system to obtain the actual calibration parameters of the imaging system.
The accurate model of the multi-angle scanning coded hole X-ray diffraction tomography system is a result obtained by carrying out numerical calculation on a general physical model of the multi-angle scanning coded hole X-ray diffraction tomography system according to actual calibration parameters. The process comprises calibrating a detector energy response matrix R (E, E'), and calibrating the spectral shape of the incident X-ray of a fan beam
Calibration, system geometric parameter calibration and system factor calculation.
The detector energy response matrix R (E, E') is calibrated: the energy response matrix of the detector can be obtained by adopting a metal powder X-ray fluorescence method for calibration, can also be obtained by adopting a crystal powder diffraction calibration method, and can also be obtained by adopting a Monte Carlo simulation method.
Spectral shape of fan beam incident X-rays
Calibration: direct measurement with energy dispersive photon counting detectorThe optical-mechanical spectrum and estimating the spectral shape of the fan-beam incident X-rays from the measured optical-mechanical spectrum based on the detector energy response matrix R (E, E')
The system geometric parameter calibration refers to energy dispersion photon counting detector space position calibration and coding hole template space position calibration, and pen beam X-ray direct signal motor stepping translation change relation calibration measured by the detector is carried out under the irradiation of pen beam X-ray measured by the pen beam collimator.
Calculating a system factor: according to the system geometric parameter calibration result, in the calculation formula (1) under the condition of discretizing object pixel and discretizing detector pixel
And &>
The actual accurate model of the multi-angle scanning CAXRDT is obtained and recorded as H XRD Namely:
I XRD ＝H XRD (f) (6)
optionally, in an embodiment of the present application, the image reconstruction module is further configured to construct an iterative optimization objective function according to the imaging system accurate model, and obtain a diffraction tomographic reconstruction result of the object to be imaged by optimizing the iterative optimization objective function.
For multi-angle encoded diffraction detection signal I XRD Is reconstructed into pairs H XRD And (5) an inversion process. Including model-based iterative reconstruction methods. Actual accurate model H according to multi-angle scanning CAXRDT XRD Constructing an iterative optimization objective function:
wherein l MAP 0 is the overall iterative optimization objective function, l fidelity 0 is a data fidelity cost function according to the systemNoise model derived I XRD And H XRD (f) The statistical noise model may include a poisson noise model, a gaussian noise model. l prior The prior cost function of 0 image can comprise total variation minimum, non-local mean filtering, dictionary learning, low rank and the like. f is the diffraction tomographic image to be optimized.
The diffraction fault reconstruction result f can be obtained by optimizing f by adopting a gradient descent method, an alternating iterative optimization method (ADMM) and a split Bregman method.
Optionally, in an embodiment of the present application, the image reconstruction module is further configured to train a deep neural network by using multi-angle scanning coded hole X-ray diffraction tomography data based on an imaging system accurate model, and reconstruct the multi-angle coded diffraction detection signal through the trained deep neural network to obtain a diffraction tomography reconstruction result of the object to be imaged.
For multi-angle encoded diffraction detection signal I XRD Is reconstructed into pairs H XRD The inversion process also includes using a deep neural network based reconstruction method.
Design deep neural network as
θ Recon Are parameters of the neural network. Acquiring a large amount of multi-angle scanning CAXRDT data through simulation experiments and actual experiments for training a deep neural network to obtain a trained neural network parameter theta * Recon . Use>
Represents a pair H XRD And (5) an inversion process. The reconstruction process is then:
the multi-angle scanning coded hole X-ray diffraction tomography system can complete scanning within several minutes, and is a first minute time order fine diffraction tomography system in the field. The advantage of high spatial resolution of rotary scanning is combined with the advantage of compressed sensing of coding holes for rapid parallel data acquisition, diffraction spectrum imaging is realized on a scanned object within several minutes, the diffraction spectrum at each pixel is obtained, the material distribution of the scanned object is imaged in an indicative manner, and the spatial resolution of the material distribution imaging can reach the level of 1 mm. The multi-angle scanning CAXRDT system effectively meets the requirements of clinical medical diagnosis and material sample analysis application on imaging speed and imaging space precision.
The method is matched with the multi-angle scanning CAXRDT system, physical effects and actual factors such as discretization implementation factors, attenuation factors, diffraction angles, diffraction solid angle changes and the like are fully considered, and data acquired by the multi-angle scanning CAXRDT system can be accurately and stably reconstructed to obtain the optimal effect.
The multi-angle scanning coded aperture X-ray diffraction tomography system of the application is explained in detail through specific embodiments.
The multi-angle scanning CAXRDT system adopts a tungsten anode X-ray source, and under the working state, the tube voltage is 100kV, and the current is 5mA. Two stages of slit collimators are adopted to jointly form fan-beam incident X-rays, the length of a slot of the first stage slit collimator is 40mm, the width of the slot is 0.5mm, and the distance from the focal point of the X-ray source is 100mm. The second stage slit collimator has a slot length of 50mm, a width of 0.5mm and a distance of 300mm from the X-ray source focus. And a light path from the beam outlet of the X-ray source to the two stages of slit collimators is wrapped by lead sheets to shield redundant X-rays. The objective table is a turntable with the diameter of 80mm, the distance between the objective table and the focal point of an X-ray source is 400mm, and when the system is used, the sample placement area is within the range of 50mm in diameter by taking the rotation center of the objective table as the center of a circle, namely the imaging visual field of the system. The coding hole template and the energy dispersion photon counting detector are jointly installed on a mechanical platform capable of translating along the YZ direction, the distance between the coding hole template and the rotation center of the objective table is 150mm, the distance between the energy dispersion photon counting detector and the rotation center of the objective table is 300mm, the relative positions of the coding hole template and the energy dispersion photon counting detector are fixed, and the coding hole template and the energy dispersion photon counting detector are both located above the fan beam incident X ray. The code hole template used in this embodiment is a tungsten plate with a thickness of 1.5mm, 40 rows and 8 rows of candidate hole sites (320 candidate hole sites) are planned on the tungsten plate and distributed in a long strip area of 40mm × 8mm, the periodic intervals of the rows and the columns of the candidate hole sites are all 2mm, 160 candidate hole sites are randomly selected from the candidate hole sites to process through holes, each through hole is a square with a side length of 1mm, and a schematic diagram of the code hole template is shown in fig. 2. The energy dispersive photon counting detector has 64 x 16 detector pixels with side length of 1.6mm. Under the working condition, the measuring energy spectrum range is set to be 21keV-100keV, and the interval is 1keV.
When a sample is scanned, the sample is placed in an imaging view field of a system on an objective table, 15 data acquisition view angles are uniformly arranged in a 360-degree circumference, and the data acquisition time of a detector is 80s under each acquisition view angle. Neglecting the movement time of the turntable, the total time of one scanning is 20min. (since the detector is only positioned above the fan-beam incident X-ray in the embodiment, if the coded hole template and the detection area of the optical machine counting detector simultaneously cover two sides of the fan-beam incident X-ray, the time can be shortened by half, and the coded diffraction detection signal I under 15 degrees can be obtained XRD Is stored for subsequent reconstruction. FIGS. 3 and 4 show diagrams of encoded diffraction probe signals at an angle of 50keV energy channels for an alcohol sample in this example.
Before the energy dispersion photon counting detector is installed in a multi-angle scanning CAXRDT system, a metal powder fluorescence method is used for calibrating a detector energy response matrix R (E, E') in advance. The energy dispersion photon counting detector is used for measuring the energy spectrum of the optical machine with 100keV and the response of the detector is inverted to obtain the spectral shape of the fan beam incident X ray with 100keV
An energy dispersion photon counting detector is arranged in a multi-angle scanning CAXRDT system, a pinhole collimator is arranged in front of an X-ray source to generate pen beam X-ray irradiation detectors, and the pen beam X-ray irradiation detectors are respectively arranged along Y with the step length of 0.1mmThe detector is translated in the Z direction, and the position Y of the detector relative to the central pen beam is obtained by observing the change of the pixel with the maximum counting rate along with the translation in the YZ direction D ＝-1.7mm，Z D ＝2.9mm。
Further installing a coding hole template, sticking the lead sheet to the other coding holes, only leaving the central coding hole as a calibration hole, adjusting a YZ motor by a translation step length of 0.1mm to ensure that the total counting rate of the pencil beam X-ray irradiating the detector through the calibration hole is maximum, at the moment, the calibration hole is over against the central pencil beam, recording the translation position of the motor, and recording the Y position of the motor C ＝-0.8mm，Z C =1.0mm. The actual Y-coordinate-Y of the code hole template C Is 0.8mm, Z coordinate-Z C Is-1.0 mm. In order to remove shielding materials on the coding hole template, the pinhole collimator is replaced by the slit collimator, the ray blocker is installed, and the multi-angle scanning CAXRDT system is adjusted to return to the working state.
Calculating system factors in the formula (1) according to the system calibration result to obtain an actual accurate model H of the multi-angle scanning CAXRDT XRD 。
When multi-angle scanning CAXRDT is reconstructed, an iterative reconstruction method based on a model is adopted to encode diffraction detection signals I XRD And (3) reconstruction, firstly, constructing a maximum posterior probability cost function, adopting a Poisson noise distribution model for the likelihood function, adopting total variation minimum prior in a space dimension for image prior, and adopting second-order smooth term prior in a diffraction spectrum dimension. The maximum posterior probability cost function in this embodiment is:
l MAP (f，I XRD )＝l Poisson (I XRD ，H XRD (f))+l TV-xy (f)++l Smooth-q (f) (10)
wherein l Poisson As a likelihood function of the Poisson distribution,/ TV-xy Is a space dimension total variation minimum cost function, l Smooth-q And the cost function is constrained for diffraction spectrum dimension second order smoothness. The diffraction fault reconstruction result f is obtained by optimizing the formula (10) by using a split-Bregman method, as shown in FIG. 5, wherein the reference numeral 1 in FIG. 5 is 80% of alcohol by mass fraction, the reference numeral 2 is 40% of alcohol by mass fraction, and the reference numeral 3 is water.
Using quilt based on segmentationThe three-dimensional attenuation coefficient distribution estimation of the scanned object is used for carrying out primary reconstruction on each scanned object without considering the attenuation of the ray, namely mu (x, y, z, E) equivalent to 0, of the object in the first reconstruction. And performing threshold segmentation on the primary reconstruction result, and replacing the part with the object with the attenuation coefficient of water to approximately estimate the three-dimensional attenuation coefficient distribution of the scanned object. After the three-dimensional attenuation coefficient distribution of the scanned object is obtained, the incident attenuation factor is calculated
Diffraction attenuation factor->
And detecting the signal I for the encoded diffraction XRD And carrying out accurate reconstruction to obtain a diffraction fault reconstruction result.
The multi-angle scanning coded aperture X-ray diffraction tomography system that this application embodiment provided combines the high spatial resolution advantage of rotatory scanning XRDT with the advantage of the accelerated collection of coded aperture formation of image, provides a new quick XRDT system of high spatial resolution, defines as multi-angle scanning CAXRDT, can effectively satisfy the application of XRDT technique in clinical medicine diagnosis and material sample analysis.
Next, a multi-angle scanning coded hole X-ray diffraction tomography method provided by the embodiment of the application is described with reference to the attached drawings.
FIG. 6 is a flowchart of a multi-angle scanning code hole X-ray diffraction tomography method according to an embodiment of the present application.
As shown in FIG. 6, the multi-angle scanning coded aperture X-ray diffraction tomography method utilizes the multi-angle scanning coded aperture X-ray diffraction tomography system of the above embodiment, and the imaging method comprises the following steps:
and S101, controlling the object to be imaged to move so that the object to be imaged forms a plurality of imaging angles relative to the X-ray source and the energy dispersion photon counting detector.
In step S102, multi-angle coded diffraction detection signals corresponding to the object to be imaged at a plurality of imaging angles are collected.
In step S103, the multi-angle encoded diffraction detection signal is reconstructed by using the imaging system accurate model, so as to obtain a diffraction fault reconstruction result of the object to be imaged.
Optionally, in an embodiment of the present application, before reconstructing the multi-angle encoded diffraction detection signal by using the accurate model of the imaging system, the method further includes: and calculating a general physical model of the imaging system according to the actual calibration parameters of the imaging system to obtain an accurate model of the imaging system, wherein the general physical model of the imaging system is a physical relation between the multi-angle coded diffraction detection signal and a diffraction fault reconstruction result.
Optionally, in an embodiment of the present application, reconstructing the multi-angle encoded diffraction detection signal by using an accurate imaging system model to obtain a diffraction fault reconstruction result of the object to be imaged, includes: and constructing an iterative optimization objective function according to the accurate model of the imaging system, and optimizing the iterative optimization objective function to obtain a diffraction fault reconstruction result of the object to be imaged.
Optionally, in an embodiment of the present application, reconstructing the multi-angle encoded diffraction detection signal by using an accurate imaging system model to obtain a diffraction fault reconstruction result of the object to be imaged, includes: based on an accurate model of an imaging system, a deep neural network is trained by utilizing multi-angle scanning coded hole X-ray diffraction tomography data, and multi-angle coded diffraction detection signals are reconstructed through the trained deep neural network to obtain a diffraction tomography reconstruction result of an object to be imaged.
Optionally, in an embodiment of the present application, the method further includes: and calibrating the energy response matrix of the detector, the spectral shape of the incident X-ray of the fan beam and the geometric parameters of the imaging system to obtain the actual calibration parameters of the imaging system.
It should be noted that the foregoing explanation of the multi-angle scanning code aperture X-ray diffraction tomography system embodiment is also applicable to the multi-angle scanning code aperture X-ray diffraction tomography method of the embodiment, and is not repeated here.
According to the multi-angle scanning coded aperture X-ray diffraction tomography method, the advantage of high spatial resolution of rotary scanning XRDT and the advantage of accelerated acquisition of coded aperture imaging are combined, a novel high spatial resolution rapid XRDT system is provided, the system is defined as multi-angle scanning CAXRDT, and the application of XRDT technology in clinical medical diagnosis and material sample analysis can be effectively met.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of implementing the embodiments of the present application.
Claims (10)
1. A multi-angle scanning coded aperture X-ray diffraction tomography system, comprising:
an X-ray source for generating cone beam incident X-rays of a continuous energy spectrum;
the slit collimator is arranged on a propagation path of the cone beam incident X-ray so that the cone beam incident X-ray forms a fan beam incident X-ray after passing through the slit collimator;
the object stage is used for placing an object to be imaged, and the object stage is arranged on a propagation path of the fan beam incident X-ray so that the object to be imaged is irradiated by the fan beam incident X-ray to generate an original diffraction X-ray;
the coding hole template is arranged on a propagation path of the original diffraction X-ray so that the original diffraction X-ray forms a coding diffraction X-ray after passing through the coding hole template;
the ray blocker is arranged between the object stage and the coding hole template and used for absorbing fan-beam transmission X rays penetrating through the object to be imaged;
the energy dispersion photon counting detector is arranged on a propagation path of the coded diffraction X-ray and is used for detecting the coded diffraction X-ray corresponding to the object to be imaged under a plurality of imaging angles to obtain a multi-angle coded diffraction detection signal;
and the image reconstruction module is used for reconstructing the multi-angle coding diffraction detection signal by using an imaging system accurate model to obtain a diffraction fault reconstruction result of the object to be imaged.
2. The system of claim 1, further comprising:
a mechanical motion module for controlling the object to be imaged to move so as to change an imaging angle of the object to be imaged relative to the X-ray source and the energy dispersive photon counting detector.
3. The system of claim 1, further comprising:
and the model calculation module is used for calculating a general physical model of the imaging system according to the actual calibration parameters of the imaging system to obtain an accurate model of the imaging system, wherein the general physical model of the imaging system is a physical relationship between the multi-angle coded diffraction detection signal and the diffraction fault reconstruction result.
4. The system of claim 3, further comprising:
and the calibration module is used for calibrating the energy response matrix of the detector, the spectrum shape of the incident X-ray of the fan beam and the geometric parameters of the imaging system to obtain the actual calibration parameters of the imaging system.
5. The system of claim 1 or 3, wherein the image reconstruction module is further configured to construct an iterative optimization objective function according to the accurate imaging system model, and obtain a diffraction tomographic reconstruction result of the object to be imaged by optimizing the iterative optimization objective function.
6. The system of claim 1 or 3, wherein the image reconstruction module is further configured to train a deep neural network using multi-angle scanning coded aperture X-ray diffraction tomographic imaging data based on the accurate imaging system model, and reconstruct the multi-angle coded diffraction detection signal through the trained deep neural network to obtain a diffraction tomographic reconstruction result of the object to be imaged.
7. A multi-angle scanning coded aperture X-ray diffraction tomography method using the multi-angle scanning coded aperture X-ray diffraction tomography system of any one of claims 1 to 6, comprising the steps of:
controlling the object to be imaged to move such that the object to be imaged forms a plurality of imaging angles with respect to the X-ray source and the energy-dispersive photon counting detector;
collecting multi-angle coded diffraction detection signals corresponding to the object to be imaged under a plurality of imaging angles;
and reconstructing the multi-angle coded diffraction detection signal by using an accurate imaging system model to obtain a diffraction fault reconstruction result of the object to be imaged.
8. The method of claim 7, further comprising, prior to reconstructing the multi-angle encoded diffraction detection signals using an accurate model of an imaging system:
and calculating a general physical model of the imaging system according to the actual calibration parameters of the imaging system to obtain an accurate model of the imaging system, wherein the general physical model of the imaging system is a physical relation between the multi-angle coded diffraction detection signal and the diffraction fault reconstruction result.
9. The method according to claim 7, wherein reconstructing the multi-angle encoded diffraction detection signal by using an accurate imaging system model to obtain a diffraction fault reconstruction result of the object to be imaged comprises:
and constructing an iterative optimization objective function according to the imaging system accurate model, and optimizing the iterative optimization objective function to obtain a diffraction fault reconstruction result of the object to be imaged.
10. The method of claim 7, wherein reconstructing the multi-angle coded diffraction detection signal by using an accurate imaging system model to obtain a diffraction fault reconstruction result of the object to be imaged comprises:
based on the accurate model of the imaging system, a deep neural network is trained by utilizing multi-angle scanning coded hole X-ray diffraction tomography imaging data, and the multi-angle coded diffraction detection signal is reconstructed through the trained deep neural network to obtain a diffraction tomography reconstruction result of the object to be imaged.
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