Patent Application
20240016465
The present application claims priority from Japanese Patent Application No. 2022-112634, filed on Jul. 13, 2022, the entire disclosure of which is incorporated herein by reference.
The present disclosure relates to a radiation image processing device, a radiation image processing method, and a radiation image processing program which quantify a composition of a subject by using a radiation image.
In the related art, various methods of deriving a composition of a human body, such as fat and muscle, have been proposed. For example, JP2021-058363A proposes a method of, for each of two radiation images acquired by radiation transmitted through a subject and having different energy distributions from each other, deriving a body thickness of the subject as a first body thickness and a second body thickness, and deriving a composition ratio of the subject, such as muscle and fat, based on the first body thickness and the second body thickness. In addition, it is also possible to derive a composition image in which a thickness of the composition is a pixel value, based on the derived composition ratio.
Here, the radiation emitted from a radiation source has an energy distribution. An attenuation coefficient of the radiation in the subject is dependent on the energy of the radiation, and the attenuation coefficient has a characteristic of being less as an energy component is higher. For this reason, a phenomenon called beam hardening occurs in which the radiation loses a relatively large amount of low-energy components in the process of transmitting a substance, and the proportion of high-energy components is increased. A degree of beam hardening depends on a fat thickness and a muscle thickness in the subject. Therefore, in the method disclosed in JP2021-058363A, the first body thickness and the second body thickness are derived by using attenuation coefficients μf(tf, tm) and μm(tf, tm) which is an attenuation coefficient μf of the fat and an attenuation coefficient μm of the muscle represented as non-linear functions of a fat thickness tf and a muscle thickness tm.
However, in the method disclosed in JP2021-058363A, the attenuation coefficient depends on both the fat thickness and the muscle thickness. For this reason, in an image of one composition, the contrast is decreased due to an influence of the beam hardening of the other composition.
The present disclosure has been made in view of the above circumstances, and is to enable derivation of a composition image having a high image quality for a plurality of compositions in a subject.
The present disclosure relates to a radiation image processing device comprising at least one processor, in which the processor derives, based on at least one radiation image based on radiation that is transmitted through a subject including a plurality of compositions, a thickness of at least one composition of the plurality of compositions for each pixel of the radiation image, and derives a composition image for the at least one composition by using an attenuation coefficient based only on the thickness of the at least one composition.
Note that, in the radiation image processing device according to the present disclosure, the processor may acquire two radiation images based on radiation that is transmitted through the subject and has different energy distributions from each other, derive body thicknesses of the subject as a first body thickness and a second body thickness, respectively, for each pixel for each of the two radiation images by using an attenuation coefficient according to an order in which the radiation is transmitted through the plurality of compositions, and derive the thickness of the at least one composition based on the first body thickness and the second body thickness.
In addition, in the radiation image processing device according to the present disclosure, the processor may derive the thickness of the at least one composition by regarding the subject as a model that is divided such that the plurality of compositions each are grouped together to have one thickness.
In addition, in the radiation image processing device according to the present disclosure, the processor may derive the thickness of the at least one composition based on a difference between the first body thickness and the second body thickness.
In addition, in the radiation image processing device according to the present disclosure, the processor may change a thickness of the composition and an attenuation coefficient for each composition to derive the first body thickness and the second body thickness by using the changed thickness of the composition and the changed attenuation coefficient for each composition, and derive the thickness of the at least one composition such that a difference between the first body thickness and the second body thickness is equal to or less than a predetermined threshold value.
In addition, in the radiation image processing device according to the present disclosure, the processor may remove scattered ray components included in the two radiation images, and derive the thickness of the at least one composition based on the two radiation images from which the scattered ray components are removed.
In addition, in the radiation image processing device according to the present disclosure, the two radiation images may be acquired by two radiation detectors stacked on each other by simultaneously irradiating the two radiation detectors with the radiation transmitted through the subject.
In addition, in the radiation image processing device according to the present disclosure, the processor may display the composition image on a display.
In addition, in the radiation image processing device according to the present disclosure, the plurality of compositions may be muscle and fat.
In addition, in the radiation image processing device according to the present disclosure, the plurality of compositions may be a bone part and a soft part.
In addition, in the radiation image processing device according to the present disclosure, the plurality of compositions may be a contrast agent injected into the subject and a tissue other than the contrast agent.
The present disclosure relates to a radiation image processing method comprising deriving, based on at least one radiation image based on radiation that is transmitted through a subject including a plurality of compositions, a thickness of at least one composition of the plurality of compositions for each pixel of the radiation image, and deriving a composition image for the at least one composition by using an attenuation coefficient based only on the thickness of the at least one composition.
The present disclosure relates to a radiation image processing program causing a computer to execute a procedure of deriving, based on at least one radiation image based on radiation that is transmitted through a subject including a plurality of compositions, a thickness of at least one composition of the plurality of compositions for each pixel of the radiation image, and a procedure of deriving a composition image for the at least one composition by using an attenuation coefficient based only on the thickness of the at least one composition.
According to the present disclosure, it is possible to derive the composition image having the high image quality.
In the following description, an embodiment of the present disclosure will be described with reference to the drawings.
The imaging apparatus 1 is an imaging apparatus for performing energy subtraction by a so-called one-shot method for converting radiation, such as X-rays, emitted from a radiation source 3 and transmitted through a subject H into energy and irradiating a first radiation detector 5 and a second radiation detector 6 with the converted radiation. During the imaging, as shown in
As a result, in the first radiation detector 5, a first radiation image G1 of the subject H by low-energy radiation also including so-called soft rays is acquired. In addition, in the second radiation detector 6, a second radiation image G2 of the subject H by high-energy radiation from which the soft rays are removed is acquired. The first and second radiation images G1 and G2 are input to the radiation image processing device 10.
Note that, in the present embodiment, a scattered ray removal grid that removes a scattered ray component of the radiation transmitted through the subject H is not used during the imaging of the subject H. Therefore, the first radiation image G1 and the second radiation image G2 also include a primary ray component and the scattered ray component of the radiation transmitted through the subject H.
Here, the energy subtraction processing is processing of generating an image in which different tissues (for example, a soft part and a bone part) in the subject are extracted by using two radiation images obtained by irradiating the subject with two types of radiation having different energy distributions by using the fact that an attenuation amount of the transmitted radiation differs depending on the substance constituting the subject. The imaging apparatus 1 in the radiography system according to the present embodiment can perform the energy subtraction processing. However, in the present embodiment, since a composition image of the subject is derived, the detailed description of the energy subtraction processing will be omitted.
The first and second radiation detectors 5 and 6 can perform recording and reading-out of the radiation image repeatedly. A so-called direct-type radiation detector that directly receives emission of the radiation and generates an electric charge may be used, or a so-called indirect-type radiation detector that converts the radiation into visible light and then converts the visible light into an electric charge signal may be used. In addition, as a method for reading out a radiation image signal, it is desirable to use a so-called thin film transistor (TFT) readout method in which the radiation image signal is read out by turning a TFT switch on and off, or a so-called optical readout method in which the radiation image signal is read out by emission of read out light. However, other methods may also be used without being limited to these methods.
Then, the radiation image processing device according to the present embodiment will be described. First, with reference to
The storage 13 is realized by a hard disk drive (HDD), a solid state drive (SSD), a flash memory, and the like. A radiation image processing program 12 installed in the radiation image processing device 10 is stored in the storage 13 as a storage medium. The CPU 11 reads out the radiation image processing program 12 from the storage 13, expands the read out radiation image processing program 12 to the memory 16, and executes the expanded radiation image processing program 12.
The radiation image processing program 12 is stored in a storage device of the server computer connected to the network or in a network storage in a state of being accessible from the outside, and is downloaded and installed in the computer that configures the radiation image processing device 10 in response to the request. Alternatively, the radiation image processing program 12 is distributed in a state of being recorded on a recording medium, such as a digital versatile disc (DVD) or a compact disc read only memory (CD-ROM), and is installed in the computer that configures the radiation image processing device 10 from the recording medium.
Then, a functional configuration of the radiation image processing device according to the present embodiment will be described.
The image acquisition unit 21 acquires the first radiation image G1 and the second radiation image G2 of the subject H from the first and second radiation detectors 5 and 6 by causing the imaging apparatus 1 to perform the energy subtraction imaging of the subject H. The imaging conditions are set as described above in a case of the acquisition of the first radiation image G1 and the second radiation image G2.
The scattered ray removal unit 22 removes the scattered ray component generated by the scattering of the radiation in the subject H, which is included in the first and second radiation images G1 and G2. As a method for removing the scattered ray component, for example, any method disclosed in JP2014-207958A, can be used. The method disclosed in JP2014-207958 is a method for acquiring a characteristic of a grid that is assumed to be used to remove the scattered rays during the imaging of the radiation image, deriving the scattered ray component included in the radiation image based on the characteristic, and performing scattered ray removal processing by using the derived scattered ray component. Note that, in the first and second radiation images G1 and G2 in the subsequent processing, the scattered ray components are removed.
The body thickness derivation unit 23 derives the body thicknesses of the subject H, as a first body thickness and a second body thickness, respectively, for each pixel of each of the first and second radiation images G1 and G2 from which the scattered ray components are removed. Specifically, the body thickness derivation unit 23 derives a first body thickness t1 of the subject H by assuming that a brightness distribution of the first radiation image G1 coincides with the body thickness distribution of the subject H, and converting the pixel value of the first radiation image G1 into the thickness by using an attenuation coefficient of the muscle of the subject H. In addition, the body thickness derivation unit 23 derives a second body thickness t2 of the subject H by assuming that a brightness distribution of the second radiation image G2 coincides with the body thickness distribution of the subject H, and converting the pixel value of the second radiation image G2 into the thickness by using the attenuation coefficient of the muscle of the subject H.
Here, the radiation emitted from the radiation source 3 has an energy distribution, an attenuation coefficient of the radiation in the subject H is also dependent on the energy of the radiation, and the attenuation coefficient has a characteristic of being less as the energy component is higher. For this reason, a phenomenon called beam hardening occurs in which the radiation loses a relatively large amount of low-energy components in the process of transmitting the substance, and the proportion of high-energy components is increased. A degree of beam hardening depends on a fat thickness tf and a muscle thickness tm in the subject H. The degree of beam hardening also depends on an order of the substances through which the radiation is transmitted in the subject H. That is, in a case in which the radiation is transmitted through fat first, the attenuation coefficient of the fat depends only on the fat thickness tf, but the attenuation coefficient of the muscle through which the radiation is transmitted next to the fat also depends on the fat thickness tf in addition to the muscle thickness tm. Therefore, the attenuation coefficient μf of the fat can be defined as μf(tf) as a non-linear function of the fat thickness tf, and the attenuation coefficient μm of the muscle can be defined as μm(tf, tm) as non-linear functions of the fat thickness tf and the muscle thickness tm.
Here, a soft tissue of the subject H includes muscle, fat, blood, and water. In the present embodiment, a tissue other than the fat in the soft tissue is regarded as the muscle. That is, in the present embodiment, it is assumed that the muscle includes non-fat tissue including blood and water.
As in the present embodiment, the first and second radiation images G1 and G2 acquired by the radiation having two different energy distributions correspond to a low-energy image and a high-energy image, respectively. Therefore, in the present embodiment, the attenuation coefficient of the fat of the first radiation image G1, which is the low-energy image, can be represented as μlf(tf), and the attenuation coefficient of the muscle can be represented as μlm(tf, tm). In addition, the attenuation coefficient of the fat of the second radiation image G2, which is the high-energy image, can be represented as μhf(tf), and the attenuation coefficient of the muscle can be represented as μhm(tf, tm).
In addition, the pixel value G1(x,y) of each pixel of the first radiation image G1, which is the low-energy image, and the pixel value G2(x,y) of each pixel of the second radiation image G2, which is the high-energy image, are represented by Expression (1) and Expression (2) by using the fat thickness tf(x,y), the muscle thickness tm(x,y), and the attenuation coefficients μlf(x,y), μhf(x,y), μlm(x,y), and μhm(x,y) at the corresponding pixel positions. Note that, in Expression (1) and Expression (2), the description of (x,y) is omitted.
G1=μlf×tf+μlm×tm (1)
G2=μhf×tf+μhm×tm (2)
As described above, in the present embodiment, in a case in which the first body thickness t1 and the second body thickness t2 are derived, the pixel values of the first radiation image G1 and the second radiation image G2 are converted into the thicknesses by using the attenuation coefficient of the muscle in the subject H. Therefore, in the present embodiment, the body thickness derivation unit 23 derives the first body thickness t1 and the second body thickness t2 by Expression (3) and Expression (4). Note that the first body thickness t1 and the second body thickness t2 are derived in each pixel (x,y) of the first and second radiation images G1 and G2, but the description of (x,y) is omitted in Expression (3) and Expression (4).
t1=G1/μlm (3)
t2=G2/μhm (4)
In a case in which the subject H includes only the muscle at the pixel positions at which the first and second body thicknesses t1 and t2 are derived, the first body thickness t1 and the second body thickness t2 coincide with each other. However, in the actual subject H, the muscle and the fat are both included at the same pixel positions of the first and second radiation images G1 and G2. Therefore, the first and second body thicknesses t1 and t2 derived by Expression (3) and Expression (4) do not coincide with the actual body thickness of the subject H. In addition, in the first body thickness t1 derived from the first radiation image G1, which is the low-energy image, and the second body thickness t2 derived from the second radiation image G2, which is the high-energy image, the first body thickness t1 is a larger value than the second body thickness t2. For example, as shown in
Here, in the present embodiment, the attenuation coefficient in consideration of the influence of the beam hardening according to the order in which the radiation is transmitted through the fat and the muscle is used. On the other hand, in the subject H, since the fat and the muscle are mixed, the fat and the muscle having various thicknesses are alternately present on a transmission path of the radiation. However, even in a case in which the disposition of the muscle and the fat is changed under the condition that the muscle thickness and the fat thickness of the entire subject H are fixed, the attenuation coefficient for each energy is decided depending on the substance, and thus the radiation spectrum transmitted through the entire subject H is the same.
For this reason, in the present embodiment, the thickness of the composition is obtained by regarding the subject H as a model that is divided into two parts such that the fat and the muscle each are grouped together to have one thickness.
The composition thickness derivation unit 24 changes the thickness of the composition and the attenuation coefficient for each composition, causes the body thickness derivation unit 23 to derive the first body thickness t1 and the second body thickness t2 by using the changed thickness of the composition and the changed attenuation coefficient for each composition, and derives the thickness of the composition in which a difference between the first body thickness t1 and the second body thickness t2 is equal to or less than a predetermined threshold value Th1, that is, the fat thickness tf and the muscle thickness tm.
Here, the first body thickness t1 is an addition value of the fat thickness tf and the muscle thickness tm, that is, t1=tf+tm. Since tm=t1−tf, Expression (1) can be transformed into Expression (5). Note that the description of (x,y) is also omitted in Expression (5) to Expression (7).
G1=μlf×tf+μlm×(t1−tf) (5)
In a case in which Expression (5) is solved for t1, Expression (6) is obtained.
t1={G1+(μlm−μlf)×tf}/μlm (6)
In addition, since the second body thickness is t2=tf+tm, in a case in which Expression (2) is transformed in the same manner as in Expression (5) and solved for t2, Expression (7) is obtained.
t2={G2+(μhm−μhf)×tf}/μhm (7)
The composition thickness derivation unit 24 derives the fat thickness tf such that the difference between t1 and t2 is small, preferably t1=t2. However, since the attenuation coefficients μlf and μhf are non-linear functions of the fat thickness tf, and μlm and μhm are non-linear functions of the fat thickness tf and the muscle thickness tm, the fat thickness tf cannot be derived algebraically from Expression (6) and Expression (7). Therefore, in the present embodiment, the composition thickness derivation unit 24 changes the fat thickness tf and the attenuation coefficients μlf, μhf, μlm, and μhm and causes the body thickness derivation unit 23 to derive the first body thickness t1 and the second body thickness t2 by using the changed fat thickness tf and the changed attenuation coefficients μlf, μhf, μlm, and μhm. Then, the composition thickness derivation unit 24 derives the fat thickness tf in which the difference between the first body thickness t1 and the second body thickness t2 is equal to or less than the predetermined threshold value Th1, that is, |t1−t2|≤Th1. Note that the threshold value Th1 is preferably as small as possible, and more preferably Th1=0.
Specifically, in a case in which tf=0 and t1=t2, all the pixels (x,y) are the muscle. Further, in a case in which tf=0 and t1≠t2, the composition thickness derivation unit 24 derives the fat thickness tf by searching for the fat thickness tf such that |t1−t2|≤Th1 while changing the fat thickness tf. Moreover, the muscle thickness tm is derived by subtracting the fat thickness tf from the first body thickness t1 or the second body thickness t2.
The composition image derivation unit 25 derives the composition image for each of the fat and the muscle, that is, the fat image and the muscle image by using the attenuation coefficient based only on the fat thickness tf and the muscle thickness tm derived by the composition thickness derivation unit 24. Specifically, the fat image Gf and the muscle image Gm are derived by Expression (8) and Expression (9). Here, μf(tf) is the attenuation coefficient of the fat based only on the fat thickness tf, and μm(tm) is the attenuation coefficient of the muscle based only on the muscle thickness tm. That is, μf(tf) is an attenuation coefficient that depends only on the fat thickness tf without the influence of the beam hardening due to the muscle. In addition, μm(tm) is an attenuation coefficient that depends only on the muscle thickness tm without the influence of the beam hardening due to the fat. Note that the description of (x,y) is also omitted in Expression (8) and Expression (9).
Gf=I0×exp(−μf(tf)·tf) (8)
Gm=I0×exp(−μm(tm)·tm) (9)
In Expression (8) and Expression (9), I0 is the reaching dose I0 of the radiation emitted from the radiation source 3 and reaching the first radiation detector 5 on the side close to the radiation source 3 in a case in which the radiation source 3 is driven to emit the radiation to the radiation detector 5 in a state in which the subject H is not present. The reaching dose I0 is represented by Expression (10). In Expression (10), mAs is a dose and kV is a tube voltage. Here, F is a linear or non-linear function that represents a radiation dose that reaches the radiation detector 5 in a case in which the dose (for example, 1 mAs), which is a standard, is emitted to the radiation detector 5 at the SID (for example, 100 cm), which is a standard, in a state in which the subject H is not present. F is changed depending on the tube voltage. Also, since the reaching dose I0 is derived for each pixel of the radiation image G0 acquired by the radiation detector 5, (x,y) represents the pixel position of each pixel.
I0(x,y)=mAs×F(kV)/SID2 (10)
Note that a dose sensor for detecting the reaching dose may be provided in the radiation detector 5, and the reaching dose I0 may be acquired by the dose sensor. In this case, the dose sensor may be provided in the radiation detector 5 by substituting a part of the image sensor of the radiation detector 5, and the dose sensor may be provided outside a detection surface of the image in the radiation detector 5.
The display controller 26 displays the fat image Gf and the muscle image Gm derived by the composition image derivation unit 25 on the display 14.
Then, processing performed in the present embodiment will be described.
Subsequently, the composition thickness derivation unit 24 determines whether or not |t1−t2|≤Th1 (step ST5), changes the fat thickness tf in a case in which a negative determination is made in step ST5 (step ST6), and returns to step ST4. Accordingly, the processing of steps ST4 to ST6 is repeated. In a case in which a positive determination is made in step ST5, the composition thickness derivation unit 24 determines the fat thickness tf to be the fat thickness in a case in which a positive determination is made in step ST5 (step ST7). Further, the composition thickness derivation unit 24 derives the muscle thickness tm (step ST8). Then, the composition thickness derivation unit 24 determines whether or not the fat thickness tf and the muscle thickness tm of all the pixels are derived (composition thickness derivation of all the pixels: step ST9), and returns to step ST3 in a case in which a negative determination is made in step ST9. As a result, the processing of steps ST3 to ST9 is repeated. In a case in which a positive determination is made in step ST9, the composition image derivation unit 25 derives the fat image Gf and the muscle image Gm (composition image derivation: step ST10), and the display controller 26 displays the fat image Gf and the muscle image Gm on the display 14 (composition image display: step ST11), and the processing is terminated.
As described above, in the present embodiment, as shown in Expression (8) and Expression (9), the fat image Gf and the muscle image Gm are derived by using the attenuation coefficient μf(tf) of the fat based only on the fat thickness tf and the attenuation coefficient μm(tm) the muscle based only on the muscle thickness tm. Therefore, in a case of deriving the fat image Gf, the influence of the beam hardening due to the muscle can be removed, and in a case of deriving the muscle image Gm, the influence of the beam hardening due to the fat can be removed. Therefore, it is possible to prevent a decrease in contrast of a plurality of composition images due to the influence of the beam hardening due to other compositions, and as a result, it is possible to derive the composition image having a high image quality in which the contrast is improved.
In addition, the body thicknesses of the subject H are derived as the first body thickness t1 and the second body thickness t2 for each pixel of each of the first and second radiation images G1 and G2 by using the attenuation coefficient according to the order in which the radiation is transmitted through the fat and the muscle, and the composition image of the subject H is derived based on the difference between the first body thickness t1 and the second body thickness t2. Therefore, it is possible to derive the first body thickness t1, the second body thickness t2, and further the fat ratio in consideration of the influence of the beam hardening according to the order of the substances through which the radiation is transmitted in the subject H. Therefore, according to the present embodiment, it is possible to derive the composition thickness in the subject with high accuracy.
In particular, in the present embodiment, the composition is obtained by regarding the subject H as the model that is divided into two parts such that the fat and the muscle each are grouped together to have one thickness. Therefore, as compared with a case in which the fat thickness, the muscle thickness, and the disposition thereof are simultaneously obtained in a case in which the composition is derived by performing the repetitive calculation, it is possible to prevent the desired fat thickness tf from being diverged, an error from the actual fat thickness being large, and the processing time being long.
Note that, in the embodiment described above, the fat thickness tf is derived and then the muscle thickness tm is derived, but the muscle thickness tm may be derived and then the fat thickness tf may be derived. In this case, tf=t1−tm, and in a case in which t1 is derived based on Expression (1), Expression (11) is obtained. Further, in a case in which Expression (2) is solved for t2, Expression (12) is obtained.
t1={G1+(μlf−μlm)×tm}/μlf (11)
t2={G2+(μhf−μhm)×tm}/μhf (12)
In this case, the composition thickness derivation unit 24 derives the muscle thickness tm by searching for tm in which the difference between the first body thickness t1 and the second body thickness t2 is equal to or less than a predetermined threshold value Th2, that is, |t1−t21|≤Th2, and derives the fat thickness tf by subtracting the derived muscle thickness tm from the first body thickness t1 or the second body thickness t2.
Note that, in the embodiment described above, the fat image Gf and the muscle image Gm may be used to quantify a fat mass and a muscle mass. In this case, as shown in Expression (13), a muscle mass M(x,y) (g/cm2) for each pixel of a muscle image Gm need only be derived by multiplying each pixel (x,y) of the muscle image Gm by a coefficient C1(x,y) representing a relationship between a predetermined pixel value and the muscle mass. In addition, as shown in Expression (14), a fat mass F(x,y) (g/cm2) for each pixel of a fat image Gf need only be derived by multiplying each pixel (x,y) of the fat image Gf by a coefficient C2(x,y) representing a relationship between a predetermined pixel value and the fat mass. Note that the display controller 26 may display the distributions of the derived muscle mass and fat mass on the display 14.
M(x,y)=C1(x,y)×Gm(x,y) (13)
F(x,y)=C2(x,y)×Gf(x,y) (14)
In addition, in the embodiment described above, it is assumed that the radiation is transmitted through the fat first, but the present disclosure is not limited to this. The composition may be derived on the assumption that the radiation is transmitted through the muscle first. In this case, the attenuation coefficient μm of the muscle can be defined as μm(tm) as the non-linear function of the muscle thickness tm, and the attenuation coefficient μf of the fat can be defined as μf(tf, tm) as the non-linear functions of the fat thickness tf and the muscle thickness tm. Therefore, the attenuation coefficient of the fat for the first radiation image G1, which is the low-energy image, can be represented as μlf(tf, tm), and the attenuation coefficient of the muscle can be represented as μlm(tm). In addition, the attenuation coefficient of the fat for the second radiation image G2, which is the high-energy image, can be represented as μhf(tf, tm), and the attenuation coefficient of the muscle can be represented as μhm(tm).
In addition, in the embodiment described above, the first body thickness t1 and the second body thickness t2, and further the fat image Gf and the muscle image Gm, are derived by using the attenuation coefficient in consideration of the order of the substances through which the radiation is transmitted in the subject H, but the present disclosure is not limited to this. As disclosed in JP2021-058363A, the attenuation coefficients μf(tf, tm) and μm(tf, tm) represented as non-linear functions of the fat thickness tf and the muscle thickness tm may be used.
In addition, in the embodiment described above, the fat thickness tf and the muscle thickness tm are derived such that the first body thickness t1 and the second body thickness t2 derived by the body thickness derivation unit 23 coincide with each other, but the present disclosure is not limited to this. The fat thickness tf and the muscle thickness tm may be derived by using any other method.
Further, in the embodiment described above, the fat thickness tf and the muscle thickness tm are derived, and the fat image Gf and the muscle image Gm are derived, but the present disclosure is not limited to this. At least one of the fat thickness tf or the muscle thickness tm may be derived, and at least one of the fat image Gf or the muscle image Gm may be derived.
In addition, in the embodiment described above, the composition images of the fat and the muscle of the subject H are derived, but the present disclosure is not limited to this. The technology of the present disclosure can also be applied in a case in which the composition images of the bone part of the subject H and the soft part other than the bone part are derived. In this case as well, in a case of deriving the first body thickness t1 and the second body thickness t2, the attenuation coefficient according to the order in which the radiation is transmitted through the bone part and the soft part need only be used. Here, in a case in which the radiation is transmitted through the soft part in the subject H first, an attenuation coefficient μs of the soft part can be defined as μs(ts) as a non-linear function of a soft part thickness ts, and an attenuation coefficient μb of the bone part can be defined as μb(ts, tb) as non-linear functions of the soft part thickness ts and a bone part thickness tb.
In addition, the composition for which the composition image is obtained is not limited to the fat and the muscle, and the bone part and the soft part. The technology of the present disclosure can also be applied in a case of deriving composition images of an artificial object, such as artificial bone or silicon embedded in a human body, and a human body tissue, or composition images of fat and mammary gland in a breast. In addition, in a case in which the imaging is performed by injecting the contrast agent into the subject H, the technology of the present disclosure can also be applied in a case in which composition images of the contrast agent and a tissue other than the contrast agent is derived.
Further, in the embodiment described above, the scattered ray components are removed from the first and second radiation images G1 and G2 by the scattered ray removal unit 22, but the present disclosure is not limited to this. For example, in a case in which the scattered ray removal grid is used during the imaging, processing of deriving the composition image may be performed without removing the scattered ray components from the first and second radiation images G1 and G2. In this case, in the radiation image processing device according to the present embodiment, the scattered ray removal unit 22 is not required.
Further, in the embodiment described above, the first and second radiation images G1 and G2 are acquired by the one-shot method, but the first and second radiation images G1 and G2 may be acquired by a so-called two-shot method in which the imaging is performed twice using only one radiation detector. In a case of the two-shot method, a position of the subject H included in the first radiation image G1 and the second radiation image G2 may shift due to a body movement of the subject H. Therefore, in the first radiation image G1 and the second radiation image G2, it is preferable to perform the processing according to the present embodiment after registration of the subject is performed.
In addition, in the embodiment described above, the processing of deriving the composition image is performed by using the radiation image acquired in the system that captures the radiation images G1 and G2 of the subject H using the first and second radiation detectors 5 and 6, but it is needless to say that the technology of the present disclosure can be applied even in a case in which the first and second radiation images G1 and G2 are acquired using an accumulative phosphor sheet instead of the radiation detector. In this case, the first and second radiation images G1 and G2 need only be acquired by stacking two accumulative phosphor sheets, emitting the radiation transmitted through the subject H, accumulating and recording radiation image information of the subject H in each of the accumulative phosphor sheets, and photoelectrically reading the radiation image information from each of the accumulative phosphor sheets. Note that the two-shot method may also be used in a case in which the first and second radiation images G1 and G2 are acquired by using the accumulative phosphor sheet.
In addition, the radiation in the embodiment described above is not particularly limited, and α-rays or γ-rays can be applied in addition to X-rays.
In addition, in the embodiment described above, for example, various processors shown below can be used as the hardware structures of processing units that execute various pieces of processing, such as the image acquisition unit 21, the scattered ray removal unit 22, the body thickness derivation unit 23, the composition thickness derivation unit 24, the composition image derivation unit 25, and the display controller 26 of the radiation image processing device 10. As described above, the various processors include, in addition to the CPU that is a general-purpose processor which executes software (program) and functions as various processing units, a programmable logic device (PLD) that is a processor whose circuit configuration can be changed after manufacture, such as a field programmable gate array (FPGA), and a dedicated electrical circuit that is a processor having a circuit configuration which is designed for exclusive use in order to execute a specific processing, such as an application specific integrated circuit (ASIC).
One processing unit may be configured by one of these various processors, or may be configured by a combination of two or more processors of the same type or different types (for example, a combination of a plurality of FPGAs or a combination of the CPU and the FPGA). In addition, a plurality of the processing units may be configured by one processor.
As an example of configuring the plurality of processing units by one processor, first, as represented by a computer of a client, a server, and the like there is an aspect in which one processor is configured by a combination of one or more CPUs and software and this processor functions as a plurality of processing units. Second, as represented by a system on chip (SoC) or the like, there is an aspect of using a processor that realizes the function of the entire system including the plurality of processing units by one integrated circuit (IC) chip. In this way, as the hardware structure, the various processing units are configured by using one or more of the various processors described above.
Further, as the hardware structures of these various processors, more specifically, it is possible to use an electrical circuit (circuitry) in which circuit elements, such as semiconductor elements, are combined.
The supplementary notes of the present disclosure will be described below.
Supplementary Note 1
A radiation image processing device comprising at least one processor, in which the processor derives, based on at least one radiation image based on radiation that is transmitted through a subject including a plurality of compositions, a thickness of at least one composition of the plurality of compositions for each pixel of the radiation image, and derives a composition image for the at least one composition by using an attenuation coefficient based only on the thickness of the at least one composition.
Supplementary Note 2
The radiation image processing device according to Supplementary Note 1, in which the processor acquires two radiation images based on radiation that is transmitted through the subject and has different energy distributions from each other, derives body thicknesses of the subject as a first body thickness and a second body thickness, respectively, for each pixel for each of the two radiation images by using an attenuation coefficient according to an order in which the radiation is transmitted through the plurality of compositions, and derives the thickness of the at least one composition based on the first body thickness and the second body thickness.
Supplementary Note 3
The radiation image processing device according to Supplementary Note 2, in which the processor derives the thickness of the at least one composition by regarding the subject as a model that is divided such that the plurality of compositions each are grouped together to have one thickness.
Supplementary Note 4
The radiation image processing device according to Supplementary Note 2 or 3, in which the processor derives the thickness of the at least one composition based on a difference between the first body thickness and the second body thickness.
Supplementary Note 5
The radiation image processing device according to any one of Supplementary Notes 2 to 4, in which the processor changes a thickness of the composition and an attenuation coefficient for each composition to derive the first body thickness and the second body thickness by using the changed thickness of the composition and the changed attenuation coefficient for each composition, and derives the thickness of the at least one composition such that a difference between the first body thickness and the second body thickness is equal to or less than a predetermined threshold value.
Supplementary Note 6
The radiation image processing device according to any one of Supplementary Notes 2 to 5, in which the processor removes scattered ray components included in the two radiation images, and derives the thickness of the at least one composition based on the two radiation images from which the scattered ray components are removed.
Supplementary Note 7
The radiation image processing device according to any one of Supplementary Notes 2 to 6, in which the two radiation images are acquired by two radiation detectors stacked on each other by simultaneously irradiating the two radiation detectors with the radiation transmitted through the subject.
Supplementary Note 8
The radiation image processing device according to any one of Supplementary Notes 1 to 7, in which the processor displays the composition image on a display.
Supplementary Note 9
The radiation image processing device according to any one of Supplementary Notes 1 to 8, in which the plurality of compositions are muscle and fat.
Supplementary Note 10
The radiation image processing device according to any one of Supplementary Notes 1 to 8, in which the plurality of compositions are a bone part and a soft part.
Supplementary Note 11
The radiation image processing device according to any one of Supplementary Notes 1 to 8, in which the plurality of compositions are a contrast agent injected into the subject and a tissue other than the contrast agent.
Supplementary Note 12
A radiation image processing method comprising deriving, based on at least one radiation image based on radiation that is transmitted through a subject including a plurality of compositions, a thickness of at least one composition of the plurality of compositions for each pixel of the radiation image, and deriving a composition image for the at least one composition by using an attenuation coefficient based only on the thickness of the at least one composition.
Supplementary Note 13
A radiation image processing program causing a computer to execute a procedure of deriving, based on at least one radiation image based on radiation that is transmitted through a subject including a plurality of compositions, a thickness of at least one composition of the plurality of compositions for each pixel of the radiation image, and a procedure of deriving a composition image for the at least one composition by using an attenuation coefficient based only on the thickness of the at least one composition.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2022-112634 | Jul 2022 | JP | national |
