Medical image processing method and medical image processing apparatus

Abstract

To improve the quality of images acquired by photon counting CT using automatic exposure control. [Solution] The method includes obtaining calibration scan data from calibration scans performed using multiple slabs, performing function fitting based on the calibration scan data to generate a fitting function that represents the relationship between a count measurement value detected for one of the multiple slabs and the tube current applied to the X-ray tube, and which corresponds to the multiple slabs, establishing a calibration table based on the calibration scan data, obtaining subject scan data from subject scans performed on the imaging target, performing data correction on the subject scan data based on the calibration table and the multiple fitting functions, and reconstructing an image of the imaging target based on the data correction.

Description

[Technical Field]

[0001] Embodiments disclosed herein and in the drawings relate to medical image processing methods and medical image processing apparatus. [Background technology]

[0002] This application relates to Patent Document 1, titled "TWO-STEP MATERIAL DECOMPOSITION CALIBRATION METHOD FOR A FULL SIZE PHOTON COUNTING COMPUTED TOMOGRAPHY SYSTEM," filed on June 29, 2020, and granted on February 15, 2022; Patent Document 2, titled "COUNTING RESPONSE AND BEAM HARDENING CALIBRATION METHOD FOR A FULL SIZE PHOTON-COUNTING CT SYSTEM," filed on January 22, 2021, and granted on May 23, 2023; and Patent Document 3, titled "MATERIAL DECOMPOSITION CALIBRATION METHOD AND APPARATUS FOR A FULL SIZE PHOTON COUNTING CT SYSTEM," filed on March 31, 2021, and granted on April 2, 2024. The contents of the above patents are incorporated herein by reference.

[0003] This disclosure relates to X-ray computed tomography (CT) imaging technology based on a photon counting detector.

[0004] Computed tomography (CT) imaging is commonly used in medical diagnosis. Generally, a radiation source, such as an X-ray tube, irradiates the patient's body at a series of projection angles, generating projection images from various viewpoints. These projection images can then be used to reconstruct an image of the patient's body.

[0005] However, ionizing radiation from CT scans may increase the risk of developing cancer later in life. CT scans have been reported to provide the highest total medical radiation exposure in the United States compared to other medical imaging modalities.

[0006] Generally, different diagnostic CT imaging protocols require varying exposure levels for different anatomical structures of the body. Ideally, the patient should be scanned with the lowest possible radiation dose while producing clinically acceptable image quality. However, dose reduction often results in a low signal-to-noise ratio (SNR), which can affect the detection of specific structures or pathological conditions.

[0007] One effective approach to address this problem in CT imaging is modulation of the X-ray tube current, known as Automatic Exposure Control (AEC). AEC aims to simplify the radiologist's workflow by automatically optimizing the exposure of a CT scan by reducing the amount of radiation to the patient's body while maintaining consistent image quality. This approach is widely applied across various protocols and anatomical areas of CT scanners, including Photon Counting Detector (PCD) based CT.

[0008] Because most patients have asymmetrical anatomical shapes, the X-ray tube current can be modulated within the XY plane and along the Z axis during one rotation. This modulation takes into account changes in decay path length to optimize the balance between image quality and patient dose efficiency in order to achieve a more uniform dose across the detector surface throughout the scan. However, the calibration of the forward model of a PCD detector typically uses data samples acquired under individual tube currents, which presents challenges to the calibration or correction of PCD-based CT scanners by AEC design.

[0009] Therefore, it is desirable to develop improved calibration or correction approaches for PCD CT scanners equipped with AEC modulation. [Prior art documents] [Patent Documents]

[0010] [Patent Document 1] U.S. Patent No. 11249035 [Patent Document 2] U.S. Patent No. 11653892 [Patent Document 3] U.S. Patent No. 11944484 [Overview of the project] [Problems that the invention aims to solve]

[0011] One of the problems that the embodiments disclosed herein and in the drawings aim to solve is to improve the quality of images acquired by a photon counting CT using automatic exposure control. 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]

[0012] The medical image processing method according to the embodiment is a method for performing subject scan data correction in an X-ray imaging system including a photon counting detector and an X-ray tube for irradiating X-rays, the method including obtaining calibration scan data from a calibration scan performed using a plurality of slabs, performing function fitting based on the calibration scan data to generate a fitting function representing the relationship between the count measurement value detected for one of the plurality of slabs and the tube current applied to the X-ray tube, generating a plurality of fitting functions corresponding to the plurality of slabs, establishing a calibration table based on the calibration scan data, obtaining subject scan data from a subject scan performed on an imaging target, performing data correction on the subject scan data based on the calibration table and the plurality of fitting functions, and reconstructing an image of the imaging target based on the data correction.

Brief Description of Drawings

[0013] [Figure 1] FIG. 1 is a diagram showing an example of a bin response function of a photon counting detector according to an embodiment. [Figure 2A] FIG. 2A is a diagram showing an air scan and a slab scan performed during a calibration procedure according to an embodiment. [Figure 2B] FIG. 2B is a diagram showing an air scan and a slab scan performed during a calibration procedure according to an embodiment. [Figure 2C] FIG. 2C is a diagram showing an air scan and a slab scan performed during a calibration procedure according to an embodiment. [Figure 3] FIG. 3 is a block diagram of a subject scan data correction apparatus according to an embodiment. [Figure 4] FIG. 4 is a diagram showing a flowchart of a subject scan data correction process including an offline part and an online part according to an embodiment. [Figure 5] FIG. 5 is a block diagram of a calibration scan data processing circuit and a subject scan data correction circuit according to an embodiment. [Figure 6] Figure 6 shows an exemplary function fitting of slab count measurements along the tube current axis according to this embodiment. [Figure 7] Figure 7 shows an exemplary fitting function for a selected detector pixel according to this embodiment. [Figure 8] Figure 8 shows a two-dimensional projection according to an embodiment, which projects the detected count measurement value onto the projected count measurement value at the nearest calibration tube current. [Figure 9] Figure 9 is a flowchart showing the subject scan data correction process, including the offline and online sections according to the embodiment. [Figure 10] Figure 10 is a block diagram of the calibration scan data processing circuit and the subject scan data correction circuit according to the embodiment. [Figure 11] Figure 11 shows an example of the calculation of supplemental calibration data using the fitting function according to the embodiment. [Figure 12] Figure 12 is a flowchart showing the subject scan data correction process, including the offline and online sections according to the embodiment. [Figure 13] Figure 13 is a block diagram of the calibration scan data processing circuit and the subject scan data correction circuit according to the embodiment. [Figure 14] Figure 14 is a flowchart showing the subject scan data correction process, including the offline and online sections according to the embodiment. [Figure 15] Figure 15 shows an example of a photon counting computed tomography scanner system that can incorporate the technology according to this embodiment. [Modes for carrying out the invention]

[0014] The following disclosure provides many different embodiments, or examples, for carrying out different features of the subject matter provided. Specific examples of components and arrangements are described below for the sake of simplicity in this disclosure. Of course, these are merely examples and are not intended to be limiting.

[0015] For example, the order in which the different steps described herein are presented is for clarity. In general, these steps can be performed in any suitable order. Furthermore, although each of the different features, techniques, and configurations of this specification may be discussed in different places within this disclosure, each of the concepts is intended to be performed independently or in combination with one another. Thus, this disclosure can be embodied and considered in many different ways.

[0016] Furthermore, as used herein, words such as "a, an" generally mean "one or more" unless otherwise specified.

[0017] Traditionally, energy-integrating detectors (EIDs) and photon-counting detectors (PCDs) have been used to measure computed tomography (CT) projection data. PCDs offer several advantages, including the ability to perform spectral CT. In this case, the PCD decomposes the count of incident X-rays into spectral components called energy bins, and these energy bins collectively span the energy spectrum of the X-ray beam. Unlike non-spectral CT, spectral CT generates information attributable to different materials exhibiting different X-ray attenuations, as a function of X-ray energy. These differences allow for the discrimination of spectrally decomposed projection data to different material components. For example, two material components for material discrimination could be bone and water.

[0018] While PCDs offer rapid response times, the high X-ray flux rates characteristic of clinical X-ray 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, potentially degrading the image reconstructed from the PCD. With these effects corrected, spectral CT offers many advantages over conventional CT. Because spectral CT extracts complete tissue characterization information from scanned objects, various clinical applications can benefit from spectral CT technology, including improved material identification.

[0019] One challenge in using semiconductor-based PCDs more effectively for 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 degrade the material components resulting from material discrimination.

[0020] As mentioned above, in photon counting CT systems, semiconductor-based detectors using direct conversion are designed to resolve the energy of individual incident photons and measure multiple energy bin counts for each integration period. However, due to the detection physical properties 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 the associated front-end electronics. As stated above, because the signal induction time is finite, under high counting rate conditions, the energy response is also distorted by pulse pile-up.

[0021] Due to the heterogeneity of the sensor material and the complexity of the integrated detection system, accurately modeling the detector response of a PCD based solely on Monte Carlo simulations using physical theory or specific modeling of the signal induction process that determines the accuracy of the forward model for each measurement is difficult. Furthermore, uncertainties in modeling the incident X-ray tube spectrum introduce additional errors into the forward model. All of these factors ultimately degrade the decay line integral accuracy (in counting imaging mode) or material discrimination accuracy (in spectral imaging mode) obtained from PCD measurements, and consequently affect the quality of the generated spectral image.

[0022] Figure 1 shows an example of the bin response function of a photon counting detector. Specifically, Figure 1 shows the bin response function S of the photon counting detector. b An example (E) is shown, where each curve represents an exemplary function for the energy bin. As illustrated, due to charge sharing, pulse pile-up effects, etc., the bin response function has a very wide distribution beyond the ideal bin energy window for each counter.

[0023] As described above, Patent Documents 1, 2, and 3 propose PCD forward models and calibration methods for both counting imaging mode and spectral imaging mode. Generally, calibration procedures can be applied based on multiple transmission measurements of various known attenuation path lengths, and the forward model can be refined to match the calibration measurements. These approaches typically use static scans with material of a predetermined thickness (often in the form of a rectangular slab).

[0024] For example, if the number of energy bins is n, the PCD forward model is given by equation (1).

[0025]

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[0026] Here, E represents the incident energy, E’ represents the measured energy, and N b,j represents the count measured at a given detector pixel j for energy bin b, and Φ b (E’) represents a binning function that models the function of a data acquisition system (Data Acquisition System: DAS) (or ASIC) that generates digital data indicating the counts detected by the detector. Φ b (E’) is given as follows.

[0027] [Number]

[0028] Here, T b and T b+1 are the low energy threshold and high energy threshold of energy bin b, E min and E max are the low energy threshold and high energy threshold of the incident spectrum energy range, N 0,j is the incident beam spectrum, which can be represented by the air flux measured at detector pixel j using an air scan, and S 0,j (E)D(E,E’) is the detector response calibration term (“DR”).

[0029] [Number]

[0030] As described above, in order to calibrate the parameters of the forward model, a series of slab scans using known materials and thicknesses can be performed. N b,i,j Taking N as the measured count at detector pixel j for energy bin b and slab i (i = 1, ···, m), the parameters of the PCD forward model can be determined by solving a minimization problem using Equation (2).

[0031] [Number]

[0032] Here, y b,i With respect to the energy bin b, slab i, and detector pixel j, a specific air flux N is given based on equation (1). 0,j Under DR j This is a figure calculated using [a specific method / tool].

[0033] Note that the above formula is provided for the spectral imaging mode of photon counting CT. When photon counting CT operates in counting imaging mode, the calculation can be shortened as follows:

[0034]

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[0035]

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[0036] For example, if PCD calibration scan data is acquired using slab "1, ..., m", this procedure is performed using the following attenuation sample att i A series of measurements are generated using this method.

[0037]

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[0038] Figures 2A, 2B, and 2C show air scans and slab scans using different combinations of known materials and thicknesses. Specifically, Figures 2A-2C show air scans and slab scans performed during the calibration procedure, with the slab scans using different combinations of known materials and thicknesses. In the examples shown in Figures 2B-2C, the PCD calibration slab scan utilizes two base materials (i.e., K=2), such as solid water / aluminum or other similar combinations (e.g., iodine, calcium, etc.), to cover the decay phase space that may occur in the sample scan. Each of these data points N b,i,j (In spectral imaging mode, or in counting imaging mode, N tot,i,j ) is used to calculate the cost function.

[0039] For practical reasons, calibration procedures are generally performed with individual tube currents. The calibration data is then used to generate calibration tables associated with these specific tube currents. Performing subsequent subject scans on the imaging target with the same fixed tube currents used during the calibration procedure allows for sufficiently accurate calibration based on these calibration tables.

[0040] However, applying calibration tables under uncalibrated flux conditions makes it difficult to achieve the required accuracy. For example, calibration tables associated with low tube currents cannot be directly used to calibrate subject scan data acquired at high tube currents because it increases the pile-up effect in the measured values.

[0041] Furthermore, compared to conventional EID CT, PCD CT generally has smaller pixel elements, resulting in significantly larger data sizes. Given the limited calibration time available for CT imaging systems in clinical settings, maintaining a manageable size for processing and reconstructing subject scan data remains a challenging task.

[0042] This disclosure provides a method and apparatus for enabling accurate calibration or correction in a photon-counting CT with AEC modulation, even when calibration scans are performed at individual tube current points. This method and apparatus can be applied in the context of the PCD forward models and calibration methods described in Patent Documents 1, 2, and 3. However, this method and apparatus can also be applied to any PCD calibration or correction scheme that uses calibration data acquired at individual tube current points. The CT imaging system is not limited to CZT / CdTe PCD, and other semiconductor materials that experience similar problems in terms of uniformity of detector response between pixels and pile-up effects that distort the response under different flux conditions can also be used.

[0043] Figure 3 shows a block diagram of a subject scan data correction device 300 according to an embodiment of the present disclosure. The subject scan data correction device 300 includes a calibration scan data acquisition circuit 310, a calibration scan data processing circuit 320, a subject scan data acquisition circuit 330, a subject scan data correction circuit 340, and a target image reconstruction circuit 350. The various circuits included in the subject scan data correction device 300 are examples of processing circuits.

[0044] Figure 3 shows a block diagram of a subject scan data correction device 300 according to an embodiment of the present disclosure. The subject scan data correction device 300 includes a calibration scan data acquisition circuit 310, a calibration scan data processing circuit 320, a subject scan data acquisition circuit 330, a subject scan data correction circuit 340, and a target image reconstruction circuit 350.

[0045] The calibration scan data acquisition circuit 310 acquires scan data generated from the calibration procedure and transmits it to the calibration scan data processing circuit 320. As described above, the calibration procedure may include an air scan and multiple slab scans performed on slabs with different attenuation path lengths, and individual tube currents are applied to the X-ray tubes. The tube currents applied to the X-ray tubes are also referred to as the first number (n1) of tube currents. The calibration scan data processing circuit 320 processes the received data to generate a set of calibration tables related to those individual tube currents applied during the calibration procedure, as well as a set of fitting functions related to the slabs.

[0046] For example, in one embodiment, a fitting function generated based on calibration scan data can be used to process the subject scan data as if it had been acquired with the tube current used during the calibration procedure applied. In another embodiment, supplementary calibration data can be calculated based on the fitting function, while the subject scan data can remain unchanged. An alternative embodiment may include calculating a supplementary calibration table based on a calibration table generated using the calibration scan data, and both the supplementary calibration table and the generated calibration table can then be used to correct the subject scan data.

[0047] The subject scan data acquisition circuit 330 acquires scan data generated from a subject scan performed on the imaging target and transmits it to the subject scan data correction circuit 340. The subject scan data correction circuit 340 performs data correction of the subject scan data based on a calibration table and a fitting function. Subsequently, the target image reconstruction circuit 350 reconstructs the image of the imaging target based on this data correction.

[0048] Figure 4 shows a flowchart of the subject scan data correction process according to an embodiment of the present disclosure. The subject scan data correction process includes an offline unit 400 performed on calibration scan data and an online unit 450 performed on subject scan data.

[0049] The offline unit 400 is started in step S405 by acquiring calibration scan data generated by a calibration procedure including air scan and slab scan. In step S410, function fitting is performed to generate a fitting function corresponding to the slab based on the calibration scan data. In step S415, a calibration table is established based on the calibration scan data for use in correcting the subject scan data.

[0050] The online unit 450 is started in step S455 by acquiring subject scan data generated by a subject scan performed on the imaging target. In step S460, data correction is performed on the acquired subject scan data based on the calibration table and fitting function. In step S465, the target image of the imaging target is reconstructed based on the data correction.

[0051] Processing of calibration scan data and correction of subject scan data are described below with reference to different embodiments of this disclosure.

[0052] Figure 5 shows a block diagram of a calibration scan data processing circuit 320 and a subject scan data correction circuit 340 according to one embodiment of the present disclosure. The calibration scan data processing circuit 320 includes a calibration scan data receiving circuit 510, a current-dependent calibration table generation circuit 520, a slab eigenfunction fitting circuit 530, and a calibration table storage unit 540. The subject scan data correction circuit 340 includes a subject scan data receiving circuit 550, a subject scan data projection circuit 555, a calibration table search circuit 560, and a line integral sinogram generation circuit 570. The various circuits included in the calibration scan data processing circuit 320 and the subject scan data correction circuit 340 are examples of processing circuits.

[0053] The calibration scan data receiving circuit 510 receives calibration scan data from the calibration scan data acquisition circuit 310 and transmits the received data to the current-dependent calibration table generation circuit 520 and the slab eigenfunction fitting circuit 530. The current-dependent calibration table generation circuit 520 generates a calibration table based on the calibration scan data and stores the calibration table in the calibration table storage unit 540.

[0054] As mentioned earlier, the detector response of an EID CT is uniform with respect to the incident flux, making its modeling straightforward. However, due to the pulse pile-up effect, the detector response of a PCD CT is sensitive to the incident flux and therefore sensitive to the tube current. To calibrate for such effects and other distortions, different slab measurements N at individual tube currents are required. i The parameters of the detector response forward model need to be calibrated using (m,j), where i is the energy bin index, m is the slab index, and j is the tube current index. Then, based on the known path length of the slab used and the measured bin counts, a set of forward model calibration tables can be generated.

[0055] Furthermore, reference normalization can also be applied to slab scan data. For example, a reference detector can be installed on the X-ray tube side to detect the tube output flux. The readout from the reference detector is proportional to the incident flux to the main pixel array of the PCD detector. Therefore, the PCD output bin count can be normalized by the reference detector reading as follows, before subsequent data processing.

[0056]

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[0057] Here, D ref This value is from the reference detector on the tube side. Note that this reference normalization can be applied not only to calibration scan data but also to subject scan data. For simplicity, in the following explanation, unless otherwise specified, all measured counts refer to the counts derived after this reference normalization.

[0058] Based on the behavior of slab scan data at different tube currents, the slab eigenfunction fitting circuit 530 determines a fitting function that maps the relationship between the count measurement and the applied tube current. Figure 6 shows an exemplary linear fitting function for a selected slab's reference normalized count measurement at a selected detector pixel across a range of tube currents. As seen in Figure 6, the fitted count closely matches the measured count within a bar of statistical error.

[0059] Figure 7 shows exemplary fitting functions for multiple slabs in a selected detector pixel according to embodiments of the present disclosure. Each fitting function represents the relationship between the count measurement obtained from the corresponding slab and the tube current applied to the X-ray tube. In Figure 7, the top-to-bottom curves represent the fitting functions generated for slabs ranging from thin to thick. For thinner slabs, the reference normalized count decreases as the tube current increases due to the pulse pile-up effect. For thicker slabs, the change in the tube current range is smaller. This is because the count rate decreases rapidly in thicker slabs, and the pile-up effect becomes very small.

[0060] By considering the statistical error of the measurements, the parameters of the fitting function can be estimated, for example, using the weighted least squares method. Depending on the number of tube currents applied in the calibration scan, a polynomial of a different order (k) can be selected as the fitting function, where "k-1" is smaller than the total number of calibration tube current points to prevent overfitting.

[0061]

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[0062]

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[0063] The parameter {a} can be determined by minimizing the following equation.

[0064]

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[0065] Once parameter {a} is determined, the fitting function can be used by the subject scan data projection circuit 555 for two-dimensional data projection, as described later.

[0066] The subject scan data receiving circuit 550 receives subject scan data from the subject scan data acquisition circuit 330 and transmits it to the subject scan data projection circuit 555. Based on the fitting function, the subject scan data projection circuit 555 projects the count measurement values ​​at each pixel of the PCD detector onto the projected count measurement values ​​for each view of the subject scan data.

[0067] For example, in a scenario where a slab scan is performed with four fixed tube currents of 50mA, 100mA, 150mA, and 200mA, the current-dependent calibration table generation circuit 520 generates calibration tables for these individual tube current points. However, in subsequent subject scans with an AEC design, the tube current may be automatically modulated for each view over a continuous range based on the decay path length of the object being imaged. For example, some views of the subject scan data may be acquired with tube currents such as 60mA and 70mA. Directly applying the calibration tables for 50mA, 100mA, 150mA, and 200mA would not provide the accuracy required to calibrate these views.

[0068] In this embodiment, count measurements obtained from a subject scan with AEC modulation can be converted to count measurements at the nearest calibrated tube current based on a fitting function. For example, Figure 8 shows a two-dimensional projection for projecting the detected count measurement onto a projected count measurement at the nearest calibrated tube current.

[0069]

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[0070]

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[0071]

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[0072]

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[0073]

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[0074] The fitting function f3, which corresponds to the decay path length of the view, can be obtained as a linear interpolation of the fitting functions f1 and f2.

[0075]

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[0076]

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[0077]

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[0078]

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[0079]

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[0080] The tube current y applied during a subject scan can be measured directly from the X-ray tube in mA units, or by a reference detector in any unit proportional to the tube output flux.

[0081] To ensure the accuracy of the linear interpolation in equations (9) and (10), the spacing of the slab path lengths should not be too large. The optimal spacing design should balance calibration time and interpolation accuracy. In one embodiment, the spacing of the slab path lengths is, for example, 5 cm or less.

[0082] In addition to the exemplary polynomial represented by equation (5), other types of fitting functions can be used, as long as the count measurements can be fitted with a reasonable number of parameters. The interpolation in equation (9) is not limited to a linear method between two fitting functions; if the error is sufficiently small, the nearest calibration point can be used, or it can be extended to two or more adjacent points using more complex interpolation methods such as cubic splines.

[0083] This two-dimensional interpolation can be applied to the subject scan data pixel by pixel and view by view. In counting imaging mode with AEC modulation, the total count N tot =ΣN i This is processed. In spectral imaging mode with AEC modulation, the individual energy bin counts N i This is processed.

[0084] To optimize the results of subject scans with AEC modulation, the fitting function and interpolation method can differ between counting imaging mode and spectral imaging mode, and even between individual energy bins in spectral imaging mode.

[0085] The subject scan data projection circuit 555 transmits the projected count measurements to the line integral sinogram generation circuit 570. The calibration table retrieval circuit 560 retrieves calibration tables from the calibration table storage unit 540 and transmits them to the line integral sinogram generation circuit 570. The line integral sinogram generation circuit 570 uses the projected count measurements to generate a line integral sinogram based on the retrieved calibration tables. The generated line integral sinogram is transmitted to the target image reconstruction circuit 350 for use in image reconstruction.

[0086] Figure 9 shows a flowchart of a subject scan data correction process, including an offline section 900 and an online section 950, according to an embodiment of the present disclosure. In step S905, calibration scan data is received, including slab scan data generated using multiple slabs of a predetermined attenuation path length with multiple tube currents applied to the X-ray tube. In step S910, function fitting is performed based on the calibration scan data to generate a fitting function for each of the multiple slabs. In step S915, a calibration table is generated based on the calibration scan data. Each calibration table corresponds to one of the multiple tube currents. In step S920, the generated calibration tables are stored for use in processing the subject scan data.

[0087] In step S955, the subject scan data is received. In step S960, a two-dimensional projection is performed pixel by pixel and view by view based on the subject scan data and fitting function, generating projected count measurements. In step S965, the stored calibration table is retrieved. In step S970, a line integral sinogram is generated using the projected count measurements based on the retrieved calibration table.

[0088] In the approach described in the above embodiment, a polynomial fitting function determined based on calibration scan data is used to project the count measurements obtained from the subject scan to the nearest calibration tube current point. This ensures accuracy when applying calibration tables prepared for individual fixed tube current points in subsequent data processing and correction.

[0089] In alternative embodiments of this disclosure, a polynomial fitting function is used to prepare a calibration table at more precise tube current points without altering the subject scan data. In other words, based on the fitting function, calibration data can be estimated at specific unapplied tube current points within the potential tube current range of the subject scan, and an additional calibration table can be created for these tube current points. Both the calibration table generated using the calibration data and the additional calibration table generated using the estimated calibration data can then be applied to data processing and correction of the subject scan data. This approach reduces data processing time at the online end because it does not require performing a two-dimensional projection on the subject scan data.

[0090] Figure 10 shows a block diagram of a calibration scan data processing circuit 320 and a subject scan data correction circuit 340 according to one embodiment of the present disclosure. The calibration scan data processing circuit 320 includes a calibration scan data receiving circuit 1010, a current-dependent calibration table generation circuit 1020, a slab eigenfunction fitting circuit 1030, a supplementary calibration data calculation circuit 1035, and a calibration table storage unit 1040. The subject scan data correction circuit 340 includes a subject scan data receiving circuit 1050, a calibration table search circuit 1060, and a line integral sinogram generation circuit 1070. The structure and function of the calibration scan data receiving circuit 1010, the slab eigenfunction fitting circuit 1030, the subject scan data receiving circuit 1050, the calibration table search circuit 1060, and the line integral sinogram generation circuit 1070 can be the same as those of the corresponding components shown in Figure 5. The various circuits included in the calibration scan data processing circuit 320 and the subject scan data correction circuit 340 are examples of processing circuits.

[0091] The supplemental calibration data calculation circuit 1035 receives fitting functions generated from the slab eigenfunction fitting circuit 1030. Using these fitting functions, the supplemental calibration data calculation circuit 1035 calculates supplemental calibration data for specific tube currents that are not applied during the slab scan and transmits the calculated data to the current-dependent calibration table generation circuit 1020. The current-dependent calibration table generation circuit 1020 not only generates a calibration table for the tube current points used during the slab scan, but also uses the calculated supplemental calibration data to generate a calibration table for the unapplied tube currents.

[0092] Figure 11 shows an example of calculating supplemental calibration data using a fitting function according to an embodiment of the present disclosure. In Figure 11, for tube current point x5 between tube current points x1 and x2 applied during slab scanning, the fitting functions f1~f are generated from the measured slab data (indicated by circular dots). m Based on (corresponding to slab 1~m), supplementary count measurements f1(x), f2(x5), ..., f m (x5) (shown in squares) can be calculated. Then, using supplemental count measurements, an additional calibration table for tube current x5 can be generated.

[0093]

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[0094] Furthermore, supplementary calibration data can be calculated at multiple unapplied current points distributed across the current range of the subject scan. This allows for the preparation of calibration tables for more current points without extending the calibration time. By generating a sufficiently fine calibration grid across the potential current range of the subject scan, errors in data processing and correction of the subject scan data can be suppressed.

[0095] Compared to the embodiments shown in Figures 5 and 9, the advantage of this embodiment is that more calculations are completed before the subject scan. This reduces the online scan data processing time and makes it easier to meet clinical workflow requirements.

[0096] Furthermore, there are methods for calculating supplemental calibration data for uncurrent-applied tube current points, which include more advanced fitting functions or interpolation schemes such as piecewise interpolation based on two adjacent tube current points and cubic splines using more neighboring measurements. The fitting function is not limited to polynomials; various functions that can accurately describe the data behavior along the tube current axis can be used.

[0097] Similar to the embodiments shown in Figures 5 and 9, in this embodiment the fitting function and method may differ between the counting imaging mode and the spectral imaging mode, and further between individual energy bins in the spectral imaging mode.

[0098] Figure 12 shows a flowchart of a subject scan data correction process, including an offline unit 1200 and an online unit 1250, according to an embodiment of the present disclosure. The offline unit 1200 is started in step S1205 by receiving calibration scan data, which includes slab scan data generated using multiple slabs of a predetermined path length with multiple tube currents applied to the X-ray tube. In step S1210, function fitting is performed based on the calibration scan data to generate a fitting function for each slab. In step S1215, supplemental calibration data is calculated for one or more unapplied tube currents based on the fitting function. The unapplied tube currents for which supplemental calibration data is calculated are examples of a second number (n2) of tube currents. In step S1220, a calibration table is generated based on the calibration scan data and the supplemental calibration data. Each calibration table corresponds to one tube current, including both applied and unapplied tube currents. A calibration table corresponding to a single tube current, which includes both the applied and unapplied tube currents, is an example of a third number (n3) subcalibration table. In step S1225, the generated calibration table is stored for use in correcting the subject scan data.

[0099] The online unit 1250 is started in step S1255 by receiving subject scan data. In step S1260, a stored calibration table is retrieved. In step S1265, a line integral sinogram is generated using the received subject scan data based on the retrieved calibration table. By using a calibration table corresponding to the nearest tube current point, selected from both the original calibration table and a supplementary calibration table, the correction accuracy of the subject scan data can be significantly improved.

[0100] Additional calibration tables for uncurrent-applied tube current points can be created using other methods. For example, these calibration tables can be generated by interpolating existing calibration tables prepared for adjacent tube current points that are applied during the calibration scan.

[0101] Figure 13 shows a block diagram of a calibration scan data processing circuit 320 and a subject scan data correction circuit 340 according to one embodiment of the present disclosure. The calibration scan data processing circuit 320 includes a calibration scan data receiving circuit 1310, a current-dependent calibration table generation circuit 1320, a calibration table interpolation circuit 1330, and a calibration table storage unit 1340. The subject scan data correction circuit 340 includes a subject scan data receiving circuit 1350, a calibration table search circuit 1360, and a line integral sinogram generation circuit 1370. The structure and function of the calibration scan data receiving circuit 1310, the current-dependent calibration table generation circuit 1320, the subject scan data receiving circuit 1350, the calibration table search circuit 1360, and the line integral sinogram generation circuit 1370 can be the same as those of the corresponding components shown in Figure 5. The various circuits included in the calibration scan data processing circuit 320 and the subject scan data correction circuit 340 are examples of processing circuits.

[0102] The calibration table interpolation circuit 1330 acquires the calibration table generated by the current-dependent calibration table generation circuit 1320 for the applied tube current points, performs interpolation on the acquired calibration table, and generates a supplementary calibration table for the unapplied tube current points. The calibration tables generated by both the current-dependent calibration table generation circuit 1320 and the calibration table interpolation circuit 1330 are stored in the calibration table storage unit 1340 for use in processing and correcting the subject scan data.

[0103] For example, assume that the PCD forward model at calibration tube current point mA1 is given by equation (12) below, and the forward model at the adjacent calibration tube current point mA2 is given by equation (13) below.

[0104]

number

[0105]

number

[0106] Therefore, when the tube current x is between mA1 and mA2, the forward model can be expressed as a linear combination of FW1 and FW2, where S0 and D are tunable components of the forward model with parameters calibrated from slab data.

[0107]

number

[0108] The coefficient c can be determined based on the value of the tube current x, as follows:

[0109]

number

[0110] The interpolation of the AEC forward model is not limited to the linear method of equation (14), but any form based on nearby tube current points can be used. By completing many calculations before the subject scan, the online scan data processing time can be reduced compared to the embodiments shown in Figures 5 and 9.

[0111] Figure 14 shows a flowchart of a subject scan data correction process, including an offline unit 1400 and an online unit 1450, according to one embodiment of the present disclosure. The offline unit 1400 is started in step S1405 by receiving calibration scan data, which includes slab scan data generated using multiple slabs of a predetermined path length while multiple tube currents are applied to the X-ray tube. In step S1410, a calibration table is generated based on the calibration scan data. In step S1415, a supplementary calibration table is generated by interpolating the generated calibration table. In step S1420, the generated calibration table and the supplementary calibration table are stored for use in correcting the subject scan data.

[0112] The online unit 1450 is started in step S1455 by receiving subject scan data. In step S1460, the stored calibration table is retrieved. In step S1465, a line integral sinogram is generated using the corrected subject scan data based on the retrieved calibration table.

[0113] There are no restrictions on the method used to generate the AEC tube current profile for subject scanning. Instead, various methods are available, such as using a scout scan to estimate the 3D path length profile of the object being imaged and generating the tube current profile of the scanned area accordingly.

[0114] The embodiments described herein can be used in a photon-counting CT scanner system, which comprises one or more X-ray tubes for emitting X-ray radiation and an array of detector pixels for receiving X-ray radiation propagating within the field of view (FOV) of the CT scanner system. The detector response correction scheme can be applied to both the PCD counting model and the spectral forward model.

[0115] The detector response correction approach can be implemented in a photon-counting CT scan system, as will be described later with reference to Figure 15. The X-ray CT apparatus 1 shown in Figure 15 includes a gantry 10, a patient table 30, and a console 40 that performs processing by a medical imaging processing device. For convenience of explanation, Figure 13 shows multiple gantry 10s.

[0116] In this embodiment, the rotation axis of the rotating frame 13 in the non-tilted state, i.e., the longitudinal direction of the top plate 33 of the bed 30, is defined as the "Z-axis direction," the axis direction perpendicular to the Z-axis direction and horizontal to the floor surface is defined as the "X-axis direction," and the axis direction perpendicular to the Z-axis direction and perpendicular to the floor surface is defined as the "Y-axis direction."

[0117] For example, the gantry frame 10 and patient bed 30 are installed in the CT examination room, and the console 40 is installed in a control room adjacent to the CT examination room. The console 40 is not necessarily installed in the control room. For example, the console 40 can be installed in the same room as the gantry frame 10 and patient bed 30. In any case, the gantry frame 10, patient bed 30, and console 40 are connected to each other via wired or wireless means so that they can communicate with one another.

[0118] The stand 10 is a scanner configured for performing X-ray CT imaging on a subject (or imaging target) P. The stand 10 includes an X-ray tube 11, an X-ray detector 12, a rotating frame 13, an X-ray high-voltage device 14, a control device 15, a wedge filter 16, a collimator 17, and a data acquisition system (DAS) 18.

[0119] The X-ray tube 11 is a vacuum tube that generates X-rays by emitting thermionic electrons from the cathode (filament) to the anode (target) in response to the application of high voltage and filament current from the X-ray high-voltage device 14. Specifically, X-rays are generated when thermionic electrons collide with the target. An example of the X-ray tube 11 is a rotating anode type X-ray tube that generates X-rays by emitting thermionic electrons to a rotating anode. The X-rays generated in the X-ray tube 11 are shaped into a cone beam by, for example, a collimator 17 and applied to the subject P.

[0120] The X-ray detector 12 detects the X-rays irradiated by the X-ray tube 11 and transmitted through the subject P, and outputs an electrical signal corresponding to the X-ray dose to the DAS 18. The X-ray detector 12 includes, for example, a plurality of X-ray detection element rows, each containing a plurality of X-ray detection elements aligned in the channel direction (X-axis direction, i.e., column direction) along an arc centered on the focal point of the X-ray tube 11. The X-ray detector 12 has an array structure in which a plurality of X-ray detection element rows, each containing a plurality of X-ray detection elements aligned in the channel direction, are aligned in the segment direction (Z-axis direction, i.e., column direction).

[0121] Specifically, the X-ray detector 12 can be, for example, a direct conversion type detector that includes a semiconductor element that converts incident X-rays into an electrical signal. The X-ray detector 12 is an example of a PCD according to this embodiment and is also called "PCD12".

[0122] The rotating frame 13 supports the X-ray generator and X-ray detector 12 so that they can rotate around a rotation axis. Specifically, the rotating frame 13 is an annular frame that supports the X-ray tube 11 and the X-ray detector 12 so that the X-ray tube 11 faces the X-ray detector 12, and rotates the X-ray tube 11 and the X-ray detector 12 under the control of a control device 15, which will be described later. The rotating frame 13 is rotatably supported by a fixed frame (not shown) made of metal such as aluminum. Specifically, the rotating frame 13 is connected to the end of the fixed frame via bearings. The rotating frame 13 rotates at a predetermined angular velocity around the rotation axis Z while receiving power from the driver of the control device 15.

[0123] In addition to the X-ray tube 11 and X-ray detector 12, the rotating frame 13 includes and supports an X-ray high-voltage device 14 and a DAS 18. Such a rotating frame 13 is housed in a substantially cylindrical casing in which an aperture (bore) 19 forming an imaging space is formed. The aperture approximately coincides with the field of view (FOV). The central axis of the aperture coincides with the rotation axis Z of the rotating frame 13. Detection data generated by the DAS 18 is transmitted, for example, from a transmitter (not shown) located in the non-rotating part of the mount (such as a fixed frame, not shown in Figure 13) to a receiver (not shown) and then forwarded to a console 40.

[0124] The X-ray high-voltage device 14 includes an electrical circuit such as a transformer and a rectifier, and includes a high-voltage generator that has the function of generating a high voltage to be applied to the X-ray tube 11 and a filament current to be supplied to the X-ray tube 11, and an X-ray control device configured to control the output voltage according to the X-rays irradiated by the X-ray tube 11. The high-voltage generator may be of the transformer type or the inverter type. The X-ray high-voltage device 14 may be installed on the rotating frame 13, which will be described later, or on the fixed frame (not shown) of the stand 10.

[0125] The control device 15 includes a processing circuit, including a CPU (Central Processing Unit), and a driver, such as a motor or drive unit. The processing circuit includes a processor, such as a CPU or microprocessor (MPU), and memory, such as read-only memory (ROM) or random access memory (RAM), as hardware resources. The control device 15 can be implemented using an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other complex programmable logic device (CPLD) or simple programmable logic device (SPLD). The control device 15 controls the X-ray high-voltage device 14 and DAS 18, etc., according to instructions from the console 40. The processor performs the above control by reading and executing a program stored in memory.

[0126] A CPU can execute computer programs that include a set of computer-readable instructions for performing the functions described herein, and these programs are stored in the non-transient electronic memory and / or on a hard disk drive, CD, DVD, flash drive, or any other known storage medium. Furthermore, computer-readable instructions may be provided as utility applications, background daemons, or components of an operating system, or a combination thereof, and may be executed in conjunction with processors and operating systems well known to those skilled in the art. Furthermore, a CPU can be implemented as multiple processors working concurrently and cooperatively to execute instructions.

[0127] Furthermore, the control device 15 has the function of controlling the operation of the frame 10 and the bed 30 in response to input signals from the console 40 or the input interface 43, which will be described later and is attached to the frame 10. For example, the control device 15 controls the rotation of the rotating frame 13, the tilting of the frame 10, or the operation of the bed 30 and the top plate 33 in response to the input signal. The control of tilting the frame 10 is performed by the control device 15 rotating the rotating frame 13 around an axis parallel to the X-axis direction based on tilt angle information input via the input interface 43 attached to the frame 10. The control device 15 can be installed in either the frame 10 or the console 40. The control device 15 may be configured by directly incorporating the program into the processor's circuitry rather than storing the program in memory. In this case, the processor performs the above-mentioned control by reading and executing the program incorporated into the circuitry.

[0128] The wedge filter 16 is a filter for adjusting the dose of X-rays irradiated from the X-ray tube 11. Specifically, the wedge filter 16 is a filter that allows X-rays irradiated from the X-ray tube 11 to pass through and attenuates the X-rays so that the X-rays irradiated from the X-ray tube 11 to the subject P exhibit a predetermined distribution. For example, the wedge filter 16 (or bowtie filter) is a filter obtained by processing aluminum to have a predetermined target angle and a predetermined thickness.

[0129] The collimator 17 is a lead plate or the like used to narrow the range of application of X-rays that have passed through the wedge filter 16, and includes a slit formed by combining lead plates or the like. The collimator 17 is sometimes called an "X-ray diaphragm".

[0130] The DAS18 generates digital data (also called "detection data") indicating the X-ray count detected by the X-ray detector 12 for each of several energy bands (also called "energy bins" or simply "bins"). The detection data is a set of data of count values ​​identified by the channel number and row number of the X-ray detection element from which it was generated, the view number indicating the collected view (also called the projection angle), and the energy bin number. The DAS18 is implemented, for example, by an application-specific integrated circuit (ASIC) that implements circuit elements capable of generating detection data. The detection data is transferred to the console 40.

[0131] The bed 30 is a device on which a subject P is placed, scanned, and moved, and includes a base 31, a bed drive device 32, a top plate 33, and a support frame 34.

[0132] The base 31 is a housing that supports the support frame 34 so that it can move in the vertical direction.

[0133] The patient bed drive unit 32 is a motor or drive unit that moves the tabletop 33 on which the patient P is placed in the longitudinal direction of the tabletop 33. The patient bed drive unit 32 moves the tabletop 33 according to control by the console 40 or the control device 15. For example, the patient bed drive unit 32 moves the tabletop 33 in a direction perpendicular to the patient P so that the body axis of the patient P placed on the tabletop 33 coincides with the central axis of the bore of the rotating frame 13. The patient bed drive unit 32 may also move the tabletop 33 in the axial direction of the patient P in accordance with X-ray CT imaging performed using the gantry 10. The patient bed drive unit 32 generates power by driving at a rotational speed corresponding to the duty cycle of the drive signal from the control device 15. The patient bed drive unit 32 is implemented by a motor such as a direct drive motor or a servo motor.

[0134] The top plate 33, provided on the upper surface of the support frame 34, is a plate on which the subject P is placed. The bed drive device 32 can move not only the top plate 33 but also the support frame 34 in the longitudinal direction of the top plate 33.

[0135] The console 40 includes a memory 41, a display 42, an input interface 43, and a processing circuit 44. Data communication between the memory 41, the display 42, the input interface 43, and the processing circuit 44 is performed via a bus. Although the console 40 is described separately from the mount 10, the mount 10 may include the console 40 or some of the components of the console 40.

[0136] Memory 41 is a storage device such as a hard disk drive (HDD), solid state drive (SSD), or integrated circuit storage device, and stores various types of information. For example, memory 41 stores projection data and reconstructed image data. Memory 41 is not limited to HDDs or SSDs, but may also be a driver that reads and writes various types of information to portable storage media such as CDs, DVDs, or flash memory, or to semiconductor memory such as random access memory (RAM). The storage area of ​​memory 41 may be provided within the X-ray CT apparatus 1, or it may be provided in an external storage device connected via a network. For example, memory 41 stores data of CT images or displayed images. Memory 41 also stores the control program according to this embodiment.

[0137] The display 42 displays various types of information. For example, the display 42 outputs medical images (CT images) generated by the processing circuit 44 and a GUI (Graphical User Interface) for receiving various operations from the operator. As the display 42, for example, a liquid crystal display (LCD), a cathode ray tube (CRT) display, an organic electroluminescent display (OELD), a plasma display, or any other display can be used as appropriate. The display 42 may be mounted on the stand 10. The display 42 may be a desktop type, or it may consist of a tablet terminal that can communicate wirelessly with the console 40.

[0138] The input interface 43 receives various input operations from the operator, converts the received input operations into electrical signals, and outputs the electrical signals to the processing circuit 44. For example, the input interface 43 receives from the operator the acquisition conditions for collecting projection data, the reconstruction conditions for reconstructing CT images, and the image processing conditions for generating post-processed images from CT images. As the input interface 43, for example, a mouse, keyboard, trackball, switch, button, joystick, touchpad, or touch panel display can be used as appropriate. In this embodiment, the input interface 43 does not necessarily include physical operating components such as a mouse, keyboard, trackball, switch, button, joystick, touchpad, or touch panel display. For example, the input interface 43 also includes an electrical signal processing circuit that receives electrical signals corresponding to input operations from an external input device provided separately from the device, and outputs the electrical signals to the processing circuit 44. The input interface 43 may be provided on the stand 10. The input interface 43 may be configured by a tablet terminal that can communicate wirelessly with the console 40.

[0139] The processing circuit 44 controls the overall operation of the X-ray CT apparatus 1 in response to electrical signals of input operations output from the input interface 43. For example, the processing circuit 44 includes a processor such as a CPU, MPU, or Graphics Processing Unit (GPU) as hardware resources, and memory such as ROM or RAM. The processor, which executes a program loaded into memory, enables the processing circuit 44 to perform system control functions 441, preprocessing functions 442, reconstruction functions 443, and display control functions 444. Each of these functions (system control function 441, preprocessing function 442, reconstruction function 443, and display control function 444) is not necessarily realized by a single processing circuit. A processing circuit can be configured by combining multiple independent processors, and each processor can execute its respective program to realize the function.

[0140] The system control function 441 controls each function of the processing circuit 44 based on input operations received from the operator via the input interface 43. Specifically, the system control function 441 reads a control program stored in the memory 41 and loads it into the memory within the processing circuit 44, and controls each part of the X-ray CT apparatus 1 according to the loaded control program. For example, the processing circuit 44 executes each function of the processing circuit 44 based on input operations received from the operator via the input interface 43. For example, the system control function 441 acquires a two-dimensional positioning image of the subject P and determines the scan range, imaging conditions, etc. The positioning image is sometimes called a "scanogram" or "scout image".

[0141] The preprocessing function 442 generates data obtained by performing preprocessing on the detection data output from DAS18. The data before preprocessing (detection data) and the data after preprocessing can be collectively called "projection data". The preprocessing function 442 is an example of a preprocessor.

[0142] The reconstruction function 443 generates CT image data by performing reconstruction processing on the projection data generated by the preprocessing function 442, using methods such as filtered backprojection, iterative reconstruction, and stochastic image reconstruction. The reconstruction function 443 is an example of a reconstruction processor. Image filtering, smoothing, volume rendering, or image difference processing can be applied to the CT image data as needed. The reconstruction function 443 may also perform subject scan data correction according to the embodiment. That is, the processing circuit 44 equipped with the reconstruction function 443 may perform image processing as various processing circuits shown in Figures 3, 5, 10, 13, etc. The display control function 444 converts the CT image data generated by the reconstruction function 443 into tomographic image data of a predetermined cross-section, i.e., three-dimensional image data by known methods, based on input operations received from the operator via the input interface 43. The generation of three-dimensional image data can be performed directly by the reconstruction function 443. The display control function 444 is an example of a display control device.

[0143] In one embodiment, the X-ray tube 11 is a single source irradiating with X-ray energy across a broad spectrum, and the PCD 12 can use semiconductor-based direct X-ray radiation detectors such as cadmium telluride (CdTe), zinc cadmium telluride (CZT), silicon (Si), mercury iodide (HgI2), and gallium arsenide (GaAs). As mentioned above, semiconductor-based direct X-ray detectors generally have a much faster time response than indirect detectors such as scintillator detectors. The fast time response of direct detectors allows for the resolution of individual X-ray detection events, although some pile-up of detection events may occur with the high X-ray flux typical in clinical X-ray applications. The energy of the detected X-rays is proportional to the signal generated by the direct detector, and the detection events can be organized into energy bins to obtain spectrally resolved X-ray data for spectral CT.

[0144] In light of the above teachings, numerous modifications and variations of the embodiments presented herein are possible. Therefore, it should be understood that within the scope of the claims, this application may be implemented in ways other than those specifically described herein. The present invention is not limited to the embodiments described herein. In particular, features of the illustrated embodiments can be combined in variations not shown.

[0145] With respect to the above embodiments, the following additional notes are disclosed as aspects of the invention and selective features. (Note 1) A method for performing subject scan data correction in an X-ray imaging system including a photon counting detector and an X-ray tube for irradiating with X-rays, Calibration scan data is obtained from calibration scans performed using multiple slabs. By performing function fitting based on the calibration scan data, a fitting function is generated that represents the relationship between the count measurement value detected for one of the plurality of slabs and the tube current applied to the X-ray tube, and a plurality of fitting functions corresponding to the plurality of slabs are generated. A calibration table is established based on the calibration scan data. Subject scan data is obtained from subject scans performed on the imaging target. Based on the calibration table and the plurality of fitting functions, data correction of the subject scan data is performed. Based on the data correction, the image of the target to be imaged is reconstructed. A medical image processing method, including the following. (Note 2) The calibration scan data is obtained from the calibration scan performed using each of the plurality of slabs with a first number (n1) tube current applied to the X-ray tube. Based on the calibration scan data, the calibration table is defined as a sub-calibration table of the first number (n1), where each sub-calibration table corresponds to one of the tube currents among the first number (n1). A subcalibration table of the first number (n1) is stored for use when performing the aforementioned data correction. As for the aforementioned data correction, For each view of the subject scan data, based on the plurality of fitting functions, the count measurement values ​​detected by each pixel of the photon counting detector are projected onto the projected count measurement values ​​as if the projected count measurement values ​​were detected when a specific tube current from the first number (n1) of tube currents was applied to the X-ray tube. Based on the subcalibration table of the first number (n1), a line integral sinogram is generated using the projected count measurements. The process may further include reconstructing the image of the object being imaged based on the line integral sinogram. (Note 3) The X-ray imaging system further comprises a tube current detector configured to directly or indirectly detect the tube current applied to the X-ray tube during the subject scan. For each view of the subject scan data, a corresponding fitting function for the decay path length corresponding to the count measurement is derived using at least one of the plurality of fitting functions, based on the count measurement detected by each pixel of the photon counting detector and the corresponding tube current detected when the view was acquired. The projected count value may further include calculating, based on the derived corresponding fitting function, the count value corresponding to the tube current among the first number (n1) of tube currents that is closest to the corresponding tube current detected when the view was acquired. (Note 4) By performing the function fitting based on the calibration scan data, a corresponding polynomial fitting function is generated for each of the multiple slabs. The degree of the polynomial fitting function may be determined based on the first number (n1). (Note 5) As the line integral sinogram, when the X-ray imaging system operates in counting imaging mode, a counting line integral sinogram is generated, and when the X-ray imaging system operates in material discrimination imaging mode, a base material line integral sinogram is generated. When the X-ray imaging system operates in the material discrimination imaging mode, it may further include generating a fitting function specific to each individual energy bin for each of the plurality of slabs. (Note 6) From the calibration scan performed using each of the plurality of slabs having different attenuation path lengths, the calibration scan data is obtained. The step in the damping path length between the plurality of slabs does not have to be greater than a predetermined threshold. (Note 7) The calibration table may further include establishing a specific calibration table based on the calibration scan data, which is used for at least one of calibrating the detector response of the X-ray imaging system and correcting the pile-up effect of the X-ray imaging system. (Note 8) The calibration scan data is obtained from the calibration scan performed using each of the plurality of slabs with a first number (n1) tube current applied to the X-ray tube. A second number (n2) tube current, different from the first number (n1) tube current, is applied to the X-ray tube, and the supplemental calibration data is calculated based on the plurality of fitting functions, as if the supplemental calibration data were obtained from calibration scans performed on each slab of the plurality of slabs. Based on the calibration scan data and the supplementary calibration data, a third number (n3) of sub-calibration tables are established to form the established calibration table. A subcalibration table of the third number (n3) is stored for use in the aforementioned data correction, As the data correction, a line integral sinogram is generated using the subject scan data based on the subcalibration table of the third number (n3), A medical image processing method for reconstructing the image of the object to be imaged based on the line integral sinogram, Each sub-calibration table in the third number (n3) corresponds to one of the tube currents of the first number (n1) and the second number (n2), and "n3 = n1 + n2". (Note 9) The calculation of the supplemental calibration data includes calculating a count measurement corresponding to each of the second number (n2) tube currents for each fitting function of the plurality of fitting functions. The tube currents of the first number (n1) and the second number (n2) are distributed over the range of tube currents applied during the subject scan. The tube current step between the tube currents of the first number (n1) and the second number (n2) does not have to be greater than a predetermined threshold. (Note 10) An apparatus for performing subject scan data correction in an X-ray imaging system including a photon counting detector and an X-ray tube for irradiating with X-rays, Calibration scan data is obtained from calibration scans performed using multiple slabs. By performing function fitting based on the calibration scan data, a fitting function is generated that represents the relationship between the count measurement value detected for one of the plurality of slabs and the tube current applied to the X-ray tube, and a plurality of fitting functions corresponding to the plurality of slabs are generated. A calibration table is established based on the calibration scan data. Subject scan data is obtained from subject scans performed on the imaging target. Based on the calibration table and the plurality of fitting functions, data correction of the subject scan data is performed. A medical image processing apparatus comprising a processing circuit for reconstructing the image of the target to be imaged based on the aforementioned data correction. (Note 11) The processing circuit acquires the calibration scan data from the calibration scan performed using each of the plurality of slabs with a first number (n1) of tube currents applied to the X-ray tube, Based on the calibration scan data, the calibration table is defined as a sub-calibration table of the first number (n1), where each sub-calibration table corresponds to one of the tube currents among the first number (n1). A subcalibration table of the first number (n1) is stored for use when performing the aforementioned data correction. As for the aforementioned data correction, For each view of the subject scan data, based on the plurality of fitting functions, the count measurement values ​​detected by each pixel of the photon counting detector are projected onto the projected count measurement values ​​as if the projected count measurement values ​​were detected when a specific tube current from the first number (n1) of tube currents was applied to the X-ray tube. Based on the subcalibration table of the first number (n1), a line integral sinogram is generated using the projected count measurements. The system may be configured to reconstruct the image of the object to be imaged based on the line integral sinogram. (Note 12) The X-ray imaging system further comprises a tube current detector configured to directly or indirectly detect the tube current applied to the X-ray tube during the subject scan. The processing circuit, for each view of the sample scan data, derives a corresponding fitting function for the decay path length corresponding to the count measurement, using at least one fitting function from the plurality of fitting functions, based on the count measurement detected by each pixel of the photon counting detector and the corresponding tube current detected when the view was acquired. The system may be further configured to calculate, as the projected count value, the tube current that is closest to the corresponding tube current detected when the view was acquired, among the first number (n1) of tube currents, based on the derived corresponding fitting function. (Note 13) The processing circuit is further configured to generate a corresponding polynomial fitting function for each of the multiple slabs by performing the function fitting based on the calibration scan data, The degree of the polynomial fitting function may be determined based on the first number (n1). (Note 14) The processing circuit generates a counting line integral sinogram when the X-ray imaging system operates in counting imaging mode, and generates a base material line integral sinogram when the X-ray imaging system operates in material discrimination imaging mode. When the X-ray imaging system operates in the material discrimination imaging mode, it may be further configured to generate a fitting function specific to each of the multiple slabs, for each individual energy bin. (Note 15) The processing circuit is further configured to acquire calibration scan data from the calibration scan performed using each of the plurality of slabs having different attenuation path lengths. The step in the damping path length between the plurality of slabs does not have to be greater than a predetermined threshold. (Note 16) The processing circuit may be further configured to establish a specific calibration table, as the calibration table, based on the calibration scan data, which is used for at least one of calibrating the detector response of the X-ray imaging system and correcting the pile-up effect of the X-ray imaging system. (Note 17) The processing circuit acquires the calibration scan data from the calibration scan performed using each of the plurality of slabs with a first number (n1) of tube currents applied to the X-ray tube, A second number (n2) tube current, different from the first number (n1) tube current, is applied to the X-ray tube, and the supplemental calibration data is calculated based on the plurality of fitting functions, as if the supplemental calibration data were obtained from calibration scans performed on each slab of the plurality of slabs. Based on the calibration scan data and the supplementary calibration data, a third number (n3) of sub-calibration tables are established to form the established calibration table. A subcalibration table of the third number (n3) is stored for use in the aforementioned data correction, As the data correction, a line integral sinogram is generated using the subject scan data based on the subcalibration table of the third number (n3), The system is further configured to reconstruct the image of the object being imaged based on the line integral sinogram, Each sub-calibration table in the third number (n3) corresponds to one of the tube currents of the first number (n1) and the second number (n2), and "n3 = n1 + n2". (Note 18) The processing circuit is further configured to calculate a count measurement value corresponding to each of the second number (n2) tube currents for each fitting function of the plurality of fitting functions, The tube currents of the first number (n1) and the second number (n2) are distributed over the range of tube currents applied during the subject scan. The tube current step between the tube currents of the first number (n1) and the second number (n2) does not have to be greater than a predetermined threshold. (Note 19) A method for performing subject scan data correction in an X-ray imaging system including a photon counting detector and an X-ray tube for irradiating with X-rays, Calibration scan data is acquired from calibration scans performed using each slab of a plurality of slabs with a first number (n1) tube current applied to the X-ray tube. A calibration table of the first number (n1) used for data correction, wherein each calibration table is established based on the calibration scan data, and each corresponds to one of the tube currents among the first number (n1) tube currents. For a second tube current (n2) that is different from the first tube current (n1), a calibration table for the second number (n2) is calculated based on the calibration table for the first number (n1). Subject scan data is obtained from subject scans performed on the imaging target. Based on the calibration tables of the first number (n1) and the second number (n2), the data correction of the subject scan data is performed. Based on the data correction, the image of the target to be imaged is reconstructed. A medical image processing method, including the following. (Note 20) The calculation of the calibration table for the second number (n2) includes selecting two or more calibration tables from the calibration table for the first number (n1) that correspond to the tube current closest to the specific tube current for each particular tube current of the second number (n2), Interpolation may be performed on the two or more selected calibration tables in order to derive the calibration table for the specific tube current.

[0146] In light of the above teachings, numerous modifications and variations of the embodiments presented herein are possible. Therefore, it should be understood that, within the scope of the claims, this disclosure may be implemented in ways other than those specifically described herein.

[0147] According to at least one embodiment described above, the quality of images acquired by photon counting CT using automatic exposure control can be improved.

[0148] 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]

[0149] 300: Subject scan data correction device 310: Calibration scan data acquisition circuit 320: Calibration scan data processing circuit 330: Subject scan data acquisition circuit 340: Subject scan data correction circuit 350: Target image reconstruction circuit 510: Calibration scan data receiving circuit 520: Current-dependent calibration table generation circuit 530: Slab Eigenfunction Fitting Circuit 540: Calibration Table Storage Unit 550: Subject scan data receiving circuit 555: Subject scan data projection circuit 560: Calibration Table Search Circuit 570: Line Integral Sinogram Generator Circuit 1010: Calibration scan data receiving circuit 1020: Current-dependent calibration table generation circuit 1030: Slab Eigenfunction Fitting Circuit 1035: Supplementary calibration data calculation circuit 1040: Calibration Table Storage Unit 1050: Subject scan data receiving circuit 1060: Calibration table search circuit 1070: Line Integral Sinogram Generator Circuit 1310: Calibration scan data receiving circuit 1320: Current-dependent calibration table generation circuit 1330: Calibration Table Interpolation Circuit 1340: Calibration Table Storage Unit 1350: Subject scan data receiving circuit 1360: Calibration Table Search Circuit 1370: Line Integral Sinogram Generator Circuit 1:X-ray CT device 11:X-ray tube 12: X-ray detector 40: Console 41: Memory 42: Display 43: Input Interface 44: Processing Circuit 441: System control function 442: Preprocessing function 443: Reconfiguration function 444: Display control function

Claims

1. A method for performing subject scan data correction in an X-ray imaging system including a photon counting detector and an X-ray tube for irradiating with X-rays, Calibration scan data is obtained from calibration scans performed using multiple slabs. By performing function fitting based on the calibration scan data, a fitting function is generated that represents the relationship between the count measurement value detected for one of the plurality of slabs and the tube current applied to the X-ray tube, and a plurality of fitting functions corresponding to the plurality of slabs are generated. A calibration table is established based on the calibration scan data. Subject scan data is obtained from subject scans performed on the imaging target. Based on the calibration table and the plurality of fitting functions, data correction of the subject scan data is performed. Based on the data correction, the image of the target to be imaged is reconstructed. A medical image processing method, including the following.

2. The calibration scan data is obtained from the calibration scan performed using each of the plurality of slabs with a first number (n1) tube current applied to the X-ray tube. Based on the calibration scan data, the calibration table is defined as a sub-calibration table of the first number (n1), where each sub-calibration table corresponds to one of the tube currents among the first number (n1). A subcalibration table of the first number (n1) is stored for use when performing the aforementioned data correction. As for the aforementioned data correction, For each view of the subject scan data, based on the plurality of fitting functions, the count measurement values ​​detected by each pixel of the photon counting detector are projected onto the projected count measurement values ​​as if the projected count measurement values ​​were detected when a specific tube current from the first number (n1) of tube currents was applied to the X-ray tube. Based on the subcalibration table of the first number (n1), a line integral sinogram is generated using the projected count measurements. Based on the line integral sinogram, the image of the object to be imaged is reconstructed. The medical image processing method according to claim 1.

3. The X-ray imaging system further comprises a tube current detector configured to directly or indirectly detect the tube current applied to the X-ray tube during the subject scan. For each view of the subject scan data, a corresponding fitting function for the decay path length corresponding to the count measurement is derived using at least one of the plurality of fitting functions, based on the count measurement value detected by each pixel of the photon counting detector and the corresponding tube current detected when the view was acquired. Based on the derived corresponding fitting function, the count value corresponding to the tube current that is closest to the corresponding tube current detected when the view was acquired, out of the first number (n1) of tube currents, is calculated as the projected count value. The medical image processing method according to claim 2.

4. By performing the function fitting based on the calibration scan data, a corresponding polynomial fitting function is generated for each of the multiple slabs. The medical image processing method according to claim 2, wherein the degree of the polynomial fitting function is determined based on the first number (n1).

5. As the line integral sinogram, when the X-ray imaging system operates in counting imaging mode, a counting line integral sinogram is generated, and when the X-ray imaging system operates in material discrimination imaging mode, a base material line integral sinogram is generated. The medical image processing method according to claim 2, wherein when the X-ray imaging system operates in the material discrimination imaging mode, a fitting function specific to each individual energy bin is generated for each of the plurality of slabs.

6. From the calibration scan performed using each of the plurality of slabs having different attenuation path lengths, the calibration scan data is obtained. The medical image processing method according to claim 1, wherein the step in the attenuation path length between the plurality of slabs is not greater than a predetermined threshold.

7. The medical image processing method according to claim 1, wherein a specific calibration table is established based on the calibration scan data, which is used as the calibration table for at least one of calibrating the detector response of the X-ray imaging system and correcting the pile-up effect of the X-ray imaging system.

8. The calibration scan data is obtained from the calibration scan performed using each of the plurality of slabs with a first number (n1) tube current applied to the X-ray tube. A second number (n2) tube current, different from the first number (n1) tube current, is applied to the X-ray tube, and the supplemental calibration data is calculated based on the plurality of fitting functions, as if the supplemental calibration data were obtained from calibration scans performed on each slab of the plurality of slabs. Based on the calibration scan data and the supplementary calibration data, a third number (n3) of sub-calibration tables are established to form the established calibration table. A subcalibration table of the third number (n3) is stored for use in the aforementioned data correction. As the data correction, a line integral sinogram is generated using the subject scan data based on the subcalibration table of the third number (n3), A medical image processing method for reconstructing the image of the object to be imaged based on the line integral sinogram, The medical image processing method according to claim 1, wherein each sub-calibration table in the third number (n3) corresponds to one of the tube currents of the first number (n1) and the second number (n2), and "n3 = n1 + n2".

9. The calculation of the supplemental calibration data includes calculating the count measurement value corresponding to each of the second number (n2) tube currents for each fitting function of the plurality of fitting functions, The tube currents of the first number (n1) and the second number (n2) are distributed over the range of tube currents applied during the subject scan. The medical image processing method according to claim 8, wherein the tube current step between the first number (n1) and the second number (n2) of tube currents is not greater than a predetermined threshold.

10. An apparatus for performing subject scan data correction in an X-ray imaging system including a photon counting detector and an X-ray tube for irradiating with X-rays, Calibration scan data is obtained from calibration scans performed using multiple slabs. By performing function fitting based on the calibration scan data, a fitting function is generated that represents the relationship between the count measurement value detected for one of the plurality of slabs and the tube current applied to the X-ray tube, and a plurality of fitting functions corresponding to the plurality of slabs are generated. A calibration table is established based on the calibration scan data. Subject scan data is obtained from subject scans performed on the imaging target. Based on the calibration table and the plurality of fitting functions, data correction of the subject scan data is performed. A medical image processing apparatus comprising a processing circuit for reconstructing the image of the target to be imaged based on the aforementioned data correction.

11. A method for performing subject scan data correction in an X-ray imaging system including a photon counting detector and an X-ray tube for irradiating with X-rays, Calibration scan data is acquired from calibration scans performed using each slab of a plurality of slabs with a first number (n1) tube current applied to the X-ray tube. A calibration table of the first number (n1) used for data correction, wherein each calibration table is established based on the calibration scan data, and each corresponds to one of the tube currents among the first number (n1) tube currents. For a second number (n2) tube current that is different from the first number (n1), a calibration table for the second number (n2) is calculated based on the calibration table for the first number (n1). Subject scan data is obtained from subject scans performed on the imaging target. Based on the calibration tables of the first number (n1) and the second number (n2), the data correction of the subject scan data is performed. Based on the data correction, the image of the target to be imaged is reconstructed. A medical image processing method, including the following.

12. The calculation of the calibration table for the second number (n2) includes selecting two or more calibration tables from the calibration table for the first number (n1) that correspond to the tube current closest to the specific tube current for each particular tube current of the second number (n2), The medical image processing method according to claim 11, comprising performing interpolation on two or more selected calibration tables in order to derive a calibration table for a specific tube current.

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