JPH0743768B2 - X-ray image processing method and apparatus - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION (Field of Industrial Use) The present invention records an X-ray image when copying an image obtained by irradiating an object with X-rays (hereinafter referred to as “X-ray image”). Regarding the image processing applied to the signal representing the original image density after reading the density of the X-ray image recorded in the original photo (hereinafter referred to as "original image density") from the original plate (hereinafter referred to as "original photo") In particular, the present invention relates to an X-ray image processing method for improving the graininess of an X-ray image reproduced as a visible image on a copy photograph and the like, and an apparatus for carrying out this method.

(Prior Art) A photographic film for recording an X-ray image must have sufficient sensitivity and a wide exposure range for photographing, and must also have high contrast, sharpness and fine graininess necessary for observation and interpretation. However, these conditions often conflict with each other, and it is difficult to obtain an X-ray image satisfying all of these conditions by photographing X-rays directly on a photographic film. The reality is that the film is designed at the expense of little by little.

Therefore, an X-ray image is recorded by using a photographic film having a low gamma value designed to meet the later image processing.
After reading the X-ray image from the original photo on which the line image was recorded and converting it into an electrical signal, and subjecting this to image processing,
Various methods for improving contrast, sharpness, and graininess by reproducing a visible image on a copy photograph or the like have been studied.

(Problems to be Solved by the Invention) X-rays are often harmful to the human body and the like when the exposure dose is large, and it is desirable to perform imaging with X-rays with a dose as low as possible.

However, as the X-ray dose applied to the subject at the time of shooting is reduced, the influence of X-ray quantum noise on the X-ray image increases, the graininess of the image deteriorates, and the reproduced image has a rough and rough impression.

As one method of improving the graininess, there is a method of recording a blurred image at the time of shooting by thickening the photographic film or enlarging the grains of the emulsion used in this photographic film, but other methods such as sharpness are used. There is a limit to suppressing the deterioration of the image quality performance and improving the graininess. As described above, the X-ray image is read from the original photograph on which the X-ray image is recorded and converted into an electric signal. After image processing, a method of reproducing a visible image on a copy photograph or the like is desirable.

Among the methods for improving the graininess, the device measures include increasing the diameter of the exciting light to be scanned and blurring the image when reading, inputting the read analog image signal to an analog filter and blurring. Conceivable. Despite the need for delicate control in order to improve graininess and suppress deterioration of other image quality performance such as sharpness as much as possible, each of the above methods has a degree of freedom that can be controlled although the mechanism is complicated. There is a problem that it is possible to control only the extremely low direction of time-series image signal flow (main scanning direction). In addition, as a method of improving this graininess by image processing, FFT (Fast Fourier Transform)
A method of performing frequency processing using, and a method of digitally blurring each scanning point by obtaining an average value of image densities around the scanning point can be considered. The method using the FFT has a very large degree of controllable degree of freedom, but has a problem that the processing speed is too slow to be applied to a large-capacity image signal, and a high cost is required to increase the processing speed. The above-mentioned digitally blurring method has a problem that the processing time is short, but delicate control cannot be performed, and the blurring is usually excessive.

In view of the above-mentioned problems, the present invention can improve the graininess of an X-ray image and minimize deterioration of other image quality performance, and further, allow sufficient computing time without complicating the apparatus. It is an object of the present invention to provide an X-ray image processing method within the range, and an apparatus capable of implementing this method.

(Means for Solving Problems) In the X-ray image processing method of the present invention, an original photograph on which X-ray image information is recorded is scanned, the original image density at each scanning point is read, and then a copy photograph or the like. In reproducing the X-ray image as a visible image, the original image density within a predetermined peripheral range corresponding to each scanning point or the image density obtained by subjecting a signal representing the original image density to an intermediate process is averaged. 1 obtained by
Or the density of a plurality of blur masks obtained by changing the above predetermined range is D _us.k (k = 1,2, ..., n; n is an integer indicating the number of blur masks), the original image density or the original image density. Image density after intermediate processing on the signal
D _b1 , _b2 and one or a plurality of attenuation coefficients corresponding to the above-mentioned one or a plurality of blur masks respectively are _represented by β _k (k = 1, 2,
, N), where D'is the image density after the arithmetic processing, at least one of the attenuation coefficients β _k (k = 1,2, ..., n) is the attenuation coefficient β _l (1 is 1 to n). Is a variable that is always within the range of 0 ≦ B _l <1 and changes in each X-ray image, and the original image density or a function of the image density obtained by performing intermediate processing on the original image density. And
Using this damping coefficient β _l It is characterized in that the spatial frequency component higher than the spatial frequency component possessed by the density D _{us.l of} the blur mask corresponding to the attenuation coefficient β ₁ is attenuated by the calculation according to

Further, the X-ray image processing apparatus of the present invention for carrying out the above X-ray image processing method scans an original photograph on which X-ray image information is recorded, and after reading the original image density at each scanning point, A 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 apparatus for reproducing an X-ray image as a visible image on a copy photograph or the like, the arithmetic unit corresponds to each scanning point and has an original image density within a predetermined surrounding range or a signal representing the original image density. D _us.k (k = 1,2, ..., n; n) is obtained by averaging the image densities obtained by performing the intermediate processing on the image density of one or a plurality of blur mask densities obtained by changing the predetermined range. Is an integer indicating the number of blur masks), the original image density or the image density after intermediate processing of the signal representing the original image density is D _b1 , _b2 , 1 corresponding to the one or more blur masks, respectively. When one or a plurality of attenuation coefficients is β _k (k = 1,2, ..., n) and the image density after the calculation process is D ′, the attenuation coefficient β _k (k = 1,2, ... at least 1 out of n)
The attenuation coefficient β _l (l is an integer within 1 to n) is a variable that is always in the range of 0 ≦ β _l <1 and changes in each X-ray image, and the original image density or this original image It is a function of the image density obtained by performing the intermediate processing on the density, and using this attenuation coefficient β _l The calculation is performed according to the equation

(Operation) In the X-ray image processing method of the present invention, as described above, at least one of the attenuation coefficients β _k (k = 1, 2, ..., N) always has an attenuation coefficient β _l of 0 ≦ β _l <1. Is a variable having a value within the range of, and is a function of the original image density or an image density obtained by applying an intermediate process to the original image density, The calculation is performed according to the formula.

By transforming (1) above, Becomes

Focusing on this equation (2) the second term beta _l of _{(D b2} -D us.l), the parentheses _{D b2} -D us.l of this section, a D _b2 of the unsharp mask for example, the original image density density D
_By subtracting _us.l , the low spatial frequency component of the _blur mask density D _us.l is subtracted from D _b2 . By subtracting from this _{D b2} -D us.l to 0 ≦ β _{l <β} was multiplied by a first attenuation coefficient _{β l l (D b2 -D us.l} ) a further example original image density D _b1,
In the region of β ₁ ≠ 0 (β ₁ is a variable that changes in the X-ray image) in the X-ray image, the high spatial frequency components of D _b1 to D _b2- D _us.l can be attenuated. This high spatial frequency component is matched with the granular noise of the image, and the attenuation coefficient β
_l is a variable that changes within the range of 0 ≦ β ₁ <1, and by defining an appropriate value as a function of the original image density or the image density obtained by performing intermediate processing on the original image density, Depending on the state of each area, it is possible to attenuate the granular noise of the image and minimize deterioration of other image quality performance such as sharpness. Further, an X-ray image processing apparatus for carrying out this calculation method realizes an apparatus for carrying out the above X-ray image processing method without making the apparatus particularly complicated, as compared with a conventional X-ray image processing apparatus. In addition, the calculation time can be set within a sufficiently allowable range. The image densities D _b1 and D _b2 may both be original image densities, one or both of which perform intermediate image processing on a signal representing the original image density, and the image density after performing this image processing. May be

Next, the third and fourth terms of the above equation (2) will be described.
Granular noise has a fairly wide range of spatial frequency components. Therefore, when the granular noise cannot be suppressed sufficiently by the combination of the first term and the second term in the equation (2), or the spatial frequency band is changed for each area in one screen, more detailed image processing can be performed. When it is desired to perform, the spatial frequency band is changed from the second term and the same calculation as the second term is performed in the third term.
Item 4 or item 4 can be performed. In addition, in the third and fourth terms, the damping coefficient β _m (m ≠ l)
May be set to β _m <0, and a calculation proposed by the present applicant in JP-A-55-87953, which emphasizes a specific spatial frequency component, may be combined.

Here, the above-mentioned image processing method is described in
-87953, etc. proposed the non-sharp mask density D _us and the original photo density D
_org , the emphasis coefficient is β, and the density reproduced in a copy photograph is D ′, a specific spatial frequency component is calculated according to the following equation: D ′ = D _org + β (D _org −D _us ). The basic difference from the case of performing the emphasis calculation will be described.

The simplest formula for the present invention is the first formula of the above formula (2).
Only the second term and the second term, that is, D ′ = D _b1 −β ₁ (D _b2 −D _us.l ) (4).

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

However, it has been clarified by the inventors of the above-mentioned JP-A-55-87953 that the spatial frequency of the particle noise is simultaneously overlapped with the spatial frequency that affects other image quality performances such as sharpness. It can be fully imagined that other image quality performance will be deteriorated to an unrecoverable level if the spatial frequency of the particle noise is positively attenuated. Therefore, conventionally, the granular performance can be improved without actively attenuating the spatial frequency component of particle noise. The image quality is improved by emphasizing the spatial frequency components having a relatively large contribution to the image quality performance such as sharpness rather than the contribution to the image quality.

As a result of further detailed study of the properties of the granular noise, the present inventors subtly select the spatial frequency to be attenuated and the degree of attenuation of this spatial frequency, and positively suppress the spatial frequency component of the granular noise. By doing so, it has been found that the granular noise can be made inconspicuous and deterioration of other image quality performance such as sharpness can be suppressed to the minimum.

The damping coefficient β ₁ for performing the above damping is 0 ≦ β ₁ <1
By changing the range within the range, it is possible to optimize each region in the image for almost all images. This attenuation coefficient β _l is, for example, in an X-ray image,
The degree of attenuation is increased to make it more blurred for areas of low image density where grain noise is relatively conspicuous, and the degree of attenuation for areas of high image density where grain noise is relatively unnoticeable so that the detailed structure becomes clearer. For each subject in an image, such as a bone portion, a lung field portion, a heart portion in an X-ray image of the chest of a human body, for each subject. Various functional forms are selected according to the purpose of image processing, such as changing so as to perform optimum image processing.

(Examples) Examples of the present invention will be described below 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.

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

On the other hand, the continuous emitted light 5 emitted from the laser light source 4 is the motor 13
Is reflected and deflected by a rotary polygon mirror 6 which is driven at a high speed in the direction of an arrow and passes through a focusing lens 7 such as an fθ lens, and then an optical path is changed by a mirror 8 to enter the original photograph 1 and the sub-scanning direction ( The main scanning is performed in the arrow X direction that is substantially perpendicular to the (arrow Y direction). This continuous light 5 is intensity-modulated by the density (original image density) of the X-ray image recorded in the original photograph 1 and is transmitted, and the transmitted continuous light is condensed by the light collector 10 to serve as a photodetector. Is detected photoelectrically by a photomultiplier (photomultiplier tube) 11. The light collector 10 is made by molding a light guide material such as an acrylic plate, and the linear incident end face 10a is arranged so as to extend along the main scanning line on the original photograph 1. The light receiving surface of the photomultiplier 11 is coupled to the emitting end surface 10b formed in an annular shape. The continuous light 5 that has entered the light collector 10 from the incident end face 10a travels through the inside of the light collector 10 by repeating total reflection, is emitted from the emission end face 10b and is received by the photomultiplier 11, and the X The photomultiplier 11 detects the amount of the continuous light 5 that carries the line image information.

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

The signal representing the digitized original image density D _org thus obtained is input to the calculation unit 18, and the calculation unit 18 averages the image densities in the surrounding predetermined range corresponding to each scanning point. The density of the defocus mask D
_us.k (k = 1,2, ..., n; n is the number of blur masks obtained by changing the above predetermined range) is calculated, and the original image density D _org or the original image density D _org input to the calculation unit 18 is calculated.
Image densities obtained by applying intermediate processing to the signal representing _org are D _b1 , D _b2
And an attenuation coefficient β _k (k = 1,2, ..., n) prepared in advance as a function of the original image density D _org corresponding to the blur mask, respectively, The image density D ′ after the arithmetic processing is obtained according to the equation

In the present specification, for simplification, the same symbol, for example, D _org, is used when representing "image density" and when representing "signal representing image density".

The simplest calculation process of the formula (5) is one _{blur mask} having the density D us.l and the attenuation coefficient β.
_l (0 ≦ β ₁ <1: β ₁ is a variable and is a function of the original image density or the image density obtained by performing intermediate processing on the original image density), D ′ = D _b1 −β ₁ (D _b2 −D _{us .l} ) ... Calculation processing according to the equation (6). This calculation processing means to attenuate the spatial frequency component higher than the spatial frequency component of the density D _{us.l of} the blur mask, and by appropriately selecting the spatial frequency component to be attenuated and the degree of attenuation, While improving the graininess of the upper image,
It is possible to minimize deterioration of other image quality performance such as sharpness.

The image density D ′ that has been subjected to the above calculation by the calculation unit 18 is stored in the memory 19, and the X-ray image based on the signal representing the image density is reproduced and displayed on the image display device 20 as necessary.

3A to 3C are block diagrams showing different configuration examples of the arithmetic unit 18 shown in FIG. 2, respectively.

In the configuration example of FIG. 3A, a signal representing the original image density D _org is input to the storage means 21 from the left side of the drawing and temporarily stored. Original image density temporarily stored in storage means 21
A signal representing D _org is directly input to a subtracting means 24 described later, and n blur mask density calculating means 2 such as a blur mask density calculating means 22a for calculating the density of the first blur mask.
Input to 2a, 22b, ..., 22n in parallel. In these blur mask density calculation means 22a, 22b, ..., 22n, N ₁ × N ₁ , N ₂ × N ₂ , ..., N _n × N _n scanning points in the surroundings are respectively corresponding to the respective scanning points. Image density of the image is averaged and the density of the _blurred mask is D _us.1 , D
_us.2 , ..., D _us.n are required. The densities D _us.1 , D _us.2 , ..., D _us.n of these blur _masks are respectively input to n attenuation term calculation means 23a, 23b, ..., 23n such as the first attenuation term calculation means 23a. , The attenuation terms β ₁ (D _org −D _us.1 ), β
₂ (D _org −D _us.2 ), ..., β _n (D _org −D _us.n ) are calculated. These attenuation terms and the original image density D _org
Is input to the subtraction means 24, Is calculated, and the image density D ′ after the arithmetic processing is obtained.

FIG. 3B is a block diagram showing a configuration example of the calculation unit 18 different from that in FIG. 3A. 3A for the same parts as in FIG. 3A
The same numbers as in the figure are attached and the description is omitted.

In the blur mask density calculation means 22 'in this configuration example,
First, an average value of 3 × 3 scanning points centering on each scanning point is obtained, and then the average value of these average values is obtained to obtain 9
The density of the blur mask corresponding to each attenuation term calculation means 23a, 23b, ..., 23n is calculated by obtaining the average value of the scanning points of × 9, 15 × 15, etc., and each attenuation term calculation means 23a, 23b, ..., 23n
It was designed to be sent to. By doing so, the density of the blurred mask can be calculated efficiently.

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

The signal representing the original image density D _org is once stored in the storage means 2.
After being stored in 1 ″, it is sent to the blur mask density calculation means 22 ″. The blur mask density calculator 22 ″ calculates the density D _{us.1 of} the blur mask corresponding to the attenuation coefficient β ₁ based on the original image density D _org . The density D of this blur mask
_A signal representing _us.1 is sent to the attenuation term calculation means 23 ″, and β ₁ (D _org −D _us.1 ) is calculated in the attenuation term calculation means 23 ″,
It is sent to the subtraction means 24 ″. In the subtraction means 24 ″, the image density D ₁ = D after the original image density D _org is subjected to the intermediate processing.
_org −β ₁ (D _org −D _us.1 ) is calculated.

The signal representing the image density D ₁ of this calculation result is stored in the storage means 2
It is returned to 1 ″ and stored in place of the original image density D _org stored in the storage means 21 ″. This image density D ₁
Is sent to the blur mask density calculation means 22 ″,
This time, the density D _{us.2 of} the blur mask corresponding to the attenuation coefficient β ₂ is calculated based on the image density D ₁ , and the signal representing the density D _{us.2 of} this blur mask is sent to the attenuation calculation means 23 ″, and β
₂ (D ₁ −D _us.2 ) is calculated. The result of this calculation is sent to the subtraction means 24 ″, and the image density D ₂ = D ₁ −β ₂ (D ₁ −D) obtained by further subjecting the signal representing the image density D ₁ to the second intermediate processing is applied.
_us.2 ) is calculated.

By repeating the above loop n times, the finally calculated image density D ′ is D ′ = D _n−1 −β _n (D _n−1 −D _us.n ) (7) Is obtained as.

Thus, the image density D _1, D ₂ which has been subjected to intermediate treatment, ..., D _n-1
Also , the deterioration of image quality performance such as sharpness can be minimized by calculating the density D _us.1 , D _us.2 , ..., D _us.n of the _blur mask using Eq. The granular noise can be effectively attenuated while being held down.

The above equation (7) uses the same image densities D _n-1 as the image densities D _b1 and D _b2 as compared with the above-mentioned equation (5). However, for example, the attenuation term calculating means shown in FIG. 3C is used. 23 "in stores directly input a signal representing the original image density D _org, this attenuation term calculating means 23" image density D _1, D ₂ of the intermediate treatment in the calculation of, ..., D _n-1 , Always using the original image density D _org , β ₁ (D _org −D _us.1 ) β ₂ (D _org −D _us.2 ) ……………………………… The image signals D _b1 and D _b2 may be different from each other, for example, by calculating and finally calculating D ′ = D _n−1 −β _n (D _org −D _us.n ) (8).

FIG. 1A shows that n = 2 using the X-ray image processing method of the present invention.
It is the graph which showed the example calculated in the case of (a blur mask and two attenuation coefficients) in the spatial frequency domain. The horizontal axis represents the spatial frequency, and the vertical axis represents the relative value with the DC component being 1. For simplification, the signal representing the image density D ′ after the arithmetic processing is Fourier transformed and the signal shown in the spatial frequency domain is also expressed by D ′.

Graph A is an ideal graph showing optimum spatial frequency characteristics for suppressing granular noise for a certain X-ray image and minimizing deterioration of other image quality performance such as sharpness. In contrast to this graph A, the graph A'is the density D _us.1 and D _us.2 of the _{blur mask} 15 around each scanning point 15 × 15.
, 5 × 5 scanning points are used as average values, and the attenuation coefficients β ₁ and β ₂ are used.
Using β ₁ = 0.1 and β ₂ = 0.4 respectively, the calculation of D ′ = D _org −β ₁ (D _org −D _us.1 ) −β ₂ (D _org −D _us.2 ) …… (9) It is a graph showing the result in the spatial frequency domain, which is sufficiently similar to graph A.

Graph B is an ideal graph showing optimum spatial frequency characteristics for other radiation images. In contrast to the graph B, the graph B ′ uses the average values of 15 × 15 scanning points and 3 × 3 scanning points around each scanning point as the densities D _us.1 and D _us.2 of the _{blur mask} , respectively, and the attenuation coefficient β _{As 1} and β ₂ , β ₁ = 0.1 and β ₂ =
A graph showing the calculation result of D ′ = D _org −β ₁ (D _org −D _us.1 ) −β ₂ (D _org −D _us.2 ) ... (10) in the spatial frequency domain using 0.8 Is. Also in this case, the graph B ′ is sufficiently close to the graph B.

As shown in FIG. 1A, the damping coefficient β _k (k = 1, 2, ...,
The optimum value of 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 β ₁ with the image density as a variable. In this graph, an area C having a relatively low image density in which grain noise is relatively conspicuous is blurred as an attenuation coefficient β _l = α, and a detailed structure is clear in an area E in which image noise is relatively inconspicuous and in which grain noise is relatively inconspicuous. As described above, β = 0 is set to stop the blurring, and β ₁ is reduced in the intermediate region D as the image density becomes higher. As shown in FIG. 1B, by changing β _k (k = 1,2, ..., n) in one X-ray image according to the image density, the same value can be obtained for one entire X-ray image. In comparison with the case of using β _k (k = 1, 2, ..., N), more detailed image processing can be performed.

Note that the graph of FIG. 1B is merely one example, and for example, the attenuation coefficient β ₁ may change in a curve with respect to the image density, and it may be changed depending on the type of X-ray image, the purpose of image processing, and the like. Appropriate function form is defined.

Further, β _k (k = 1, 2, ..., N) does not have to be a function of image density, but may be a function of image density even if it is changed for each subject in one image as described above. As in the case
More detailed image processing can be performed.

In this way, the X-ray images are classified according to the type of the subject in the entire image (for example, the chest of the human body, the head, etc.), the intensity of the X-rays applied to the subject, and the blur mask is adapted to each X-ray image. The density noise of the X-ray image is effectively attenuated according to each region in the image and the sharpness is reduced by determining the density calculation method and the function of the attenuation coefficient and performing the arithmetic processing according to the above-described method. It is possible to obtain a reproduced image in which deterioration of other image quality performance is suppressed to the minimum.

(Effect of the Invention) According to the present invention, an original photograph on which X-ray image information is recorded is scanned, and the original image density at each scanning point is read, and then the attenuation coefficient β _k (k = 1, 2, ..., N). ), At least one of the attenuation coefficients β ₁ is always within the range of 0 ≦ β ₁ <1 and changes in each image, and the original image density or the original image density is subjected to intermediate processing. It is a function of image density, and this attenuation coefficient β _l
Using Since the calculation is performed according to the equation, the spatial frequency component higher than the spatial frequency component possessed by the density D _{us.l of the blur mask} can be attenuated, and the X-rays can be _adjusted according to each region in the X-ray image. The granular noise of the image can be effectively attenuated, and deterioration of other image quality performance can be suppressed to the minimum. Further, the apparatus for carrying out this method is not particularly complicated, and the calculation time can be set within a sufficiently acceptable range.

[Brief description of drawings]

FIG. 1A is a graph showing an example calculated in the spatial frequency domain using the X-ray image processing method of the present invention, and FIG. 1B shows an example of a function of the attenuation coefficient β ₁ with the image density as a variable. 2 is a graph, FIG. 2 is a perspective view showing an example of an X-ray image processing apparatus for carrying out the X-ray image processing method of the present invention, and FIGS. 3A to 3C are different from each other in the arithmetic section shown in FIG. It is a block diagram showing an example of composition. 1 …… Original photograph 2,13 …… Motor, 3 …… Photo transport means 4 …… Laser, 6 …… Rotating polygon mirror 10 …… Concentrator 11 …… Photomultiplier 16 …… Amplifier, 17 …… A / D converter 18 …… Calculator, 19 …… Memory 20 …… Image display device

─────────────────────────────────────────────────── ─── Continuation of the front page (51) Int.Cl. ⁶ Identification code Internal reference number FI technical display location 9163-4C A61B 6/00 350 N

Claims (5)

[Claims] 1. Scanning an original photograph on which X-ray image information is recorded, reading the original image density at each scanning point, and then reproducing each X-ray image as a visible image on a copy photograph, etc. One of the original image densities in the surrounding predetermined range corresponding to the point, or one obtained by averaging the image densities subjected to the intermediate processing in the signal representing this original image density, or obtained by changing the above-mentioned predetermined range The density of a plurality of blur masks is D _us.k (k = 1, 2, ..., N; n is an integer indicating the number of blur masks), the original image density or a signal representing the original image density is subjected to intermediate processing. Subsequent image densities are D _b1 and D _b2 , and one or a plurality of water reduction coefficients corresponding to the one or a plurality of blur masks are β.
_k (k = 1,2, ..., n), where D ′ is the image density after the arithmetic processing, at least 1 of the attenuation coefficients β _k (k = 1,2, ..., n)
The attenuation coefficient β ₁ (l is an integer within 1 to n) is a variable that is always in the range of 0 ≦ β ₁ <1 and changes in each X-ray image, and the original image density or It is a function of the image density obtained by performing intermediate processing on the signal representing the original image density, and using this attenuation coefficient β _l The X-ray image processing method is characterized in that the spatial frequency component higher than the spatial frequency component having the density D _{us.l of} the blur mask corresponding to the attenuation coefficient β _l is attenuated by performing the calculation according to 2. The original image densities or image densities D _b1 and D _b2 after intermediate processing of the signals representing the original image densities are all the same original image densities. The X-ray image processing method according to claim 1. 3. An image density obtained by subjecting the original image density or a signal representing the original image density to intermediate processing.
Claims ₁ and ₂ are characterized in that both D _b1 and D _b2 have the same image density obtained by applying the same intermediate processing to the signal representing the original image density.
The X-ray image processing method according to the item. 4. An image density obtained by subjecting the original image density or a signal representing the original image density to intermediate processing.
One of D _b1 and D _b2 is the original image density or an image density obtained by subjecting the signal representing the original image density to the first intermediate processing, and the other is a second image density representing the original image density. The image density according to claim 1, wherein the image density has been subjected to the intermediate processing of
Line image processing method. 5. An original photograph on which X-ray image information is recorded is scanned, the original image density at each scanning point is read, a signal representing the original image density is processed by an arithmetic unit, and the processed image is obtained. Based on the signal representing the concentration,
In an X-ray image processing apparatus for reproducing an X-ray image as a visible image on a copy photograph or the like, the arithmetic unit corresponds to each scanning point and has an original image density within a predetermined surrounding range or a signal representing the original image density. D _us.k (k = 1,2, ..., n; n) is obtained by averaging the image densities obtained by performing the intermediate processing on the image density of one or a plurality of blur mask densities obtained by changing the predetermined range. Is an integer indicating the number of blur masks), the original image density or an image density obtained by subjecting the signal representing the original image density to intermediate processing is D _b1 , D _b2 , one corresponding to each of the one or more blur masks. Alternatively, when a plurality of attenuation coefficients are β _k (k = 1,2, ..., n) and the image density after the arithmetic processing is D ′, the attenuation coefficients β _k (k = 1,2, ..., n) ) At least 1
The attenuation coefficient β _L (l is an integer within 1 to n) is a variable that is always in the range of 0 ≦ β ₁ <1 and changes in each X-ray image, and the original image density or It is a function of the image density obtained by performing intermediate processing on the signal representing the original image density, and using this attenuation coefficient β _l An X-ray image processing apparatus, characterized in that the calculation is performed in accordance with