JPH01106278A - Method and device for processing x-ray image - Google Patents

Abstract

PURPOSE:To effectively attenuate the granular noise of an X-ray image and to suppress the deterioration of picture quality performance by attenuating a space frequency component higher than a space frequency component included in vignette masking density obtained by averaging image density. CONSTITUTION:An original photograph 1 on which the X-ray image information of an object is recorded is scanned by laser beams projected from a laser light source 4 and the laser beams modulated at its intensity by the density of the X-ray image are detected by a photomultiplier 11 through a converging body 10. The output of the photomultiplier 11 is inputted to an operation part 18 through an amplifier 16 and an A/D converter 17. The operation part 18 averages the image density in a prescribed range to find out the vignette masking density and attenuates a space frequency component higher than the one included in the vignette masking density from the original image density. The obtained image density is stored in a memory 19 and displayed on an image display device 20 at need.

Description

[Detailed Description of the Invention] (Industrial Application Field) The present invention relates to an image obtained by irradiating a subject with X-rays (hereinafter referred to as "
When copying an X-ray image (hereinafter referred to as "X-ray image"), the density of the X-ray image recorded on the original photograph (hereinafter referred to as "original image density") is This invention relates to image processing applied to the signal representing the original image density after reading the original image density, particularly an X-ray image processing method for improving the graininess of an X-ray image reproduced as a visible image in a photocopy, etc., and this method. The present invention relates to a device for carrying out the process.

(Prior Art) Photographic film for recording X-ray images must have sufficient sensitivity and wide exposure range for photographing, as well as high contrast, sharpness, and fine graininess necessary for observation and interpretation. However, these conditions often conflict with each other, and if X-rays are taken directly onto photographic film, it is difficult to obtain an X-ray image that satisfies all of these conditions. The reality is that films are designed at the expense of image reading aptitude.

Therefore, X-ray images are recorded using photographic film with a low gamma value designed to be suitable for later image processing, and
After reading the X-ray image from the original photograph in which the ray image was recorded, converting it into an electrical signal, and performing image processing on this,
Various methods have been studied to improve contrast, sharpness, and graininess by reproducing images as visible images in photocopies and the like.

(Problems to be Solved by the Invention) X-rays are often harmful to the human body when exposed to a large amount of radiation, so it is desirable to perform imaging using X'-rays with as low a dose as possible.

However, as the amount of X-rays irradiated to the subject during imaging is reduced, the influence of X-ray quantum noise and the like on the X-ray image becomes greater, and the graininess of the image deteriorates, resulting in a reproduced image with a coarse and grainy impression.

One way to improve this graininess is to make the photographic film thicker or to increase the grain size of the emulsion used in this photographic film to record blurry images during shooting, but other methods such as sharpness etc. There are limits to minimizing deterioration in image quality performance and improving graininess, so as mentioned above, it is necessary to read the X-ray image from the original photograph in which it was recorded and convert it into an electrical signal. It is desirable to perform image processing and then reproduce the image as a visible image in a photocopy or the like.

Among the ways to improve this graininess, device-wise improvements include increasing the diameter of the scanning excitation light to blur the image during reading, and inputting the read analog image signal to an analog filter to blur it. Conceivable. Although delicate control is required to improve graininess and minimize deterioration of other image quality performance such as sharpness, each of the above methods has a relatively complicated mechanism and a limited degree of freedom in control. This method has problems such as being able to control only the direction of the flow of time-series image signals (main scanning direction), which is extremely slow. Furthermore, as a method for improving this graininess through image processing, FFT (Fast Fourier
Conceivable methods include frequency processing using Transfo+m), and a method of digitally blurring each scanning point by calculating the average value of the image density around this scanning point. Although the method using FFT has a very large degree of freedom in control, it has problems such as the processing speed is too slow to be applied to large-capacity image signals, and increasing the processing speed involves a large increase in cost. The digital blurring method described above has a fast processing time, but does not allow delicate control.
This usually has the problem of being too blurred.

In view of the above-mentioned problems, the present invention can improve the graininess of X-ray images and minimize the deterioration of other image quality performance, and also allows sufficient calculation time without complicating the device. It is an object of the present invention to provide an X-ray image processing method within the scope and an apparatus with which this method can be carried out.

(Means for Solving the Problems) The X-ray image processing method of the present invention scans an original photograph in which X-ray image information is recorded, reads the original image density at each scanning point, and then scans a copy photograph, etc. When reproducing an X-ray image as a visible image, the original image density within a predetermined surrounding area corresponding to each scanning point or the image density obtained by performing intermediate processing on a signal representing this original image density are averaged. 1 obtained by
Du■, k (k=1, 2,..., nun
is an integer indicating the number of blur masks), the image density after performing intermediate processing on the original image density or a signal representing the original image density is Dkl+I), 2, 1 corresponding to the one or more blur masks, respectively. βk (k=1, 2,..., n),
When the image density after calculation processing is D', at least one attenuation coefficient βl (QJ is an integer between 1 and n) among the attenuation coefficients βk (k = 1, 2, ..., n) is It is a variable that is always within the range of 0≦βl and changes within each X-ray image, and calculations are performed according to the formula using this attenuation coefficient βl, and the density D us of the blur mask corresponding to the attenuation coefficient βl is calculated. t
It is characterized by attenuating spatial frequency components higher than the spatial frequency components possessed by.

Furthermore, the X-ray image processing apparatus of the present invention for carrying out the above-mentioned X-ray image processing method scans an original photograph in which X-ray image information is recorded, reads the original image density at each scanning point, and then This signal representing the original image density is processed by the calculation unit, and based on the processed image density signal,
In an X-ray image processing device that reproduces an X-ray image as a visible image on a photocopy or the like, the calculation unit generates an original image density within a predetermined surrounding area corresponding to each scanning point or a signal representing this original image density. D is the density of one blur mask obtained by averaging the image density obtained by performing intermediate processing, or of a plurality of blur masks obtained by changing the predetermined range.
,..., nun is an integer indicating the number of blur masks),
The image density after performing intermediate processing on the original image density or a signal representing this original image density is D&
l+Db2, one or more attenuation coefficients respectively corresponding to the one or more blur masks are βk
(k=1, 2,..., n), and when the image density after calculation processing is D', the attenuation coefficient β is (k=1, 2,..., n).
..., n), at least one attenuation coefficient βk (integer is an integer within 1 to n) is always in the range 0≦βl and is a variable that changes within each X-ray image, and this attenuation This method is characterized in that calculations are performed according to a formula using a coefficient βk.

(Function) As described above, in the X-ray image processing method of the present invention, at least one of the attenuation coefficients βk (k=1, 2, . . . , n) always satisfies 0≦βl. is a variable with a value within the range p' −I) , , −Σ β−(D−2D, −, k
)...The calculation is performed according to the formula (1).

Transforming the above (1), D""D, +-βl (DI12 p,,,L)-
Σ βk (Db2 Du-,-)...(ak-
It becomes 1+1.

Focusing on the second term βl (Db2Du*L) in equation (2), we can see that D in parentheses of this term, 2-Du, ,
For example, by subtracting the density of the blur mask, . . This Dh2D
β is obtained by multiplying uat by the damping coefficient βl of O≦βl.

(D=2 D, , , t) can be further calculated as, for example, the original image density, or by subtracting it from 1,
In a region in the line image where βl≠0 (βl is a variable that changes within the X-ray image), the high spatial frequency components of Db, Db2-D, and L can be attenuated. By matching this high spatial frequency component with the granular noise of the image, and by setting an appropriate value for the attenuation coefficient βl as a variable that changes within the range of 0≦βl, - depending on the state of each region in the image, It is possible to attenuate image granular noise and minimize deterioration in image quality performance such as sharpness. Furthermore, an X-ray image processing device for carrying out this calculation method is capable of realizing a device for carrying out the above-mentioned X-ray image processing method without making the device particularly complicated compared to conventional X-ray image processing devices. In addition, the calculation time can be kept within an allowable range. The above image density Db
1. Both Db2 may be the original image density, or one or both may be the image density after performing intermediate image processing on a signal representing the original image density and performing this image processing. .

Next, the third and fourth terms of Equation 21 above will be explained.

Grain noise has a fairly wide range of spatial frequency components. Therefore, in cases where the granular noise cannot be suppressed sufficiently by the combination of the first and second terms in the above equation (2),
If you want to perform more detailed image processing by changing the spatial frequency band for each area in the screen, the second term is different from the second term by changing the spatial frequency band and performing the same calculation as the second term in the third term. This can be done in Section 4 or Section 4.

In addition, in the third and fourth terms, the attenuation coefficient βk, (m≠9J) is set to βk×O, and for example, an operation that emphasizes a specific spatial frequency component proposed by the present applicant in JP-A No. 55-87953. may be combined.

Here, the above-mentioned image processing method was developed by the applicant
5-87953, etc., where the density of the non-sharp mask is D51, the density of the original photo is Darg+, the emphasis coefficient is βk, and the density reproduced in the copied photo, etc. is D', D' - [) 0 ,1+β(Dol,-D us)
- The basic difference from the case where calculation is performed to emphasize a specific spatial frequency component according to equation (3) will be explained.

The simplest equation for the present invention is the first equation (2) above.
term and the second term only, that is, D' −D,, −βk (Db2 p,,,L)・
...(4).

As described above, this equation (4) indicates that the spatial frequency component of granular noise is actively attenuated.

However, the inventors of the above-mentioned Japanese Patent Application Laid-open No. 55-87953 have revealed that the spatial frequency of particle noise overlaps with the spatial frequency that affects image quality performance such as sharpness. It can be easily imagined that actively attenuating the spatial frequency component of particle noise would irreparably degrade other image quality performance. Image quality is improved by emphasizing spatial frequency components whose contribution rate to image quality performance is relatively greater than that of sharpness.

As a result of examining the properties of granular noise in more detail, the present inventors have determined that the spatial frequency to be attenuated and the degree to which this spatial frequency is attenuated are delicately selected to actively suppress the spatial frequency components of granular noise. They have discovered that this makes it possible to make granular noise less noticeable and to minimize deterioration in image quality performance such as sharpness.

The damping coefficient βl for performing the above damping is 0≦βl<l
By changing within the range of , each region within the image can be optimized for almost all images. This attenuation coefficient βk is, for example, in an X-ray image,
For areas with low image density where granular noise is relatively noticeable, the degree of attenuation is increased to make them more blurred, and for areas of high image density where granular noise is relatively less noticeable, the attenuation level is increased so that the detailed structure becomes clearer. or, for example, in an X-ray image of the chest of a human body, a bone part, a lung field part, a heart part, etc. - for each object in the image, for each object. Various functional forms are selected depending on the purpose of image processing, such as changing so that optimal image processing is performed.

(Embodiments) Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings.

FIG. 2 is a perspective view showing an example of an X-ray image processing apparatus using the X-ray image processing method of the present invention.

An original photograph 1 on which X-ray image information of the subject is recorded is conveyed (sub-scanned) in the direction of arrow Y by a photograph conveying means 3 driven by a motor 2.

On the other hand, the readout light 5 emitted from the laser light source 4 is transmitted to the motor 1.
A rotating polygon mirror 6 that is driven by 3 and rotates at high speed in the direction of the arrow.
After passing through a focusing lens 7 such as an fθ lens, the optical path is changed by a mirror 8, and the beam enters the original photograph 1, mainly in the direction of arrow X, which is substantially perpendicular to the sub-scanning direction (direction of arrow Y). scan. This readout light 5 is transmitted after being intensity-modulated depending on the density of the X-ray image recorded on the original photograph 1 (original image density). It is photoelectrically detected by a photomultiplier (photomultiplier tube) 11. The light condenser 1O is made by molding a light-guiding material such as an acrylic plate, and is arranged so that the linear incident end surface 10a extends along the main scanning line on the original photograph 1. The light receiving surface of the photomultiplier 11 is coupled to the annularly formed output end surface 10b.

The readout light 5 entering the light condenser 10 from the incident end surface 10a travels inside the light condenser 10 by repeating total reflection,
The photomultiplier 1 is emitted from the output end face 10b.
A photomultiplier 11 detects the amount of the readout light 5 which is received by the readout light 5 and carries the X-ray image information.

The analog output signal output from the photomultiplier 11 is amplified by an amplifier 16 and digitized by an A/D converter 17 at a predetermined recording scale factor.

The signal representing the digitized original image density D0,1 obtained in this way is input to the calculation unit 18, and the calculation unit 18 averages the image density within a predetermined range around each scanning point. By doing this, the density of the blur mask, k (k=1.2.-, nun is the number of blur masks obtained by changing the above predetermined range), is calculated, and the calculation unit 1
The original image density D01.8 inputted to D01. Alternatively, the image density obtained by performing intermediate processing on the signal representing the original image density D or is calculated using the attenuation coefficient βk( Using k=1゜2,...,n), D' -D,, -Σ βk (D-2D,,, -).
...The image density D' after the arithmetic processing is determined according to the equation (5).

In this specification, for the sake of simplicity, the same symbol, eg, D02, is used to represent the "image density" and the "signal representing the image density."

The simplest calculation process among the calculation processes shown in equation (5) above uses one blur mask having the density DumL and the attenuation coefficient βl (0≦βl), and calculates D′ ” D b
+-βl (Db2Dum, t)...This is an arithmetic process according to the formula (6). This arithmetic processing is performed using the blur mask density I)t+1. This means attenuating spatial frequency components higher than the spatial frequency components of It is possible to minimize the deterioration of image quality performance in the same area.

The image density D' after the above-described calculation has been performed by the calculation unit 18 is stored in the memory 19, and an X-ray image based on a signal representing this image density is reproduced and displayed on the image display device 20 as necessary.

FIGS. 3A to 3C each show the calculation unit 18 shown in FIG.
FIG. 3 is a block diagram showing different configuration examples.

In the configuration example of FIG. 3A, original image density D01. A signal representing - is input to the storage means 21 from the left side of the figure, and -
time is remembered. The original image density temporarily stored in the storage means 21. 1. The signal representing subtraction means 2, which will be described later,
n blur mask density calculation means 22a, 22b, .
2n in parallel. These blur mask density calculation means 22a, 22b, . . .

22n, the surrounding N1 corresponds to each scanning point.
The image densities of xl'J1, N2XN2, -, N, and XNn scanning points are averaged to obtain the blur mask density D□I+
Dlll, 2+...+ Dul,. is required.

The density Dum, l+D of these blur masks. 1.2.・
..., D8°. are the first damping term calculating means 23a, respectively.
n attenuation product calculating means 23a, 23b, etc.
・, 23n, and the damping term βl (D
erg D us, l) r β2 (Darg
-Dum, 2) + ”'+ β. (D, , -D
u.

,. ) is calculated. These attenuation terms and the original image density D o r□ are input to the subtraction means 24 and calculated, and the image density D' after the calculation process is obtained.

FIG. 3B is a block diagram showing an example of the configuration of the arithmetic unit 18 different from that shown in FIG. 3A. The same parts as in FIG. 3A are given the same numbers as in FIG. 3A, and explanations thereof will be omitted.

The blur mask density calculation means 22' in this configuration example first calculates the average value of 3x3 scanning points centering on each scanning point, and further calculates the average value of these average values to calculate 9x9, 15x15, etc. Each attenuation product calculating means 23a, 23b, . . . calculates the average value of the scanning points.
..., 23n, and each attenuation product calculation means 23a, 23b, .

23n. By doing this, the density of the blur mask can be calculated efficiently.

FIG. 3C is a block diagram showing a further different configuration example of the calculation unit 18 shown in FIG. 2.

After the signal representing the original image density D01 is temporarily stored in the storage means 21', the blur mask density calculation means 22
’. The blur mask density calculating means 22' calculates the density of the blur mask corresponding to the attenuation coefficient β1 based on the original image density D0,1. The density of this bokeh mask. , 1 is sent to the attenuation product calculation means 23', and the attenuation product calculation means 23' calculates β1 (D
-,,-D 0. +) is calculated and sent to the subtraction means 24'. In the subtraction means 24', the original image density D
Image density D after performing intermediate processing on 0 and 1, wm
p, , , -βl (D-, , -D., 1) are calculated.

A signal representing the image density D1 as a result of this calculation is returned to the storage means 21'' and is stored in place of the original image density D02 stored in the storage means 21''. A signal representing this image density D1 is sent to the blur mask density calculation means 22.
', the density Du*,2 of the blur mask corresponding to the attenuation coefficient β2 is calculated based on the image density D1, and a signal representing the density Dos,2 of the blur mask is sent to the attenuation product calculation means 23''. , β2 (DI −D, −
, 2) is calculated.

This calculation result is sent to the subtraction means 24'', and the image density is calculated.
The image density D2-D, -β2- (DI D-, 2), which is obtained by further performing second intermediate processing on the signal representing , is calculated.

By repeating the above loop n times, the final image density D' subjected to arithmetic processing is D'-Dn-, -β-
It is found as (D-+ D,-,-)-(7).

In this way, the image density after intermediate processing is D1°D2+
...+Dn-1 to determine the density of the blur mask D ua-
11Dus, 21...,D. 1. By performing calculations such as , and calculations represented by equation (7), it is possible to effectively attenuate granular noise while minimizing deterioration in image quality performance such as sharpness.

In comparison with the above-mentioned equation (5), the above equation (7) uses the same image density Dn-1 as the image density Db1 and Db2, but the attenuation product calculation means 23' shown in FIG. 3C, for example, Also, the original image density D01. The attenuation product calculating means 23' directly inputs and stores a signal representing
In the calculation in D2., the image density after intermediate processing is calculated.・
・Do not use +D++-1, always use the original image density D01, and calculate βl (Do-□-Ri,, 1) β2 (D-,, Du-, 2), etc. Finally, p′ m Dfi−, −βk−(D, , , −D us
, n) −481, etc., the image signal Db1
, Db2 may be different.

FIG. 1A shows an image of n-2 obtained using the X-ray image processing method of the present invention.
(Bokeh mask and two attenuation coefficients) is a graph showing an example of calculation in the spatial frequency domain. The horizontal axis shows the spatial frequency, and the vertical axis shows the relative value with the DC component being 1.

For the sake of simplicity, a signal representing the image density D' after the arithmetic processing is Fourier-transformed and is expressed in the spatial frequency domain in the same way as D'.

Graph A is an ideal graph showing optimal spatial frequency characteristics for suppressing grainy noise and minimizing deterioration of image quality performance such as sharpness for a certain X-ray image. In contrast to graph A, graph A' uses the average values of 15 x 15 and 5 x 5 scanning points around each scanning point as the density D us, In Du ua, 2 of the blur mask, respectively, and the attenuation coefficient β1. β+-0, 1, respectively as β2
p′ −p, , −βl using β2−0.4
(D-1t-'D-,+)-β2 (D, ,, -D
u-, 2) -- This is a graph showing the calculation result of (9) in the spatial frequency domain, and is sufficiently approximated to graph A.

Graph B is an ideal graph showing optimal spatial frequency characteristics for other radiation images. In contrast to this graph B, graph B' is the density of the blur mask Dus, l+ Du
a, 15 x 15 around each scanning point as 2,
Using the average value of 3×3 scanning points, the attenuation coefficient β8. β2
Using βk -0,1 and β2-0.8 as p' wm Do, , -β1 (D-1, Du
aυ−β2 (D, , D, , 2) --(1
0) is a graph showing the calculation results in the spatial frequency domain. In this case as well, graph B' closely approximates graph B.

As shown in FIG. 1A, the damping coefficient βk (k=1, 2
, ..., n) is first determined by the type of X-ray image.

FIG. 1B is a graph showing an example of a function of the attenuation coefficient βl with image density as a variable. In this graph, areas C with low image density where granular noise is relatively noticeable are blurred using an attenuation coefficient βk-α, and areas E with high image density where granular noise is relatively inconspicuous are blurred so that the detailed structure becomes clear. This indicates that blurring is stopped as β-0, and βl is made smaller as the image density becomes higher in the intermediate region. As shown in FIG. 1B, even in one X-ray image, β varies depending on the image density.

By changing (k=1, 2,..., n), the same value βk (k=1
．． 2. ..., n), it is possible to perform more fine-grained image processing.

Note that the graph in Figure 1B is just one example; for example, the attenuation coefficient βl may vary in a curved manner with respect to the image density, and may be changed depending on the type of X-ray image, the purpose of image processing, etc. A functional form is determined.

Furthermore, even if βk (k=1, 2, ..., n) is not a function of image density, and even if it is changed for each subject in two images as described above, it can be a function of image density. In the same way as in the above case, more detailed image processing can be performed.

In this way, X-ray images are divided according to the type of subject (for example, the chest, head, etc.) of the whole image, the intensity of the X-rays irradiated to the subject, etc., and the By determining the calculation method for the density of the blur mask and the function of the attenuation coefficient, and performing calculation processing according to the method described above, the grain noise in the X-ray image can be effectively attenuated according to each region within the image. It is possible to obtain a reproduced image in which deterioration in image quality performance such as sharpness is minimized.

(Effects of the Invention) The present invention scans an original photograph in which X-ray image information is recorded, and after reading the original image density at each scanning point, the attenuation coefficient βk (k=1, 2, . . . At least one of the attenuation coefficients βk of n) is always within the range of 0≦βl and is a variable that changes within each image;
Since the calculation is performed according to the formula using this attenuation coefficient βk, it is possible to attenuate spatial frequency components higher than those of the density Dum,1 of the blur mask, and each It is possible to effectively attenuate granular noise in an X-ray image depending on the region, and to minimize deterioration in other image quality performance. Further, the apparatus for carrying out this method is not particularly complicated, and the calculation time can be kept within a sufficiently allowable range.

[Brief explanation of the drawing]

FIG. 1A is a graph showing an example of calculation using the X-ray image processing method of the present invention in the spatial frequency domain, and FIG. 1B is a graph showing an example of the function of the attenuation coefficient βk with image density as a variable. , FIG. 2 is a perspective view showing an example of an X-ray image processing apparatus implementing the X-ray image processing method of the present invention, and FIGS. 3A to 3C show different configurations of the calculation unit shown in FIG. 2. FIG. 2 is a block diagram showing an example. 1... Original photo 2.13... Motor 3... Photo conveying means 4... Laser 6... Rotating polygon mirror 10
...Concentrator 11...Photomultiplier 16...Amplifier 17...A/D converter 18...Arithmetic unit 19...Memory 2
0...Image display device Figure 1A Old figure Figure 2

Claims (7)

[Claims] (1) After scanning the original photograph in which X-ray image information is recorded and reading the original image density at each scanning point, when reproducing the X-ray image as a visible image on a copy photograph, etc., at each scanning point. 1 obtained by averaging the original image density within a surrounding predetermined range or the image density obtained by performing intermediate processing on a signal representing this original image density.
D_u_■_,_k (k=1, 2,...,
n; n is an integer indicating the number of blur masks), and the image density after performing intermediate processing on the original image density or a signal representing this original image density is D_b_1, D_b
_2, one or more attenuation coefficients corresponding to the one or more blur masks respectively are β_k (k=1,
2,...,n), and when the image density after calculation processing is D', at least one attenuation coefficient β_l( l is an integer from 1 to n) is always in the range of 0≦β_l and is a variable that changes within each X-ray image, and using this attenuation coefficient β_l, there are ▲mathematical formulas, chemical formulas, tables, etc.▼ The density D_u of the blur mask corresponding to the attenuation coefficient β_l is calculated according to the formula:
An X-ray image processing method characterized by attenuating spatial frequency components higher than spatial frequency components possessed by ____,_l. (2) The X-ray image processing method according to claim 1, wherein the attenuation coefficient β_l is a variable always in the range of 0≦β_l<1. (3) The attenuation coefficient β_l is a function of the original image density or an image density obtained by performing intermediate processing on a signal representing the original image density. X-ray image processing method. (4) Image density D after performing intermediate processing on the original image density or a signal representing this original image density
Claim 1, wherein both _b_1 and D_b_2 have the same original image density.
3. The X-ray image processing method according to any one of Items 3 to 3. (5) Image density D_b obtained by performing intermediate processing on the original image density or a signal representing this original image density.
_1 and D_b_2 are the same image density obtained by performing the same intermediate processing on the signal representing the original image density. The X-ray image processing method according to any one of the items. (6) Image density D_b obtained by performing intermediate processing on the original image density or a signal representing this original image density.
_1, D_b_2 is a first input to the original image density or a signal representing the original image density.
Claims 1 to 3 are characterized in that the image density is an image density obtained by performing intermediate processing on the signal representing the original image density, and the other is an image density obtained by performing a second intermediate processing on the signal representing the original image density. The X-ray image processing method according to any one of . (7) After scanning the original photograph in which X-ray image information is recorded and reading the original image density at each scanning point, the signal representing the original image density is processed by the calculation unit, and the processed image density is calculated. In an X-ray image processing device that reproduces an X-ray image as a visible image on a photocopy or the like based on a signal representing the image, the calculation section calculates the density of the original image within a predetermined range around each scanning point, or The density of one blur mask obtained by averaging the image density obtained by performing intermediate processing on the signal representing the original image density or of a plurality of blur masks obtained by changing the predetermined range is D_u_■_
, _k (k=1, 2, ..., n; n is an integer indicating the number of blur masks), and the image densities obtained by performing intermediate processing on the original image density or a signal representing this original image density are D_b_1, D_b_2, When one or more attenuation coefficients corresponding to the one or more blur masks are β_k (k=1, 2, . . . , n), and the image density after calculation processing is D′, At least one damping coefficient β_l (l is an integer within 1 to n) among the damping coefficients β_k (k=1, 2, . . . , n) is always in the range 0≦β_l, and each of the above-mentioned X An X-ray image processing device characterized in that the attenuation coefficient β_l, which is a variable that changes within a line image, is used to perform calculations according to the formula ▲ which includes mathematical formulas, chemical formulas, tables, etc. ▼.