Calibration method and X-ray scanner system

Abstract

To make a calibration method for an X-ray scanner system be efficient.SOLUTION: A calibration method comprising: placing at least one slab in a field of view of an X-ray scanner system; scanning, on the X-ray scanner system, the slab with X-ray tubes located at plural locations disposed at different irradiation angles relative to the slab; generating material decomposition data based on the scanning; and calibrating a forward model for the X-ray scanner system based on the material decomposition data.SELECTED DRAWING: Figure 10

Description

[Technical Field]

[0001] Embodiments disclosed herein and in the drawings relate to calibration methods and X-ray scanner systems. [Background technology]

[0002] Computed tomography (CT) systems and methods are commonly used in medical imaging and diagnosis. A CT system typically creates projection images of a subject's body at a series of projection angles. For example, a radiation source, such as an X-ray tube, is used to irradiate the subject's body, generating projection images at various angles. From these projection images, an image of the subject's body can be reconstructed.

[0003] Traditionally, energy-integrating detectors (EIDs) and / or photon-counting detectors (PCDs) have been used to measure CT projection data. PCDs offer many advantages, including the ability to perform spectral CT. PCDs decompose the count of incident X-rays into spectral components called energy bins, so that these energy bins as a whole spread across the energy spectrum of the X-ray beam. Unlike non-spectral CT, spectral CT generates information attributable to various materials that exhibit different X-ray attenuations as a function of X-ray energy. These differences make it possible to discriminate spectrally decomposed projection data to different reference materials. For example, two reference materials for material discrimination are bone and water.

[0004] While PCD response times are fast, the high X-ray flux rates characteristic of clinical radiographic imaging mean that multiple X-ray detection events can occur within the detector's time response in a single detector. This phenomenon is called pile-up. If left uncorrected, the pile-up effect can distort the PCD energy response and degrade images reconstructed from the PCD. When these effects are corrected, spectral CT offers many advantages over conventional CT. Spectral CT extracts highly accurate tissue characterization information from imaged objects, and many clinical settings can benefit from spectral CT technology, including improved material differentiation.

[0005] One challenge in more effectively using semiconductor-based PCDs in spectral CT is performing material discrimination of projection data in a robust and efficient manner. For example, pile-up correction in the detection process may be incomplete, and these incompletenesses reduce the reliability of reference materials based on material discrimination.

[0006] In photon counting CT systems, semiconductor-based detectors using direct conversion are designed to resolve the energy of individual incident photons and generate multiple energy bin count measurements for each integration period. However, due to the detection physics of such semiconductor materials (e.g., CdTe / CZT), the detector's energy response is significantly degraded / distorted by charge sharing, k-escape and scattering effects in the energy storage and charge induction processes, as well as electronic noise from associated front-end electronics. Due to the finite signal induction time, under high counting rate conditions, pulse pile-up also distorts the energy response, as described above.

[0007] Due to the non-uniformity and complexity of the sensor materials in the integrated detection system, it is difficult to accurately model the detector response of PCD based only on Monte Carlo simulations using specific modeling of physical theories or signal induction processes. Note that this modeling determines the accuracy of the forward model for each measurement. Also, due to the uncertainty in the modeling of the incident X-ray tube spectrum, additional errors occur in the forward model due to this modeling. All these factors ultimately lead to a decrease in the accuracy of material discrimination in PCD measurements, i.e., from the generated spectral images.

[0008] To solve similar problems, calibration methods have been proposed in the literature. The general idea is to use multiple transmission measurements with various known path lengths to modify the forward model so that it matches the calibration measurements. Several ideas, such as Non-Patent Document 1 and Non-Patent Document 2, are applied to the estimation of the X-ray spectrum in conventional CT. Non-Patent Document 2 is adopted for photon-counting detectors to estimate the combined system spectral response (see Non-Patent Document 3). However, considering the feasibility of application, especially in the third-generation CT geometry, there can be many variations in the detailed design and implementation of the calibration method.

Prior Art Documents

Non-Patent Documents

[0009]

Non-Patent Document 1

Non-Patent Document 2

Non-Patent Document 3

[0010] One of the problems that the embodiments disclosed herein and in the drawings aim to solve is to improve the efficiency of the calibration method in an X-ray scanner system. However, the problems that the embodiments disclosed herein and in the drawings aim to solve are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described later can also be positioned as other problems. [Means for solving the problem]

[0011] The calibration method of the embodiment includes placing at least one slab within the field of view of an X-ray scanner system, scanning the slab using X-ray tubes positioned at multiple locations with different irradiation angles to the slab in the X-ray scanner system, generating material discrimination data based on the scan, and calibrating the forward model of the X-ray scanner system based on the material discrimination data. [Brief explanation of the drawing]

[0012] [Figure 1] Figure 1 shows an example of the PCD bin response function Sb(E) of a photon count detector. Each curve represents an example function for each energy bin. [Figure 2] Figure 2 shows the workflow for substance discrimination calibration and processing. [Figure 3] Figure 3 shows the normalized linear decay coefficients for various materials. [Figure 4] Figure 4 shows a schematic diagram of the calibration structure design, where a pile-up correction table Pb is generated and used individually for each current (mA). [Figure 5]Figure 5 shows a schematic diagram of another calibration structure design. In this design, a universal pile-up correction table Pb is generated for the entire current (mA) range. [Figure 6] Figure 6 shows the calibration scan procedure. [Figure 7] Figure 7 shows the calibration slab path lengths for various detector pixels. [Figure 8] Figure 8 shows an example of a calibration slab design, in which the calibration slab is aligned in the Z direction along at least part of the patient bed or other movable mechanism within the detector field. [Figure 9] Figure 9 shows various addition schemes that can be used for discriminant calibration and processing. [Figure 10] Figure 10 is a schematic diagram illustrating how different X-ray tube positions generate various path lengths for slab scans during calibration. [Figure 11] Figure 11 shows a CT scanner system that can incorporate an example disclosed in the embodiments. [Modes for carrying out the invention]

[0013] The calibration method and embodiments of the X-ray scanner system will be described below with reference to the attached drawings. One embodiment of the calibration method includes placing at least one slab within the field of view of the X-ray scanner system, scanning the slab using X-ray tubes positioned at multiple locations with different irradiation angles to the slab in the X-ray scanner system, generating material discrimination data based on the scan, and calibrating the forward model of the X-ray scanner system based on the material discrimination data.

[0014] In one embodiment, the slab has a shape in which the path length changes depending on the irradiation angle.

[0015] In one embodiment, the calibration method includes using the X-ray tube at at least one rotational speed to generate air calibration data based on at least one air scan, and calibrating the forward model of the X-ray scanner system based on the material discrimination data and the air calibration data.

[0016] In one embodiment, the scan is performed with the position of the X-ray tube fixed at each of the multiple locations with different irradiation angles.

[0017] In one embodiment, the substance discrimination data includes a weighted bin response and a pulse pile-up correction term.

[0018] In one embodiment, the forward model includes a weighted bin response, a pulse pile-up correction term, at least one linear damping coefficient in the slab, at least one path length in the slab, and the air calibration data.

[0019] In one embodiment, the slab is positioned horizontally within the field of view of the X-ray scanner system.

[0020] In one embodiment, the slab is positioned such that at least some of the X-ray paths pass through the slab at each of the irradiation angles.

[0021] In one embodiment, the calibration method further includes scanning an object after the calibration of the forward model of the X-ray scanner system.

[0022] In one embodiment, the slab is composed of multiple materials.

[0023] In one embodiment, the X-ray scanner system is a photon counting CT scanner system. In one embodiment, the X-ray scanner system is a third-generation photon counting CT scanner system.

[0024] In one embodiment, the slab has multiple heights.

[0025] In one embodiment, the slab has a plurality of widths that differ in the height direction.

[0026] An X-ray scanner system in one embodiment includes at least one slab positioned within the field of view of the X-ray scanner system, and a processing unit that scans the slab using X-ray tubes positioned at a plurality of locations with different irradiation angles to the slab, generates material discrimination data based on the scan, and calibrates the forward model of the X-ray scanner system based on the material discrimination data.

[0027] Throughout this specification, any reference to “one embodiment” or “embodiment” means that certain features, structures, materials, or properties described in relation to an embodiment are included in at least one embodiment of the Application, but not that they are present in all embodiments.

[0028] Therefore, the phrases “in one embodiment” or “in one embodiment” appearing in various places throughout this specification do not necessarily refer to the same embodiment of this application. Furthermore, certain features, structures, materials, or properties can be combined in any suitable manner in one or more embodiments.

[0029] This disclosure relates to a photon counting CT scanner system for material discrimination. The CT scanner comprises one or more X-ray tubes that emit X-ray radiation and an array of detector pixels for receiving X-ray radiation propagating through the field of view of the CT scanner system.

[0030] In transmission measurements using a Photon Counting Energy-Resolving Detector (PCD), the forward model can be formulated as shown in equation (1) below.

[0031] [Number]

[0032] Here, S b (E) represents the bin response function defined by the following equation (2).

[0033] [Number]

[0034] Here, R(E, E’) is the response function of the detector. E bL and E bH are the low energy threshold and high energy threshold of each counting bin. Figure 1 shows a model example of the typical S b (E) function. Here, the long tail on the energy window is induced by charge sharing, k escape, and scattering effects. The low energy tail is mainly due to the finite energy resolution from the associated electronic noise. N0 is the total flux from the air scan, μ m and l m are the linear attenuation coefficient and path length of the m-th reference material. w(E) is the normalized incident X-ray spectrum. In practice, neither w(E) nor S b (E) is exactly known, and the two can be combined as one term, i.e., S wb (E) = w(E)S b (E), which is hereinafter referred to as the weighted bin response function. If S wb (E) can be calibrated by measurement, the decomposition problem under low flux conditions can be sufficiently solved.

[0035] In the case of high flux scan conditions (e.g., a few percent pulse pile-up), the pulse pile-up brings additional spectral distortion to the measurement. One way to correct the pile-up effect is to introduce an additional correction term (see, for example, Non-Patent Document 3 above that uses the measured count rate as an input). And this type of additional calibration is a flux-independent weighted bin response Swb Based on accurate estimates in (E). S wb The first problem addressed in this application is how to estimate (E).

[0036] Under typical CT clinical scan conditions, pulse pileup of several percent or more is common in some measurements. The resulting impact on material discrimination depends on the measured spectrum and flux. Without knowing the actual detector response, the number of transmission measurements that can be performed to adjust the forward model is limited. For a complete CT system in a clinical setting, it is important to have a viable calibration procedure. Therefore, the second problem addressed in this application is a method for efficiently parameterizing the model and optimizing the calibration procedure.

[0037] In a full-size CT system, additional practical challenges in performing such a two-stage calibration include: the fan angle-dependent weighted spectral response due to beam pre-filtering (such as a bowtie filter), the limited minimum flux due to the operating specifications of the X-ray tube and the fixed system geometry, full detector ring calibration due to varying detector responses across pixels, limited space for in-system calibration phantom placement, the complexity of calibration on a rotating system with a scattering prevention grid, systematic errors in calibration and associated mechanical design tolerances, and the problem of non-ideal detectors with uniformity issues regarding energy resolution, counting, and energy threshold setting drift.

[0038] To achieve image quality that competes with conventional energy-integrating detector (EID) based systems, which feature much simpler detector response modeling and associated calibrations, while maintaining similar calibration procedures / workflows that do not significantly increase system downtime, the above non-ideal factors must be taken into consideration.

[0039] In one non-limiting embodiment, a two-step calibration method is applied for a PCD forward model for material discrimination. This method uses 1) an expectation maximization (EM) method to calculate a flux-independent weighted bin response function S wb It consists of two parts: (E) estimation and (2) estimation of the pile-up correction term.

[0040] P b (E,N b ,N tot ) is the energy (E) and the measured bin count (N). b ,N tot ) is a function of N. b This is the count for each bin, N tot This is the total count of all energy bins. The calibrated forward model can be expressed as follows: (3)

[0041]

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[0042] Here, instead of using only two materials, we use 2 to 5 different materials such as polypropylene, water, aluminum, titanium / copper, and K-absorbing edge materials to analyze the weighted bin response function S at low flux. wb Calibrate (E). Using a more selective substance for calibration reduces the number of total pathway lengths and yields equivalent or better results.

[0043] Step 1: Using a suitable tube spectral model to capture characteristic peaks in the incident spectrum and a physical model to simulate the spectral response of the photon count detector, S wb Initial estimates of (E) can be generated. By using the EM method (e.g., see Non-Patent Document 1), S wb (E) can be reliably estimated for this extremely adverse condition problem based on several transmission measurements.

[0044] Here, P b(E,Nb,Ntot) are assumed to be constant in step 1. The calibrated forward model can be simplified to a system of linear equations in equation (4).

[0045]

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[0046] Typically, the number of data measurements (M) is equal to the number of unknowns (E). max This is far less than the given value. Assuming a Poisson distribution for data acquisition, we derive an iterative EM algorithm and the unknown energy bin response function S as described below. wb We can find the optimal estimate for (E).

[0047] When estimating the bin response function using low-flux data acquisition, the pile-up effect correction Pb is assumed to be a known term (e.g., a constant). Therefore, the model is simplified to equation (5) below.

[0048]

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[0049] Let equation (6) below represent the decay path length of the j-th measurement. Therefore, for each measured value j, the following equation (7) is obtained.

[0050]

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[0051]

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[0052] In M measurement, data acquisition can be described in the matrix format of equation (8) or equation (9).

[0053]

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[0054]

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[0055] By applying the EM iterative algorithm, S wb (E) can be estimated as shown in equation (10) below.

[0056]

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[0057]

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[0058] S wb The update formula for (E) is given by the following equation (11).

[0059]

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[0060] Step 2: Calibration of each detector pixel with each tube voltage (kVp) setting from S wb Once (E) is estimated, it is stored in the system as a software calibration table. This is the pile-up correction term P for higher flux scans. b (E,N b ,N tot ) is used as input for further estimation. Next, both tables are used for material discrimination of the object / patient scan to estimate the pathway length of the reference material.

[0061] The calibration table is updated as needed based on variations in system / detector performance. This can also be designed as an iterative procedure. If the image quality is insufficient with the quality check phantom, this calibration process is repeated using the calibration table updated from the last iteration as the initial guess.

[0062] Figure 2 shows the high-level workflow in the above process. Steps 1) to 4) represent the calibration workflow, and steps 5) to 8) show how to generate spectral images using the calibration table during patient / object manipulation scans.

[0063] First, a series of low-flux scans on various material slabs are collected at each tube's kVp setting, which is the peak potential applied to the X-ray tube. Typical CT systems support several kVp settings from 70 to 140 kVp, generating different energy spectra from the X-ray tube for various scanning protocols. For CT scans, both mA and kVp must be pre-selected before turning on the X-ray tube. Next, the low-flux weighted bin response function S wb This is estimated, and this estimated S wb Using a high-flux slab scan, the pile-up correction term P b Additional parameters are estimated for each detector pixel. wb and P b Using the estimated calibration table, the calibration quality is checked against a quality phantom, such as a uniform water phantom or a phantom with multiple inserts using a uniform, known material. Image quality is evaluated using a predefined standard, and if it passes, the calibration table at that point is saved and used for the next patient / object scan data processing. Otherwise, the procedure is S wb and P bUse the last iteration as the initial guess and re-run the first three steps. Here, the generally inspected criteria are the accuracy, uniformity, spatial resolution, noise, and artifacts of the image CT numbers. To check the quality of this calibration, it is necessary to check all of these measurement criteria. In particular, it is necessary to check the accuracy and artifacts, such as rings or bands in images indicating insufficient calibration.

[0064] To select the optimal material and path length for this calibration, use the normalized linear attenuation coefficient curve (Figure 3) for energy to select different ones from each other. For example, polypropylene, water, aluminum, and titanium are a good combination group for such calibration, covering a wide range of common substances present in the human body.

[0065] To meet the low-flux conditions through the calibration measurement and minimize the pile-up effect in the flow diagram, in Step 1, it can be selected to use "nτ < x". Here, "x ≒ 0.005~0.01", "n" is the pixel counting rate at the lowest tube flux setting, and "τ" is the effective dead time of the PCD application-specific integrated circuit (ASIC). By satisfying this condition, the shortest path length of each selected calibration material can be calculated, and the remaining path lengths can be selected either by equal intervals of the path length or by the obtained measurement counting rate.

[0066] For the calibration of the pile-up correction term Pb in Step 3, the same slab material and path length are used for the scan at the high mA setting. The calibration data are grouped by mA, and different correction tables can be generated for each mA setting (Figure 4), or a universal correction table (Figure 5) can be generated for continuous mA settings, including measurements in all flux ranges (e.g., low to high mA, high to low mA, or the most frequently used values first).

[0067] Calibration measurements should be performed using sufficient statistics to minimize the effects of statistical variation. One non-restrictive example is to use statistics greater than 1000 times as the general integration period for the calibration data set to minimize the statistical error transferred in the calibration. Each energy bin b of the calibration measurement corresponds to the S wb (E) and P b (E,N b ,N tot ) will be used to update.

[0068] The estimation is very unfavorable because only a limited number of measurements can be performed using a small number of energy bins. In this case, proper initial estimation is essential for accurate estimation, as this imposes additional constraints on the EM method. One design variation to accommodate non-ideal detectors is S, especially when there are slight variations in the actual energy threshold setting of the ASIC. b The initial estimation allows for a more flexible energy window for each bin. Setting the lower threshold xkeV lower and the higher threshold ykeV higher allows for a more flexible energy window for the first S b The result is as shown in equation (12).

[0069]

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[0070] Here, "x" and "y" can be selected from "5 to 10 keV" to allow for specific variations in ASIC performance while simultaneously imposing additional constraints on the EM problem.

[0071] The design described in the embodiment uses three or more materials in calibration, which provides higher sensitivity for constraining the weighted bin response function estimation problem of the photon count detector.

[0072] Furthermore, this method includes a high-flax pile-up correction term P b (This is E,N here) b and N totDifferent parameterizations are used for the function of N. tot This feature is introduced to better approximate the true pile-up phenomenon and can significantly improve the model's ability under higher flux conditions with fewer parameters.

[0073] Furthermore, to accommodate non-ideal detector / ASIC performance, it is also possible to calculate initial estimates of the weighted bin response function by expanding the energy threshold window.

[0074] A two-stage calibration method for the PCD forward model for material discrimination is proposed. This consists of the following two parts: 1) A flux-independent weighted bin response function S using the state-of-the-art EM (Expectation Maximization) method. wb (E) Estimate, 2) Energy (E) and number of bins measured (N) b ,N tot The pile-up correction term P is a function of ). b (E,N b ,N tot This is an estimation of N. b This is the count for each bin, N tot This is the total count of all energy bins. The calibrated forward model can be expressed as shown in equation (3) above.

[0075] Furthermore, in order to calibrate the forward PCD measurement model of equation (3), in one embodiment, at least one slab of a predetermined material and a known thickness is placed horizontally within the field of view of the CT scanner. By using a slab of the predetermined material, the linear attenuation coefficient of the slab can be determined. Furthermore, by knowing the thickness of the slab, the path length of the X-ray radiation passing through the slab can be determined. Slab measurement can be performed by stationary scanning. In this case, the X-ray tube is placed in a fixed position on the CT scanner and operates at various flux levels.

[0076] In one embodiment, slab scanning can also be performed at multiple fixed X-ray tube positions to increase path length sampling and coverage using the same slab. The slab is positioned so that at least some X-ray paths pass through the slab at each irradiation angle for each X-ray tube position.

[0077] To apply patient / object scanning while the gantry is rotating, an additional air scan can be performed at each rotation speed to compensate for the additional shadow effect on each pixel when the anti-scattering grid (ASG) deviates during rotation. This air scan could generate an air calibration table that may contain data on the number of photons arriving for each integration period of each pixel.

[0078] In the case of full-ring calibration in third-generation geometry, the path lengths of the calibration material in the peripheral detectors can be designed differently from those in the central detector, depending on the bowtie filtering and the shape of the typical scan object. A narrower path length range can be used towards the edge of the fan beam, and the relationship between the path length ranges of each material can be derived based on the material and shape of the bowtie filter. Furthermore, multi-material slab phantoms can be designed to implement calibration measurements.

[0079] Figure 6 shows one embodiment of calibration method 600. In step S610, a slab of known material is first placed on the patient bed of the CT scanner and leveled so that the path length is known and controlled. Next, in S620, one or more stationary X-ray tubes (e.g., three different X-ray tubes in three different positions) positioned in the CT gantry scan the slab. From this scan, a material discrimination calibration process is performed in the next step S630 to generate a discrimination calibration table as described above. Furthermore, in S640, an air scan is performed at various rotational speeds to create an air calibration table. In S650, a patient / object scan (at a known rotational speed) can be acquired. The discrimination calibration table, air calibration table, and patient / object scan can be used in S660 for phantom / object scan processing, and a calibrated forward model is available.

[0080] The range of the slab calibration path length (L) can be designed to cover the maximum attenuation length of the clinical scan (for example, L water = 0.1~40cm, L bone (=0.1~10cm). This can be estimated through a representative set of clinical scans using different scanning protocols. Typically, this range may depend on the fan angle, as the field of view (FOV) is attenuated far less at the edges than the center due to the patient's shape and size. The choice of calibration path length range may depend on the different imaging tasks focusing on various anatomical structures. The calibration path length range is universal across the fan angle and can better cover unusual cases where the patient is too large or needs to be significantly shifted from the isocenter. In other words, different calibration path length ranges can be used at different fan angles to improve the accuracy and efficiency of calibration. The slab scan used for forward model calibration can be selected based on the imaging task to produce the best image quality.

[0081] As shown in Figure 7, in typical fan-beam coverage of third-generation CT, a flat slab is used for this calibration, resulting in a slightly different actual path length across the entire detector array. The actual path length L of each detector pixel in these calibration scans is different. i This can be calculated by the following equation (13).

[0082]

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[0083]

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[0084] To minimize path length errors, calibration with various slabs and thicknesses can be performed using a static scan configuration without rotation. The slab must be large enough to cover the entire detector array and must be kept sufficiently horizontal throughout the data acquisition. For thicker slabs, if the cavity size of the CT gantry cannot cover the entire detector surface in a single slab position, the slab position can be adjusted and multiple scans can be used to cover the entire detector surface. In another embodiment, calibration with different slabs and thicknesses can be performed using a scan configuration with rotation.

[0085] Additional system variations at different rotational speeds (e.g., tube flux, ASG shadow, etc.) can be captured by air scans and reference detectors and corrected accordingly in the air flux term N0 of the forward model. For example, air scans can be performed at each rotational speed before patient / object scans to calibrate ASG deviations, as well as other beam path variations during rotation that induce incident flux variations across the detector in various fields of view.

[0086] Referring to Figure 8, various calibration slabs can be combined in a direction along at least a portion of the length of the patient bed to form a long, wedge-shaped phantom. That is, the slabs may be configured to have multiple heights. As shown in Figure 8, each calibration path length can be detected without readjusting the phantom by moving the position of the bed (or whatever transport mechanism is used to carry the slabs), thus accelerating the calibration process.

[0087] To capture spectral variations across the entire fan beam after the bowtie filter and detector response variations across different detector pixels, this calibration process can be performed pixel by pixel in each bowtie / filter configuration. Combined pixel mode (N T ×N C For this, the calibration can be performed based on the measurement of the sum (or average) of the combined pixels of each filter configuration. For example, Figure 9 shows various summing schemes for discrimination calibration and processing, where the following object scan material discrimination can choose to use one of the summing patterns with the corresponding calibrated table. The summing schemes shown in Figure 9 are calibrations based on A) the sum over the macro pixel pitch, e.g., 3x3 combined mode, B) the sum over the row direction (e.g., 1x3 combined mode), C) the sum over the channel direction (e.g., 3x1 combined mode), and D) the individual micro pixels (e.g., 1x1).

[0088] As shown in Figure 10, to increase the combination of calibration path lengths for each slab calibration, the X-ray tubes can be placed in various locations and the slabs can be fixed horizontally in the XY plane. When performing a stationary scan, the scan is performed with the X-ray tubes fixed at each position indicated by "-θ", "0", and "θ". That is, the stationary scan is performed with the X-ray tubes fixed at each of several positions with different irradiation angles. Figure 10 is a schematic diagram showing how the path lengths of different slab scans can be formed by arranging multiple tubes in this calibration. As an example, for a given slab thickness T, the fan angle φ iIn the detector pixel i located at (1), when the tube is positioned at different locations (-θ, 0, θ), the measured path length is given by equations (14), (15), and (16).

[0089]

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[0092] Here, "x1 = θ - φ" and "x2 = θ + φ". In one embodiment, a typical range for φ can be between 0 and 25 degrees, and θ can be selected between 20 and 60 degrees, depending on the spacing of the slab thickness. By using this park-and-shoot method, the path length sample for most detector channels can be tripled, thus significantly reducing the number of calibration slabs required to cover the same or wider path length range. The calibration sample can also be further increased by stopping the tube at four or more positions according to the same calculation method as above. For wide-cone systems, the calibration path length must be calculated based on the angle projected in both the channel direction and the row direction.

[0093] In one embodiment, the slab is flat and kept horizontal during calibration. This is to reduce / control uncertainty in the path length. In another embodiment, the slab does not necessarily have to be flat or horizontal as long as the path length is known and controlled. For example, the slab is not limited to a flat plate, but may be shaped like a column, cone, or polyhedron. That is, the shape of the slab is not particularly limited as long as the path length can be determined and the path length changes depending on the irradiation angle. The slab may also be configured to have multiple widths of different heights. For example, the slab may be constructed by stacking multiple plates of different widths. Furthermore, the slab is not limited to being positioned horizontally, but may also be positioned vertically or at an inclination.

[0094] Furthermore, in one embodiment, each slab is composed of a single material. In another embodiment, the slab does not necessarily have to consist of a single material. For example, the slab may contain multiple materials. Examples of materials for the slab include polypropylene, water, aluminum, titanium / copper, microstructure surrogates, other polymers, stainless steel or other metals, k-edge materials, and various microstructure mimics. When the slab is composed of multiple materials, the slab may be composed of a combination of a first member made of the first material and a second member made of the second material, or it may be composed of a single member in which part is the first material and the other part is the second material.

[0095] At least one slab can also be arranged in various ways to obtain multiple path lengths from one or more materials. For example, multiple slabs can be arranged adjacent to a patient's bed for scanning as the patient's bed moves within the radiography gantry. The multiple slabs can be at the same height for multiple materials, at multiple heights for the same material, or at multiple heights for multiple materials. In another exemplary embodiment, the slabs can be held and suspended within the field of view of the CT scanner (e.g., using a robotic arm). In another exemplary embodiment, the multiple slabs can be aligned with a z-direction shift between each pair of adjacent slabs. Multiple stepwise path length data can be acquired sequentially as the slabs enter and exit the scan field of view.

[0096] In one embodiment, it can be understood that the above technology can be applied to a CT scanner or CT device. Figure 11 shows an implementation of a horizontal radiography gantry included in a CT scanner or CT device. As shown in Figure 11, the radiography gantry 1150 (shown from the side) includes an X-ray tube 1151, an annular frame 1152, and a multi-row or two-dimensional array type X-ray detector 1153. The X-ray tube 1151 and the X-ray detector 1153 are mounted diametrically across an object OBJ (e.g., a patient) on the annular frame 1152, which is rotatably supported around a rotation axis RA. A rotation unit 1157 rotates the annular frame 1152 at a high speed, such as 0.4 seconds / revolution, while the object OBJ (e.g., a patient) moves in and out of the illustrated page along axis RA.

[0097] Embodiments of the X-ray CT apparatus according to the present invention will be described below with reference to the figures in the attached drawings. Note that X-ray CT apparatuses include various types of devices, such as rotary / rotating apparatuses in which the X-ray tube and X-ray detector rotate together around the object being inspected, and stationary / rotating apparatuses in which many detection elements are arranged in a ring or plane, and only the X-ray tube rotates around the object being inspected. The present invention can be applied to any of these types. Here, the currently dominant rotary / rotating type will be given as an example.

[0098] The multislice X-ray CT system further includes a high-voltage generator 1159 that generates a tube voltage applied to the X-ray tube 1151 via a slip ring 1158 so that the X-ray tube 1151 generates X-rays. The X-ray detector 1153 is positioned on the opposite side of the X-ray tube 1151 across the object OBJ (e.g., the patient) to detect emitted X-rays that have passed through the object OBJ (e.g., the patient). The X-ray detector 1153 further includes individual detector elements or units and may also be a photon counting detector. In the fourth-generation geometric system, the X-ray detector 1153 may be one of several detectors arranged in a 360° arrangement around the object OBJ (e.g., the patient).

[0099] The CT scanner further includes other devices for processing the signals detected from the X-ray detector 1153. The data acquisition circuit or data acquisition system (DAS) 1154 converts the signals output from the X-ray detector 1153 of each channel into voltages, amplifies the signals, and further converts the signals into digital signals. The X-ray detector 1153 and DAS 1154 are configured to process a predetermined total number of projections per rotation (TPPR).

[0100] The above data is transmitted via a non-contact data transmitter 1155 to a processing unit 1156 housed in a console outside the radiography gantry 1150. The processing unit 1156 performs specific corrections, such as sensitivity correction, on the raw data. Memory 1162 stores the resulting data (also called projection data at the stage immediately preceding the reconstruction process). Memory 1162, along with the reconstruction unit 1164, input unit 1165, and display 1166, is connected to the system controller 1160 via a data / control bus 1161. The system controller 1160 controls a current regulator 1163, which limits the current to a level sufficient to drive the CT system. In one embodiment, the system controller 1160 implements optimized scan acquisition parameters as described above. The reconstruction unit 1164 may include circuitry configured to perform the above techniques, such as method 600. The reconstruction unit 1164 is an example of a processing unit.

[0101] The methods and systems described herein can be implemented in many technologies, but generally relate to imaging apparatuses and / or processing circuits for performing the technologies described herein. In one embodiment, the processing circuit is implemented as one of the following circuits: an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a Generic Array of Logic (GAL), a Programmable Array of Logic (PAL), a circuit of logic gates enabling one-time programmability (e.g., using fuses) or a circuit of reprogrammable logic gates, or a combination thereof. Furthermore, the processing circuit may include a computer processor circuit having embedded and / or external non-volatile computer-readable memory (e.g., RAM, SRAM, FRAM®, PROM, EPROM, and / or EEPROM) for storing computer instructions (binary executable instructions and / or interpreted computer instructions) for controlling the computer processor to perform the processes described herein. A computer processor circuit can implement a single processor or multiple processors having a single core or multiple cores, each of which supports a single thread or multiple threads, and each of which can implement a single processor or multiple processors having a single core or multiple cores.

[0102] This disclosure presents a two-stage material discrimination calibration method and apparatus design for a full-size photon counting CT system, comprising the following key components: Slabs of known materials and thicknesses are used for two-stage material discrimination calibration in a third-generation PCD-based CT system. A slab of each selected material, appropriately sized to cover the entire surface of the detector, is used for the calibration scan, and the slab may need to be horizontal during the scan. A static scanning scheme using multiple fixed X-ray tube positions is designed to increase the calibration path length sample for each slab thickness, and the calibration procedure can be accelerated by stacking slabs of various thicknesses and materials in the Z direction. The calibration path length range is designed to cover the size / shape of the target scan object. The calibration path length sample or range can be the same across all detector channels in the entire fan beam, or subgroups of samples can be used to target path length ranges for object scans across different detector channels. The sample and result tables used for calibration can be specific to the imaging task. To correct the differences in shadows between static calibration scans and rotational object scans, an air scan under the same data acquisition conditions is used to extract detection geometric efficiency coefficients at each rotational speed, while also providing normalization of the tube flux using a tube-side reference detector, similar to the method used in conventional CT systems.

[0103] According to at least one embodiment described above, the calibration method in an X-ray scanner system can be made more efficient.

[0104] While several embodiments of the present invention have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These embodiments can be carried out in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalents. [Explanation of symbols]

[0105] 1150: Radiography gantry 1164: Reconfiguration device

Claims

1. Place at least one slab within the field of view of the X-ray scanner system, In the aforementioned X-ray scanner system, the slab is scanned from multiple different angles using multiple X-ray tubes, each positioned at multiple locations with different irradiation angles relative to the slab. Based on the aforementioned scan, material discrimination data is generated, Based on the aforementioned material discrimination data, the forward model of the X-ray scanner system is calibrated. A calibration method that includes the following.

2. The calibration method according to claim 1, wherein the slab has a shape in which the path length changes according to the irradiation angle.

3. Using the X-ray tube at at least one rotational speed, air calibration data is generated based on at least one air scan. Calibrating the forward model of the X-ray scanner system based on the aforementioned material discrimination data and the aforementioned air calibration data. The calibration method according to claim 1, including the following:

4. The calibration method according to claim 1, wherein the scan is performed with the position of each of the plurality of X-ray tubes fixed at each of the plurality of positions with different irradiation angles.

5. The calibration method according to claim 1, wherein the substance discrimination data includes a weighted bin response and a pulse pile-up correction term.

6. The calibration method according to claim 1, wherein the forward model includes a weighted bin response, a pulse pile-up correction term, at least one linear damping coefficient in the slab, at least one path length in the slab, and air calibration data.

7. The calibration method according to claim 1, wherein the slab is positioned horizontally within the field of view of the X-ray scanner system.

8. The calibration method according to claim 1, wherein the slab is arranged such that at least some of the X-ray paths pass through the slab at each of the irradiation angles.

9. The calibration method according to claim 1, further comprising scanning an object after the calibration of the forward model of the X-ray scanner system.

10. The calibration method according to claim 9, wherein the slab is composed of multiple materials.

11. The calibration method according to claim 1, wherein the X-ray scanner system is a photon counting CT scanner system.

12. The calibration method according to claim 1, wherein the slab has multiple heights.

13. The calibration method according to claim 1, wherein the slab has a plurality of widths that differ in the height direction.

14. At least one slab positioned within the field of view of the X-ray scanner system, In the aforementioned X-ray scanner system, the slab is scanned from multiple different angles using multiple X-ray tubes, each positioned at multiple locations with different irradiation angles relative to the slab. Based on the aforementioned scan, material discrimination data is generated, A processing unit that calibrates the forward model of the X-ray scanner system based on the aforementioned material discrimination data. An X-ray scanner system equipped with [the following features].

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