JP3291410B2 - Method and apparatus for analyzing composition of target object - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to means for processing CT image data of a test object (object) using radiation (X-rays, gamma rays, etc.), and in particular, to process CT image data of the object and analyze its composition. And a method for performing the method.

[0002]

2. Description of the Related Art A CT apparatus is an apparatus that visualizes the inside of a subject as a two-dimensional tomographic image or a three-dimensional stereoscopic image. Techniques have been proposed for accurately obtaining a physical quantity of an object to be inspected using data collected and processed by a CT apparatus.

For example, as a conventional technique for processing CT image data collected and processed by such a CT apparatus, there is a technique described in Japanese Patent Application Laid-Open No. 61-156482.

In the technique disclosed in this publication, after a frequency distribution of “CT value” (a physical quantity corresponding to a linear absorption coefficient), which is CT image data, is created, the frequency distribution spread by noise is generated. Therefore, a method for removing the influence of noise is provided. Here, the frequency distribution in which the spread has occurred due to noise will be specifically described as follows.

[0005] That is, it is assumed that a substance made of a certain homogeneous material is photographed by a CT apparatus in a state where no noise is present, and a numerical value indicating that the linear absorption coefficient of the substance is "10" is obtained. When there is noise, the linear absorption coefficient of the substance is distributed according to a Gaussian distribution with an average value of “10”. This is the frequency distribution in which spread has occurred due to noise.

[0006] When the noise level is large, the standard deviation of the Gaussian distribution is large (ie, the Gaussian distribution is widened). Conversely, when the noise level is small, the standard deviation of the Gaussian distribution is small (ie, the Gaussian distribution). Becomes narrower).

The problem when noise is present is as follows.
That is, a case occurs where the linear absorption coefficients of two or more substances are apparently indistinguishable. For example, if a substance having a linear absorption coefficient of “10” and a substance having a linear absorption coefficient of “11” exist, the frequency distribution of the linear absorption coefficient may seemingly overlap due to the influence of noise. . At this time, ideally, the linear absorption coefficient is distributed so as to have two peaks, but actually, the linear absorption coefficient is not distributed so as to clearly have two peaks. It is not possible to recognize that two substances are present simply by referring to the frequency distribution of. Therefore,
The technique described in Japanese Patent Application Laid-Open No. 61-156482 has provided means for solving such a problem.

[0008]

In the frequency distribution obtained by the above-mentioned prior art, the horizontal axis represents the linear absorption coefficient, and the vertical axis represents the number of pixels having the value of the linear absorption coefficient. I was According to this frequency distribution, although the linear absorption coefficient of the test object can be obtained, the physical quantity such as the density and volume of the test object is not expressed, so the information of the actual physical quantities (density, mass, and volume) of the test object is obtained. Cannot be obtained immediately.

Therefore, it has not been possible to analyze the composition of the test object using the above-mentioned conventional technology.

Accordingly, an object of the present invention is to provide means for analyzing the composition of a test object using a CT apparatus. The composition analysis refers to the following items.

(1) The "density" of the substance for each constituent substance of the test object is determined.

(2) The "volume" of the substance for each constituent substance of the test object is determined.

(3) A ratio “volume ratio” of the volume of each constituent substance to the volume of the test object is determined.

(4) The "mass" of the substance to be inspected for each constituent substance is determined.

(5) The ratio “mass ratio” of the mass of each constituent substance to the mass of the test object is determined.

That is, the present invention provides means for performing a composition analysis based on tomographic image information captured by a CT apparatus.

[0017]

To achieve the above-mentioned object, the following means are conceivable.

That is, an object composed of a plurality of constituent materials is irradiated with radiation from a plurality of directions, and image reconstruction processing is performed on data obtained by detecting radiation transmitted through the object in each direction. The line absorption coefficient for each pixel constituting the cross-sectional image of the object is determined for each pixel, and the density uniquely corresponding to the line absorption coefficient is determined for each pixel, and the object is uniquely identified for each pixel. Assuming that the volume element is divided into three-dimensional volume elements, the number of volume elements corresponding to pixels having a certain density and the volume amount of one volume element are determined. And the number of
The volume of one of the volume elements is multiplied to obtain the volume for the certain density. When the density is used as a parameter, the composition of the object for which the density spectrum is to be obtained, indicating the distribution state of the volume with respect to a change in the parameter. It is an analysis method.

The volume amount of one volume element is determined by a "thickness" determined by parameters including at least dimensions of a radiation source for irradiating radiation, a collimator provided in a detector for detecting radiation, and the image reconstruction processing. And the “thickness (H)” is S, the height of the collimator included in the detector is A, and the “thickness (H)” is The distance “D” from the center of the object and the distance L between the radiation source and the detector are obtained by a predetermined rule, and the “area (Sr)” is determined for displaying the result of the image reconstruction processing. Pixel area (S
i) and Sr, which is determined by “Si = K · Sr (K is a constant determined in advance during image reconstruction processing and data detection by the detector)”.

The volume of each constituent material and the volume of the object can be obtained by the following processing.

That is, the density in the density spectrum is a, and the volume with the density a as a parameter is V
(A), when V (a) is observed in the direction in which a increases, a distribution having one unimodal shape is regarded as volume distribution data for one constituent substance, and the distribution having the unimodal shape is obtained. The maximum value of the distribution is defined as the volume of the constituent substance, and the volume of each constituent substance is determined.

Further, the sum of the volumes of the respective constituent substances is obtained, and the volume of the object is obtained.

[0023]

First, an object composed of a plurality of constituent materials is irradiated with radiation from a plurality of directions, and in each direction, an image reconstruction process is performed on data obtained by detecting radiation transmitted through the object. . Next, a line absorption coefficient for each pixel constituting the cross-sectional image of the object is determined for each pixel, and a density uniquely corresponding to the line absorption coefficient is determined for each pixel.

Next, when it is assumed that the object is divided into three-dimensional volume elements so as to uniquely correspond to each pixel, the number of volume elements corresponding to pixels having a certain density,
Then, the volume of one volume element is determined, and the number of the volume elements is multiplied by the volume of one volume element to determine the volume for the certain density.

Then, when the density is used as a parameter, a density spectrum showing a volume distribution state with respect to a change in the parameter is obtained.

The volume amount of one volume element is determined by a “thickness” determined by a parameter including at least dimensions of a radiation source for irradiating radiation and a collimator provided in a detector for detecting radiation, and the image reconstruction processing. And “area” determined by a parameter including at least the above condition.

Further, the "thickness (H)" indicates that the height of the radiation source is S, the height of the collimator provided in the detector is A, the distance D between the radiation source and the center of the object, the radiation source and the detector The area (Sr) is obtained by calculating a pixel area (Si) determined for displaying the result of the image reconstruction processing and Sr using the distance L of "Si
= K · Sr (K is a constant determined in advance during image reconstruction processing and data detection by the detector) ”.

Further, the calculation of the volume and the volume ratio, which is one mode of the composition analysis, is performed as follows.

The volume of each constituent is determined as follows.

That is, in the density spectrum, the density is a and the volume with the density a as a parameter is V (a).
When V (a) is observed in the direction in which a increases, a distribution having one unimodal shape is regarded as volume distribution data for one constituent substance, and the maximum value of the distribution having the unimodal shape is determined. The volume of each component is determined as the volume of the component.

The volume of the object is obtained as follows.

That is, the sum of the volumes of the respective constituent substances is obtained, and the volume of the object is obtained.

Then, the volume ratio of the constituent substance, which is the ratio of the volume of the object to the volume of the constituent substance, can be obtained for each constituent substance. As described above, by using the density spectrum of the object, the volume and mass of the object can be obtained.

[0034]

Embodiments of the present invention will be described below with reference to the drawings.

First, C for capturing a two-dimensional tomographic image
By making an outline of CT measurement data and image reconstruction related to T, an effort is made to facilitate understanding of the present invention.

In the CT measurement of an object to be inspected (also appropriately referred to as an "object"), "projection data" of the object to be inspected, which is required for image reconstruction calculation, is usually measured.

As shown in FIG. 4, in a radiation beam existing along a straight line L specified by two parameters “θ” and “r”, the intensity of the incident radiation is “I ₀ ” and is transmitted through the subject. When the obtained radiation intensity is “I”, the projection data P of the straight line L is a value defined by the following equation.

[0038]

(Equation 1)

Since the radiation intensity I after passing through the object to be inspected depends on the parameters θ and r defining the straight line L, the radiation intensity I is calculated using the parameters θ and r.
Can be expressed as I (r, θ). Therefore, since the projection data P of the straight line L also depends on the parameters θ and r, P (r,
θ).

Therefore, when the above (Equation 1) is expressed by using the parameters θ and r of the straight line L, the following equation is obtained.

[0041]

(Equation 2)

The projection data is a set of data represented by the equation (2) when the parameter r changes from negative infinity to positive infinity and the parameter θ changes from 0 to π. If the range of the object to be inspected is within the circle having the radius D, the range of the parameter r is from “−D” to “+ D”.

Next, image reconstruction will be briefly described.

The image reconstruction operation is performed by using the following (Equation 3) to (Equation 6).

[0045]

(Equation 3)

[0046]

(Equation 4)

[0047]

(Equation 5)

[0048]

(Equation 6)

Briefly describing the processing using each equation, the Fourier transform of the projection data is performed by (Equation 3), and the filtering of the projection data in the frequency space is performed by (Equation 4). This (Equation 4)
The function “h” in the middle is called a filter function, and a Shepp-Logan filter function is frequently used in CT image reconstruction calculation. (Equation 5) is an equation for performing the inverse Fourier transform, and specifically, is an equation for converting the projection data filtered by (Equation 4) into data in a real space.

(Equation 6) is a back-projection (back-projection) operation, and the result of this operation, f
(X, y) represents the linear absorption coefficient of the radiation at the point (x, y) of the subject. Here, all the functions in the equations are described as continuous functions. However, in order to actually perform the calculation by a computer, appropriate discretization is performed.

This discretization is performed by discretizing each parameter as shown in the following (Equation 7) to (Equation 11).

[0052]

(Equation 7)

[0053]

(Equation 8)

[0054]

(Equation 9)

[0055]

(Equation 10)

[0056]

[Equation 11]

Since Δx and Δy in Equation 11 are fixed values, the function f is actually a function of m and n. In this sense, the function f is described as f (m, n) as appropriate.

Now, a method for analyzing the composition of an object, which is an object of the present invention, will be described with reference to the drawings. Here, in order to facilitate understanding, a description will be given using a CT apparatus that captures a two-dimensional tomographic image as an example.

Incidentally, the composition analysis can be realized by the following two processes. That is, (1) a process of creating a “density spectrum” expressing the vertical axis as volume and the horizontal axis as density based on CT tomographic image information, and (2) referring to the density spectrum as described above. This is a process for performing composition analysis.

First, a method of creating a density spectrum will be described.

The creation of the density spectrum is performed in four main steps (steps 1 to 4). “Step 1” is obtained from the above (Equation 3) by (Equation 11),
The linear absorption coefficient f (m, n) of the test object is converted into the density of the test object. Next, “Step 2” finds the volume of a rectangular parallelepiped of the real cross section corresponding to the pixel on the CT tomographic image.

Next, in step 3, referring to the result obtained in step 1, a frequency distribution having the density on the horizontal axis and the number on the vertical axis is obtained. Further, in “Step 4”, a rectangular parallelepiped volume of the cross section of the real object to be inspected corresponding to the pixel obtained in Step 2 is obtained, and the horizontal axis represents the density and the vertical axis represents the frequency distribution obtained in Step 3. Is a volume, and a density spectrum is obtained.

Hereinafter, how to achieve these four steps will be described.

First, step 1 will be described.

In general, when the interaction between a substance and radiation is in the Compton scattering region, a proportional relationship is established between the linear absorption coefficient and the density of the test object. For example, as shown in FIG. 5, taking the density of a substance on the horizontal axis and the linear absorption coefficient of X-ray on the vertical axis, the incident radiation is X for each of concrete, aluminum, iron, copper, lead, and tungsten. Plotting the linear absorption coefficient when the energy is 1 M (eV) and 4 M (eV) with a line, it can be seen that a proportional relationship is established between the linear absorption coefficient and the density of the test object. .

Therefore, from the linear absorption coefficient f (m, n) of the test object obtained by (Equation 3) to (Equation 11),
The corresponding density d (m, n) can be determined by the following equation.

[0067]

(Equation 12)

Here, C and D are constants determined by the energy of the radiation. These two constants can be obtained from the straight line shown in FIG. That is, "C"
Is the slope of the straight line, and "D" is the value of the vertical axis at the point where the straight line and the vertical axis intersect. For example, X-ray energy is 1M
At (eV) and 4M (eV), C and D are as follows, respectively.

C = 0.0662: D = −0.01380
2 (in the case of 1M (eV)) C = 0.040671: D = −0.024869 (4M
(In the case of (eV)) Since the energy of the X-ray becomes a value unique to the apparatus,
The constants C and D determined by the X-ray energy may be obtained in advance.

Next, step 2 will be described.

First, the relationship between the CT tomographic image calculated by (Equation 3) to (Equation 11) and the cross section of the real object will be described with reference to FIG. The CT tomographic image is composed of image units (pixels) called pixels, and a pixel can be designated by two integer values m and n as shown in the figure. These two integer values m and n are given by (Equation 1)
These are the same parameters as shown in 1). That is, the numerical value corresponding to the pixel (m, n) is f (m,
n).

The cross section of the real object corresponding to the pixel (m, n) on the CT tomographic image is a rectangular parallelepiped as shown in FIG. Then, the numerical value f (m, n) represents the average value of the linear absorption coefficient in the rectangular solid.

Next, the pixels (m,
A method of obtaining the volume of a rectangular parallelepiped of the cross section of the real object corresponding to n) will be described.

First, a method for obtaining the thickness H will be described with reference to FIG.

FIG. 7 is a schematic diagram when the CT apparatus is viewed from the lateral direction. The size of the source is "S", the height of the collimator arranged in front of the detector is "A", the length of the collimator is "T", the distance between the source and the detector is "L", Assuming that the distance between the source and the center of the test object is “D”, the thickness “H” of the test object can be expressed by the following (formula 13) to (formula 16). “B” is the size of the radiation source viewed from the detector side.

[0076]

(Equation 13)

[0077]

[Equation 14]

[0078]

(Equation 15)

[0079]

(Equation 16)

The thickness H is represented by "S" for the size of the radiation source, "A" for the height of the collimator disposed in front of the detector, "T" for the length of the collimator, and "L" for the distance between the radiation source and the detector. , And the distance “D” between the radiation source and the center of the object to be inspected, as shown in (Equation 13) to (Equation 16).
In any case, the thickness "H" can be determined from the geometry of the CT device.

Next, a method of obtaining the base area of a rectangular parallelepiped corresponding to one pixel will be described with reference to FIG. This base area is calculated based on the projection data collection condition (Equation 7),
It is determined from the image reconstruction parameter conditions (Equation 9) and (Equation 10), and how to determine them will be described.

FIG. 8A shows a state in which a real object is photographed in accordance with (Equation 7) with the radiation beam interval set to Δr. The size of the radiation beam interval Δr is determined by the operator who operates the CT apparatus. By arranging the detectors in an array, the same effect as changing the radiation beam interval can be obtained, but here, a method for obtaining the bottom area of the rectangular parallelepiped corresponding to one pixel will be described. It is assumed that the radiation beam interval is set to Δr, and an actual object to be inspected is photographed by changing this.

FIG. 8B is a CT tomographic image obtained by discretizing projection data captured at the radiation beam interval Δr by (Equation 9) and (Equation 10). (Equation 9) and (Equation 10)
The discretization shown in the following shows that the operator operating the CT device
This is performed by determining Δx and Δy.

It should be noted that Δx, Δ
y does not indicate the pixel spacing on the display screen. Since the interval between pixels on the display screen is determined by the resolution of the display device (for example, CRT), it cannot be arbitrarily determined by the operator of the CT device. That is, Δx and Δy mean that the pixel interval in the horizontal direction of the CRT is virtually considered as Δx, and the pixel interval in the vertical direction is virtually considered as Δy. And Δx, Δy
Is arbitrary, the two quantities are equal to the Δ
can be related to r. This relationship is expressed by (Equation 17),
(Expression 18).

[0085]

[Equation 17]

[0086]

(Equation 18)

Here, a and b are constants, and Δr, Δx, Δ
y.

According to (Equation 17) and (Equation 18), Δx and Δy arbitrarily determined by the operator of the CT apparatus can be linked to the projection data acquisition conditions. As a result, the bottom area of the real rectangular parallelepiped corresponding to one pixel can be calculated by the following (Equation 19).

[0089]

[Equation 19]

That is, the bottom area of the real rectangular parallelepiped corresponding to one pixel is “ab · Δr · Δr”.
Therefore, according to the above description, the volume of the rectangular parallelepiped corresponding to one pixel can be calculated by the following equation (Equation 20).

[0091]

(Equation 20)

Next, step 3 will be described with reference to FIG. Density 1 (g / cm ³ ) shown in FIG.
FIG. 9B shows a CT tomographic image created in step 1 after CT imaging is performed on a real cross section of the object to be inspected. The CT tomographic image shown in FIG. 9B is composed of a total of 100 pixels.
The data for each pixel is a numerical value written in the figure, and is a value calculated in step 1 described above. A frequency distribution graph can be created by counting the number of pixels having the same numerical value in the CT tomographic image shown in FIG. 9B, and this frequency distribution graph is shown in FIG. 9C. .

Next, step 4 will be described with reference to FIG. For the frequency distribution graph created in step 3, the number of pixels on the vertical axis is converted into a volume value using the volume of a rectangular parallelepiped corresponding to the pixel obtained in step 2. For example, assuming that the volume of a rectangular parallelepiped of a real cross section corresponding to one pixel of the CT tomographic image shown in FIG. 9B is 10 (cm ³ ), the density is 1 (g / c).
m ³ ), the number of pixels is “33 (pieces)”, so when converted to volume, 33 × 10 = 330 (cm ³ )
Becomes As described above, when the vertical axis is converted from the number of pixels to the volume value for each density, a density spectrum can be generated.

Next, a method for performing a composition analysis using the density spectrum will be described. As described above, the composition analysis refers to the following items.

(1) Find the "density" of the substance for each constituent substance of the test object.

(2) The “volume” of the substance for each constituent substance of the test object is obtained.

(3) The ratio “volume ratio” of the volume of each constituent substance to the volume of the test object is determined.

(4) Obtain the “mass” of the substance for each constituent substance of the test object.

(5) The ratio “mass ratio” of the mass of each constituent substance to the mass of the test object is determined.

Hereinafter, a method of performing the composition analysis will be described with reference to the drawings.

(1) An analysis is performed to determine the “density” of a substance for each constituent substance of a test object.

The present analysis method will be described with reference to FIG.
FIG. 11 shows a certain density spectrum created by the method described above. From this density spectrum, a peak of the volume value is detected, and the substance corresponding to the peak is a constituent substance constituting the test object. That is, four types of A, B, C, and D in the figure are the substances constituting the test object, and their densities are “1.0, 1.6, 2.0,
2.4 (g / cm ³ ) ".

As described above, the density of each constituent material can be easily obtained by referring to the density spectrum.

(2) An analysis is performed to determine the “volume” of the substance for each constituent substance of the test object.

The analysis method will be described with reference to FIG.

As described above, it was found that there were four types of constituent substances A, B, C, and D of the test object.
The volume occupied by each constituent material is “25
0, 350, 400, 300 (cm ³ ) "from the density spectrum.

As described above, the volume of each constituent material can be easily obtained by referring to the density spectrum.

(Third) An analysis is performed to determine the ratio “volume ratio” of the volume of each constituent substance to the volume of the test object.

The analysis method will be described with reference to FIG.
As described above, the constituent materials constituting the test object are A,
It can be seen that there are four types, B, C, and D, and the volume of each substance is “250, 350, 400, 300 (cm ³ )”. Therefore, the volume of the whole test object is
“250 + 350 + 400 + 300 = 1300 (c
m ³ ) ”.

Therefore, the volume ratio of the substance A constituting the test object is “250 ÷ 1300 = 19 (%)”. Similarly, the volume ratio of the substances B, C, and D is “27”.
(%), 31 (%), and 23 (%). "

(Fourth) An object to be inspected is analyzed to determine the "mass" of the substance for each constituent substance.

The analysis method will be described with reference to FIG.

As described above, from the (first) and (second) analysis results, the constituent substances constituting the test object are A, B, C,
D, and the density of each substance is “1.
0, 1.6, 2.0, 2.4 (g / cm ³ ) "
Further, the volume of each substance is “250, 350, 40”.
0, 300 (cm ³ ) ".

Here, since the mass can be obtained by multiplying the density and the volume, the mass of each substance A constituting the test object is “1.0 (g / cm ³ ) × 250 (cm ³ ). = 250
(G) ", and similarly, the masses of the substances B, C, and D become" 560, 800, 720 (g) ".

(Fifth) Analysis is performed to determine the ratio “mass ratio” of the mass of each constituent substance to the mass of the test object.

The analysis method will be described with reference to FIG. As described above, based on the (first), (second) and (third) analysis results, the substance constituting the test object is A,
It was found that there were four types, B, C, and D, and the mass of each constituent material was “250, 560, 800, 720 (g)”. Further, the mass of the test object is 2330 (g) because it is the sum of the masses of the constituent substances of the test object. Accordingly, the mass ratio of the substance A constituting the test object is “250 ÷ 2330 = 11 (%)”, and similarly, the mass ratio of the substances B, C, and D is “24, 34, 31”.
(%).

As described above, the composition of the test object could be analyzed.

Next, a method for measuring the density resolution will be described below.

Here, the “density resolution” is a physical quantity indicating how far apart the density of two substances can be distinguished. The measurement of the density resolution is achieved by a process of creating a density spectrum having a vertical axis as a volume and a horizontal axis as a density based on a CT tomographic image, and a process of measuring the density resolution from the density spectrum. At this time, a substance having a uniform density is used as the test object.

Among the methods for measuring the density resolution, the creation of the density spectrum has already been described, and will not be described again. Here, a method for measuring the density resolution from the density spectrum will be described with reference to the drawings.

FIG. 12 shows a density spectrum created by photographing the test object shown in FIG. 9A. In the density spectrum, a spread occurs due to noise at the time of data collection of the object to be inspected and noise due to discretization in image reconstruction.

FIG. 10 is a drawing showing the density spectrum of a certain substance. As can be seen by comparing the density spectrum shown in FIG. 10 with the density spectrum shown in FIG. 12, the density spectrum shown in FIG. Has a density of 1.0 (g
/ Cm ³ ), the distribution is sharp peak-like, but the density spectrum of FIG. 12 shows a density of 1.0 (g / cm ³ ).
³ ) Density 0.9 or 1.1 (g / cm ³ )
Until the distribution has spread.

Substances having close densities that are buried in this spread become virtually indistinguishable.
Therefore, the density resolution is measured as follows.

First, after preparing a density spectrum, a peak in the density spectrum is detected. The width of the density spectrum having a half value of the maximum value of the peak is referred to as the peak half width.

Taking peak B in FIG. 12 as an example, the maximum value of this peak is 150 (cm ³ ), half the maximum value is 75 (cm ³ ), and the half value width is 0. 23
(G / cm ³ ).

At this time, the density resolution is calculated by the following equation (Equation 21) and becomes 0.23 (%).

[0127]

(Equation 21)

This means that for a substance having a density of 1.0 (g / cm ³ ), the density of another substance is “± 0.115”.
(%) "Indicates that they can be identified in the CT tomographic image.

An embodiment of the apparatus according to the present invention will be described with reference to the drawings.

FIG. 1 shows C having a function of performing composition analysis.
1 shows a configuration example of a T device.

The CT apparatus according to the present invention includes a radiation source 1, a one-dimensional or two-dimensional array detector 2, and an object mounted thereon.
A rotatable table 4, a driving device 5 for the table 4,
A signal processing circuit 7 having at least a function of A / D converting an output signal of the array detector 2, a memory 8 for storing various calculation results and data necessary for various processing, a program for performing predetermined processing, and the like; A computing device 9 for performing processing relating to reconstruction computation and composition analysis, a control device 10 having a function of controlling each device, an input device 11 for inputting commands and parameters required for measurement, and outputting various computation results and the like And an output device 12.

The test object 3 is placed on a table 4 arranged between the radiation source 1 and the array detector 2, and is placed on the table 4 by a table driving device 5. Translation and rotation are performed. The object 3 is irradiated with the radiation 6 from the radiation source 1 during translation and rotation, and the array detector 2 detects the radiation transmitted through the object 3.

The signals detected by the array detector 2 are amplified by the signal processing circuit 7 and then converted from analog to digital. The detector output signal converted into a digital signal is transferred to the memory 8 and stored. Inspection object 3
An operator inputs parameters relating to the imaging conditions and parameters relating to the arrangement conditions of the radiation source 1, the array detector 2, and the table 4 to the control device 10 via the input device 11, and the parameters are stored in the memory 8. It is memorized.

When the output signal of the detector 2 is stored in the memory 8, the control device 10 sends a command to the arithmetic device 9 to execute an image reconstruction operation. Note that the image reconstruction operation corresponds to performing the operations from (Equation 3) to (Equation 11) described above. The result of the image reconstruction operation is stored in the memory 8 and output to the output device 12.

Here, when the operator sends a command for performing the composition analysis to the control device 10 via the input device 11, the control device 10 instructs the arithmetic device 9 to perform the composition analysis. To instruct.

The arithmetic unit 9 performs a composition analysis to
From the memory 8, the parameters relating to the imaging conditions, the parameters relating to the arrangement conditions, and the image reconstruction calculation result are called, and the composition analysis is performed.

The results of the composition analysis are stored in the memory 8 and output from the output device 12. When the operator sends a command to the control device 10 via the input device 11 to measure the density resolution, the control device 10
Instructs the arithmetic unit 9 to measure the density resolution. In addition, in order to measure the density resolution, the arithmetic unit 9 calls out parameters relating to imaging conditions, parameters relating to arrangement conditions, and an image reconstruction calculation result from the memory 8 and measures the density resolution. Then, the measurement result of the density resolution is stored in the memory 8 and the output device 12
Output from

FIG. 2 is a flowchart showing the contents of processing for performing composition analysis.

In step 201, the operator inputs the arrangement conditions of the apparatus shown in FIG. Examples of the arrangement conditions include the size S of the radiation source, the distance L between the radiation source and the detector, the distance D between the radiation source and the center of the test object, the length T of the collimator, the interval A in the height direction of the collimator, and the like. Can be

Next, in step 202, the operator sets the inspected object 3 on the table 4.

Next, in step 203, the operator inputs shooting conditions.

The photographing conditions are Δr, Δθ, Δx, and Δy shown in (Equation 7) to (Equation 10) described above.

Next, in step 204, CT imaging is performed, and the collected data is stored in the storage device.

In step 205, the arithmetic unit performs an image reconstruction operation shown in (Equation 3) to (Equation 11). In step 206, the arithmetic unit 9 executes the calculation of (Equation 12), and performs a process of converting the linear absorption coefficient, which is the calculation result of step 205, into a density.

Next, in step 207, the arithmetic unit 9 calculates (Equation 20), and obtains the volume of the rectangular parallelepiped of the cross section of the real object, which corresponds to the pixel of the CT tomographic image.

In step 208, the arithmetic unit 9 creates a frequency distribution graph in which the horizontal axis represents density and the vertical axis represents the number of pixels with reference to the result of step 206.

Next, at step 209, the arithmetic unit 9
However, referring to the processing result in step 207 and the processing result in step 208, the horizontal axis represents the density,
Create a density spectrum where the vertical axis is volume.

Then, in step 210, the arithmetic unit 9
However, the composition analysis is performed by the above-described method with reference to the density spectrum created in step 209.

Next, FIG. 3 is a flowchart showing the contents of processing for measuring the above-mentioned density resolution by the CT apparatus shown in FIG.

First, in step 301, the operator inputs the arrangement conditions of the apparatus shown in FIG. The arrangement conditions include parameters such as the size S of the radiation source, the distance L between the radiation source and the detector, the distance D between the radiation source and the center of the object, the length T of the collimator, and the interval A in the height direction of the collimator. Is mentioned.

Next, in step 302, the operator sets the test object 3 on the table 4.

Next, in step 303, the operator inputs photographing conditions. The photographing conditions are Δr, Δθ, Δx, Δy, etc. shown in (Equation 7) to (Equation 10) described above.

Next, in step 304, CT imaging is performed, and the imaging data is stored in the storage device.

Next, at step 305, the arithmetic unit 9
Performs an image reconstruction operation using (Equation 3) to (Equation 11).

Next, at step 306, the arithmetic unit 9
Executes the calculation of (Equation 12), and performs a process of converting the linear absorption coefficient, which is the processing result in step 305, into a density.

Next, at step 307, the arithmetic unit 9
Performs the calculation shown in (Equation 20), and obtains the volume of a rectangular parallelepiped of the cross section of the real object to be inspected, which corresponds to the pixel of the CT tomographic image.

Next, at step 308, the arithmetic unit 9
However, from the processing result in step 306, a frequency distribution graph is created in which the horizontal axis is the density and the vertical axis is the number of pixels.

Next, at step 309, the arithmetic unit 9
However, referring to the processing result of step 307 and the processing result of step 308, the horizontal axis represents density, and the vertical axis represents volume.
Create a density spectrum.

Then, in step 310, step 3
With reference to the density spectrum created in step 09, the density resolution is measured by the method described above.

As described above, the composition analysis and the measurement of the density resolution can be performed by the apparatus configuration as shown in FIG.
It becomes possible.

[0161]

According to the present invention, it is possible to easily analyze the composition of a subject from a CT image taken by a CT apparatus. Further, according to the present invention, it is possible to accurately measure density resolution, which is one of the performance evaluations of a CT apparatus.

[Brief description of the drawings]

FIG. 1 is a configuration diagram of a CT apparatus according to the present invention.

FIG. 2 is a flowchart for explaining processing content of composition analysis.

FIG. 3 is a flowchart for explaining processing contents at the time of density resolution measurement.

FIG. 4 is an explanatory diagram of parameters of a radiation beam transmitted through an inspection object.

FIG. 5 is an explanatory diagram of a relationship between a material density and a linear absorption coefficient.

FIG. 6 is an explanatory diagram of a relationship between a CT tomographic image and a cross section of a corresponding real object.

FIG. 7 is an explanatory diagram for determining a thickness of an imaging section from a geometric shape of the apparatus.

FIG. 8 is an explanatory diagram of photographing conditions and image reconstruction conditions.

FIG. 9 is an explanatory diagram of a relationship between a real cross section, a CT tomographic image thereof, and a frequency distribution having a density on a horizontal axis.

FIG. 10 is an explanatory diagram of a density spectrum.

FIG. 11 is an explanatory diagram illustrating a method of performing composition analysis from a density spectrum.

FIG. 12 is an explanatory diagram for explaining a method of measuring a density resolution from a density spectrum.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Radiation source, 2 ... (One-dimensional or two-dimensional) array detector, 3 ... Test object, 4 ... Table, 5 ... Driver, 6
... Radiation, 7 ... Signal processing circuit, 8 ... Memory, 9 ... Computing device, 10 ... Control device, 11 ... Input device, 12 ... Output device

──────────────────────────────────────────────────続 き Continuing from the front page (72) Inventor Masahiro Kondo 3-1-1 Kochi-cho, Hitachi-shi, Ibaraki Hitachi, Ltd. Hitachi Plant (56) References JP-A-61-156482 (JP, A) JP-A-4-96875 (JP, A) JP-A-4-369460 (JP, A) (58) Fields investigated (Int. Cl. ⁷ , DB name) G01N 23/00-23/227 G01N 9/24 A61B 6/00-6/14 313 JICST File (JOIS)

Claims (8)

(57) [Claims] An object composed of a plurality of constituents is irradiated with radiation from a plurality of directions, and in each direction, an image reconstruction process is performed on data obtained by detecting radiation transmitted through the object. The line absorption coefficient for each pixel constituting the cross-sectional image of the object is determined for each pixel, and the density uniquely corresponding to the line absorption coefficient is determined for each pixel, and the object is uniquely identified for each pixel. Assuming that the volume element is divided into three-dimensional volume elements, the number of volume elements corresponding to pixels having a certain density and the volume element 1
The volume of each of the volume elements is determined, and the number of the volume elements is multiplied by the volume of the one volume element to obtain a volume for the certain density. A method for analyzing the composition of an object for which a density spectrum is to be obtained, showing a distribution state of the volume with respect to 2. The method according to claim 1, wherein the volume amount of one volume element is determined by a “thickness” determined by a parameter including at least dimensions of a collimator provided in a radiation source for irradiating radiation and a detector for detecting radiation. The area is determined by multiplying by an “area” determined by a parameter including at least the conditions of the image reconstruction processing. Further, the “thickness (H)” is the height of the source and the height of the collimator provided in the detector. A, a distance D between the source and the center of the object, and a distance L between the source and the detector are obtained by a predetermined rule, and the “area (Sr)” is the result of the image reconstruction processing. The area of the pixel (Si) determined for display and Sr are determined by “Si = K · Sr (K is a constant determined in advance during image reconstruction processing and data detection by the detector)”. A method for analyzing the composition of an object characterized by that . 3. The method according to claim 1, wherein the density in the density spectrum is a, the volume with the density a as a parameter is V (a), and V (a) increases in the direction of increasing a. ) Is observed, a distribution having one unimodal shape is regarded as volume distribution data for one component, and the maximum value of the distribution having the unimodal shape is defined as the volume of the component, and each component is regarded as a volume. A method for analyzing the composition of an object, comprising determining a volume of the object. 4. The method for analyzing the composition of an object according to claim 3, further comprising obtaining a sum of the volumes of the respective constituent substances to obtain a volume of the object. 5. The method according to claim 1, wherein
Further, in the density spectrum, the density is a and the density a is a parameter .
V (a) is the volume of the meter, and the volume V is the density a
The mass w (a), which is a value multiplied by (a), is obtained,
When the degree a is a parameter,
W (a), which is the distribution of mass with respect to each other, is obtained . When w (a) is observed in the direction in which
The distribution having a peak shape is calculated by
Regarding distribution data, the maximum of the distribution having the unimodal shape
Using the value as the mass of the constituent substance, calculate the mass of each constituent substance.
A method for analyzing the composition of an object, comprising: 6. The method according to claim 5, further comprising: obtaining a total sum of masses of the respective constituent substances to obtain a mass of the object.
A method for analyzing the composition of an object, characterized in that: 7. An apparatus comprising a plurality of constituent substances,
Sources that emit radiation from several directions, and in each direction,
A detector for detecting radiation transmitted through an object, and the detector
Function to perform image reconstruction processing on the data detected by
At least a computing device and a computation result on the display screen
A display device having at least a display function, wherein the arithmetic unit performs image reconstruction processing to cut off an object.
The line absorption coefficient for each pixel constituting the plane image is calculated for each pixel.
, And the density uniquely corresponding to the linear absorption coefficient
A means for obtaining each pixel and a three-dimensional body so that an object is uniquely associated with each pixel.
Has a certain density when it is assumed to be divided into product elements
Number of volume elements and volume element 1 corresponding to the pixel
The volume of each of the pieces is determined, and the number of
Multiply by the volume of one product element to obtain
Calculate the volume, and the distribution state of the volume with respect to the change in density
And means for obtaining a density spectrum.
An apparatus for analyzing the composition of a target object. 8. The method according to claim 1, wherein
Further, in the density spectrum, the density is a and the density a is a parameter .
Let V (a) be the volume of the meter, and the direction in which a increases
Then, when V (a) is observed, the maximum value of V (a) is obtained,
The difference in density corresponding to half the volume of the maximum value is calculated as V
The value obtained by dividing the maximum value of (a) by the density a is
Characterized by a density resolution indicating the degree of resolution
Elephant composition analysis method.