WO2018003918A1 - Radiographic imaging device, radiographic imaging method, and radiographic imaging program - Google Patents

Abstract

The present invention improves image quality by reducing artifacts in a reconstructed image obtained as a result of estimating nonuniformity of an incident distribution in a detector so as to accurately estimate an amount of incident radiation. Provided is a radiographic imaging device that is provided with: an X-ray source that emits X-rays; a detection unit in which pixels, each comprising a plurality of sub-pixels for detecting X-rays, are arranged in a two-dimensional array; a signal processing unit which generates an output signal in accordance with the intensity of the X-rays on the basis of detection signals supplied from the sub-pixels; a signal addition unit which generates an X-ray count signal for each of the pixels by adding output signals of the sub-pixels belonging to the pixel; and an image generation unit which generates an image on the basis of the X-ray count signal, wherein the image generation unit is provided with a nonuniformity estimation unit which estimates nonuniformity of an incident X-ray distribution in a pixel subject to processing on the basis of the X-ray count signal of said pixel subject to processing and the X-ray count signal of a pixel located near the pixel subject to processing.

Description

Radiation imaging apparatus, radiation imaging method, and radiation imaging program

The present invention relates to a radiation imaging apparatus, and more particularly to a radiation imaging apparatus, a radiation imaging method, and a radiation imaging program for acquiring a projection image or a tomographic image of a subject with a photon counting type X-ray detector.

Conventionally, in a medical radiation imaging apparatus using X-rays such as a computed tomography apparatus (CT), X-rays irradiated from an X-ray source and transmitted through a subject are detected by a detector, and X caused by the subject is detected. By acquiring information on line attenuation, the state in the subject is imaged and used for diagnosis.
In recent years, in such a radiation imaging apparatus, there has been an active movement toward realizing a higher-accuracy apparatus by decomposing each of the radiation transmitted through the subject and detecting X-ray photons (pulse mode). It has become. In the field of CT, it is called photon counting CT (PCCT) and is expected as a next-generation apparatus.

As an example of a detector applied to PCCT, Non-Patent Document 1 discloses a so-called photon counting type detector that divides a pixel into a plurality of subpixels and counts and processes photons for each subpixel. In the following description, a pixel composed of a plurality of subpixels is referred to as a macro pixel in order to clearly distinguish the pixel and the subpixel.
As in the detector disclosed in Non-Patent Document 1, when X-ray photons are counted for each subpixel, the amount of data obtained is increased by the number of divided subpixels. For this reason, the amount of data output from the detector is reduced by adding the count value (count rate) of the sub-pixels in each macro pixel and obtaining the output value for each macro pixel.

By the way, in each subpixel divided into a plurality of times, the time (dead time) for processing one photon of radiation is finite. Therefore, when the incident rate of radiation is high, a plurality of photons are timed during the dead time. So-called pile-up, which is input in an overlapping manner, occurs. When pile-up occurs, X-ray photons cannot be counted correctly, and it becomes difficult to accurately acquire energy information of X-ray photons, resulting in artifacts in the reconstructed image. Therefore, in order to accurately acquire X-ray photon information, it is necessary to correct the influence due to pileup and estimate the amount of X-ray photons (radiation) incident on the subpixel.

However, there are the following problems in estimating the amount of X-ray photons (radiation) incident on the subpixels. That is, when the distribution of the radiation incident on the macro pixel is not uniform, variation occurs between the dead times of a plurality of subpixels constituting the macro pixel. However, since the detector obtains an output value for each macro pixel, information regarding the variation between the dead times of the sub-pixels is lost by the addition process. For this reason, if the incidence rate of the X-ray photons in each subpixel is estimated without considering the variation between the dead times of the subpixels, the estimation accuracy of the incidence rate of the X-ray photons in each subpixel deteriorates. The estimation accuracy of the true incident rate of the X-ray photon with respect to the macro pixel is deteriorated. Due to the deterioration of the estimation accuracy, there arises a problem that image quality deterioration such as artifacts occurs in the reconstructed image.

The present invention has been made in view of the above circumstances, and the X-ray incident distribution on each subpixel is non-uniform, and even if the dead time of each subpixel varies, the incident distribution is not non-uniform. The purpose is to contribute to the improvement of image quality by estimating the uniformity.

In order to solve the above problems, the present invention provides the following means.
According to one aspect of the present invention, an X-ray source that irradiates X-rays, a detection unit that includes a plurality of sub-pixels that detect the X-rays, a detection unit that two-dimensionally arranges the X-rays, and the X signal based on a detection signal from the sub-pixels. A signal processing unit that generates an output signal corresponding to the intensity of the line, a signal addition unit that generates an X-ray count signal for each pixel by adding the output signals of the sub-pixels belonging to the pixel, and the X-ray An image generation unit that generates an image based on the count signal, the image generation unit including the X-ray count signal of the pixel to be processed and the X-ray count of a pixel located in the vicinity of the pixel to be processed Provided is a radiation imaging apparatus including a non-uniformity estimation unit that estimates non-uniformity of an X-ray incident distribution of the processing target pixel based on a signal.

According to the present invention, even if the X-ray incident distribution for each subpixel is non-uniform and the dead time of each sub-pixel varies, the non-uniformity of the incident distribution is estimated. This can contribute to the improvement of image quality.

1 is a block diagram showing an outline of an X-ray CT apparatus according to a first embodiment of the present invention. The schematic structure of the computer of the X-ray CT apparatus which concerns on the 1st Embodiment of this invention is shown, (A) is a block diagram, (B) is a functional block diagram of CPU in a computer. It is a perspective view showing the outline of the X-ray detector concerning a 1st embodiment of the present invention. It is explanatory drawing which shows the example of the relationship between the arrangement | sequence of the detection element of the X-ray detector which concerns on the 1st Embodiment of this invention, and a pixel. It is explanatory drawing which shows the example of the relationship between the arrangement | sequence of the detection element of the X-ray detector which concerns on the 1st Embodiment of this invention, and a pixel. It is a block diagram which shows schematic structure of the signal processing part of the X-ray detector which concerns on the 1st Embodiment of this invention. FIG. 7 is an enlarged explanatory diagram in which a part of the signal processing circuit of FIG. 6 is extracted. It is the schematic diagram which showed the count rate characteristic in a Mahi type and a non-mahi type signal processing circuit. It is a reference figure which shows the example in case the incident distribution with respect to an X-ray detector is not uniform. It is a table | surface which shows various data, such as a count rate and an incident rate, when the incident distribution with respect to an X-ray detector is not uniform. It is a graph which shows the count rate characteristic explaining that incidence rate estimation will be underestimated when the incident distribution with respect to an X-ray detector is not uniform. It is a flowchart which shows the flow of the imaging process in the X-ray CT apparatus which concerns on the 1st Embodiment of this invention. 3 is a flowchart showing a flow of non-uniformity estimation to incidence rate estimation value calculation in the X-ray CT apparatus according to the first embodiment of the present invention. 3 is a flowchart showing a flow of non-uniformity estimation to incidence rate estimation value calculation in the X-ray CT apparatus according to the first embodiment of the present invention. It is a reference figure which shows the example in case the incident distribution with respect to an X-ray detector is not uniform. It is explanatory drawing which shows the example of the arrangement | sequence of the sub pixel and pixel relationship of the X-ray detector which concerns on the 1st Embodiment of this invention. 6 is a flowchart showing a flow of non-uniformity estimation to incidence rate estimation value calculation in an X-ray CT apparatus according to a second embodiment of the present invention. 10 is a flowchart showing a flow of non-uniformity estimation to incidence rate estimation value calculation in an X-ray CT apparatus according to a third embodiment of the present invention. 10 is a flowchart showing a flow of non-uniformity estimation to incidence rate estimation value calculation in an X-ray CT apparatus according to a fourth embodiment of the present invention.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings.
A radiation imaging apparatus according to the present invention is based on an X-ray source that irradiates X-rays, a detection unit that two-dimensionally arranges pixels including a plurality of subpixels that detect the X-rays, and a detection signal from the subpixels A signal processing unit that generates an output signal according to the intensity of the X-ray, a signal addition unit that generates an X-ray count signal for each pixel by adding the output signals of the sub-pixels belonging to the pixel, and An image generation unit configured to generate an image based on the X-ray count signal, and the image generation unit includes the X-ray count signal of the processing target pixel and the X of the pixel located in the vicinity of the processing target pixel. The radiation imaging apparatus includes a non-uniformity estimation unit that estimates non-uniformity of an X-ray incident distribution of the processing target pixel based on a line count signal.
According to such a radiation imaging apparatus, the X-ray incident distribution on each sub-pixel is non-uniform, and even if the dead time of each sub-pixel varies, the non-uniformity of the incident distribution can be reduced. Since it can be estimated, the image quality can be improved by using the estimated non-uniformity.

Hereinafter, embodiments of the present invention will be described more specifically.
<First Embodiment>
Hereinafter, an X-ray CT apparatus will be described with reference to the drawings as an example of a radiation imaging apparatus according to an embodiment of the present invention.

As shown in FIG. 1, the X-ray CT apparatus includes an X-ray source 120, an X-ray detector 1150, and the X-ray source 120 and the X-ray detector 150 as an imaging system. The gantry rotating unit 110 that rotates around the center, the bed 140 disposed in the opening of the gantry rotating unit 110, the operation of these imaging systems, and the X-ray detector 150 acquired along with the operation of the imaging system A control unit 170 that processes the signal and a computer 180 that generates a reconstructed image based on the data obtained by the X-ray detector 150 are provided.

For example, an X-ray tube can be applied to the X-ray source 120. The X-ray source 120 emits X-ray photons by causing an electron beam accelerated by a tube voltage to collide with a target metal such as tungsten or molybdenum and generating X-rays from the collision position (focal point). A filter 125 is provided in the vicinity of the X-ray source 120. The filter 125 adjusts the flux and energy distribution of the X-ray photons 130 emitted from the X-ray source 120. Therefore, after the X-ray photons emitted from the X-ray source 120 are subjected to the adjustment of the flux and energy distribution by the filter 125, a part of the X-ray photons is absorbed by the subject 200 according to the substance distribution in the subject. The part passes through the subject 200 and is detected by an X-ray detector 150 described later.

The gantry rotating unit 110 arranges the X-ray source 120 and the detector 150 facing each other and rotates around a predetermined rotation axis. An opening into which the subject 200 is inserted is provided at the center of the gantry rotating unit 110, and a bed 140 on which the subject 200 is laid is disposed in the opening. The bed 140 and the gantry rotating unit 110 are relatively movable in a predetermined direction. In general, in CT, in order to acquire data from all directions, the data is acquired while rotating the X-ray source 120 and the detector 150 around the subject 200 by rotating the gantry rotating unit 110 at a predetermined speed. The speed of rotation is typically about 1 to 4 revolutions per second. Also, the time for accumulating data for acquiring projection data (one view) from a certain direction is typically on the order of 0.1 to 1 millisecond.

The X-ray detector 150 detects X-ray photons incident on the X-ray detector 150, and collects and processes, for example, a detection unit 151 that classifies into four energy ranges and a detection signal output from the detection unit 151. And a signal processing unit 152. The X-ray photon detection signals output from the detection unit 151 are processed in a pulse mode by the plurality of signal processing units 152 and counted. The counting here includes obtaining energy information in addition to counting the detected X-ray photons. In addition, if the X-rays scattered by the subject 200 are detected, an undesired signal is generated. Therefore, a collimator 145 is disposed in front of the detection unit 151 when viewed from the X-ray source 120 side, and the scattered X-rays are detected. It is preferable to block. Details of the X-ray detector 150 will be described later.

The control unit 170 controls the gantry rotating unit 110, the X-ray source 120, the bed 140, the X-ray detector 150, etc., and performs predetermined processing on the signals detected and collected by the X-ray detector 150 to perform the computer 180. Forward to.

The computer 180 includes a CPU 181 and a storage unit 182 as shown in FIG. In addition, as illustrated in FIG. 2B, the CPU 181 realizes the function of an image generation unit 183 including a non-uniformity estimation unit 184 and a signal correction unit 185. The computer 180 stores the signal acquired from the signal processing unit 152 of the X-ray detector 150 via the control unit 170 in the storage unit 182 and generates a reconstructed image of the tomographic image of the subject based on these signals and the like. To do.

Further, the computer 180 is connected to the display device 191 and the input device 192, and the reconstructed image generated by the CPU 181 functioning as the image generation unit 183 is displayed on the display device 191 in accordance with an instruction from the CPU 181. The input device 192 also includes imaging conditions in the X-ray CT apparatus, that is, parameters necessary for data collection, such as a voltage value or tube current applied to the X-ray source 120 from a high-voltage power supply (not shown), An input such as the speed of the rotational operation of the X-ray source 120 is received. The display device 191 can display the parameters input by the input device 192 and their values.

In addition, the computer 180 estimates the incidence rate of X-ray photons incident on each sub-pixel 21 as necessary in order to correct the effect of pileup, and the non-uniformity estimation unit 184 detects the detection unit 151. The non-uniformity of the incident distribution of the X-rays incident on is estimated. Here, in the present embodiment, the incidence rate means the number of X-ray photons incident per unit time per detection unit (pixel or sub-pixel). Details of the X-photon incidence rate estimation in the computer 180 will be described later.

Note that the control unit 170 and the computer 180 can be partially or wholly constructed as a system including a CPU (Central Processing Unit), a memory, and a main storage unit, and the functions of the units constituting the control unit 170 and the computer 180 are included. Can be realized by the CPU loading the program stored in the storage unit in advance into the memory and executing it. Also, some or all of the functions can be configured by hardware such as ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array).

Next, the X-ray detector 150 will be described.
The X-ray detector 150 has a detection unit 151 that two-dimensionally arranges a plurality of pixels 20 and detects and outputs an X-ray photon for each pixel, and collects and processes output signals from each pixel 20 of the detection unit 151. And a signal processing unit 152.

As shown in FIG. 3, the detection unit 151 is a unit of the X-ray detector 150 and includes a plurality of pixels 20 that detect incident X-ray photons. An X-ray photon 130 that has passed through the subject 200 enters each pixel 20 and is counted. The number of pixels included in the detection unit 151 can be, for example, 892 in the longitudinal direction and 64 in the lateral direction.
As shown in FIG. 3, the detection unit 151 is arranged in an arc shape with the X-ray source 120 as the center, and rotates while maintaining the positional relationship with the X-ray source 120 as the gantry rotation unit 110 rotates. To do. Therefore, in the example shown in FIG. 3, the pixels 20 are depicted as being approximately arranged in a curved surface shape. However, in general, the surface of the pixels is often a flat surface having no curvature, and the detection unit 151 The arrangement of the pixels 20 may be a polygonal shape.
Note that a collimator 145 (see FIG. 1) is disposed on the X-ray source 120 side of the pixel 20 in order to remove X-ray photons scattered by the subject 200. The collimator 145 may be a two-dimensional rectangular collimator whose pitch and shape coincide with those of the pixels 20 or a one-dimensional slit collimator.

In the detection unit 151, the pixel 20 is a detection element group in which a plurality of detection elements as the sub-pixel 21 are arranged, and this detection element group constitutes the pixel 20 that is one unit of the X-ray detector 150. That is, it can be said that one pixel 20 is divided into a plurality of subpixels 21. The sub-pixel 21 included in each pixel 20 is a so-called photon counting type detection element, detects incident X-ray photons, and performs counting by dividing into, for example, four energy ranges.

Therefore, in the detector 151, the sub-pixel 21 detects X-ray photons independently and generates an output signal for each pixel 20 by adding the output signals from the plurality of detection elements 21 constituting the pixel 20. Yes.
FIG. 4 shows an example in which a plurality of detection elements 21 having the same size are arranged as a pixel 20 in a total of four elements, two elements in the channel direction and two elements in the slice direction. In the example of FIG. 4, the pixel 20 is 1 mm square, for example, and each subpixel is 0.5 mm square. Hereinafter, in the present embodiment, description will be made assuming that the pixel 20 includes four subpixels 21.

The pixel 20 can be composed of, for example, a total of nine detection elements of the same size, 3 elements in the channel direction and 3 elements in the slice direction, and 16 elements in total in the channel direction and 4 elements in the slice direction. It can also consist of pieces. Thus, n elements in the channel direction and m elements in the slice direction and the number of sub-pixels constituting the pixel can be determined as appropriate (n and m are natural numbers). In addition, the sizes of the sub-pixels constituting the pixels are not necessarily the same size, and a configuration in which sub-pixels having different sizes are mixed can be used.

For example, as shown in FIG. 5, each detection element 21 constituting each pixel 20 is provided with positive and negative electrodes 41 and 42 so as to sandwich the detection layer 40, and a signal processing unit 152 is connected to each electrode 41 and 42. Has a structured.
In the present embodiment, a negative electrode 41 (hereinafter referred to as “common electrode 41”) provided on the incident surface of the X-ray photon 130 (the upper surface of the detection layer 40 in FIG. 4) is a common electrode that covers the entire pixel 20. It has become. A positive electrode 42 (hereinafter referred to as “individual electrode 42”) is provided for each detection element 21 as a subpixel, and an individual channel 165 of the signal processing unit 152 is connected to each individual electrode 42. That is, a signal is read out for each subpixel, and X-ray photon counting including acquisition of energy information is performed.

As described above, the pixel 20 includes one common electrode 41 and the number of individual electrodes 42 corresponding to the sub-pixel 21 (detection element). In other words, the pixel 20 includes a plurality of individual electrodes 42 in the surface of the detection layer 40, and a region corresponding to one individual electrode 42 forms one subpixel 21. As in the example shown in FIG. 4, when a direct radiation detection material is used as the detection layer 40, when viewed from the upper surface of the pixel 20, the boundary of the subpixel 21 (see FIG. 3) is physically May not be visible.

The detection layer 40 is easy to be finely processed and can directly read out an electric signal, for example, a direct type such as cadmium telluride, zinc cadmium telluride, thallium bromide, mercury iodide, bismuth iodide. It is preferable to apply a compound semiconductor that is a radiation detection material. In addition, the detection layer 40 can be a scintillator (indirect radiation detection material) optically coupled with an optical device. In addition, the thickness of the detection layer 40 is preferably about 0.5 mm to 3 mm.

The X-ray photon 130 enters the detection layer 40 from the common electrode 41 side, detects the X-ray photon, and generates an amount of charge corresponding to the energy. For example, a voltage of −600 V is applied to the common electrode 41 by a high voltage power source (not shown). It is desirable that the X-ray photons are not attenuated at the common electrode 41 and the individual electrodes 42. The common electrode 41 and the individual electrode 42 are sufficiently thinner than the detection layer 40 and can be processed to a thickness of 1 μm or less.

As shown in FIGS. 6 and 7, the signal processing unit 152 includes a channel 165 for each subpixel 21, detects an output signal from the subpixel 21 belonging to the pixel 20 through the channel 165, and the signal adding unit 166 Addition is performed in accordance with a predetermined condition, and collected and processed as an output signal of each pixel 20.

6 and 7 show an example of each channel 165 of the signal processing unit 152 connected to each sub-pixel 21. FIG. Each channel 165 has a charge-sensitive preamplifier 310a that converts an X-ray photon detected as a charge signal into a voltage signal (described using 310a in FIG. 7 as a representative of 310; the same applies hereinafter), A waveform shaping amplifier 320a for shaping the voltage signal converted by the type preamplifier 310a, four comparators 330a1 to 330a4 for obtaining energy information by comparing a voltage related to the voltage signal and a reference voltage, and a counter 340a1 to 340a4.

The signal processing in the channel 165 configured in this way is performed as follows. A signal read from an arbitrary sub-pixel a in the pixel 20 is first converted from a charge signal to a voltage signal by the charge-sensitive preamplifier 310a and output to the waveform shaping amplifier 320a. The voltage signal converted in the charge-sensitive preamplifier 310a is shaped in the waveform shaping amplifier 320a (hereinafter, the shaped voltage signal is referred to as “detection signal”) and output to the four comparators 330a1 to 330a4. The

The different reference voltages th1 to th4 are supplied to the comparators 330a1 to 330a4, and the detection signals are compared with the reference voltages th1 to th4 in the comparators 330a1 to 330a4. As a result of comparison in each of the comparators 330a1 to 330a4, when the detection signal is larger than the reference voltage, the counters 340a1 to 340a4 corresponding to the comparators count up. Thereby, X-ray photons can be classified into four types according to the energy and counted.

Note that the counters 340a1, 340a2, and 340a3 may be configured to count up when the detection signal is larger than th1, th2, th3, and smaller than th2, th3, th4.

Each channel 165 stops counting up when a predetermined measurement time (one view) ends, and counts of counters (for example, 340a1, 340b1, 340c1, 340d1) having the same threshold value in the four sub-pixels 21 in the pixel 20. The numerical value (counting rate) is added by the signal adding unit 166, and the output signal of the pixel 20 is generated. After the same operation is performed on all four counters having different threshold values, four count values corresponding to different threshold values, that is, corresponding to energy regions, are generated as output signals for one pixel 20. Are output to the control device 170.

Note that the amount of data can be reduced by adding the signals detected by the sub-pixels 21 as the signals of the pixel 20 and outputting the signals separately from the sub-pixels 21 and outputting the signals separately. Can do. In addition, although the signal addition part 166 described simple addition in the above-mentioned example, it is not restricted to this, Weighted addition etc. can also be performed and it determines suitably according to the structure of a signal processing part, etc. Can do.

Here, prior to the description of the necessity of estimating the incidence rate with respect to the sub-pixel 21, the dead time in the PCCT signal processing circuit (the signal processing unit 152 in the present embodiment) will be described.
In PCCT, it is necessary to consider how the dead time of a signal processing circuit affects the count value obtained by measurement. From the viewpoint of dead time, the signal processing circuit can ideally be roughly classified into two types, which are sometimes referred to as “mahi type” and “non-mahi type”, respectively. FIG. 8 shows the count rate characteristics (relationship between incidence rate and count rate) of the Mahi type and the non-Mahi type. Here, the incidence rate is the number of X-ray photons incident per unit time per detection unit (pixel or subpixel) as described above, and the count rate is one detection unit (pixel or subpixel). ) Is the number of X-ray photons detected (counted) per unit time.

In the following description, for convenience of explanation, it is assumed that the quantum efficiency is 1 (no photon is transmitted without being detected), and the detected photon is applied to the sub-pixel in which the total energy is detected.
In this case, the count rate expected in an ideal case where the dead time is 0 is equal to the incidence rate. It is known that the count rate characteristic 410 in the case of the Mahi signal processing circuit is expressed by the following equation (1), where x is the incidence rate and y is the count rate when there is a finite dead time (FIG. 8). reference).

Here, τ is the dead time of the signal processing circuit, and is, for example, 20 nanoseconds. On the other hand, the count rate characteristic 420 in the case of the non-mahi type can be expressed by the following equation (2) (see FIG. 8).

As shown in FIG. 8, in the Mahi signal processing circuit, the count rate becomes the maximum value at an incidence rate of 50 Mcps per channel (5 × 10 ⁷ counts per second), and the count rate is increased even if the incidence rate is further increased. Shows a property of decreasing (the incidence rate at which the count rate takes the maximum value is determined depending on the dead time).

However, in such a high count rate region where the count rate decreases even when the incidence rate increases, the so-called pile-up in which the time intervals between the radiation signals become too short and overlap each other becomes extremely significant, and energy information It is difficult to obtain the data with high accuracy. In the region of 50 Mcps or less per channel, both the Mahi-type count rate characteristic 410 and the non-Mahi-type count rate characteristic 420 are similar in that they are upwardly convex monotonically increasing functions.

Even in the count rate region where the pile-up is not so noticeable and energy information can be acquired with high accuracy, the effect that the count rate is reduced by the dead time cannot be ignored. Accordingly, in order to acquire accurate X-ray photon information, it is necessary to correct the influence of pile-up (dead time) and estimate the X-ray photon (radiation amount) incident on the subpixel. .

Next, the response of the detector when the X-ray incident distribution is not uniform will be described.
For convenience of explanation, it is assumed that the incident distribution is biased only in the width direction of the pixel 20, that is, in the left-right direction in FIG. In addition, the pixel 20 will be described as being divided into two sub-pixels 21L and 21R having the same size. Two sub-pixels 21 are arranged in the left-right direction in FIG. In addition, what is necessary is just to convert suitably into the incident rate per unit area, when the subpixel contained in a pixel is a mutually different magnitude | size.

In the configuration shown in FIG. 7, X-ray photon count values of four types of energy corresponding to the reference voltages th1 to th4 supplied to the comparators 330a1 to 330a4 are obtained. On the other hand, in estimating non-uniformity, it is necessary to use the total number of events that caused the dead time. Therefore, in the following description, the count rate or the incidence rate refers to the total number of events (sometimes referred to as the total count rate or the total incidence rate) for which the detection signal is greater than the reference voltage th1.

FIG. 9 shows an example in which pixels 20b and 20c are arranged adjacent to the pixel 20a so as to sandwich the pixel 20a as a part of the detection unit 151. In FIG. 9, X-rays are uniformly incident on the pixels 20b and 20c arranged on both sides of the pixel 20a. On the other hand, the incidence rate of X-rays at the pixel 20a is lower as it is closer to the pixel 20b and higher as it is closer to the pixel 20c. That is, X-rays are not uniformly incident on the pixels 20a. It is considered that such a change in incidence rate is mainly caused by a change in the density and thickness of a substance existing between the X-ray source 120 and the pixels 20a, 20b, and 20c.
When the density and thickness change is considered to be a linear function spatially, the incidence rate is expected to change exponentially.

10 shows various values necessary for estimating the X-ray incidence rate x with respect to the sub-pixel 21 as Table 1. Hereinafter, according to Table 1 of FIG. 10, the response of the detector when the X-ray incidence distribution is not uniform and the estimation of the incidence rate x will be examined.

For example, the simulation is performed by setting the incidence rate x for each sub-pixel included in the pixels 20a, 20b, and 20c as follows. That is, the incidence rates x _bL and x _bR in the sub-pixels 21bL and 21bR included in the pixel 20b are 2.5 Mcps, and both have the same incidence rate and are set to have a uniform distribution. Meanwhile, the incidence rate _{x aL} to subpixels 21aL included in the pixel 20a 5Mcps, incidence rate _{x aR} to subpixel 21aR is 10 Mcps, set to be exponentially-varying distance from the subpixel 20bR . Further, the incidence rates x _cL and x _cR of the sub-pixels 21cL and 21cR included in the pixel 20c are both 20 Mcps, and the incidence rates on both are set to have a uniform distribution (third stage in Table 1). . Accordingly, the incident rates x _b , x _a , and x _c to the pixels 20b, 20a, and 20c in such a setting are 5, 15, and 40 Mcps, respectively (the fourth stage in Table 1).

However, when X-rays are detected by the detector 150 and processed with a finite dead time, the actually measured count rate y is lower than the incidence rate x due to pileup. Therefore, the count rate per sub-pixel is, for example, as shown in the fifth row of Table 1, the count rates y _bL and y _bR of the sub-pixels 21bL and 21bR are both 2.4 Mcps, and the count rate y _aL of the sub-pixel 21aL is 4.5Mcps, count rate _{y aR} subpixel 21aR is 8.3Mcps, subpixel 21cL, 21cR count rate _{y cL,} the _{y cR} are both 13.8Mcps.
However, as described above, the values of the count rates y _L and y _R for each of the sub-pixels are not output, and are added as the count rate y (= y _L + y _R ) for each pixel by the signal integration unit 166. The count rates y _b (= y _bL + y _bR ), y _a (= y _aL + y _aR ), and y _c (= y _cL + y _cR ) obtained from 20b, 20a, and 20c are 4.8, 12.8, and 27, respectively. .7 Mcps (6th row in Table 1).

At this time, the count rate y decreased by pileup by grasping in advance the count rate characteristic y = f (x) of the signal processing circuit as shown in FIG. Based on the count rate characteristic y = f (x), the incidence rate x of each pixel from which the effect of pileup has been removed can be calculated.
The incidence rate prediction value x (7 in Table 1) obtained by using the count rate characteristic y = f (x) from the pixel count value y (6th stage in Table 1), which eliminates the effect of pileup by this calculation. In the pixels 20b and 20c where the incident distribution is uniform within the pixels, the first stage corresponds to the incident rate x (fourth stage in Table 1) initially set in the simulation, but 1.6% in the pixels 20a. It can be seen that this is underestimated (8th row in Table 1). In view of the fact that CT is a device that provides medical diagnostic images, this underestimation is a non-negligible deviation that can lead to image quality degradation such as artifacts.

The phenomenon of underestimation can be qualitatively understood from the graph (count rate characteristic y = f (x)) showing the relationship between the incidence rate x and the count rate y shown in FIG. The function shown in the graph of FIG. 11 is a function of a monotonically increasing curve that is convex upward, and shows an example of the count rate characteristic y = f (x) of the detector 150. When the incident distribution to the sub-pixels is not uniform, for example, when the incident rates x are different such as x = a and x = b, the obtained count rates y are y = f (a) and y = f (b), respectively. Become.

In this case, the count rate per sub-pixel averaged in the pixel composed of two sub-pixels is calculated as (f (a) + f (b)) / 2, from which the count rate characteristic y = f (x) The incidence rate x = c calculated with reference to is always a value smaller than the true average incidence rate (a + b) / 2 when f (x) is an upwardly convex curve. That is, when the incident distribution of X-ray photons is a non-uniform pixel, the predicted incidence rate x obtained by estimation from the count rate y and the count rate characteristic y = f (x) is always underestimated. End up. The degree of underestimation is determined by the intensity of non-uniformity of the incident distribution of X-ray photons and the incidence rate x. The larger the bias in the distribution of the incidence rate x of X-ray photons, the underestimation occurs. The larger the curvature of the count rate characteristic y = f (x), the lower the evaluation.

For this reason, the incident rate predicted value x calculated from the count rate y and the count rate characteristic y = f (x) is not used as it is, but the X-rays incident on the detector 150 are not uniform. Considering the case, it is necessary to correct the incident rate predicted value x obtained from the count rate characteristic y = f (x) and accurately estimate the incident X-ray dose.
Therefore, when the X-rays incident on such sub-pixels are not uniform, the computer 180 reduces the deviation of the predicted incidence rate x due to non-uniformity indicating the non-uniformity. The nonuniformity of the incident distribution to the pixel is estimated using the count value y of the neighboring pixel, and the predicted incidence rate of the pixel is corrected.

For this reason, the image generation unit 183 of the computer 180 receives the non-uniformity estimation unit 184 for estimating the non-uniformity and the incidence of X-rays incident on the pixels based on the estimation result by the non-uniformity estimation unit. and a signal correction unit 185 for calculating the rate estimated value x _E.

The non-uniformity estimation unit 184 performs processing based on the count value y (X-ray count signal) of the processing target pixel and the count value y (X-ray count signal) of a pixel located in the vicinity of the processing target pixel. Estimate the non-uniformity of the X-ray incidence distribution of the pixels. Here, as described above, since the incidence rate prediction value x can be obtained from the count rate y by using the count rate characteristic y = f (x), in the present embodiment, the non-uniformity estimation unit 184 When estimating the non-uniformity, for example, the count rate characteristic y = f (x) previously stored in the storage unit 182 can be used.

(Calculation method of estimated incidence rate)
Hereinafter, according to examples shown in Table 1 in FIG. 10, an example of a method of calculating the incidence rate estimate x _E pixels 20a by nonuniformity estimator 184 in this embodiment.
It is shown in the 7th stage of the Table 1, according to the count rate characteristic y = incidence rate prediction value obtained from f (x) x, incidence rate predicted value x _a pixels 20a, the incident rate prediction value x _b pixels 20b It is estimated that the incident distribution at the pixel 20a is non-uniform. Pixel 20b is two subpixels 21bL, consists 21BR, since the incidence rate predicted value _{x b} pixels 20b is 5Mcps, subpixel 21bL, 21bR of the incidence rate predicted value _{x bL, x bR} are each 2.5Mcps Can be considered.

Sub distribution of the incident rate _{x a} to the pixel 20a is, assuming that increases exponentially with increasing distance from the adjacent subpixels 21BR, subpixel 21aL and 21aR of the incidence rate _{x aL, x aR} is adjacent The incident rate x _bR of the pixel 21bR is expressed as x _aL = p × k = 2.5 × k Mcps and x _aR = p × k ² = 2.5 × k ² Mcps, respectively, using p and the parameter k. Can do. The result of adding these incident rates x _aL and x _aR is equal to the predicted incident rate x _a = 14.8 Mcps of the pixel 20a obtained from the actual count rate with reference to the count rate characteristic y = f (x). The following formula (3) is established.

Solving this equation (3) gives k = 1.98. Thus, incidence rate predicted value _{x aL} tentatively subpixel 21aL is 5.0Mcps, incidence rate predicted value _{x bR} subpixel 21aR can obtain the calculation result of the 9.8Mcps. That is, the incidence rate _{x bR} subpixel 21bR adjacent, from the distribution of the assumed exponential incidence rate, tentative subpixel 21aL, incidence rate predicted value _x aL of _{21aR, x bR} is calculated.

Next, the predicted count rate values y _calaL and y _calaR corresponding to the incident rate predicted values x _{aL and} x _bR of the provisional subpixels 21aL and 21aR are calculated with reference to the count rate characteristic y = f (x). To do. That is, when the provisional count rate prediction values y _calaL and y _{calaR in} which the incidence rate prediction values x _aL and x _aR of the provisional subpixels 1aL and 21aR take values of 5.0 Mcps and 9.8 Mcps, respectively, are calculated, These are 4.5 Mcps and 8.1 Mcps, respectively. Count rate prediction value y _cala overall pixel 21a obtained by adding these, 12.6Mcps becomes, and thus about 1.5% smaller than the actual counting rate _y a = 12.8Mcps (5 row in Table 1) .

Therefore, by adding 1.5% to the incident rate predicted values x _aL and x _aR of the provisional subpixels 21aL and 21aR (that is, 1.015 times), the provisional incident rate predicted value x _{aL is} calculated. , X _aR are corrected, and estimated incidence rates x _EaL , x _EaR are obtained. The corrected subpixel 21aL, incidence rate estimated value _x EAL of _{21aR, x EaR} are each 5.0Mcps, the 10.0Mcps (9 row of Table 1). As a whole, the incident rate estimated value x _Ea = x _EaL + x _EaR = 15.0 _Mcps after correction. Thus, as an incident rate estimated value x _Ea of pixel 20a, in consideration of non-uniformity of the X-ray, the provisional value calculated incidence rate of the sub-pixels 21bR neighboring were corrected according to the actual count rate By using this value, it is possible to calculate a highly accurate incidence rate estimated value (10th stage in Table 1).

(Other methods for calculating the estimated incidence rate)
In addition, the computer 180 can acquire an accurate incidence rate estimated value of the pixel 20a by paying attention to the count rate in consideration of the dead time of the sub-pixel 21. Specifically, the non-uniformity estimation unit 184 uses the count rate characteristic f (x) of the signal processing unit 152 acquired in advance by actual measurement or simulation, and the distribution of the incidence rate to the pixel 20a is an adjacent subpixel. Assuming that it increases exponentially with distance from 21bR, the following equation (4) is used. p is an incident rate x _bR of the adjacent sub-pixel 21bR, and k is a parameter.

By solving equation (4), k = 2 is obtained. Thus, incidence rate estimated value x _EAL subpixel 21aL is 5.0Mcps incidence rate estimated value x _EBR subpixel 21aR can obtain the calculation result of the 10.0Mcps. That is, the incidence rate _{x bR} subpixel 21bR adjacent, from the distribution of the assumed exponential incidence rate, the sub-pixel 21aL, incidence rate estimated value x _EAL of 21aR, x _EBR is calculated. The calculated incidence rate estimation values x _EaL and x _EbR coincide with the incidence rate 5 Mcps to the subpixel 21 aL and the incidence rate 10 Mcps to the subpixel 21 aR, which are initially set for the simulation (third stage in Table 1). ). As a result, the incidence rates of the subpixels 21aL and 21aR can be estimated to be 5.0 Mcps and 10.0 Mcps, respectively (the ninth stage in Table 1), and the entire pixel 20a is 15.0 Mcps. Therefore, it can be seen that a highly accurate estimated value is obtained as the incident rate estimated value of the pixel 20a (the 10th stage in Table 1).
According to this calculation method, the incident rate estimated value can be calculated from the count rate characteristic and the actual count rate without using the incident rate predicted value.

Thus, in the above-described embodiment, in order to estimate the accurate incidence rate to the pixel 20a, the data including the count rate of the pixel 20a itself to be estimated and the count rate of the pixel 20b adjacent to the pixel 20a are used. Including data was used. Similarly, for example, the incidence rate on the pixel 20a can be estimated using the data of the pixel 20a itself and the adjacent pixel 20c. Moreover, the incident rate estimated value of the pixel can be calculated using the count value of the pixel located in the vicinity of the pixel whose incidence rate is to be estimated, not limited to the adjacent pixel.

Then, based on a plurality of estimated values for one pixel obtained in this way, the final calculation is performed using the arithmetic average, geometric average, harmonic average, median, maximum, minimum, and other methods. The estimated incidence rate to the pixel 20a is calculated, and the influence due to the non-uniformity of the incident distribution is corrected. In an actual detector, pixels are arranged two-dimensionally. Therefore, a plurality of estimated values may be acquired based on the respective count values and the count values of the pixels with respect to the four macro pixels adjacent on the side or the eight pixels including the pixels adjacent on the corner. .

It should be noted that although the number of adjacent pixels in the pixel located at the end of the detector is smaller than that in the central part, the influence of non-uniformity can be estimated using only the estimated value obtained. In the above-described example, the calculation is performed on the assumption that the incident distribution in the pixel changes exponentially, but a different distribution may be assumed. For example, bones in a subject and metal bolts used in the orthopedic field may cause a more rapid change in incidence rate. As described above, the incidence rate predicted value calculated from only the count rate characteristic is underestimated as the deviation of the incidence rate distribution is larger. Therefore, the incidence rate that changes more rapidly by the estimated value calculation method according to the present embodiment. It is preferable that a strong correction according to the incidence rate distribution is performed by assuming the distribution of ## EQU1 ## and an accurate incidence rate is calculated.

On the contrary, when the focus of the X-ray tube that emits X-rays is large, a sudden change in the incidence rate on a scale smaller than the focus size cannot occur in principle, and therefore correction by the incidence rate estimation method in this embodiment is performed. The degree of need for is reduced.
Therefore, it is preferable to adjust the strength of correction by the estimated value calculation method according to the present embodiment in consideration of clinical imaging conditions.

Note that the computer 180 calculates the incident rate estimated values corresponding to the counters 340a1 to 340a based on the total incident rates acquired by executing the estimated value calculation method described above in consideration of the influence of non-uniformity. And stored in the storage unit 182. When the influence of pile-up is small, the dead time that occurs randomly does not affect the distribution of the detection signal size.

Therefore, the total count rate is 12.8 Mcps, for example, the count rates of the counters 340a1 to 4 are 12.8 Mcps, 8.96 Mcps, 6.4 Mcps, 2.56 Mcps (100%, 70%, 50%, 20%), the incidence rate estimated values corresponding to the counters 340a1 to 4 are 15.0 Mcps, 10.5 Mcps, and 7 based on the total incidence rate estimation rate of 15.0 Mcps obtained according to the present embodiment. Values of 5 Mcps, 3.0 Mcps (100%, 70%, 50%, 20% of the total incidence rate estimate) are obtained.
Note that the method of calculating an accurate incidence rate estimation value using the count rate characteristics and the like according to the above-described embodiment can be applied regardless of whether the signal processing unit 152 is the above-described Mahi type or non-mahi type. is there.

The flow of imaging processing in the X-ray CT apparatus configured as described above will be described with reference to the flowchart of FIG.
In step S <b> 101, parameters for clinical imaging by the user, that is, input of imaging conditions are received via the input device 192. The imaging conditions can include information about the imaging target such as the imaging region, what kind of reconstruction is performed, and parameters for calculating the incidence rate estimation value according to the imaging region and the like. The parameters include parameters that affect the focal point size of the X-ray tube, such as tube current.

In the next step S102, the subject is irradiated with radiation based on the imaging conditions set in step S101, and count values as projection images are collected for each subpixel. In the signal processing unit 152, the count value output from the detection unit 151 is processed for each subpixel, and is output to the signal addition unit 166. The signal adding unit 166 adds the count value for each sub-pixel and outputs it to the control unit 170 as the count value for each pixel.

Subsequently, in step S103, the nonuniformity estimation unit 184 described above estimates the influence of the nonuniformity of the incident distribution based on the count value for each pixel obtained in step 102, and then estimates the incidence rate. Calculate At this time, apparatus characteristics such as the size of the focal point of the X-ray tube and parameters determined in step S101 are taken into consideration. The flow of processing for calculating the estimated incidence rate by the non-uniformity estimation unit 184 and the signal correction unit 185 will be described later.

In step S104, the image generation unit 183 generates a reconstructed image based on the incidence rate estimation value obtained in step 530, and displays the generated reconstructed image on the output device 191 to present it to the user.
In addition, various correction processes and other processes can be included in the imaging process in the X-ray CT apparatus according to the present embodiment described above. Further, once the count value is acquired in step S102, parameters and the like necessary for calculating the incidence rate estimated value can be input, and step S103 and step S104 can be executed.

Subsequently, the flow of processing from non-uniformity estimation for each pixel to calculation of the incidence rate estimated value will be described with reference to the flowcharts of FIGS. Since the detailed calculation method is as described above, the repeated description here is omitted.

First, the non-uniformity estimation unit 184 outputs an output signal (hereinafter, referred to as a count value) of a processing target pixel (for example, the pixel 20a in FIG. 9) that is a pixel for calculating an incidence rate estimation value stored in the storage unit 182. (Referred to as “count rate”) (step S201), and then the count rate of any pixel (for example, pixel 20b in FIG. 9) located in the vicinity of the pixel to be processed is read (step S202).

In step S203, the non-uniformity estimation unit 184 estimates non-uniformity of the processing target pixel, and in step S204, corrects the incident rate of the processing target pixel to calculate an incident rate estimated value. Specifically, for example, in step S203, the non-uniformity estimation unit 184 and the signal correction unit 185 read a program stored in advance in the storage unit 182 and operate as follows. First, non-uniformity estimator 184, a count rate y _a processing target pixel, the process from the count rate y _b for the pixel located in the vicinity of the target pixel, X-rays incidence rate to the processing target pixel is not one It is determined that

For example, non-uniformity estimator 184, previously determined by referring to the count rate characteristics had been, counting rate y _a and y _b in incidence rate prediction value x _a of the corresponding neighboring _pixels, calculates x _b If the difference is greater than or equal to a predetermined value, it is determined that the X-ray incidence rate to the processing target pixel is non-uniform. Or a a count rate y _a counting rate y _b compared directly, if the difference is not less than a predetermined value, X-rays incidence rate to the processing target pixel may be determined to be non-uniform. The count rate characteristic y = f (x) may be held by the non-uniformity estimation unit 184 or the signal correction unit 185 as a function (formula) obtained in advance, or the count rate and the incidence rate. You may hold | maintain as a table of estimated values.

If incidence rate is non-uniform, in step 204, the signal correction unit 185, the count rate y _b of the neighboring pixels, by referring to the count rate characteristics, incidence rate of neighboring pixels corresponding to the count rate y _b A predicted value _xb is calculated (see step S251 in FIG. 14). Next, the signal correction unit 185 calculates the incidence rate predicted value _xbR of the subpixels in the neighboring pixels (step S252). For example, assuming a uniform incidence rate in the neighboring pixels to calculate the incidence rate prediction value x _bR subpixels by equally dividing the incidence rate prediction value XBR.

Next, the signal correction unit 185 assumes that the incidence rate distribution in the processing target pixel changes exponentially with respect to the incidence rate predicted value xbR of the neighboring subpixel as the distance from the neighboring subpixel increases. (For example, the provisional incidence rate predicted values x _aL and x _aR for each sub-pixel included in the processing target pixel are calculated by the above-described equation (3) (step S253). The signal correction unit 185 calculates the provisional count rate prediction values y _calaL and y _calaR corresponding to the provisional subpixel incidence rate prediction values x _{aL and} x _bR with reference to the count rate characteristics (step S254). ). These and count rate prediction value _{y cala} = y calaL + y calaR the entire processing target pixel obtained by adding, the ratio q of the count rate _{y a} of the actual processing target pixel acquired in step S201 is calculated (step S255). Step S253 in the calculated tentative subpixel incidence rate prediction value _{x aL,} by multiplying the _{x aR} ratio q, the incident rate estimated value _{x EAL,} seek _{x EaR} (step S256).

And it progresses to step S205 and the signal correction | amendment part 185 memorize | stores the calculated incidence rate estimated value in the memory | storage part 182 temporarily.

In step S206, the signal correction unit 185 determines whether the calculation of the incidence rate estimation values for the pixels located in the vicinity of the processing target pixel has been completed. That is, the signal correction unit 185 determines whether the calculation of the incidence rate estimation value has been completed for all pixels at a predetermined position among the pixels in the vicinity of the pixel, and the calculation of the incidence rate estimation value has not been completed. In that case, the process returns to step S202 and the above-described processing is repeated.

When the signal correction unit 185 determines that the calculation of the incidence rate estimation value has been completed for all the pixels at the predetermined position, the process proceeds to step S207, and the signal correction unit 184 is obtained for all the pixels at the predetermined position. From the incident rate estimated value, for example, the incident rate estimated value of the processing target pixel is calculated by a predetermined method, such as an arithmetic mean, geometric mean, harmonic mean, median value, maximum value, minimum value, or the like.

In step S <b> 208, the signal correction unit 185 stores the calculated incidence rate estimation value of the processing target pixel in the storage unit 182. In step S209, it is determined whether the processing from the non-uniformity estimation for all the pixels obtained from the detection unit 151 to the calculation of the incidence rate estimated value has been completed. If the processing for all the pixels has not been completed, step S201 is performed. Return to and repeat the same process. On the other hand, when the processing for all the pixels is finished, this processing is finished and the process proceeds to generation of a reconstructed image.
Note that the processing from the non-uniformity estimation to the incidence rate estimation value calculation described above can be performed sequentially simultaneously with the generation of the reconstructed image.

(Modified example of calculation method of estimated incidence rate)
The calculation method of the incidence rate estimation value in consideration of the non-uniformity of the incident distribution is not limited to the above-described method, and for example, various methods can be considered as described below.
In the above-described example, an example in which one incident rate estimation value is obtained for the pixel 20a from the data of two pixels of the pixel 20a and the adjacent pixel 20b has been described (see FIG. 9). In addition, it is also possible to calculate one incident rate estimated value from data such as the counting rate of three pixels 20a, 20b, 20c including the pixel 20a, or more pixels including the pixel 20a. Then, the case where one incident rate estimated value is calculated from the count rates of the three pixels 20a, 20b, and 20c including the pixel 20a will be described.

As shown in Table 1 of FIG. 10, since the incidence rate prediction values based on the count rate characteristics of the pixels 20b and 20c are 5 Mcps and 40 Mcps, respectively, the incidence rates are 2.5 Mcps and 20 Mcps per subpixel in each pixel. I think there is. Then, since the incidence rate is 8 times at a distance of 3 subpixels from the subpixel 21bR to 21cL, the incidence rates of the subpixels 21aL and 21aR are, for example, 2.5 × 8 ^ {(1 / 3) ^α } Mcps, 2.5 × 8 ^ {(2/3) ^α } Mcps. In this case, it is considered that the count rate of the pixel 20a coincides with the actual measurement, and the following equation (5) can be considered for the count rate characteristic f (x).

Solving the above equation (5) yields α = 1. Therefore, it is possible to obtain an accurate incidence rate estimation value of 5.0 Mcps and 10.0 Mcps as the incidence rates of the subpixels 21aL and 21aR and 15.0 Mcps as the pixel 20a. In addition, regarding the incident rates of the subpixels 21aL and 21aR, not only the formula (5) but also a function that connects the incident rates of the subpixels 21bR and 21cL can be freely set.

In addition, it is possible to estimate the non-uniformity of the incident distribution by using the data of neighboring pixels with a wider range instead of using only the data of adjacent pixels. For example, in the above-described method, since the incident rate prediction value based on the count rate characteristic of the pixel 20b adjacent to the pixel 20a to be processed is 5 Mcps, the incident rate prediction value of the subpixel 21bR (and subpixel 21bL) is set to 2 The effect of non-uniformity of the incident distribution on the pixel 20a was estimated.

As shown in FIG. 15, the incidence rate of the sub-pixel 21bR can be calculated using not only the adjacent pixel 20b but also the count rate of the pixel 20d.
For example, when the predicted incidence rate of the pixel 20d is 3 Mcps, assuming that the change in the incidence distribution is a linear function, the incidence rates on the subpixels 21dR, 21dL, 21bR, and 21bL are 1.25 Mcps and 1 respectively. .75 Mcps, 2.25 Mcps, 2.75 Mcps. Therefore, it is possible to estimate the non-uniformity of the incident distribution on the pixel 20a assuming that the incident rate of the sub-pixel 21bR is 2.75 Mcps. In the estimation of the incidence rate to the subpixel 21bR, not only a linear function distribution but also an exponential distribution or other distributions can be assumed.

In the above-described example, for simplicity, a method using a one-dimensional detector and using data obtained from pixels located in the same row has been described. However, data of pixels located in neighboring rows is used. You can also. For example, as shown in FIG. 16, using the data of neighboring pixels 20b + and 20b− existing in the same column as the pixel 20b, the incidence rate of the subpixel 21bR is estimated by an appropriate weighted average operation, and based on this The influence of the non-uniformity of the incident distribution on the pixel 20a can be estimated.

<Second Embodiment>
In the above-described first embodiment, the incident rate estimation value is calculated for all pixels. However, it is not always necessary to calculate the incident rate estimated value for all pixels, and switching between calculating or not calculating the incident rate estimated value for each pixel may be performed.

For example, if it is determined from the comparison with the count rate of the adjacent pixel that the radiation incidence rate to the pixel is a maximum value, a minimum value, or a saddle point, the incident distribution in the pixel is not uniform. It can be considered that the processing time can be shortened without calculating the incident rate estimated value by judging that the characteristics can be ignored. Note that the determination of switching according to whether or not the estimated incidence rate is calculated may be directly designated by the user using the input device 192, or indirectly through setting of imaging and reconstruction conditions. May be.

When switching whether to calculate the incidence rate estimated value for each pixel or not, for example, according to the flowchart shown in FIG. 17, processing from non-uniformity estimation for each pixel to calculation of the incidence rate estimated value is performed.
The non-uniformity estimation unit 184 outputs an output signal (hereinafter referred to as “count”) regarding the count value of the processing target pixel (for example, the pixel 20a in FIG. 9) that is a pixel for calculating the incidence rate estimation value stored in the storage unit 182. (Referred to as “rate”) (step S301), and then the count rate of any pixel (for example, pixel 20b in FIG. 9) located in the vicinity of the pixel to be processed is read (step S302).

In step S303, the non-uniformity estimation unit 184 compares the count rates of the pixel and the pixel read in step S302, so that the radiation incidence rate to the pixel becomes a maximum value, a minimum value, or a saddle point. It is determined whether or not to correct the counting rate of the pixel. If it is determined in step S303 that the pixel is not corrected, the process proceeds to step S309. If it is determined in step S303 that the pixel is corrected, the process proceeds to step S304.

In step S304, the non-uniformity estimation unit 184 estimates the non-uniformity of the processing target pixel, corrects the incident rate of the processing target pixel, and calculates the incident rate estimated value. That is, in step S304, the non-uniformity estimation unit 184, according to the program stored in advance in the storage unit 182, as described above, the count rate of the processing target pixel and the pixel located in the vicinity of the processing target pixel. Based on the count rate, non-uniformity for each sub-pixel included in the processing target pixel is estimated, and an incidence rate estimated value corresponding to the non-uniformity is calculated. Then, the incidence rate estimation value for each sub-pixel is added to calculate the incidence rate estimation value of the processing target pixel. In step S305, the signal correction unit 185 temporarily stores the calculated incidence rate estimated value in the storage unit 182.

In step S306, the signal correction unit 185 determines whether all the calculation of the incidence rate estimation value for the pixel located in the vicinity of the processing target pixel is completed. That is, the signal correction unit 185 determines whether the calculation of the incidence rate estimation value has been completed for all pixels at a predetermined position among the pixels in the vicinity of the pixel, and the calculation of the incidence rate estimation value has not been completed. In that case, the process returns to step S302 and the above-described processing is repeated.

When the signal correction unit 185 determines that the calculation of the incidence rate estimation value has been completed for all the pixels at the predetermined position, the process proceeds to step S307, and the signal correction unit 184 is obtained for all the pixels at the predetermined position. From the incident rate estimated value, for example, the incident rate estimated value of the processing target pixel is calculated by a predetermined method, such as an arithmetic mean, geometric mean, harmonic mean, median value, maximum value, minimum value, or the like.

In step S308, the signal correction unit 185 stores the calculated incidence rate estimation value of the processing target pixel in the storage unit 182. In step S309, it is determined whether the processing from the non-uniformity estimation for all the pixels obtained from the detection unit 151 to the incidence rate estimated value calculation is completed. If the processing for all the pixels is not completed, step S201 is performed. Return to and repeat the same process. On the other hand, when the processing for all the pixels is finished, this processing is finished and the process proceeds to generation of a reconstructed image.

<Third Embodiment>
In addition, the signal adding unit 166 outputs information on the non-uniformity of the incident distribution in the pixel together with the count rate (output signal) for reference when estimating the influence of the non-uniformity in the pixel. May be. That is, when it can be determined that the incidence rate non-uniformity is more than a certain level among the sub-pixels constituting an arbitrary pixel, data that sets a flag for the pixel is output in advance, and the storage unit It is stored in 182.

As a result, the incidence rate estimated value is calculated only for the flagged pixels, or the incidence rate estimated value is calculated by determining that the uniformity of the incident X-ray is low, that is, the non-uniformity is high. It is possible to perform processing such as correcting the count rate more strongly. The signal adding unit 166 can set, for example, a flag of 0 or 1 as a flag to be stored together with the count rate, and can also output a quantitative value such as the degree of non-uniformity as a flag. As a result, although the amount of data to be output is slightly increased, the amount of data is still small compared to outputting the count rates of all subpixels, and the calculation cost for calculating the incidence rate estimated value can be reduced.

In this case, for example, processing from non-uniformity estimation for each pixel to incidence rate estimation value calculation is performed according to the flowchart shown in FIG.
In step S <b> 401, the non-uniformity estimation unit 184 reads the count rate related to the count value of the processing target pixel that is a pixel for calculating the incidence rate estimation value stored in the storage unit 182 together with the flag. In step S402, the non-uniformity estimation unit 184 determines whether or not to correct the count rate of the pixel by determining whether or not the pixel is flagged. If it is determined in step S402 that the pixel is not corrected, the process proceeds to step S409. If it is determined in step S402 that the pixel is corrected, the process proceeds to step S403.

Subsequently, in step S403, the count rate of any pixel located in the vicinity of the processing target pixel is read. In step S404, the non-uniformity estimation unit 184 estimates the non-uniformity of the processing target pixel, corrects the incidence rate of the processing target pixel, and calculates an incidence rate estimated value. In other words, in step S404, the non-uniformity estimation unit 184, according to the program stored in advance in the storage unit 182, as described above, the count rate of the processing target pixel and the pixel located in the vicinity of the processing target pixel. Based on the count rate, non-uniformity for each sub-pixel included in the processing target pixel is estimated, and an incidence rate estimated value corresponding to the non-uniformity is calculated. Then, the incidence rate estimation value for each sub-pixel is added to calculate the incidence rate estimation value of the processing target pixel. In step S405, the signal correction unit 185 temporarily stores the calculated incidence rate estimated value in the storage unit 182.

In step S406, the signal correction unit 185 determines whether or not the calculation of the incidence rate estimation values for the pixels located in the vicinity of the processing target pixel has been completed. That is, the signal correction unit 185 determines whether the calculation of the incidence rate estimation value has been completed for all pixels at a predetermined position among the pixels in the vicinity of the pixel, and the calculation of the incidence rate estimation value has not been completed. In that case, the process returns to step S403 and the above-described processing is repeated.

When the signal correction unit 185 determines that the calculation of the incidence rate estimation value has been completed for all the pixels at the predetermined position, the process proceeds to step S407, and the signal correction unit 184 is obtained for all the pixels at the predetermined position. From the incident rate estimated value, for example, the incident rate estimated value of the processing target pixel is calculated by a predetermined method, such as an arithmetic mean, geometric mean, harmonic mean, median value, maximum value, minimum value, or the like.

In step S408, the signal correction unit 185 stores the calculated incidence rate estimation value of the processing target pixel in the storage unit 182. In step S409, it is determined whether the processing from non-uniformity estimation for all the pixels obtained from the detection unit 151 to calculation of the incidence rate estimated value has been completed. If the processing for all the pixels has not been completed, step S401 is performed. Return to and repeat the same process. On the other hand, when the processing for all the pixels is finished, this processing is finished and the process proceeds to generation of a reconstructed image.

<Fourth Embodiment>
Moreover, when calculating the estimated incidence rate to the pixel, the estimated incidence rate obtained from the count rate characteristic for the adjacent pixel (the seventh row in Table 1 in FIG. 10) was used. However, there is a possibility that the predicted incidence rate is affected by the nonuniformity of the incident distribution.

Therefore, in order to further improve the accuracy of estimation, it is possible to perform a process of calculating the same incident rate estimated value again using the calculated incident rate estimated value instead of the incident rate predicted value. A sequential process that repeats this process a plurality of times is also possible.

In this case, for example, processing from non-uniformity estimation for each pixel to incidence rate estimation value calculation is performed according to the flowchart shown in FIG.
The non-uniformity estimation unit 184 reads the count rate related to the count value of the processing target pixel that is the pixel for calculating the incidence rate estimation value stored in the storage unit 182 (step S501), and near the processing target pixel. The count rate of any pixel located is read (step S502).

Subsequently, the non-uniformity estimation unit 184 estimates the non-uniformity of the processing target pixel, and the signal correction unit 185 corrects the incident rate of the processing target pixel based on the non-uniformity of the processing target pixel to obtain the incident rate estimated value. Calculate (step S503), and temporarily store the calculated incidence rate estimated value in the storage unit 182 (step S504).

In step S505, the signal correction unit 185 determines whether calculation of the incidence rate estimation value has been completed for all pixels at a predetermined position among the pixels in the vicinity of the pixel, and calculation of the incidence rate estimation value is completed. If not, the process returns to step S502 and the above-described processing is repeated. When the signal correction unit 185 determines that the calculation of the incidence rate estimation value has been completed for all the pixels at the predetermined position, the process proceeds to step S506, and the signal correction unit 185 is obtained for all the pixels at the predetermined position. From the incident rate estimated value, for example, the incident rate estimated value of the processing target pixel is calculated by a predetermined method such as arithmetic mean, and the calculated incident rate estimated value of the processing target pixel is stored in the storage unit 182 ( Step S507).

In step S508, it is determined whether the processing from the non-uniformity estimation for all the pixels obtained from the detection unit 151 to the incidence rate estimated value calculation is completed. If the processing for all the pixels is not completed, step S501 is performed. Return to and repeat the same process. On the other hand, when the processing for all the pixels is completed, the process proceeds to the next step S509, and it is determined whether or not the accuracy of the incidence rate estimated value stored in the storage unit 152 is sufficient. As a result of the determination, if it is determined that the accuracy is insufficient, the process returns to step S502, and the incident rate estimated value calculation process is performed again using the calculated incident rate estimated value instead of the pixel count rate. Do. On the other hand, if it is determined in step S509 that the accuracy of the incidence rate estimated value calculated by the signal correction unit 185 is sufficient, the present process is terminated and the process proceeds to generation of a reconstructed image.

As described above, according to each of the above-described embodiments, even if the X-ray incident distribution on each subpixel is non-uniform and the dead time of each subpixel (detection element) varies. Since the non-uniformity of the incident distribution of the sub-pixel is estimated using the count rate in the pixels near the sub-pixel, the X-ray incident distribution can be properly grasped. As a result, since the incident X-ray dose is accurately estimated based on the non-uniformity of the incident distribution, artifacts in the acquired reconstructed image can be reduced to improve the image quality.

In each of the above-described embodiments, the count rate characteristic indicating the relationship between the count rate and the incident rate has been described. However, the count rate characteristic f (x) may be given using an analytical expression or a lookup table. Further, it may be given by using interpolation as necessary.
Further, the calculation of the incidence rate estimated value by the non-uniformity estimation and the correction based on the non-uniformity estimation result is not necessarily performed independently of the image reconstruction in the image generation unit, and can be performed simultaneously. . It can also be performed simultaneously with other corrections (for example, pile-up correction). As an example, when using the successive approximation method in image reconstruction, the estimation of the effects of non-uniformity is performed simultaneously with other detector responses in a forward problem to create a reconstructed image. Is possible.

Further, in each of the above-described embodiments, subpixel division is performed by providing a common electrode on the upper surface of the direct radiation detection material and a subpixel electrode on the lower surface. An electrode may be provided for each. Similarly, adjacent pixels 20 may share a common electrode on the upper surface, or may have electrodes individually. Further, as a detector material, not a direct radiation detection material but a scintillator (indirect radiation detection material) optically coupled to an optical device can be used. As a method of dividing the subpixel in this case, a scintillator whose periphery is covered with a light-shielding agent may be provided for each subpixel, or a method of generating a microcrack by a laser between subpixels for one scintillator. Sub-pixel division may be performed. As the optical device, a photomultiplier tube (PMT), a photodiode (PD), an avalanche photodiode (APD), a silicon photomultiplier tube (SiPM), or the like can be used.

20 ... Pixel, 21 ... Subpixel, 40 ... Detection layer, 41, 42 ... Electrode, 110 ... Gantry rotating part, 120 ... X-ray source, 125 ... Filter, 130 ... X-ray photons, 140 ... bed, 145 ... collimator, 150 ... X-ray detector, 151 ... detection unit, 152 ... signal processing unit, 165 ... channel, 166 ... Signal adder, 170 ... Control unit, 180 ... Computer, 181 ... CPU, 182 ... Storage, 183 ... Image generation unit, 184 ... Non-uniformity estimation 185 ... Signal correction unit 191 ... Display device 192 ... Input device

Claims (15)

1. An X-ray source that emits X-rays;
   A detection unit that two-dimensionally arranges pixels composed of a plurality of sub-pixels that detect the X-ray;
   A signal processing unit that generates an output signal corresponding to the intensity of the X-ray based on a detection signal from the subpixel;
   A signal adder that generates an X-ray count signal for each pixel by adding the output signals of the sub-pixels belonging to the pixel;
   An image generation unit that generates an image based on the X-ray counting signal,
   Based on the X-ray count signal of the pixel to be processed and the X-ray count signal of a pixel located in the vicinity of the pixel to be processed, the image generation unit determines whether the X-ray incident distribution in the pixel to be processed is not unique. A radiation imaging apparatus including a non-uniformity estimation unit that estimates the appearance.
2. The radiation imaging apparatus according to claim 1, wherein the detection unit is a photon counting type detection unit that detects X-ray photons.
3. Based on the X-ray count signal of the pixel to be processed and the X-ray count signal of a pixel located adjacent to the pixel to be processed, the non-uniformity estimation unit determines an X-ray incidence distribution in the pixel to be processed. The radiation imaging apparatus according to claim 1, wherein non-uniformity of the image is estimated.
4. Based on the X-ray count signal of the processing target pixel and the X-ray count signals of a plurality of pixels located in the vicinity of the processing target pixel, the non-uniformity estimation unit The radiation imaging apparatus according to claim 1, wherein non-uniformity of the incident distribution is estimated.
5. The non-uniformity estimation unit holds in advance a count rate characteristic indicating a relationship between an incidence rate of X-rays incident on the pixel and the X-ray count signal, and the count rate characteristic and the X of the pixel to be processed are stored. The X-ray incidence distribution non-uniformity in the processing target pixel is estimated based on a line counting signal and the X-ray counting signal of a pixel located in the vicinity of the processing target pixel. Item 2. The radiation imaging apparatus according to Item 1.
6. The image generator
   In accordance with the non-uniformity estimation result by the non-uniformity estimation unit, the X-ray count signal of the processing target pixel is corrected, and an incidence rate estimated value of the X-rays incident on the processing target pixel is calculated. A signal correction unit,
   The radiation imaging apparatus according to claim 1, wherein the image generation unit generates an image based on an estimated X-ray incidence rate.
7. The non-uniformity estimation unit holds in advance a count rate characteristic indicating a relationship between an incidence rate of X-rays incident on the pixel and the X-ray count signal, and the processing target pixel is used by using the count rate characteristic. And an incident rate predicted value of a pixel located in the vicinity of the processing target pixel, and based on the X-ray count signal and the incident rate predicted value of the processing target pixel and a pixel located in the vicinity of the processing target pixel. , Estimating non-uniformity of the X-ray incident distribution of the pixel to be processed,
   The radiation imaging apparatus according to claim 6, wherein the signal correction unit calculates an incidence rate estimated value obtained by correcting the incidence rate predicted value of the processing target pixel according to an estimation result by the non-uniformity estimation unit.
8. The image generation unit includes a signal correction unit that calculates an X-ray incidence rate estimation value in a sub-pixel in the processing target pixel,
   The signal correction unit is configured to obtain an X-ray incidence rate at a sub-pixel in the neighboring pixel from an X-ray counting signal obtained in advance from the X-ray counting signal of the pixel located in the vicinity of the processing target pixel. Calculated from the relationship with the X-ray incidence rate, the X-ray incidence rate changes according to the calculated X-ray incidence rate value and the distance from the subpixel in the neighboring pixel to the subpixel in the processing target pixel. 2. The radiation imaging apparatus according to claim 1, wherein the X-ray incidence rate estimated value of the sub-pixel in the processing target pixel is calculated using a predetermined function indicating that the pixel is to be processed.
9. The radiation imaging apparatus according to claim 6, wherein the signal correction unit calculates the incident rate estimated value so that an X-ray incident rate is higher than a value before correction when calculating the incident rate estimated value.
10. An input unit for inputting a plurality of imaging conditions including information on the imaging target and parameters affecting the focal spot size of the X-ray tube;
    The radiation imaging apparatus according to claim 1, wherein the image generation unit estimates non-uniformity of an X-ray incident distribution using at least one of the plurality of imaging conditions.
11. The signal adding unit generates information on non-uniformity in the processing target pixel based on the output signal for each sub-pixel received from the signal processing unit, and outputs the information together with the X-ray count signal. The radiation imaging apparatus according to 1.
12. The radiation imaging apparatus according to claim 1, wherein the image generation unit sequentially estimates non-uniformity of an X-ray incident distribution with respect to each pixel during image generation processing.
13. The radiation imaging apparatus according to claim 1, wherein the detection unit is configured by arranging semiconductor radiation detection elements.
14. Irradiating with X-rays;
    Outputting a detection signal of the X-ray by a detection unit in which a plurality of pixels in which the detection elements for detecting the X-ray are two-dimensionally arranged are arranged;
    Generating an output signal corresponding to the intensity of the X-ray based on the detection signal;
    Generating an X-ray count signal for each pixel by adding the output signals of the detection elements belonging to the pixel;
    Estimating non-uniformity of the X-ray incident distribution of the processing target pixel based on the X-ray counting signal of the processing target pixel and the X-ray counting signal of a pixel located in the vicinity of the processing target pixel; When,
    A radiation imaging method comprising: generating an image based on the X-ray counting signal.
15. Irradiating with X-rays;
    Outputting a detection signal of the X-ray by a detection unit in which a plurality of pixels in which the detection elements for detecting the X-ray are two-dimensionally arranged are arranged;
    Generating an output signal corresponding to the intensity of the X-ray based on the detection signal;
    Generating an X-ray count signal for each pixel by adding the output signals of the detection elements belonging to the pixel;
    Generating an image based on the X-ray counting signal;
    Estimating non-uniformity of the X-ray incident distribution of the processing target pixel based on the X-ray counting signal of the processing target pixel and the X-ray counting signal of a pixel located in the vicinity of the processing target pixel; A radiation imaging program that causes a computer to execute.

Images