X-ray ct device, method and program

Abstract

To improve accuracy of arrangement of a scattered ray removal grid relative to a radiation detector.SOLUTION: A medical image processing method includes: a radiation detector including a plurality of channels; a scattered ray removal grid (Anti-Scatter Collimators Or Grid: ASG) arranged on an incident side of the radiation detector and including a plurality of partition walls corresponding to the plurality of channels; and a processing part which executes air-scan using the ASG to acquire count data, determines offset value of the partition walls on the basis of the count data, and determines a parameter indicating difference between the ASG and the radiation detector on the basis of the offset value.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The embodiments disclosed in this specification and the drawings relate to an X-ray CT apparatus, method, and program.

Background Art

[0002] The description of the background art described in this specification is for schematically showing the background of the present disclosure. It is not explicitly or implicitly admitted that the scope of the research (work) described in this background art section and the research of the inventors of the present application on aspects of this specification that were not recognized as prior art at the time of filing are prior art to the present disclosure.

[0003] Computed Tomography (CT) systems and methods are widely used, particularly in medical imaging and diagnosis. A CT system generally creates projection images of one or more cross-sectional slices through a subject's body. An irradiation source, such as an X-ray source, irradiates the body from one side. Generally, a collimator adjacent to the X-ray source limits the angular range of the X-ray beam so that the radiation impinging on the body is limited to a planar region (i.e., the X-ray projection plane) that defines a cross-sectional slice of the body. At least one detector (generally one or more detectors) on the opposite side of the body receives the radiation that has passed through the body in the projection plane. The attenuation of the radiation that has passed through the body is measured by processing the electrical signals received from the detectors. In some implementations, a multi-slice detector configuration is used to provide volume measurement projections of the body rather than planar projections.

[0004] Typically, the X-ray source is attached to a gantry that rotates about the long axis of the body. Similarly, the detector is attached to the gantry on the opposite side of the X-ray source. Cross-sectional images of the body are obtained by performing projection attenuation measurements at a series of gantry rotation angles and transmitting the projection data / sinogram to a processor via a slip ring disposed between the gantry rotor and the gantry stator, and then processing the projection data using a CT reconstruction algorithm (e.g., inverse Radon transform, filtered back projection, Feldkamp-based cone beam reconstruction, iterative reconstruction, or other methods). For example, the reconstructed image may be a digital CT image that is a square matrix of elements (pixels), each of which represents a volume element (volume pixel or voxel) of the patient's body. Depending on the CT system, the combination of translation of the body and rotation of the gantry with respect to the body causes the X-ray source to pass through a spiral or helical trajectory with respect to the body. Next, multiple views are used to reconstruct a CT image showing the internal structure of a slice or multiple such slices.

[0005] The CT sinogram shows the attenuation through the body that varies according to the position along the detector array during various projection measurements and also varies according to the projection angle between the X-ray source and the detector array. In the sinogram, the spatial dimension refers to the position along the array of X-ray detectors. The time / angle dimension refers to the projection angle of the X-rays that varies according to the passage of time during the CT scan. The attenuation arising from a portion of the imaged object (e.g., a vertebra) traces a sine wave about the vertical axis. Those portions further from the axis of rotation correspond to sine waves with larger amplitudes, and the phase of the sine wave corresponds to the angular position of the object about the axis of rotation. An image is reconstructed from the projection data of the sinogram by performing an inverse Radon transform or any other image reconstruction method.

[0006] In a CT system, the X-rays incident on the detector ideally travel in a straight path from the X-ray source through the patient to the detector. However, X-ray scattering occurs through the patient, causing the incident X-rays to reach the detector along different non-straight paths. These scattered X-rays are the cause of the degradation of the resulting patient image. To minimize the arrival of scattered X-rays at the detector, an anti-scatter grid (ASG) may be directly installed in front of the detector. Note that the anti-scatter grid is sometimes called a collimator. By installing the ASG, scattered X-rays from an oblique angle can be absorbed by the ASG while the X-rays traveling in a straight path can freely reach the detector.

[0007] In the case of semiconductor (CdTe / CZT)-based photon counting CT (PCCT), the detector array design may include a very small pixel size compared to other CT detectors due to the trade-off between the charge sharing effect and the pulse multiple collision effect in order to achieve the best energy resolution performance. The pixel pitch can be between 250 μm and 500 μm in one dimension, while the general pixel pitch is about 1 mm. Therefore, the general detector pixel area may typically correspond to an N×N group of sub-pixels in PCCT, where N can be between 2 and 4. To maintain high dose efficiency, the ASG design can maintain the same pitch / spacing as the pixel distribution of other general systems.

[0008] One of the important applications related to PCCT is spectral imaging. To achieve good performance, accurate X-ray source position and alignment of the ASG may help solve the problem of measuring the feasibility of the detector module of the radiation detector. In practice, the ASG is not perfectly positioned or angled relative to the detector, and the entire ASG may be rotated and misaligned, for example. With current technology, it is not easy to physically measure the misalignment of the ASG or the position offset of the X-ray source. Therefore, a new method of radiation detector design for monitoring / calibration without using an external measurement tool is desired.

Prior Art Documents

Patent Documents

[0009]

Patent Document 1

Patent Document 2

Patent Document 3

Summary of the Invention

Problems to be Solved by the Invention

[0010] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to improve the accuracy of the arrangement of the scatter removal grid with respect to the radiation detector. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problems. The problems corresponding to the effects of each configuration shown in the embodiments described later can also be regarded as other problems.

Means for Solving the Problems

[0011] The X-ray CT apparatus according to the embodiment includes a radiation detector including a plurality of channels, an ASG disposed on the incident side of the radiation detector and including a plurality of partition walls corresponding to the plurality of channels, and a processing unit that performs an air scan using the ASG to acquire count data, determines an offset value for the partition wall based on the count data, and determines a parameter indicating a deviation between the ASG and the radiation detector based on the offset value.

Brief Description of the Drawings

[0012]

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[0013] The following disclosure presents many different embodiments, or examples, for implementing various features of the presented subject matter. Specific examples of components and arrangements are described below to simplify the present disclosure. These are, of course, merely examples and are not intended to be limiting. For example, the configuration of a first mechanism on or in a second mechanism in the following description may include embodiments where the first and second mechanisms are configured in a state of direct contact, and may also include implementation forms where the first and second mechanisms are not in direct contact and another mechanism is configured between the first mechanism and the second mechanism. In addition, the present disclosure may repeat reference numbers and / or reference characters in various examples. This repetition is for simplicity and clarity and does not itself define the relationship between the various embodiments and / or configurations being described. Further, to facilitate the description of the relationship of one element or mechanism to other elements or mechanisms as shown in the figures, spatial relative terms such as "upper", "lower", "under", "below", "lower side", "above", "upper side", etc. may be used in this specification. The spatial relative terms are intended to encompass various directions of the device in use or operation in addition to the direction depicted in the figures. The device may be oriented in another way (rotated 90° or in other directions), and the spatial relative descriptions used in this specification may be interpreted accordingly.

[0014] As described herein, the order of description of different procedures is presented for clarity. Generally, these steps can be performed in any suitable order. Also, each of the different features, techniques, and configurations in this specification may be described at various places in the present disclosure, but each concept is intended to be executable independently of or in combination with each other. Therefore, the present invention can be embodied and considered in many different ways.

[0015] Aspects of the present embodiment are directed to a radiation detector design for identifying an ASG offset and an x-ray source misalignment. The radiation detector design, in one embodiment, includes a radiation detector device on the opposite side of an x-ray emitter, which is composed of a two-dimensional array of 38 detector modules. According to one embodiment, a simulated offset is generated and compared with the average offset calculated by a method of the radiation detector design corresponding to the tilt angle.

[0016] For example, the present disclosure relates to an imaging device, the imaging device including a radiation detector including a plurality of channels, a scatter removal grid (ASG) disposed on the incident side of the radiation detector and including a plurality of septa corresponding to the plurality of channels, and a processing circuit configured to obtain count data via an air scan using the ASG disposed on the radiation detector, determine an ASG offset value for a first set of the plurality of septa based on the obtained count data, determine a rotational offset distance of the ASG corresponding to the first channel based on the determined ASG offset value, and adjust the arrangement of the ASG based on the determined rotational offset distance.

[0017] The present disclosure further relates to a method for adjusting a scatter removal grid (ASG) in an imaging device, the method including obtaining count data via an air scan using a scatter removal grid (ASG) disposed on the incident side of a radiation detector, the ASG being disposed on the radiation detector, the ASG including a plurality of channels and a plurality of septa corresponding to the plurality of channels, determining an offset value for a first set of the plurality of septa based on the obtained count data, determining a rotational offset distance of the ASG corresponding to the first channel based on the determined offset value, and adjusting the arrangement of the ASG based on the determined rotational offset distance.

[0018] The present disclosure further relates to a non-transitory computer-readable storage medium including executable instructions that, when executed by a circuit, cause the circuit to implement a method for adjusting an anti-scatter grid (ASG) in an imaging device, the method including obtaining count data via an air scan using an anti-scatter grid (ASG) disposed on an incident side of a radiation detector, the ASG including a plurality of channels and a plurality of septa corresponding to the plurality of channels, the ASG being disposed on the radiation detector; obtaining count data; determining an offset value for a first set of the plurality of septa based on the obtained count data; determining a rotational offset distance of the ASG corresponding to a first channel based on the determined offset value; and adjusting an arrangement of the ASG based on the determined rotational offset distance.

[0019] FIG. 1 is a schematic diagram showing an example of a radiation detector according to an embodiment. The radiation source shown in FIG. 1 faces a curved detector surface. The detector includes a plurality of microchannels arranged along the curve. Hereinafter, a plurality of microchannels are described as one unit, as a macrochannel, or simply as a channel. For example, in FIG. 1, each macrochannel includes three microchannels. The septa of the anti-scatter grid (ASG) are disposed at the right and left ends of the macrochannel. Each of the microchannels has an equal pixel width according to an example. Note that the number of microchannels included in one macrochannel is not limited, and it is not essential to configure a macrochannel with a plurality of macrochannels as one unit.

[0020] The X-ray source can emit photons. The microchannels can be configured to absorb the emitted photons and convert the photons into electrical signals. Photons traveling linearly from the radiation source may be blocked by the septa of the ASG, casting shadows (for example, left shadow L and right shadow R) on adjacent microchannels, and this shadow may reduce photon absorption by the detector. Additionally, rotational misalignment of the ASG can also occur.

[0021] For this purpose, the following embodiments describe a method and an apparatus that can solve the problem of overall rotational misalignment between the ASG and the detector. FIG. 2 is a schematic diagram showing the rotational misalignment of the ASG with respect to the radiation source and detector module according to an embodiment of the present disclosure. In one embodiment, the ASG misalignment includes a rotation of an offset angle λ with respect to the detector about one end of the detector (ASG rotation point). At this time, the offset amount of the other end of the ASG is defined as an offset distance d L Let it be. The offset distance d L is the rotational distance caused by the rotation of the angle λ. Since it may be difficult to physically measure the offset angle λ or the offset distance d L , the method of this embodiment aims to estimate the offset angle and / or the offset distance from the available scan data. Note that in FIG. 2, the center point when the ASG is regarded as an arc is illustrated as the ASG apex.

[0022] Hereinafter, an example of determining the offset distance d L as a parameter indicating the deviation between the ASG and the radiation detector will be described. Of course, the embodiment is not limited to this, and the offset angle λ may be determined as a parameter indicating the deviation between the ASG and the radiation detector.

[0023] In one embodiment, the radiation detector device includes 38 DMBs (Detector Module Blades), each having a detector pixel facing an X-ray source. In one aspect, each of the DMBs can be further subdivided into four CZT (cadmium zinc telluride: CdZnTe) sub-modules. Each of the CZT sub-modules may include, for example, an array of 36×24 micro-pixels according to one embodiment.

[0024] In one embodiment, the micro-pixels in each row direction of the DMB represent micro-rows, and the micro-pixels in each column direction of the DMB represent micro-channels. In an exemplary embodiment, the ASGs are arranged to intersect every three micro-channels. In this arrangement, the ASG septa do not cast a shadow on the central micro-pixel, and can filter scattered X-ray photons emitted by the X-ray source, thereby improving the image quality and avoiding problems that degrade the image such as ring artifacts.

[0025] In another embodiment, each of the DMBs includes an array of 12 CZT sub-modules arranged in a 2×6 grid pattern, where the ASGs are arranged for every three micro-pixels of the CZT. In this embodiment, each septum of the ASG includes a strip of lead separated by a low-attenuation gap material such as carbon fiber or aluminum that extends between every three micro-pixels.

[0026] FIG. 3 is a schematic diagram showing a shadow when misalignment according to an embodiment occurs. In FIG. 3, an exemplary misalignment of the ASG is shown in which, according to an embodiment of the present disclosure, the ASG casts a shadow on some of the micro-pixels of a three-micro-pixel channel. In one embodiment, assuming that both the ASG and the micro-pixels are accurately positioned and aligned, the shadow of the ASG may be consistent with respect to all ASG septum positions and corresponding micro-pixels. During an air scan, the counts measured for a particular micro-pixel may be directly proportional to the area where the micro-pixel is not shadowed. Note that in the embodiments, the air scan is not limited to a scan targeting air, and may be, for example, a scan targeting a phantom with a predetermined composition. As shown in FIG. 3, since there are no septa and no shadow in the central micro-channel of the channel, the total count is obtained.

[0027] However, as shown in Figure 3, if there are some misalignments between the ASG and the micro-pixels, the count and shadow length of the left and right micro-pixels of the channel may deviate from the ideal scenario. Using the following equations (1), (2), (3), and (4), the left and right shadow lengths, as well as the corresponding left and right ASG offsets, can be calculated based on the count at each micro-pixel, the ASG septum width, and the micro-pixel width.

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[0032] In the formula, W p is the micro-pixel width, N R,ch is the air count of the channel corresponding to the right micro-channel, N L,ch is the air count of the channel corresponding to the left micro-channel, N C,ch is the air count of the channel corresponding to the central micro-channel, ch is the channel identifier, and W ASG is the ASG septum width.

[0033] In one embodiment, equations (1) and (2) are used to calculate the amount of shadow (shadow R ch and shadow L ch ) of the right and left micro-channels of a given channel, based on the air count measured for the micro-channels and Wp It can be determined or calculated based on the following. Next, using equations (3) and (4), the left and right ASG offsets are determined based on the determined left and right shadow amounts and the width W of the corresponding ASG partition wall ASG and can be calculated based on this.

[0034] FIG. 4A is a diagram showing an example of a processing flow according to an embodiment. Specifically, FIG. 4A shows a non-limiting example of a flowchart of a method 400 for determining and correcting the rotational offset of an ASG according to an embodiment of the present disclosure.

[0035] In one embodiment, at step 405, the ASG air count data for different values of the offset distance d L can be determined via simulation.

[0036] In one embodiment, at step 410, an ASG offset curve can be generated from an air scan.

[0037] In one embodiment, at step 415, based on the ASG offset curve, a look-up table can be generated for different values of the offset distance d L against which.

[0038] In one embodiment, at step 420, an air scan using the ASG can be performed.

[0039] In one embodiment, at step 425, the ASG offset can be determined.

[0040] In one embodiment, at step 430, the acquired data can be smoothed.

[0041] In one embodiment, at step 435, the offset distance d L can be determined via the look-up table.

[0042] In one embodiment, at step 440, the ASG can be adjusted based on the corresponding look-up table data.

[0043] In one embodiment, briefly speaking, method 400 may include two distinct initial processes that are separately executable from each other. The first process starting at step 405 may include pre-computing or pre-determining a look-up table that takes the ASG offset as an input and outputs the offset distance d L through simulation. The second process starting at step 420 may include performing an actual scan such as an air scan using the ASG and determining the ASG offset. Next, at step 435, the value of the offset distance d L may be determined, and accordingly, the ASG may be adjusted.

[0044] FIG. 4B is a diagram showing an example of a look-up table generation process according to an embodiment. Specifically, FIG. 4B shows a non-limiting example of a schematic diagram representing the first process according to an embodiment of the present disclosure with respect to steps 405 to 415 in FIG. 4A. In one embodiment, the first process may be a simulation-based process. The upper box corresponds to step 405 and explains how the ASG air count data for different values of the offset distance d L can be simulated. The middle box corresponds to step 410 and shows an example of a simulated ASG offset curve where the offset distance d L is in the range from "0" to "0.05". As shown, as the offset distance d L increases, the ASG offset also increases across the entire changing curve for the offset distance d L in the same channel. This may be represented as an upward slope of the shown curve. The lower box corresponds to step 415 and shows an example of a curve representing the offset distance versus the ASG offset. As shown, as the ASG offset increases, the offset distance dL also increases. From this data, a look-up table can be generated.

[0045] In particular, during air scan, the ASG offset curve shape and fit may exhibit patterns and shapes. For this reason, FIG. 5 shows a set of graphs representing the ASG offset and the offset distance that varies according to the ASG offset according to an embodiment of the present disclosure. In one embodiment, the upper graph explains the ASG offset in the simulated air scan and the actual air scan. On the other hand, the lower graph explains the relationship between the offset distance and the ASG offset. As shown in the upper graph, the non-smooth solid line curve represents the actual ASG offset measurement from the air scan, which may represent noise due to individual ASG / CZT offsets.

[0046] In addition to the individual ASG offsets, an overall rise of the curve may be seen due to the offset distance d L Accordingly, the dashed curve is a quadratic polynomial fit to the ASG / CZT offset plot, which can be used to smooth the noisy curve. The last channel point (x-axis) of the polynomial fit can be used as an input to the look-up table. In one embodiment, different channels, such as the channel with the maximum offset, may be used as the input. For example, the first channel point of the polynomial fit may be used. The solid line curve that is substantially smooth (compared to the actual ASG offset curve before smoothing) and close to the dashed curve may be the simulated ASG offset curve. For example, the simulated ASG offset curve may represent an offset distance of "d L = 30 μm".

[0047] In one embodiment, the following graph illustrates the offset distance versus the ASG offset, such that the offset distance d is determined using the last channel point of the polynomial fit of the ASG offset curve (smooth or non-smooth). L As shown, the value of the last channel ASG offset of the smooth ASG offset curve may be "30.62 μm", which may correspond to an offset distance d of "21 μm" based on the curve of the following graph. L Although described as a graph, it will be understood that the above can be used to generate a look-up table and that the corresponding entry in the look-up table can be retrieved to generate the offset distance.

[0048] Regarding step 440, subsequent adjustment or correction of the ASG may be performed, for example, by a technician or operator, based on the determined value of the offset distance d. L Additionally or alternatively, the adjustment or correction of the ASG can be automatically performed, for example, by a connected computer or similar processing circuit.

[0049] In particular, as previously described, the pivot point of the ASG can be located at the first or last channel (at one end of the detector), at which time the opposite channel (at the other end of the detector) is offset by the offset distance d. L That is, the pivot point of the ASG can be assumed to have a zero offset.

[0050] In one embodiment, the pivot point of the ASG need not be positioned at the first or last channel. Additionally or alternatively, in one embodiment, there may also be a baseline offset or an overall translational offset of the ASG from the detector. That is, the ASG need not be positioned accurately and proximally to the detector at any part of the ASG.

[0051] For this purpose, FIG. 6 shows a schematic diagram of an ASG having a rotational offset and a translational offset with respect to a detector according to an embodiment of the present disclosure. Here, the value of the translational offset distance may be represented by the lateral offset distance d R in some cases. Again, the offset distance d L represents the offset distance caused by the rotation of the ASG, but may also include a translational offset. The lateral offset distance d R is an example of a parameter indicating the deviation between the ASG and the radiation detector.

[0052] FIG. 7 shows a schematic diagram of an ASG having a compression offset according to an embodiment of the present disclosure. In one embodiment, on the ASG side with respect to the detector, compressive deformation is shown, and as a result, a compression offset from the detector occurs. Multiple types of offsets such as rotational offset, translational offset, and compression offset may occur as a combination. The method described in this specification can determine each of the multiple types of offsets using the ASG offset curve. Offsets such as rotational offset, translational offset, and compression offset are examples of parameters indicating the deviation between the ASG and the radiation detector.

[0053] That is, the offset distance d L may be caused only by the rotational offset as shown in FIG. 2, may be caused only by the compression offset as shown in FIG. 7, or may be caused only by the translational offset (not shown). Also, as shown in FIG. 6, the offset distance d L may be caused by a combination of the rotational offset and the translational offset. Additionally, although not shown, the offset distance d L may occur due to any combination of multiple types of offsets such as rotational offset, translational offset, and compression offset.

[0054] The lateral offset distance d RSimilarly, as shown in FIG. 6, it may be caused only by the translational offset, or as shown in FIG. 7, it may be caused only by the compression offset. As shown in FIG. 2, when only the rotational offset occurs, the lateral offset distance d R becomes zero. In addition, the lateral offset distance d R can occur due to any combination of multiple types of offsets such as rotational offset, translational offset, and compression offset.

[0055] Referring to FIG. 2, let's review the determination of the offset distance d L . The value of the offset distance d L substantially represents the distance from the end of the ASG to the corresponding detector position (e.g., detector channel, element, pixel, etc.). Similarly, in the event of a compression offset, the opposite end of the ASG may deflect away from the detector at the opposite end of the detector. Assuming symmetric compression (as shown in FIG. 7), due to the deflection of both ends of the ASG, the ASG offset curve (substantially an air scan) shows another upward curve that terminates at the first channel. As a note, the ASG offset curve in FIG. 5 shows an upward curve starting from an offset of "0 μm" at the first channel because the rotation is fixed at the first channel. In the case of a compression offset, the ASG offset curve starts with the same ASG offset of "30.62 μm" at the first channel, then decreases until it reaches an ASG offset of "0 μm" (as shown in FIG. 7 with the ASG approaching the central detector), and may increase again until it reaches an ASG offset of "30.62 μm". Here too, since the compression offset is shown symmetrically, the ASG offsets at the first channel and the last channel are the same, and as a result, the shape of the ASG offset curve is a symmetric bow shape. Of course, these values can be used as inputs for determining the offset distance that can be used to adjust the ASG via a look-up table.

[0056] In one embodiment, the compressed ASG rotates and moves, and thus can be further extended for non-symmetrical events. For such events, the method can determine three parameters or inputs from the ASG offset curve, namely, i) the upper channel value, ii) the lower channel value, and iii) the central channel value. The upper channel value can be the highest ASG offset value, the lower channel value can be the second highest ASG offset value, and the central channel value can be the ASG offset value for the channel located between the channel corresponding to the upper channel value and the channel corresponding to the lower channel value. Due to the curvature of the ASG, the lower channel value may still be higher than the central channel value, and it should be understood that the upper channel value and the lower channel value simply represent the relationship of their values to each other (and do not include the central channel value). For example, the upper channel value may be described as the first edge channel value, additionally or alternatively, the lower channel value may be the second edge channel value, and the central channel value may be the non-edge channel value. Note that the ASG offset value is also referred to as the offset value.

[0057] In one embodiment, the three determined parameters may be used to determine the curvature of the ASG. As described above, the ASG may be different from the curvature of the detector due to compression deformation. The curvature may correlate with the value of the compression offset of the generated look-up table, and / or the value of the compression offset of the generated curve of the compression offset with respect to the ASG offset, and / or the value of the compression offset of a separate generated compression offset look-up table. By determining the curvature of the ASG, the compression offset can be determined and the ASG can be adjusted. Instead of or in addition to these, the compression offset can be used to improve the accuracy of the results in image reconstruction, data processing, and correction. The curvature of the ASG is an example of a parameter indicating the deviation between the ASG and the radiation detector.

[0058] The three determined parameters may be used to determine the lateral offset. Based on the baseline offset of the ASG offset curve, the lateral offset distance d R may be determined. For example, in the upper graph of FIG. 5, for an ASG that is not offset from the first channel of the detector, the ASG offset of the first channel (leftward on the x-axis) may be "0". This is because in the ASG shown in FIG. 2, it is assumed that one location (assumed to be the first channel) is arranged close to the detector. However, for an ASG with a lateral offset, the ASG value of the first channel (in the examples of FIGS. 2 and 5) may not be zero. Therefore, the ASG offset curve starts above zero at the first channel, and this difference between zero and the value of the ASG offset curve at the first channel may be used to determine the lateral offset distance d R . That is, the value of the ASG offset curve at the first channel (of FIGS. 2 and 5) is the lateral offset distance d R of the generated look-up table, and / or the lateral offset distance d R corresponding to the ASG offset for the curve generated for d R , and / or the lateral offset distance d R of a separately generated d R look-up table may be correlated.

[0059] As described above, the three determined parameters can be used to determine the rotational offset. In particular, the method according to the embodiment can determine the ASG offset value of the upper channel and correct or remove the offset contribution factors from the lateral offset and the compression offset. Again, referring to FIG. 5, the ASG offset value of the last channel of the smoothed ASG offset curve (upper graph) may be "30.62 μm", which is "21 μm" of d LIt may correspond. Again, the value can be obtained from the graph and / or the generated look-up table.

[0060] Referring to the offset determination described above, FIG. 8 shows a non-limiting example of a flowchart of a method 800 for determining and correcting the offset of an ASG according to an embodiment of the present disclosure.

[0061] In one embodiment, at step 805, an air scan using the ASG can be performed to generate an ASG offset curve.

[0062] In one embodiment, at step 810, the ASG offset value of the first channel (e.g., the upper channel value), the ASG offset value of the second channel (e.g., the lower channel value), and the ASG offset value of the third channel (e.g., the middle channel value) can be determined from the ASG offset curve.

[0063] In one embodiment, at step 815, the obtained data of the ASG offset curve can be optionally smoothed.

[0064] In one embodiment, at step 820, the rotational offset distance d L , the lateral offset distance d R , and the value of the compression offset can be determined based on the ASG offset value of the first channel, the ASG offset value of the second channel, and the ASG offset value of the third channel. For example, at step 820, the curvature of the ASG can be determined as the value of the compression offset.

[0065] In one embodiment, at step 825, the ASG can be adjusted or corrected based on the value determined at step 820. For example, the compression offset may be corrected, the lateral offset distance may be corrected, and the rotational offset distance may be corrected. Alternatively, any combination of the above may be corrected. The adjustment or correction may be performed, for example, by a technician or an operator. Additionally or alternatively, the adjustment or correction can be automatically performed, for example, by a connected computer or a similar processing circuit.

[0066] In one embodiment, a neural network can be used to determine the above values. The neural network is trained, for example, using a reference rotational offset distance and a corresponding reference ASG offset value. FIG. 9 shows a non-limiting example of a flowchart of a method 900 for determining and correcting an offset of an ASG according to an embodiment of the present disclosure.

[0067] In one embodiment, at step 905, an air scan using the ASG can be performed to generate an ASG offset curve.

[0068] In one embodiment, at step 910, a neural network can be used to process the acquired ASG offset data.

[0069] In one embodiment, at step 915, the neural network is used to determine, from the ASG offset curve, the ASG offset value of the first channel (e.g., the upper channel value), the ASG offset value of the second channel (e.g., the lower channel value), and the ASG offset value of the third channel (e.g., the central channel value). The neural network can use the generated look-up table (or graph) to obtain the corresponding offset distance value and compression offset based on the acquired ASG offset value.

[0070] In one embodiment, at step 920, the ASG can be adjusted or corrected based on the value determined at step 915. The adjustment or correction may be performed, for example, by a technician or an operator. Additionally or alternatively, the adjustment or correction can be automatically performed, for example, by a connected computer or a similar processing circuit.

[0071] FIG. 10A shows an example of the geometry of a single ASG septum disposed in the radiation detector of FIG. 1 according to an embodiment of the present disclosure. Here, the coordinates of the septum at the center of the detector can be obtained by the following equations (5) to (12).

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[0080] Figure 10B shows an example of the geometry of the partition wall position in an example according to an embodiment of the present disclosure. Here, the ASG partition wall coordinates can be obtained by the following equations (13) to (22).

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[0091] Each term in Formula (13) to Formula (22) can be expressed as in the following Formula (23) to Formula (33).

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[0103] Figure 11 shows an ASG rotational offset or misalignment according to an embodiment of the present disclosure. In one embodiment, the ASG can be offset by an offset distance d at one end and rotated by substantially an angle λ about the rotation point in the first detector channel. The primary coordinate system may have a base point (0,0) at the rotation point. L and can be rotated by substantially an angle λ about the rotation point in the first detector channel. The primary coordinate system may have a base point (0,0) at the rotation point.

[0104] The dual primary coordinate system may have a base point (0,0) at the rotated ASG source. The coordinate transformation may be used to calculate the misaligned ASG septum position (described herein). The ideal ASG that is transformed to the primary coordinate system and rotated can be represented by the following equations (34) to (39).

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[0111] Figure 12 shows the calculation of the misaligned ASG and the partition wall according to an embodiment of the present disclosure. In one embodiment, the rotated principal ASG transformation and the partition wall position into the double principal coordinate system can be calculated through the following equations (40) to (54).

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[0127] In one embodiment, the transformation for returning the rotated double main partition position to the main coordinate system can be calculated through the following equations (55) to (60).

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[0134] In one embodiment, the conversion for returning the rotated double main partition position to the true main coordinate system can be calculated through the following formulas (61) to (74).

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[0149] Figure 13 shows the geometry for performing ASG offset calculations according to an embodiment of the present disclosure. In one embodiment, the left and right offsets can be obtained by the following equations (75) to (76).

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[0152] When the following formula (77) is satisfied in formulas (75) to (76), it becomes as shown in formula (78). On the other hand, when formula (77) is not satisfied, it becomes as shown in formula (79).

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[0156] And when the following formula (80) is satisfied, it becomes as shown in formula (81). On the other hand, when formula (80) is not satisfied, it becomes as shown in formula (82).

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[0160] Furthermore, the intersections and angles between the light rays of the four partition walls and the detector can be obtained by the following equations (83) to (91).

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[0170] The equations for the source-partition wall corner array can be obtained by the following equations (92) to (94).

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[0174] Figures 14A and 14B show various examples of Deep Learning (DL) networks.

[0175] Figure 14A shows an example of a general artificial neural network (ANN) having N input values, K hidden layers, and 3 output values. Each layer is composed of nodes (also called neurons), and each node performs a weighted sum of the input values and compares the result of the weighted sum with a threshold to generate an output value. The ANN creates a class of functions, and in this case, the members of this class are obtained by changing details of the structure such as the threshold, connection weights, or the number and / or connectivity of the nodes. The nodes in the ANN are sometimes called neurons (or neuron nodes), and these neurons may have mutual connections between different layers of the ANN system. The simplest ANN has three layers and is called an autoencoder.

[0176] [Number]

[0177] Synapses (i.e., the junctions between neurons) store a value called a "weight" (also called a "coefficient" or "weighting coefficient" in the same sense) and process data during calculations. The output value of an ANN depends on three types of parameters: (i) the interconnection pattern between different layers of neurons, (ii) the learning process for updating the weights of the interconnections, and (iii) the activation function that converts the weighted input values of the neurons into their output activations.

[0178] Mathematically, the network function m(x) of a neuron is defined as the composition of other functions n i (x), which can in turn be defined as the composition of other functions. This may be represented, for convenience, as a network structure with arrows indicating the dependencies between variables, as shown in each figure. For example, an ANN may use a non-linear weighted sum, where m(x) = K(Σ i w i n i (x)), and K (usually called an activation function) is one of several predefined functions such as the hyperbolic tangent.

[0179] In FIG. 14A (and similarly in FIG. 14B), the neurons (i.e., nodes) are depicted as circles around a threshold function. In the non-limiting example shown in FIG. 14A, the input values are depicted as circles around a linear function, and the arrows indicate the directed connections between the neurons. In a particular implementation, the DL network is a feedforward network such as illustrated in FIGS. 14A and 14B (which may be represented, for example, as a directed acyclic graph).

[0180] The DL network 135 functions to achieve a specific task such as noise removal of CT images by searching within the class of functions F to be learned using a set of observation results to find "m* ∈ F", thereby solving a specific task with some optimal criterion. For example, in a specific implementation form, this can be achieved by defining a cost function "C: F → m", in which case, for the optimal solution "m*", it is as shown in the following equation (96) (that is, there is no solution with a cost smaller than the cost of the optimal solution). The cost function C is a measure of how far a specific solution is from the optimal solution for the problem to be solved (for example, error). The learning algorithm repeatedly searches through the solution space to find a function with a minimum cost. In a specific implementation form, the cost is minimized over a sample of data (i.e., training data).

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[0182] Figure 14B shows a non-limiting example where the DL network is a convolutional neural network (CNN). The CNN is a type of ANN and has beneficial characteristics for image processing, and thus has a special relevance for applications such as image noise removal and sinogram restoration. The CNN uses a feedforward ANN where the connectivity pattern between neurons may represent a convolution during image processing. For example, the CNN may be used in image processing optimization by using multiple layers of small neuron sets that process a part of the input image called the receptive field. Next, the output values of those sets may be tiled in an overlapping manner to obtain a better depiction of the original image. This processing pattern may be repeated over multiple layers having alternating convolutional layers and pooling layers.

[0183] FIG. 15 is a diagram showing an example of an X-ray CT apparatus according to an embodiment. The X-ray CT apparatus is also called a CT apparatus, a CT system, or a CT scanner. The X-ray CT apparatus includes a radiation imaging gantry 500. As shown in FIG. 15, the radiation imaging gantry 500 is depicted as viewed from the side and further includes an X-ray tube 501, an annular frame 502, and a multi-row or two-dimensional array type X-ray detector 503. The X-ray tube 501 and the X-ray detector 503 are attached to the annular frame 502 so as to be directly opposite to each other across the object S, and the annular frame is rotatably supported about a rotation axis RA. A rotating device 507 rotates the annular frame 502 at a high speed of "0.4 seconds / rotation", and at the same time, the object S is moved along the axis RA in the direction behind or in front of the illustrated plane.

[0184] A first embodiment of an X-ray computed tomography (CT) apparatus will be described below with reference to the accompanying drawings. It should be noted that the X-ray CT apparatus includes various types of apparatuses, such as a rotation / rotation type apparatus in which both the X-ray tube and the X-ray detector rotate around the object to be examined, and a fixed / rotation type apparatus in which a large number of detector elements are arranged in an annular or horizontal shape and only the X-ray tube rotates around the object to be examined. The embodiment is applicable to any type. Here, the currently mainstream rotation / rotation type will be exemplified.

[0185] The multi-slice X-ray CT apparatus further includes a high-voltage generator 509. The high-voltage generator generates a tube voltage that is applied to the X-ray tube 501 through the slip ring 508 so that the X-ray tube 501 generates X-rays. The X-rays are irradiated toward an object S whose cross-sectional area is represented by a circle. For example, the X-ray tube 501 has X-ray energy such that the average X-ray energy during the first scan is smaller than the average X-ray energy during the second scan. Therefore, there may be cases where two or more scans corresponding to different X-ray energies are obtained. The X-ray detector 503 is disposed on the opposite side of the X-ray tube 501 across the object S in order to detect the irradiated X-rays that have propagated through the object S. The X-ray detector 503 further includes individual detector elements or detector units.

[0186] The CT apparatus further includes other devices that process the detection signals from the X-ray detector 503. The data acquisition circuit or data acquisition system (Data Acquisition System: DAS) 504 converts the signal output from the X-ray detector 503 for each channel into a voltage signal, amplifies the signal, and further converts the signal into a digital signal. The X-ray detector 503 and the DAS 504 are configured to process a predetermined total number of projections per rotation (Total number of Projections Per Rotation: TPPR).

[0187] The above-described data is transmitted through the non-contact data transmitter 505 to the preprocessing device 506 housed in a console outside the radiation imaging gantry 500. The preprocessing device 506 performs certain corrections such as sensitivity correction on the unprocessed data. The memory 512 stores the resultant data, which is also called projection data at a stage immediately before the reconstruction process. The memory 512 is connected to the system controller 510 through the data / control bus 511 together with the reconstruction device 514, the input device 515, and the display 516. The system controller 510 controls the current regulator 513 that limits the current to a level sufficient to drive the CT system.

[0188] The detector rotates and / or is fixed with respect to the patient, regardless of the generation of the CT scanner system. In one implementation, the above-described CT system may be an example in which a third-generation geometry system and a fourth-generation geometry system are combined. In the third-generation system, the X-ray tube 501 and the X-ray detector 503 are attached diametrically opposite to each other on the annular frame 502, and rotate around the object S when the annular frame 502 rotates about the rotation axis RA. In the fourth-generation geometry system, the detector is fixedly installed around the patient, and the X-ray tube rotates around the patient. In an alternative embodiment, the radiographic gantry 500 has a number of detectors arranged on the annular frame 502, supported by a C-arm and a stand.

[0189] The memory 512 may store measurement values indicating the X-ray exposure dose at the X-ray detector 503. Further, the memory 512 can store dedicated programs for executing various steps of the methods described herein.

[0190] The reconstruction device 514 can execute various steps of the methods described herein. For example, the reconstruction device 514 can execute a scan using ASG to obtain count data, determine an offset value for the septum based on the count data, and determine a parameter indicating the deviation between the ASG and the radiation detector based on the offset value. The reconstruction device 514 is an example of a processing unit. Further, the reconstruction device 514 can execute pre-reconstruction image processing such as volume rendering processing and image difference processing, if necessary.

[0191] The pre-reconstruction processing of the projection data performed by the preprocessing device 506 may include, for example, detector calibration, detector non-linearity, and correction of the polarity effect. Further, the pre-reconstruction processing may include various steps of the methods described herein.

[0192] The post - reconstruction processing performed by the reconstruction device 514 can include, if necessary, image filtering and image smoothing, volume rendering processing, and image difference processing. The image reconstruction process can execute various steps of the methods described herein in addition to various image reconstruction methods. The reconstruction device 514 can use memory to store, for example, projection data, reconstructed images, calibration data and parameters, and computer programs, etc.

[0193] The reconstruction device 514 may include a CPU (processing circuit) implemented as discrete logic gates, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), or another Complex Programmable Logic Device (CPLD). The FPGA or CPLD implementation form may be coded in VHDL, Verilog, or any other hardware description language, and the code may be directly stored in the electronic memory inside the FPGA or CPLD, or stored as separate electronic memory. Further, the memory 512 may be non - volatile memory such as ROM, EPROM, EEPROM or FLASH memory. The memory 512 can be volatile memory such as static or dynamic RAM, and a processor such as a microcontroller or microprocessor may be provided to manage the interaction between the electronic memory and the FPGA or CPLD and the memory.

[0194] Alternatively, the CPU of the reconfiguration device 514 can execute a computer program that includes a set of computer-readable instructions for performing the functions described herein, and this program is stored in any of the aforementioned non-transitory electronic memory and / or hard disk drive, CD, DVD, FLASH drive, or any other known storage medium. Further, these computer-readable instructions may be provided as a utility application, a background daemon, or a component of an operating system, or a combination thereof, and are executed in conjunction with a processor such as the Xenon processor of Intel Corporation in the United States, or the Opteron processor of AMD Corporation in the United States, and an operating system such as Microsoft's VISTA, UNIX (registered trademark), Solaris, LINUX (registered trademark), Apple's MAC-OS, and other operating systems known to those skilled in the art. Further, the CPU may be implemented as a plurality of processors that cooperate in parallel to execute instructions.

[0195] In one implementation, the reconfigured image may be displayed on the display 516. The display 516 can be an LCD display, a CRT display, a plasma display, an OLED, an LED, or any other display known in the art.

[0196] The memory 512 can be a hard disk drive, a CD-ROM drive, a DVD drive, a FLASH drive, a RAM, a ROM, or any other electronic storage device known in the art.

[0197] The examples of radiation detector device data and functional operations described in this specification may be implemented by digital electronic circuits, tangible embodied computer software or firmware, computer hardware, including the structures disclosed in this specification and their structural equivalents, or one or more combinations thereof. Embodiments of the subject matter described in this specification may be implemented as one or more computer programs for execution by, or to control the operation of, a data processing apparatus such as a networked device or server, a user device, i.e., as one or more modules of computer program instructions encoded on a tangible non-transitory program carrier. A computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or one or more combinations thereof.

[0198] The term "data processing apparatus" means data processing hardware and may include all kinds of devices, apparatuses, and machines for processing data, such as, for example, programmable processors, computers, or multiple processors or computers. The apparatus may also be, or further include, dedicated logic circuitry, such as an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit). The apparatus may optionally include, in addition to the hardware, code for constructing an execution environment for computer programs, such as processor firmware, protocol stack, database management system, operating system, or code constituting one or more combinations thereof.

[0199] A computer program, also referred to as or may be described as a program, software, software application, module, software module, script, or code, may be described in any form of programming language including a compiled or interpreted language, or a declarative or procedural language, and it can be deployed in any form, such as a stand-alone program or module, component, subroutine, or other unit suitable for use in a computing environment. A computer program may optionally, but not necessarily, correspond to a file in a file system. The program may be part of a file that holds other programs or data, for example, one or more scripts stored in a markup language document, a single file dedicated to the program in question, or multiple related files, for example, files that hold one or more modules, subprograms, or portions of code. A computer program may be deployed to be executed on one computer or multiple computers, either located in one place or distributed across multiple places interconnected by a communication network.

[0200] According to one embodiment, the processes and logical flows described herein may be implemented by one or more programmable computers executing one or more computer programs to perform functions by operating input data and generating output. The processes and logical flows may also be implemented by a device, such as a dedicated logic circuit, implemented as, for example, an FPGA, an ASIC.

[0201] Computers suitable for the execution of a computer program include, by way of example, general-purpose or special microprocessors or both, or any other kind of central processing unit. Generally, the CPU receives instructions and data from a read-only memory or a random access memory or both. The components of a computer are a CPU for executing or running instructions, and one or more memory devices for storing instructions and data. Generally, a computer also includes or is operably connected to data received from one or more mass storage devices (such as magnetic disks, magneto-optical disks, or optical disks) for storing data, or data transmitted to the mass storage devices, or both. However, a computer need not include such devices. Further, a computer may be incorporated in another device, such as a cellular phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable memory device, such as a universal serial bus (USB) flash drive. Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and memory devices, by way of example, semiconductor memory devices (such as EPROM, EEPROM, and flash memory devices), magnetic disks (such as internal hard disks or removable disks), magneto-optical disks, and CD-ROM and DVD-ROM disks. The processor and the memory are supplemented by, or incorporated in, dedicated logic circuitry.

[0202] To provide interaction with a user, embodiments of the subject matter described herein can be implemented on a computer having a display device for displaying information to the user, such as a cathode ray tube (CRT) or liquid crystal display (LCD) monitor, a keyboard by which the user can provide input to the computer, and a pointing device, such as a mouse or trackball. Other types of devices may also be used to provide interaction with the user. For example, the feedback provided to the user may be any form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback, and the input received from the user may be in any form, including acoustic input, voice input, or tactile input. In addition, the computer can communicate with the user by sending a document to the device being used by the user and receiving a document from that device, for example, by sending a web page to a web browser on the user's device in response to a request received from the web browser.

[0203] In another embodiment, the subject matter described herein can be implemented in a computing system that includes, for example, a backend component such as a data server, or includes a middleware component such as an application server, or includes a frontend component such as a graphical user interface or a web browser through which a user can interact with an implementation of the subject matter described herein, or includes any combination of one or more such backend, middleware, or frontend components. Each component of the system can be interconnected by any form or medium of digital data communication, such as a communication network. Examples of communication networks include a Local Area Network (LAN) and a Wide Area Network (WAN), such as the Internet.

[0204] FIG. 16 shows an illustration of the hardware of device 1201 according to an embodiment of the present disclosure. In FIG. 16, device 1201, which may be any of the devices described above including a server and a user device, includes a processing circuit. The processing circuit includes one or more of the elements described next with reference to FIG. 16. Processing data and instructions can be stored in memory 1202. These processes and instructions may be stored on disk 1204, such as a Hard Drive (HDD) or a portable storage medium, or may be stored remotely. Further, the claimed advancement is not limited to the form of a computer-readable medium in which the instructions of the processes of the present invention are stored therein. For example, the instructions may be stored on a CD, DVD, flash memory, RAM, ROM, PROM, EPROM, EEPROM, hard disk, or any other information processing device that communicates with device 1201, such as a server or a computer.

[0205] Furthermore, the claimed advancements may be provided as a utility application, background daemon, or component of an operating system, or a combination thereof, and may be executed in conjunction with a CPU 1200 and operating systems such as Microsoft Windows®, UNIX, Solaris, LINUX, Apple MAC-OS, and other systems known to those skilled in the art.

[0206] The hardware elements for implementing the device 1201 can be realized by various circuit elements known to those skilled in the art. For example, the CPU 1200 may be an Intel Xeon or Core processor from Intel Corporation in the United States, an Opteron processor from AMD in the United States, or other types of processors that would be recognized by those skilled in the art. Alternatively, as would be recognized by those skilled in the art, the CPU 1200 can be implemented using an FPGA, ASIC, PLD, or discrete logic circuits. Further, the CPU 1200 may be implemented as a plurality of processors that cooperate in parallel to execute the instructions of the aforementioned processing.

[0207] The device 1201 of FIG. 16 also includes a network controller 1206, such as an Intel Ethernet® PRO network interface card from Intel Corporation in the United States, to interface with the network 1250 and communicate with other devices. As understood, the network 1250 can be a public network such as the Internet, a private network such as a LAN or WAN network, or a combination thereof, and can also include a PSTN or ISDN subnetwork. The network 1250 can be a wired system such as an Ethernet® network, or a wireless system such as a cellular network including EDGE, 3G, 4G, and 5G wireless cellular systems. The wireless network can be WiFi, Bluetooth®, or any other known wireless form of communication.

[0208] Device 1201 further includes a display controller 1208, such as an NVIDIA GeForce GTX or Quadro graphics adapter from NVIDIA Corporation in the United States, to interface with a display 1210, such as an LCD monitor. The general-purpose I / O interface 1212 interfaces with a keyboard and / or mouse 1214, as well as a touch screen panel 1216 on or separate from the display 1210. The general-purpose I / O interface also connects to various peripheral devices 1218, including printers and scanners.

[0209] The general-purpose storage device controller 1224 connects to a storage medium disk 1204, along with a communication bus 1226, which may be ISA, EISA, VESA, PCI, or similar, for interconnecting all components of the device 1201. Descriptions of the general characteristics and functions of the display 1210, keyboard and / or mouse 1214, as well as the display controller 1208, storage device controller 1224, network controller 1206, audio controller 1220, and general-purpose I / O interface 1212 are omitted in this specification for the sake of brevity, as these characteristics are known.

[0210] FIG. 17 shows an example of a certain type of computer according to an embodiment of the present disclosure. The computer 1300 may be used for the operations described in conjunction with any of the computer-implemented methods according to the foregoing one implementation form. That is, the various methods according to the embodiment may be executed by the computer 1300 in FIG. 17. The computer 1300 is, for example, a medical information processing device separate from the X-ray CT device shown in FIG. 15. Alternatively, the computer 1300 may be included in the X-ray CT device shown in FIG. 15. For example, the computer 1300 executes the various methods according to the embodiment as the reconstruction device 514 shown in FIG. 15.

[0211] For example, computer 1300 may be an example of a networked device such as a server that includes a processing circuit as discussed herein. The processing circuit includes one or more of the elements described next with reference to FIG. 17. In FIG. 17, computer 1300 includes a processor 1310, a memory 1320, a storage device 1330, and an input / output device 1340. Each of components 1310, 1320, 1330, and 1340 is interconnected using a system bus 1350. The processor 1310 can process instructions for execution within system 1300. In one implementation, processor 1310 is a single-threaded processor. In another implementation, processor 1310 is a multi-threaded processor. The processor 1310 can process instructions stored in the memory 1320 or the storage device 1330 to display graphical information on a user interface on the input / output device 1340.

[0212] The memory 1320 stores information within computer 1300. In one implementation, memory 1320 is a computer-readable medium. In one implementation, memory 1320 is a volatile memory unit. In another implementation, memory 1320 is a non-volatile memory unit.

[0213] The storage device 1330 can provide a large-capacity storage area for computer 1300. In one implementation, storage device 1330 is a computer-readable medium. In various different implementations, storage device 1330 may be a floppy (registered trademark) disk device, a hard disk device, an optical disk device, or a tape device.

[0214] The input / output device 1340 provides input / output operations to computer 1300. In one implementation, input / output device 1340 includes a keyboard and / or a pointing device. In another implementation, input / output device 1340 includes a display unit for displaying a graphical user interface.

[0215] This specification details many specific implementations, but these should not be construed as limiting the claimed scope, but rather as descriptions of features that may be specific to particular embodiments.

[0216] The specific features described herein in the context of separate embodiments may also be implemented in combination in a single embodiment. Conversely, the various features described in the context of a single embodiment may be implemented separately in multiple embodiments, or in any suitable sub-combination. Furthermore, although features may be described above as acting in a particular combination, even if initially claimed as such, one or more features from the claimed combination may in some cases be excluded from the combination, and the claimed combination may be directed to a sub-combination or a variant of a sub-combination.

[0217] In the foregoing description, specific details, such as specific forms of processing systems, descriptions of various components and processes used therein, have been set forth. However, it should be understood that the techniques of this specification may be practiced in other embodiments that depart from these specific details, and that such details are for illustrative purposes and not limiting. The embodiments disclosed herein have been described with reference to the accompanying drawings. Similarly, for purposes of explanation, specific numbers, materials, and configurations have been described to provide a complete understanding. Nevertheless, the embodiments may be practiced without such specific details. Components having substantially the same functional configuration are denoted by like reference numerals, and thus any repeated description may be omitted.

[0218] Various techniques are described as a plurality of separate operations to assist in understanding the various embodiments. The order of the description should not be construed to mean that these operations necessarily follow an order. In fact, these operations need not be performed in the order described. The described operations may be performed in an order different from that of the above embodiments. Various additional operations may be performed, and / or the described operations may be omitted in additional embodiments.

[0219] Regarding the above embodiments, the following appendices are disclosed as an aspect and optional features of the invention. (Appendix 1) A radiation detector including a plurality of channels, An anti-scatter grid (ASG) disposed on the incident side of the radiation detector and including a plurality of partition walls corresponding to the plurality of channels, Performing an air scan using the ASG to obtain count data, Based on the count data, determining an ASG offset value for the partition wall, A processing unit that determines a parameter indicating the deviation between the ASG and the radiation detector based on the ASG offset value An X-ray CT apparatus comprising the same. (Appendix 2) The processing unit may determine, as the parameter, an offset distance of the ASG corresponding to a channel at one end of the plurality of channels. (Appendix 3) The processing unit may determine the offset distance on the assumption that a channel at the other end different from the one end of the plurality of channels becomes the rotation point of the ASG. (Appendix 4) The processing unit may further determine, as the parameter, a lateral offset distance of the ASG corresponding to a channel at the other end different from the one end of the plurality of channels. (Appendix 5) The processing unit may further determine the curvature of the ASG as the parameter. (Appendix 6) The processing unit may further adjust or correct the arrangement of the ASG based on the parameter. (Appendix 7) The processing unit may further adjust or correct the arrangement of the ASG based on the offset distance and the lateral offset distance. (Appendix 8) The processing unit may determine the compression offset of the ASG as the parameter based on the offset value. (Appendix 9) The processing unit may further adjust or correct the arrangement of the ASG based on the offset distance, the lateral offset distance, and the compression offset. (Appendix 10) The processing unit may use a look-up table associating the offset value with the rotational offset distance based on the first offset value, which is the offset value corresponding to the channel at one end, to determine the rotational offset distance of the ASG corresponding to the channel at one end. (Appendix 11) The processing unit simulates air count data for different values of the rotational offset distance, generates a simulated ASG offset curve across the plurality of channels based on the air count data, and may generate the look-up table by correlating various rotational offset distances with the offset value corresponding to the channel at one end based on the ASG offset curve. (Appendix 12) The processing unit may determine the rotational offset distance corresponding to the channel at one end by applying the offset value to a machine learning model. (Appendix 13) The machine learning model may include a neural network trained using a reference rotation offset distance and corresponding reference offset values. (Appendix 14) Before determining the rotation offset distance, the processing circuit may apply a smoothing process to the ASG offset values to generate a smoothed ASG offset curve. (Appendix 15) Performing an air scan using an ASG including a plurality of partition walls corresponding to the plurality of channels, the ASG being disposed on the incident side of a radiation detector including the plurality of channels, to obtain count data, Determining an offset value for the partition wall based on the count data, Determining a parameter indicating a deviation between the ASG and the radiation detector based on the ASG offset value A method comprising the above. (Appendix 16) Performing an air scan using an ASG including a plurality of partition walls corresponding to the plurality of channels, the ASG being disposed on the incident side of a radiation detector including the plurality of channels, to obtain count data, Determining an offset value for the partition wall based on the count data, Determining a parameter indicating a deviation between the ASG and the radiation detector based on the ASG offset value A program for causing a computer to execute each process.

[0220] According to at least one embodiment described above, the accuracy of the arrangement of the scatter removal grid with respect to the radiation detector can be improved.

[0221] Although some embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope and gist of the invention, as well as in the invention described in the claims and the scope of equivalents thereof.

Description of Reference Numerals

[0222] 500: Radiation imaging gantry 514: Reconstruction device

Claims

1. a radiation detector including a plurality of channels; an anti-scatter collimator or grid (ASG) disposed on an incident side of the radiation detector and including a plurality of partitions corresponding to the plurality of channels; Performing an air scan using the ASG to obtain count data; determining an offset value for the partition based on the count data; a processor for determining a parameter indicating a misalignment between the ASG and the radiation detector based on the offset value; An X-ray CT apparatus comprising:

2. The X-ray CT apparatus according to claim 1 , wherein the processing unit determines, as the parameter, an offset distance of the ASG corresponding to an end channel of the plurality of channels.

3. 3. The X-ray CT apparatus according to claim 2, wherein the processor determines the offset distance by assuming that a channel at an end other than the one end among the plurality of channels becomes a rotation point of the ASG.

4. 3. The X-ray CT apparatus according to claim 2, wherein the processing unit further determines, as the parameter, a lateral offset distance of the ASG corresponding to a channel at the other end different from the one end among the plurality of channels.

5. The X-ray CT apparatus according to claim 4 , wherein the processing unit further determines a curvature of the ASG as the parameter.

6. The X-ray CT apparatus according to claim 1 , wherein the processing unit further adjusts or corrects a position of the ASG based on the parameters.

7. The X-ray CT apparatus according to claim 4 , wherein the processing unit further adjusts or corrects a position of the ASG based on the offset distance and the lateral offset distance.

8. The X-ray CT apparatus according to claim 4 , wherein the processing unit determines a compression offset of the ASG as the parameter based on the offset value.

9. The X-ray CT apparatus according to claim 8 , wherein the processing unit further adjusts or corrects a position of the ASG based on the offset distance, the lateral offset distance, and the compression offset.

10. 3. The X-ray CT apparatus of claim 2, wherein the processing unit determines the rotational offset distance of the ASG corresponding to the channel at the one end by using a lookup table that associates offset values ​​with rotational offset distances based on a first offset value, which is the offset value corresponding to the channel at the one end.

11. The processing unit includes: Simulate air count data for different values ​​of rotation offset distance, generating a simulated ASG offset curve across the plurality of channels based on the air count data; 11. The X-ray CT apparatus according to claim 10, wherein the look-up table is generated by correlating various rotational offset distances with offset values ​​corresponding to the one-end channel based on the ASG offset curve.

12. The X-ray CT apparatus according to claim 10 , wherein the processing unit determines the rotational offset distance corresponding to the channel at the one end by applying the offset value to a machine learning model.

13. The X-ray CT apparatus according to claim 12 , wherein the machine learning model includes a neural network that is trained using the reference rotational offset distances and the corresponding reference offset values.

14. The X-ray CT apparatus according to claim 11 , wherein the processor applies a smoothing process to the offset values ​​to generate a smoothed ASG offset curve before determining the rotational offset distance.

15. performing an air scan using an ASG that is disposed on an incident side of a radiation detector including a plurality of channels and includes a plurality of partitions corresponding to the plurality of channels, and acquiring count data; determining an offset value for the partition based on the count data; determining a parameter indicative of a misalignment between the ASG and the radiation detector based on the offset value; The method includes:

16. performing an air scan using an ASG that is disposed on an incident side of a radiation detector including a plurality of channels and includes a plurality of partitions corresponding to the plurality of channels, and acquiring count data; determining an offset value for the partition based on the count data; determining a parameter indicative of a misalignment between the ASG and the radiation detector based on the offset value; A program that causes a computer to execute each process.

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