Data processing device, data processing method, and data processing program

Abstract

The data processing device, method, and program are designed to appropriately compensate for the effects of pile-up and other factors in projected data. [Solution] The processor obtains projection data corresponding to the number of photons of radiation in each of the multiple energy bins of radiation, which is acquired by detecting radiation emitted from a radiation source and transmitted through the subject using a detector consisting of multiple photon counting type detection elements. Based on the projection data in each of the multiple energy bins, the processor derives first correction data for correcting the projection data of at least one target energy bin among the multiple energy bins that is to be corrected. In the projection data of the target energy bin, the projection values ​​that are less than or equal to a first threshold in the first correction data are corrected with the first correction data to derive first corrected projection data.

Description

Technical Field

[0001] The present disclosure relates to a data processing apparatus, a data processing method, and a data processing program.

Background Art

[0002] In recent years, a PCCT (Photon Counting Computed Tomography) apparatus, which is a radiation imaging apparatus equipped with a photon counting detector (PCD), has been known. Different from the charge integration type detector employed in conventional CT (Computed Tomography) apparatuses, the PCD can acquire projection data obtained by measuring the number of photons of incident radiation for each of a plurality of energy bins. Therefore, more information can be obtained compared to conventional CT apparatuses.

[0003] In the PCD, phenomena such as pile-up where the apparent energy of photons seems high, or undercount where the measured count value becomes smaller than the ideal value may occur, and there is a risk that the measured count value deviates from the true count value. For this reason, various methods for correcting projection data have been proposed. For example, in Patent Document 1, a method for correcting projection data has been proposed by acquiring projection data including counts corresponding to energy bins and estimating the spectrum of counts affected by pile-up.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] The pile-up and counting errors described above occur significantly when the radiation dose is high; therefore, the effects of pile-up and counting errors are more likely to appear in areas with high radiation doses, i.e., areas where the subjects are small and the projected values ​​in the projection data are low.

[0006] This disclosure is made in light of the circumstances described above and aims to enable appropriate correction of effects such as pile-up in projection data. [Means for solving the problem]

[0007] The data processing device described herein comprises a processor, The processor acquires projection data corresponding to the number of photons in each of the multiple energy bins of radiation, obtained by detecting the radiation emitted from the radiation source and transmitted through the subject using a detector consisting of multiple photon-counting type detection elements. Based on the projection data for each of the multiple energy bins, first correction data is derived to correct the projection data of at least one target energy bin among the multiple energy bins that is to be corrected. In the projection data of the target energy bin, the projection values ​​that are below the first threshold in the first correction data are corrected using the first correction data to derive the first corrected projection data.

[0008] In the data processing device described herein, the processor calibrates the projection data in each of the multiple energy bins, The calibrated projection data may be used to derive the first correction data and the first corrected projection data.

[0009] In the data processing device according to this disclosure, the processor may derive first corrected projection data by correcting projection values ​​in the projection data of the target energy bin that are greater than or equal to a second threshold and less than the first threshold, which is smaller than the first threshold in the first correction data, to projection values ​​derived by interpolation between the projection values ​​of the projection data of the target energy bin and the projection values ​​of the first correction data, and by correcting projection values ​​in the first correction data that are less than the second threshold to the projection values ​​of the first correction data.

[0010] In the data processing device according to this disclosure, the processor may set at least one of a first threshold and a second threshold based on the energy of the target energy bin, the position of a detection element corresponding to the shape of a compensating object that compensates for the dose of radiation irradiated to the subject, and at least one of the tube current of the radiation.

[0011] In the data processing device according to this disclosure, the target energy bin is at least one of the largest and smallest energy bins among a plurality of energy bins. The processor may derive first correction data by weighting the projection data of energy bins other than the largest and smallest energy bins among multiple energy bins, making the weighting of these energy bins relatively larger than that of the projection data of the largest and smallest energy bins, and then weighting and combining the multiple projection data.

[0012] In the data processing device according to this disclosure, the processor derives second correction data for correcting the contrast of the first corrected projection data according to the size of the subject, based on the projection data in each of a plurality of energy bins. The second corrected projection data may be derived by weighting and combining the second correction data and the first corrected projection data according to the size of the subject.

[0013] In the data processing device according to this disclosure, the processor may derive second correction data by weighting the projection data of energy bins in which the variation in projection values ​​due to the size of the subject is relatively smaller than that of other energy bins, and by weighting and combining the multiple projection data.

[0014] In the data processing device according to this disclosure, the processor may estimate an index representing the size of the subject based on the sum of the projected values ​​of the second correction data.

[0015] The data processing method disclosed herein involves a computer obtaining projection data corresponding to the number of photons of radiation in each of several energy bins of radiation, which is acquired by detecting radiation emitted from a radiation source and transmitted through a subject using a detector consisting of multiple photon-counting type detection elements. Based on the projection data for each of the multiple energy bins, first correction data is derived to correct the projection data of at least one target energy bin among the multiple energy bins that is to be corrected. In the projection data of the target energy bin, the projection values ​​that are below the first threshold in the first correction data are corrected using the first correction data to derive the first corrected projection data.

[0016] The data processing program disclosed herein includes a procedure for obtaining projection data corresponding to the number of photons of radiation in each of several energy bins of radiation, which is acquired by detecting radiation emitted from a radiation source and transmitted through a subject using a detector consisting of multiple photon-counting type detection elements, A procedure for deriving first correction data for correcting the projection data of at least one target energy bin among multiple energy bins that is to be corrected, based on the projection data in each of multiple energy bins, In the projection data of the target energy bin, the computer is made to execute a procedure of deriving first corrected projection data by correcting projection values that are less than or equal to a first threshold in the first correction data with the first correction data.

[0017] Note that the technology of the present disclosure may be applied to a program product.

Advantages of the Invention

[0018] According to the present disclosure, influences such as pile-up in the projection data can be appropriately corrected.

Brief Description of the Drawings

[0019] [Figure 1] Schematic configuration diagram of a data processing apparatus according to an embodiment of the present disclosure [Figure 2] Diagram showing the hardware configuration of the data processing apparatus according to the present embodiment [Figure 3] Functional configuration diagram of the data processing apparatus according to the present embodiment [Figure 4] Diagram for explaining deterioration of linearity of projection data for each energy bin [Figure 5] Diagram for explaining setting of the first threshold and the second threshold [Figure 6] Diagram for explaining derivation of the first corrected projection data [Figure 7] Diagram showing the relationship between the size and weight of the subject [Figure 8] Flowchart showing the processing performed in the present embodiment

Modes for Carrying Out the Invention

[0020] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. First, an example of the configuration of a medical imaging system including a control device of a data processing apparatus according to an embodiment of the present disclosure will be described. FIG. 1 is a schematic configuration diagram of a medical imaging system including the data processing apparatus according to the present embodiment.

[0021] As shown in Figure 1, the medical imaging system 1 of this embodiment comprises a CT scanner 2 and a console 3. The CT scanner 2 comprises a gantry 4 and a patient table 8. In the following description, the horizontal direction in Figure 1 is referred to as the X-axis, the vertical direction as the Y-axis, and the direction perpendicular to the XY plane as the Z-axis. The CT scanner 2 is an example of a radiography device.

[0022] The gantry 4 has an opening 4A, and the subject S to be photographed is placed inside the opening 4A while on the bed 8. The gantry 4 and the bed 8 are movable relative to each other in the Z-axis direction.

[0023] Inside the gantry 4, a radiation source 5 having a radiation tube 6 and a bowtie filter 7, and a detector 9 are arranged facing each other with the subject S in between. The bowtie filter 7 optimizes the radiation dose by increasing the dose near the center and decreasing the dose around the periphery in order to reduce the radiation dose in the peripheral area. The radiation emitted from the radiation tube 6 is shaped into a beam shape suitable for the size of the subject S by the bowtie filter 7 and irradiated onto the subject S. The bowtie filter 7 is an example of a compensator in this disclosure.

[0024] The detector 9 detects radiation that has passed through the subject S and generates projection data corresponding to the detected radiation dose. As an example, the detector 9 in this embodiment is a photon counting type detector in which a plurality of detection elements 9P that detect photon energy, which is the energy of photons of incident radiation, are arranged in an arc shape centered on the focal point of the radiation tube 6.

[0025] A photon counting detector measures the energy of each photon and outputs projection data corresponding to the number of photons in the radiation in each of several energy bins. In this embodiment, the detector 9 outputs projection data for each of four energy bins, for example. The four energy bins can be, for example, less than 30 keV, 30 keV to less than 50 keV, 50 keV to less than 100 keV, and 100 keV or more, but are not limited to these. The projection data is two-dimensional data in which the detection signal acquired at each of the multiple detection elements 9P included in the detector 9, i.e., the projection value, is the pixel value of each pixel. The projection value also includes the signal for each of the four energy bins.

[0026] In this embodiment, X-rays are used as an example of radiation, but the invention is not limited to this, and gamma rays or other types of radiation can also be used.

[0027] The radiation tube 6 and detector 9 are mounted on a rotating plate 4B inside the gantry 4 and are rotated around the subject S by a rotation drive unit (not shown). As radiation irradiation from the radiation tube 6 and detection of radiation by the detector 9 are repeated along with the rotation of both, projection data is acquired in multiple view units with different projection angles of radiation onto the subject. The projection data acquired by the detector 9 is output to the console 3.

[0028] The radiation dose emitted from the radiation tube 6, the rotation speed of the gantry 4, and the relative movement speed between the gantry 4 and the patient bed 8 are all set by the console 3 based on imaging conditions, including tube current, entered by the operator, such as a technician.

[0029] The console 3 in this embodiment performs control related to the imaging of the subject S, correction of projection data acquired by imaging, and generation of tomographic images from the projection data. The console 3 is an example of a data processing device in this disclosure.

[0030] Next, the data processing device according to this embodiment will be described. First, with reference to Figure 2, the hardware configuration of the data processing device according to this embodiment, which is contained within the console 3, will be described. As shown in Figure 2, the data processing device 10 contained within the console 3 is a computer such as a workstation, server computer, or personal computer, and is equipped with a CPU (Central Processing Unit) 11, non-volatile storage 13, and memory 16 as a temporary storage area.

[0031] The data processing device 10 also includes a display 14, an input device 15, and an I / F (Interface) 17. The CPU 11, storage 13, display 14, input device 15, memory 16, and I / F 17 are connected to a bus 18. The CPU 11 is an example of a processor in this disclosure.

[0032] The storage 13 is implemented using an HDD (Hard Disk Drive), an SSD (Solid State Drive), and flash memory, etc. The data processing program 12 installed on the data processing device 10 is stored in the storage 13 as a storage medium. The CPU 11 reads the data processing program 12 from the storage 13, expands it into memory 16, and executes the expanded data processing program 12.

[0033] The display 14 is a device that displays various types of screens, such as a liquid crystal display or an EL (Electro Luminescence) display.

[0034] The input device 15 is used by the operator to input instructions and various information regarding the shooting conditions, image generation and display, etc., when photographing the subject S. Examples of input devices 15 include various switches, buttons, touch panels, styluses, keyboards, and mice. The display 14 and the input device 15 may be integrated to form a touch panel display.

[0035] I / F17 communicates various types of information with the rotational drive unit (not shown) of the gantry 4, the radiation source 5, and the detector 9 via wired or wireless communication.

[0036] The data processing program 12 is stored in a memory device of a server computer connected to the network, or in network storage, in a state that allows external access, and is downloaded and installed on the computers comprising the data processing device 10 upon request. Alternatively, it may be recorded on a recording medium such as a DVD (Digital Versatile Disc) or CD-ROM (Compact Disc Read Only Memory) and distributed, and then installed from that recording medium on the computers comprising the data processing device 10.

[0037] Next, the functional configuration of the data processing device according to this embodiment will be described. Figure 3 is a diagram showing the functional configuration of the data processing device according to this embodiment. As shown in Figure 3, the data processing device 10 includes an information acquisition unit 20, a calibration unit 21, a first derivation unit 22, a first correction unit 23, a second derivation unit 24, a second correction unit 25, a reconstruction unit 26, and a display control unit 27. The CPU 11 functions as the information acquisition unit 20, calibration unit 21, first derivation unit 22, first correction unit 23, second derivation unit 24, second correction unit 25, reconstruction unit 26, and display control unit 27 by executing the data processing program 12.

[0038] The information acquisition unit 20 acquires projection data for each view obtained by imaging the subject S from the CT device 2. The projection data is data corresponding to the number of photons of radiation for each of the multiple energy bins output by the detector 9. In this embodiment, it is assumed that the first projection data P01 to the fourth projection data P04 are acquired for each of the four energy bins from the first to the fourth. The energy of the four energy bins increases in the order from the first to the fourth.

[0039] The calibration unit 21 uses calibration data acquired in advance and stored in the storage unit 13 to calibrate the first projection data P01 to the fourth projection data P04 and derives the calibrated first projection data P1 to the fourth projection data P4. Hereinafter, the calibrated first projection data P1 to the fourth projection data P4 will simply be referred to as first projection data P1 to fourth projection data P4.

[0040] Calibration data is acquired in advance by performing phantom calibration and stored in storage 13. Phantom calibration is a process in which calibration data is acquired by imaging a phantom, for example, a cylindrical phantom with known density and transmission length, using the CT scanner 2, in order to calibrate the density and transmission length of the subject S obtained from imaging. Calibration data is acquired for each energy bin. Phantom calibration is performed when the CT scanner 2 is shipped, during periodic inspections, etc.

[0041] Here, the first to fourth projection data P1 to P4 acquired by detector 9 may have projection values ​​(i.e., signal values ​​corresponding to the photon count) that deviate from the true values ​​due to effects such as pile-up or counting errors. In particular, the linearity of the projection value with respect to radiation dose deteriorates when the radiation dose is high. The effects of pile-up and the like differ depending on the energy bin. For example, in intermediate energy bins, the number of photons that slip in from lower energy bins and the number of photons that overflow into higher energy bins are roughly the same, so the effects of pile-up and the like are small. On the other hand, in the lowest energy bin among multiple energy bins, the number of photons overflows, so the effects of pile-up are large. In particular, the linearity deteriorates in the region of low projection values.

[0042] Figure 4 illustrates the deterioration of linearity in projection data for each energy bin. In Figure 4, the horizontal axis represents the position in the channel direction at detector 9, and the vertical axis represents the projection value. As shown in Figure 4, in the first projection data P1, which has the lowest energy among the four energy bins, the linearity of the projection value deteriorates in the region of low projection values, and negative projection values ​​that are not actually possible appear. Furthermore, the applicant's experiments have confirmed that the third projection data P3, which is for the third lowest energy bin among the four energy bins, has the highest linearity.

[0043] The first derivation unit 22 derives first correction data C1 for correcting the projection data of at least one target energy bin among the multiple energy bins to be corrected, in order to correct the effects of pile-up and the like described above. Specifically, the first derivation unit 22 derives first correction data C1 by weighting and combining the projection values ​​in the corresponding channels of the first to fourth projection data P1 to P4, as shown in equation (1) below. In equation (1), w1 to w4 are weighting coefficients for the first to fourth projection data P1 to P4. C1=w1×P1+w2×P2+w3×P3+w4×P4 (1)

[0044] As described above, experiments conducted by the applicant have confirmed that the third projection data P3 exhibits the highest linearity. Therefore, the first derivation unit 22 sets the weighting coefficients w1 to w4 such that weighting coefficient w3 is relatively larger than the other weighting coefficients. For example, in this embodiment, the first correction data C1 may be derived by setting (w1, w2, w3, w4) = (0, 0, 1, 0). In this case, the first correction data C1 coincides with the third projection data P3.

[0045] The first correction unit 23 derives the first corrected projection data H1 by correcting the projection values ​​in the projection data of the target energy bin that are below the first threshold in the first correction data C1 using the first correction data C1. The region in the first correction data C1 that is below the first threshold corresponds, for example, to the region in the first projection data P1 described above where the projection values ​​are low. In this embodiment, the target energy bins are the first energy bin, the second energy bin, and the fourth energy bin, but are not limited to these. Only the first energy bin, which has the worst linearity of projection values, may be used as the target energy bin.

[0046] For example, when correcting the first projection data P1, the first correction unit 23 does not correct projection values ​​in the first projection data P1 that are greater than or equal to the first threshold Th1 in the first correction data C1, and sets the projection value of the first projection data P1 to the projection value of the first corrected projection data H1. Furthermore, the first correction unit 23 corrects projection values ​​in the first correction data C1 that are greater than or equal to the second threshold Th2 and less than the first threshold Th1, to projection values ​​derived by interpolation between the projection value of the first projection data P1 and the projection value of the first correction data C1. In addition, the first correction unit 23 corrects projection values ​​in the first correction data C1 that are less than the second threshold Th2 to the projection value of the first correction data C1.

[0047] As a result, the first correction unit 23 derives the first corrected projection data H1. Similarly to the first projection data P1, the first corrected projection data H1 is also derived for the second projection data P2 of the second energy bin, the third projection data P3 of the third energy bin, and the fourth projection data P4 of the fourth energy bin based on the first threshold Th1 and second threshold Th2 in the first correction data C1. In this embodiment, since the weight coefficients in equation (1) for deriving the first correction data C1 described above are set to (w1,w2,w3,w4)=(0,0,1,0), the third projection data P3 is not corrected.

[0048] In deriving the first corrected projection data H1, the first correction unit 23 sets a first threshold Th1 and a second threshold Th2 for the first correction data C1. Figure 5 is a diagram illustrating the setting of the first and second thresholds. In this embodiment, a bowtie filter 7 is used in the CT device 2. As described above, the bowtie filter 7 optimizes the exposure by increasing the dose near the center and decreasing the dose around it in order to suppress the exposure dose in the peripheral area. Here, the effects of pile-up etc. become larger as the dose increases. In Figure 5, the first correction data C1 is corrected according to the characteristics of the bowtie filter 7, and then the first threshold Th1 and the second threshold Th2 are set. Thus, in Figure 5, it is shown that the first threshold Th1 and the second threshold Th2 are set for the first correction data C1 so that the correction is performed from lower values ​​for channels in the center of the detector 9.

[0049] The first threshold Th1 and the second threshold Th2 may be set for each energy bin of the projection data to be corrected. For example, when correcting projection data of an energy bin that is less susceptible to pile-ups, the first threshold Th1 and the second threshold Th2 may be set to be smaller than when correcting projection data of an energy bin that is more susceptible to pile-ups.

[0050] Furthermore, the first threshold Th1 and the second threshold Th2 may be set according to the tube current when imaging the subject S. Here, a smaller tube current results in a smaller amount of radiation being irradiated to the subject S, making it less susceptible to effects such as pile-up. For this reason, the smaller the tube current, the smaller the first threshold Th1 and the second threshold Th2 may be relatively. Note that the first threshold Th1 and the second threshold Th2 may be set according to all of the characteristics of the bowtie filter 7, the energy bin, and the tube current, or they may be set according to two of these. Alternatively, only the first threshold Th1 may be set.

[0051] Figure 6 is a diagram illustrating the derivation of the first corrected projection data. In Figure 6, the derivation of the first corrected projection data H1 for the first projection data P1 is explained. Note that in Figure 6, unlike Figure 5, the values ​​of the first correction data C1, the first projection data P1, and the first corrected projection data H1 have not been corrected considering the bowtie filter 7, so the thresholds Th1 and Th2 are shown as curves accordingly. In Figure 6, the first correction data C1 is divided into data area C11 where the value is greater than or equal to the first threshold Th1, data area C12 where the value is greater than or equal to the second threshold Th2 but less than the first threshold Th1, and data area C13 where the value is less than the second threshold Th2. The first projection data P1 is divided into data area P11 where the value is greater than or equal to the first threshold Th1 in the first correction data C1, data area P12 where the value is greater than or equal to the second threshold Th2 but less than the first threshold Th1, and data area P13 where the value is less than the second threshold Th2.

[0052] In the data area P11 of the first projection data P1, the first correction unit 23 uses the projection value of the first projection data P1 as the projection value of the first corrected projection data H1. In the data area P12 of the first projection data P1, the first correction unit 23 derives the projection value of the first corrected projection data H1 by interpolation between the projection value of the first projection data P1 and the projection value of the first correction data C1. In Figure 6, the interpolation operation is represented by P1 + C1. In the data area P13 of the first projection data P1, the projection value of the first correction data C1 is used as the projection value of the first corrected projection data H1. In this way, the first correction unit 23 derives the first corrected projection data H1.

[0053] Interpolation in data area P12 is performed by weighting and adding the projected value of the first correction data C1 and the projected value of the first projection data P1 according to the difference between the projected value of the first correction data C1 and the first threshold Th1 and the second threshold Th2. Specifically, if the projected value of the first correction data C1 is close to the first threshold Th1, the first correction unit 23 makes the weight of the projected value of the first correction data C1 smaller than the weight of the projected value of the first projection data P1. Conversely, if the projected value of the first correction data C1 is close to the second threshold Th2, the weight of the projected value of the first correction data C1 is made larger than the weight of the projected value of the first projection data P1.

[0054] The second derivation unit 24 derives second correction data C2 for correcting the contrast of the first corrected projection data H1 according to the size of the subject S, based on the projection data in each of the multiple energy bins. In this embodiment, the second derivation unit 24 derives the second correction data C2 by weighting and combining the projection values ​​in the corresponding channels of the first to fourth projection data P1 to P4, as shown in equation (2) below. In equation (2), w11 to w14 are weighting coefficients for the first to fourth projection data P1 to P4. The weighting coefficients w11 to w14 can be different from the weighting coefficients w1 to w4 used by the first derivation unit 22 when deriving the first correction data C1.

[0055] Here, using data with high linearity is more appropriate as an indicator of the size of the subject S. For this reason, the second derivation unit 24 derives the second correction data C2 by making the weighting coefficient w13 for the third projection data P3, which has the highest linearity as described above, relatively larger than the weighting coefficients w11, w12, and w14 for the first projection data P1, second projection data P2, and fourth projection data P4. C2=w11×P1+w12×P2+w13×P3+w14×P4 (2)

[0056] In this embodiment, the second correction data C2 is derived by setting (w11,w12,w13,w14)=(0,0,1,0). In this case, the second correction data C2 matches the third projection data P3.

[0057] The second correction unit 25 sets weights for the second correction data C2 and weight coefficients w20 for the first corrected projection data H1 according to the size of the subject S. Then, the second correction unit 25 uses the set weight coefficients w20 to weight and combine the second correction data C2 and the first corrected projection data H1 to derive the second corrected projection data H2.

[0058] The weight coefficient w20 is set based on a predetermined relationship between the size of the subject S and the weight coefficient w20. The relationship between the size of the subject S and the weight coefficient w20 is derived in advance for each of the multiple energy bins and stored in storage 13.

[0059] In this embodiment, since the second correction data C2 matches the third projection data P3, the second correction unit 25 corrects the contrast of the first projection data P1, the second projection data P2, and the fourth projection data P4 (all first corrected projection data H1) based on the contrast of the third projection data P3. The first corrected projection data H1 for the first projection data P1, the second projection data P2, and the fourth projection data P4 are designated as first corrected projection data H11, first corrected projection data H12, and first corrected projection data H14, respectively.

[0060] Here, the contrast of the projection data increases or decreases depending on the size of the subject S. The change in the contrast of the projection data also differs depending on the energy bin. For this reason, in this embodiment, the change in contrast according to the size of the subject S is measured in advance for each energy bin and weighting coefficients are derived.

[0061] In this embodiment, the contrast of the first projection data P1, second projection data P2, third projection data P3, and fourth projection data P4, corresponding to the size of the subject S, is measured in advance by photographing a phantom. Here, when the human body is radiographed, typical examples of substances that make up the human body where the contrast is high include soft tissues with a composition close to water and bone tissue which contains a lot of calcium. With water and calcium, the lower the energy, the higher the contrast, and the higher the energy, the lower the contrast. For this reason, a phantom containing water and calcium, for example, is used, and the contrast corresponding to the size of the subject S is measured in advance.

[0062] In this embodiment, the relationship between the size of the subject S and the weighting coefficient w20 is derived according to the measured contrast. For example, for the first projection data P1 (first corrected projection data H11), the larger the subject S, the higher the contrast. Therefore, in this embodiment, the contrast of the first projection data P1 is corrected to be equivalent to that of the case where the subject S is small. In this case, for the first projection data P1, as shown in Figure 7, the relationship between the size of the subject S and the weighting coefficient w20 is derived such that the weighting coefficient w20 increases as the subject S increases. The weighting coefficient w20 takes a value of 0 or greater and less than or equal to the midpoint between 0 and 1. The second correction unit 25 derives the second corrected projection data H2 by weighting and combining the first corrected projection data H1 and the second correction data C2 according to the following equation (3). In equation (3), the larger the weighting coefficient w20, the closer the contrast of the first corrected projection data H1 becomes to that of the second correction data C2. In this case, the contrast of the first corrected projection data H11 will decrease to approach that of the second correction data C2. H2 = w20 × C2 + (1 - w20) × H1 (3)

[0063] In this embodiment, the second correction unit 25 adds up the projection values ​​of all channels of the second correction data C2 and derives the square root of the added value as an index representing the size of the subject S.

[0064] On the other hand, if the contrast of the first corrected projection data H11 is corrected to be smaller, the contrast of the second corrected projection data H2 of the first corrected projection data H11 will become closer to the contrast of the second projection data P2 (first corrected projection data H12). For this reason, for the first corrected projection data H12, regardless of the size of the subject S, the relationship between the subject S and the weight coefficient w20 may be derived so that the contrast approaches that of the second correction data C2. In this case, according to equation (3), the contrast of the first corrected projection data H12 will be smaller so as to approach that of the second correction data C2.

[0065] Furthermore, regarding the contrast of the first corrected projection data H14, a weighting coefficient w20 corresponding to the size of the subject S can be derived in advance according to the measured contrast, and the second corrected projection data H14 can be derived according to the above equation (3).

[0066] The reconstruction unit 26 acquires second corrected projection data H2 at multiple projection angles from the storage unit 13 and derives tomographic images for each energy bin by performing reconstruction processing and the like.

[0067] The display control unit 27 displays the tomographic image derived by the reconstruction unit 26 on the display 14.

[0068] Next, the processing performed in this embodiment will be described. Figure 8 is a flowchart showing the processing performed in this embodiment. The CT scanner 2 takes an image of the subject S, and the information acquisition unit 20 acquires projection data for each energy bin (step ST1). Next, the calibration unit 21 calibrates the projection data (step ST2), and the first derivation unit 22 derives the first correction data C1 (step ST3). Subsequently, the first correction unit 23 corrects the projection data of the target energy bin using the first correction data C1 to derive the first corrected projection data H1 (step ST4).

[0069] Next, the second derivation unit 24 derives second correction data C2 for adjusting contrast (step ST5), and the second correction unit 25 derives second corrected projection data H2 for the target energy bin by correcting the first corrected projection data H1 with the second correction data C2 (step ST6). Then, the reconstruction unit 26 derives a tomographic image by reconstructing the second corrected projection data H2 (step ST7), and the display control unit 27 displays the tomographic image on the display 14 (step ST8), ending the process.

[0070] Here, the effects of pile-up and the like appear in regions of the projection data where the projection values ​​are relatively low. In this embodiment, based on the projection data for each of the multiple energy bins, a first correction data C1 is derived to correct the projection values ​​that are below a first threshold in the projection data of at least one target energy bin among the multiple energy bins that are to be corrected. Based on the first correction data C1, the projection values ​​that are below the first threshold in the projection data of the target energy bin are corrected. This allows for appropriate correction of the effects of pile-up and the like.

[0071] Furthermore, in this embodiment, the contrast of the first corrected projection data H1 is corrected according to the size of the subject S. Therefore, fluctuations in the contrast of the projection data for each energy bin according to the size of the subject S can be suppressed, and as a result, higher quality tomographic images can be obtained.

[0072] In the above embodiment, a second derivation unit 24 and a second correction unit 25 are provided to correct the contrast of the first corrected projection data H1, but the system is not limited to this. The system may also derive only the first corrected projection data H1 without correcting the contrast. In this case, the reconstruction unit 26 can derive a tomographic image by reconstructing the first corrected projection data H1.

[0073] Furthermore, while the above embodiment shows that the photon counting detector outputs detection signals for four energy bands, it is not limited to this. It may also output raw data for more than four or more energy bands.

[0074] Furthermore, in the above embodiment, the processor includes not only a CPU, which is a general-purpose processor that executes software (programs) and functions as various processing units, but also a PLD (Programmable Logic Device) such as an FPGA (Field-Programmable Gate Array) whose circuit configuration can be changed after manufacturing, and a dedicated electrical circuit, which is a processor with a circuit configuration specifically designed to execute a particular process, such as an ASIC.

[0075] Furthermore, the above various processes may be executed on one of these various processors, or on a combination of two or more processors of the same or different types (for example, multiple FPGAs, and a combination of a CPU and an FPGA). Alternatively, multiple processing units may be configured on a single processor. An example of configuring multiple processing units on a single processor is the use of a processor that realizes the functions of the entire system, including multiple processing units, on a single IC (Integrated Circuit) chip, such as an SoC (System on a Chip).

[0076] The following are additional notes to this disclosure. (Additional note 1) Equipped with a processor, The aforementioned processor, Projection data corresponding to the number of photons of the radiation in each of the multiple energy bins of the radiation is obtained by detecting the radiation emitted from the radiation source and transmitted through the subject using a detector consisting of multiple photon counting type detection elements. Based on the projection data in each of the plurality of energy bins, first correction data is derived for correcting the projection data of at least one target energy bin among the plurality of energy bins that is to be corrected. A data processing device that derives first corrected projection data by correcting projection values ​​in the projection data of the target energy bin that are less than or equal to a first threshold in the first correction data using the first correction data. (Additional note 2) The processor calibrates the projection data in each of the plurality of energy bins, The data processing device according to Appendix 1, which uses the calibrated projection data to derive the first correction data and the first corrected projection data. (Additional note 3) The data processing device according to appendix 1 or 2, wherein the processor corrects the projection values ​​in the projection data of the target energy bin that are greater than or equal to a second threshold smaller than the first threshold in the first correction data and less than the first threshold to projection values ​​derived by interpolation between the projection values ​​of the projection data of the target energy bin and the projection values ​​of the first correction data, and corrects the projection values ​​in the first correction data that are less than the second threshold to projection values ​​of the first correction data, thereby deriving the first corrected projection data. (Additional note 4) The data processing device according to Appendix 3, wherein the processor sets at least one of the first threshold and the second threshold based on the energy of the target energy bin, the position of the detection element according to the shape of the compensator that compensates for the dose of the radiation irradiated to the subject, and the tube current of the radiation. (Additional note 5) The target energy bin is at least one of the largest and smallest energy bins among the plurality of energy bins. The data processing device according to any one of the appendices 1 to 4, wherein the processor derives the first correction data by weighting the projection data of energy bins other than the largest and smallest energy bins among the plurality of energy bins, with the weighting of the projection data of the plurality of energy bins being relatively larger than that of the projection data of the largest and smallest energy bins, and then weighting and combining the plurality of projection data. (Additional note 6) The processor derives second correction data for correcting the contrast of the first corrected projection data according to the size of the subject, based on the projection data in each of the plurality of energy bins. A data processing device according to any one of the appendices 1 to 5, which derives second corrected projection data by weighting and combining the second correction data and the first corrected projection data according to the size of the subject. (Additional note 7) The data processing device according to Appendix 6, wherein the processor derives the second correction data by weighting and combining the multiple projection data, with a relatively larger weight given to the projection data of the energy bins among the multiple energy bins in which the variation of the projection value due to the size of the subject is relatively smaller than that of the other energy bins, compared to the projection data of the other energy bins. (Additional note 8) The data processing device according to appendix 6 or 7, wherein the processor estimates and derives an index representing the size of the subject based on the sum of the projected values ​​of the second correction data. (Additional note 9) The computer obtains projection data corresponding to the number of photons of the radiation in each of the multiple energy bins of the radiation, which is acquired by detecting the radiation emitted from the radiation source and transmitted through the subject using a detector consisting of multiple photon-counting type detection elements. Based on the projection data in each of the plurality of energy bins, first correction data is derived for correcting the projection data of at least one target energy bin among the plurality of energy bins that is to be corrected. A data processing method for deriving first corrected projection data by correcting projection values ​​in the projection data of the target energy bin that are less than or equal to a first threshold in the first correction data using the first correction data. (Additional note 10) A procedure for obtaining projection data corresponding to the number of photons of the radiation in each of the multiple energy bins of the radiation, which is obtained by detecting the radiation emitted from a radiation source and transmitted through a subject using a detector consisting of multiple photon-counting type detection elements, A procedure for deriving first correction data for correcting the projection data of at least one target energy bin among the plurality of energy bins to be corrected, based on the projection data in each of the plurality of energy bins, A data processing program that causes a computer to perform a procedure to derive first corrected projection data by correcting projection values ​​in the projection data of the target energy bin that are below a first threshold in the first correction data using the first correction data. [Explanation of Symbols]

[0077] 1. Medical imaging system 2 CT device 3 Console 4 Gantry 4A opening 4B Rotating Plate 5 Radiation source 6 Radiation tubes 7 Bowtie Filter 8 berths 9 Detectors 9P detection element 10 Data Processing Devices 11 CPU 12 Data Processing Programs 13 Storage 14 displays 15 Input Devices 16 memory 17 I / F 18 bus 20 Intelligence Acquisition Department 21 Correction Section 22 Section 1 23. First Supplementary Section 24. Section 2 25. Second Supplementary Section 26 Reconstruction Section 27 represents the Ministry of Control C1 First Correction Data H1 1st revised projection projector P1~P4 projection screen S is the test subject.

Claims

1. Equipped with a processor, The aforementioned processor, Projection data corresponding to the number of photons of the radiation in each of the multiple energy bins of the radiation is obtained by detecting the radiation emitted from the radiation source and transmitted through the subject using a detector consisting of multiple photon counting type detection elements. Based on the projection data in each of the plurality of energy bins, first correction data is derived for correcting the projection data of at least one target energy bin among the plurality of energy bins that is to be corrected. A data processing device that derives first corrected projection data by correcting projection values ​​in the projection data of the target energy bin that are less than or equal to a first threshold in the first correction data using the first correction data.

2. The processor calibrates the projection data in each of the plurality of energy bins, The data processing apparatus according to claim 1, which uses the calibrated projection data to derive the first correction data and the first corrected projection data.

3. The data processing device according to claim 1 or 2, wherein the processor corrects the projection values ​​in the projection data of the target energy bin that are greater than or equal to a second threshold smaller than the first threshold in the first correction data and less than the first threshold to projection values ​​derived by interpolation between the projection values ​​of the projection data of the target energy bin and the projection values ​​of the first correction data, and corrects the projection values ​​in the first correction data that are less than the second threshold to projection values ​​of the first correction data, thereby deriving the first corrected projection data.

4. The data processing device according to claim 3, wherein the processor sets at least one of the first threshold and the second threshold based on the energy of the target energy bin, the position of the detection element according to the shape of the compensator that compensates for the dose of the radiation irradiated to the subject, and the tube current of the radiation.

5. The target energy bin is at least one of the largest and smallest energy bins among the plurality of energy bins. The data processing device according to claim 1, wherein the processor derives the first correction data by weighting the projection data of the energy bins other than the largest and smallest energy bins among the plurality of energy bins, to be relatively larger than the projection data of the largest and smallest energy bins, and then weighting and combining the plurality of projection data.

6. The processor derives second correction data for correcting the contrast of the first corrected projection data according to the size of the subject, based on the projection data in each of the plurality of energy bins. The data processing apparatus according to claim 1, wherein a second corrected projection data is derived by weighting and combining the second correction data and the first corrected projection data according to the size of the subject.

7. The data processing device according to claim 6, wherein the processor derives the second correction data by weighting and combining the plurality of projection data, with a relatively larger weight given to the projection data of the energy bins among the plurality of energy bins in which the variation of the projection value due to the size of the subject is relatively smaller than that of the other energy bins, compared to the projection data of the other energy bins.

8. The data processing device according to claim 6, wherein the processor estimates an index representing the size of the subject based on the sum of the projected values ​​of the second correction data.

9. The computer obtains projection data corresponding to the number of photons of the radiation in each of the multiple energy bins of the radiation, which is acquired by detecting the radiation emitted from the radiation source and transmitted through the subject using a detector consisting of multiple photon-counting type detection elements. Based on the projection data in each of the plurality of energy bins, first correction data is derived for correcting the projection data of at least one target energy bin among the plurality of energy bins that is to be corrected. A data processing method for deriving first corrected projection data by correcting projection values ​​in the projection data of the target energy bin that are less than or equal to a first threshold in the first correction data using the first correction data.

10. A procedure for obtaining projection data corresponding to the number of photons of the radiation in each of the multiple energy bins of the radiation, which is obtained by detecting the radiation emitted from a radiation source and transmitted through a subject using a detector consisting of multiple photon-counting type detection elements, A procedure for deriving first correction data for correcting the projection data of at least one target energy bin among the plurality of energy bins to be corrected, based on the projection data in each of the plurality of energy bins, A data processing program that causes a computer to perform a procedure to derive first corrected projection data by correcting projection values ​​in the projection data of the target energy bin that are below a first threshold in the first correction data using the first correction data.

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