JPH0481982A - Processor for digital radiation image signal - Google Patents

Abstract

PURPOSE:To shorten a processing time for an interpolating operation, while securing the picture quality by dividing an image into plural areas and changing an interpolating operation expression in the respective areas, in the interpolating operation executed in order to change a picture element. CONSTITUTION:A CPU 15 performs as interpolating operation to radiation image information (image data) stored in an image memory 14, and simultaneously, performs various image processings being suitable for a diagnostic purpose, and the image data to which the image processing is performed is stored in the image memory 14 again. In such a state, at the time of executing the interpolating operation in order to change the number of picture element, an interpolating operation expression is changed at every image area divided into plural areas in the image, therefore, it becomes possible to execute a higher-order interpolating operation for attaching importance to the picture quality in accordance with the image area, and to execute a lower-order interpolating operation in order to shorten the calculation time. In such a way, the calculation time can be shortened, while securing a necessary picture quality.

Description

[Detailed Description of the Invention] <Industrial Application Field> The present invention relates to a processing device for digital radiation image signals, and more specifically, to reduce the processing speed of interpolation calculations performed to change the number of pixels while maintaining image quality. Regarding devices that can be used.

<Conventional technology> Radiographic images such as X-ray images are often used for disease diagnosis. irradiate,
This generated visible light, which was then irradiated onto a film using silver salt to develop the film, similar to ordinary photography.
So-called radiographs have been widely used.

However, in recent years, methods have been devised to directly extract images from the phosphor layer without using a film coated with silver salt.

In this method, the radiation transmitted through the subject is absorbed by a phosphor, and then this phosphor is excited with light or thermal energy, so that the radiation energy accumulated by the phosphor is converted into fluorescence. There is a method of emitting the fluorescent light and converting the fluorescent light to obtain an image signal.

Specifically, for example, U.S. Pat. has been done. This method uses a radiation image conversion panel with a stimulable phosphor layer formed on a support.The stimulable phosphor layer of this conversion panel is exposed to radiation that has passed through the object, and A latent image is formed by accumulating radiation energy corresponding to the degree of penetration, and then
By scanning this photostimulation layer with photostimulation excitation light, the accumulated radiation energy is emitted and converted into light,
This optical signal is photoelectrically converted to obtain a radiation image signal.

The radiographic image signals obtained in this way can be used as they are, or after being subjected to image processing, such as silver halide film, CR
It is often output to a T or the like for visualization, or digitized for image processing by a computer. Also,
The digitized radiation image signal is stored in a semiconductor storage device,
Magnetic storage device.

The image may be stored in an image storage device such as an optical disk storage device or a magneto-optical storage device, and then taken out from these image storage devices as needed and output to a silver halide film, CRT, etc. for visualization.

In addition, the silver halide film that records radiographic images is coated with a laser beam.
There is also a method of irradiating light from a light source such as a fluorescent lamp to obtain transmitted light through a silver halide film, photoelectrically converting the transmitted light to obtain a radiation image signal, and further digitizing the transmitted light.

As described above, the configuration of the apparatus for obtaining digital radiographic image signals from a silver halide film on which a radiographic image has been recorded is to scan a light beam one-dimensionally on the silver halide film, and at the same time scan the silver halide film in the scanning direction. A silver halide film with a radiation image recorded on the side of a transparent drum containing a light source may be configured to be transported in a direction perpendicular to the light source and detect the transmitted light with a photodetector installed on the opposite side of the light source. pasting,
Some devices are configured to simultaneously rotate the drum and move an aperture that guides transmitted light to a photodetector parallel to the rotation axis of the drum.

<Problem to be solved by the invention> By the way, when making a diagnosis based on radiographic images, there are cases where it is desired to enlarge the image to a larger size or reduce it to a smaller size and reproduce it. It is common practice to expand or reduce the number of pixels by interpolation, which is an operation in which the signal is converted into a continuous signal and then discretized again at a smaller or larger sampling pitch (Japanese Patent Laid-Open No. 175575/1983, etc.) reference).

In such interpolation calculations, it is preferable to perform high-order interpolation calculations so that high image quality can be maintained even after changing the number of pixels, but in this case, the interpolation calculations become complex and the calculation time increases. There is a problem in that, in an attempt to shorten calculation time, image quality deteriorates when calculations or relatively simple low-order interpolation calculations are performed.

However, especially in X-ray images for disease diagnosis, there are areas where radiation does not actually penetrate the human body, and it is wasteful to perform high-order interpolation calculations on such areas, but conventional methods Although various interpolation calculation formulas are used in interpolation calculations for radiation image signals, the interpolation calculation formulas are uniform within one image (rRest
oring 5line Interpolation
of CT 1magesJIEEE TRANSA
CTIONON MED [CAL (MAG [NG, V
OL, MI-2, NO, 3, 5 EPT [EMBER19
83, etc.), it was not possible to shorten the processing time of interpolation calculations while ensuring image quality.

The present invention was made in view of the above-mentioned problems, and it is possible to separate areas within an image where high-order interpolation calculations are performed to maintain high image quality and areas where low-order interpolation calculations are performed to reduce calculation time. The object of the present invention is to provide a processing device that can both ensure image quality and shorten calculation time by separating the data.

<Means for Solving the Problems> Therefore, a digital radiation image signal processing apparatus according to the present invention is configured as shown in FIG.

In FIG. 1, the interpolation calculation means performs interpolation calculation on pixel data of a digital radiation image to change the number of pixels.

Further, the image dividing means divides the image before the interpolation calculation into a plurality of regions. The supplementary calculation formula changing means changes the interpolation calculation formula in the interpolation calculation means for each of the plurality of regions of the image divided by the image division means.

<Operation> According to the digital radiation image processing device having such a configuration,
When performing interpolation calculations to change the number of pixels, the interpolation calculation formula is changed for each divided image area within the image, so it is possible to perform high-order interpolation calculations that emphasize image quality depending on the image area. Furthermore, it is possible to perform low-order interpolation calculations to reduce calculation time, and it is possible to reduce calculation time while ensuring the required image quality.

<Example> The present invention will be explained in detail below.

FIG. 2, which shows one embodiment, shows a radiation image information recording and reading device including a digital radiation image signal processing device according to the present invention, which is applied to chest radiography of a human body for medical use. .

Here, the radiation source l is controlled by the radiation control device 2 and emits radiation (
(Generally, X-rays) are irradiated. The recording/reading device 3 is equipped with a conversion panel 4 on a surface facing the radiation source 1 with the subject M in between, and the conversion panel 4 converts energy according to the radiation transmittance distribution of the subject M with respect to the radiation dose irradiated from the radiation source 1. is accumulated in the photostimulable layer, and a latent image of the subject M is formed there.

The conversion panel 4 is provided with a stimulable layer on a support by vapor deposition of a stimulable phosphor or coating of a stimulable phosphor paint, and the stimulable layer blocks out adverse effects and damage caused by the environment. It is shielded or covered with a protective member in order to do so.

As the stimulable phosphor material, for example, JP-A-61-7
Materials such as those disclosed in Japanese Patent Laid-open No. 2091 or Japanese Patent Application Laid-open No. 75200/1986 are used.

A light beam generator (gas laser, solid-state laser, semiconductor laser, etc.) 5 generates a light beam with controlled output intensity,
The light beam reaches the scanner 6 via various optical systems, is deflected there, and further deflects its optical path by a reflecting mirror 7, and is guided to the conversion panel 4 as stimulated excitation scanning light.

The condenser 8 has a condensing end, which is an optical fiber, located close to the conversion panel 4 where the stimulated excitation light is scanned, and has a condensing end that is proportional to the latent image energy from the conversion panel 4 scanned by the light beam. Receives stimulated luminescence of luminous intensity. 9 is a light condenser 8
It is a filter that allows only light in the stimulated emission wavelength range to pass from the light introduced from the filter 9, and the light that has passed through the filter 9 is
The light enters the photomultiplier 10 and is photoelectrically converted into a current signal corresponding to the incident light.

The output current from the photomultiplier 10 is transferred to the current/voltage converter 1
After being converted into a voltage signal in step 1 and amplified in amplifier 12,
The A/D converter 13 converts it into digital data (digital radiation image signal). This digital data is then sequentially stored in one image memory 14.

15 is a CPU that performs interpolation calculations on the radiation image information (image data) stored in the image memory 14, and at the same time performs various image processing suitable for diagnostic purposes (for example, gradation processing, 2 frequency processing, movement 1 rotation, , statistical processing, etc.), and the image data that has been subjected to image processing is stored in the image memory 14 again.

16 prints the radiation image signal in the image memo January 4 to the printer 1.
This is an interface for transmitting data to 7.

18 is a reading gain adjustment circuit, and this reading gain adjustment circuit 18 adjusts the light beam intensity of the light beam generating section 5;
The gain of the photomultiplier 10 is adjusted by adjusting the power supply voltage of the photomultiplier high-voltage power supply 19, the gain adjustment of the current/voltage converter 11 and the amplifier 12, and the input dynamic range of the A/D converter 13 are adjusted. The reading gain of the signal is adjusted comprehensively.

The image memory 14. CPU15. interface 1
6 is more specifically constructed as shown in FIG.

That is, the digital radiographic image signal from the A/D converter 13 is processed to divide the image into a plurality of regions according to pixel data in the image dividing section 28 as an image dividing means, and at the same time, the digital radiation image signal is divided into stages. A tone processing unit 22 performs gradation processing,
The image data after the gradation processing is stored in the line memory 21 constituting the image memory 14.

The interpolation calculation section 26 as an interpolation calculation means converts the pixel data after gradation processing stored in the line memory 21 into the comparison section 24 (as an interpolation calculation formula changing means) determined by the image division section 28. By comparing the positional information regarding the boundary of the image area, the switch SW is changed, and the interpolation work 25 is used as a work area for calculation, and the interpolation work 25 is controlled by the control logic 23 for each image area divided by the image dividing unit 28. An interpolation calculation is performed using a predetermined interpolation calculation formula.The pixel data after such interpolation calculation is stored in an output line memory 27 that constitutes the image memory 14 together with the line memory 21.

In FIG. 3, it is assumed that the divided image area is two areas, and furthermore, it is assumed that nearest neighbor interpolation processing that does not require calculation is performed on one of the areas, so switch SW An interpolation calculation unit 26' is not provided in one of the branches, but an interpolation calculation unit 26' may be provided here as well, or the interpolation calculation unit 26' may be shared, and the control logic 23 can calculate the interpolation calculation formula '' for each region. may be changed.

Further, although FIG. 3 shows a configuration in which interpolation processing is performed after gradation processing, this order may be reversed.

Note that 29a is a ROM attached to the CPU 15, and 29b is a RAM also attached to the CPU 15.

The digital radiation image signal stored in the output line memory 27 and subjected to gradation processing and interpolation calculation is outputted to the printer 17 via the interface 16 and hard-copied. For example, the fourth
It is configured as shown in the figure.

Furthermore, what is connected via the interface 16 is the CR
The storage device may be a monitor such as T, or a storage device (filing system) such as a semiconductor storage device.

In the printer 17 shown in FIG.
The digital radiation image signal read out via the interface 16 is first subjected to various signal correction processes in the signal correction circuit 31 via the buffer memory 30, and then sent to the D
/A converter 32 converts the signal into an analog signal. Then, in order to modulate the laser beam according to this analog signal, the output of the D/A converter 32 is input to a modulator drive circuit 33, and this modulator drive circuit 33 adjusts the output level of the D/A converter 32. A corresponding drive voltage is output to the optical modulator 34.

The optical modulator 34 modulates the laser light emitted from the laser light source 35 according to the image signal level based on the drive voltage, and the modulated laser light is transmitted to a motor (not shown).
Therefore, the light is reflected by the polygonal reflecting surface of the rotating deflection mirror (polygon mirror) 36 and distributed in the main scanning direction.

The reflected light from the deflection mirror 36 passes through an fθ lens 37 and is adjusted to a constant scanning speed, and the scanning light is received by a recording medium (photosensitive material) 38 that is conveyed in the sub-scanning direction, whereby recording is performed. A two-dimensional radiographic image is recorded on the medium 38, and then the recording medium 38 is developed to obtain a hard copy of the digital radiographic image.

Next, an example of the interpolation calculation according to the present invention performed based on the hardware configuration shown in FIG. 3 will be described.

First, as a first example, an image is generated as follows for a radiation image signal (2048 pixels x 464 pixels) of a normal human chest side surface obtained using the record reading bag f13 shown in FIG. Two areas (image area l.

It was divided into image areas φ).

That is, first, a histogram of the entire image is obtained, and as shown in FIG. 5, a threshold value St is determined that separates the signal value group having a peak at the level closest to the maximum signal value in the histogram from other signal values. Set.

Here, the threshold value St is used to divide the image of the side surface of the chest of a normal human body into a transparent part (an area with little image information) and a transparent part of the human body (an area containing a lot of image information), as shown in FIG. This is the threshold value.

Next, by determining whether or not the pixel data exceeds the threshold St for each line of image data (in the X direction shown in FIG. 6), the image area φ( Boundary pixels 0'z, 1), (X+□, 1) as shown in FIG. ,
(Xt+, 2) (X21. 2), ... is detected. In addition, at the same time as this image division processing, data conversion is performed on each pixel data using a gradation conversion curve set based on the above-mentioned histogram, and appropriate gradation processing is performed to convert the image signal 0 (I). Obtained.

Then, interpolation processing was performed on the image signal 0(I) after the gradation processing to obtain an image signal A(I) whose image size was expanded to 4096 pixels x 928 pixels. The interpolation calculation for pixel enlargement was performed by changing the interpolation calculation formula as follows based on the two image regions l and φ divided in advance based on the histogram as described above.

Image region φ→Nearest neighbor interpolation Image region l→Cubic convolution interpolation In other words, for the image region φ, where the radiation is only partially removed, the nearest neighbor is used which requires short calculation time, although image quality deterioration is inevitable. We use cubic convolution interpolation, which is a high-order interpolation calculation that increases the calculation time compared to nearest neighbor interpolation, but can suppress image quality deterioration, for the image region l, which is the transparent part of the human body, by enlarging the pixels by interpolation. This is designed to reduce the calculation time by performing Jt simple interpolation calculations on parts unrelated to diagnosis while suppressing image quality deterioration in the parts necessary for diagnosis.

Next, image area 1. The image signal A (I) of the first embodiment obtained by changing the interpolation calculation formula by φ and performing the interpolation calculation is printed using the printer 17 shown in FIG.
A hard copy CA (I) was obtained by printing on a silver halide film of inch XL finch.

On the other hand, as Comparative Example 1 to be compared with the image signal A (I) which has been subjected to the interpolation processing according to the present invention, the image signal 0 (I) obtained in the same manner as in the first embodiment is divided into image regions. The image signal P (I) of Comparative Example 1 is obtained by performing nearest neighbor interpolation over the entire image area without performing any ) was printed on a silver salt film in the same manner as in the first example above to obtain a hard copy CP (I).

Furthermore, as a second comparative example to be compared with the first example, the image signal 0(I) obtained in the same manner as in the first example was subjected to cubic multiplication over the entire image area without dividing the image area. Convolution interpolation was performed to obtain an image signal Q (I) of twice the number of pixels, 4096 pixels x 928 pixels, and the image signal Q (I) was printed on a silver halide film in the same manner as in the first embodiment. and hard copy CQ
(I) was obtained.

Table 1 Hard copy CA(I) of the first embodiment of the present invention obtained as described above, and the hard copy CA(I)
Hard copy CP (I), CQ obtained for comparison
A visual comparison of the image quality of (I) resulted in the results shown in Table 1.

That is, the image quality of the hard copy CA (I) of Example 1 and the hard copy CQ (I) of Comparative Example 2, which was subjected to cubic convolution interpolation over the entire area, were both good; The hard copy CP (I) of Comparative Example 1 subjected to nearest neighbor interpolation had significantly inferior image quality. This is because in the first embodiment and comparative example 2, the diagnostic region is processed using the same high-order interpolation calculation, whereas the nearest - When neighbor interpolation is performed, the pixels are enlarged twice by such interpolation, so that blocks of 2 pixels x 2 pixels stand out in a mosaic pattern on the human body image.

Table 1 also shows the image signal A (■) of the first embodiment,
Image signal P(I) of comparative example 1, image signal Q of comparative example 2
The time required for interpolation calculation to obtain each of (I) is shown as a relative value. Example 1 requires longer calculation time than Comparative Example 1, but the calculation time is shorter than Comparative Example 2. is made of.

As mentioned above, radiation can be extracted by performing calculations or simple interpolation calculations for the parts, and by applying high-order interpolation that can suppress image quality deterioration to the parts that pass through the human body, which are necessary for diagnosis. The time required for interpolation calculation can be shortened while ensuring the image quality required for the first embodiment, and it can be said that the first embodiment is a comprehensively superior interpolation calculation process compared to Inversion 1 and 2.

Next, as a second embodiment according to the present invention, image signal 0(I) is obtained in the same manner as in the first embodiment, and this image signal 0(I) is obtained in the same manner as in the first embodiment.
For I), change the interpolation calculation in the image area φ, l as follows to double the image size 4096 pixels x 492
The image signal B(I) was obtained by enlarging the image to 8 pixels.

Image area φ → Nearest neighbor interpolation Image area 1 → Bell spline interpolation (β = 0.7) Then, the image signal B (I) is printed on a silver halide film in the same manner as in Example 1, and a hard copy CB is obtained. (I) was obtained. Furthermore, the above β
is a positive real number β that determines the point spread function F(ω, β) of the Peruvian spline, and it is known that the spatial frequency characteristics after interpolation can be emphasized or attenuated depending on changes in β. . In the case of using the Peruvian spline interpolation calculation as described above, it is preferable that the β be about 0.4<β≦1.5.

In addition, since bell spline interpolation (β = 0.7>) was used in the image region l in the second embodiment, bell spline interpolation (β = 0.7) was used over the entire image region as comparative example 3. With double the number of pixels, 4096 pixels x 928 pixels
Obtain the image signal R' (I) of the pixel, and use this image signal R
, (, I) were printed on a silver salt film in the same manner as in Example 1 to obtain a hard copy CR(I).

Then, the image quality of the hard copies CB (I), CR (1), and the hard copy CP (I) of Comparative Example 1 described above was compared by visual evaluation, and the results shown in Table 2 were obtained. . Visual image quality evaluation (=, C, B(1
,)- and CR(I) are both good,
The image quality of CP (I) using nearest neighbor interpolation was significantly inferior to the above two hard copies. This is due to the doubling of pixels by nearest neighbor interpolation, which makes a 2 pixel x 2 pixel block stand out in a mosaic pattern on the human body image. Although the second example B (I) was longer than the comparative example IP (I), the processing time was shorter than that of the comparative example 3R (I).

In this way, in the second example as well, the processing time for interpolation calculation is shortened without degrading image quality, and the processing is overall superior to Comparative Example 1.3.

Table 2 Furthermore, as a third example, a radiation image signal (
An averaged profile was created from 2048 pixels x 464 pixels), and the image area was divided into two (image area 11 image area φ) based on this averaged profile.

That is, as shown in FIG. 7, an averaged profile in the horizontal direction (X direction) is obtained, and an image area φ with little image information corresponding to the flat part of this averaged profile and image information corresponding to other parts are Boundary pixel columns X1 and X2 are set to vertically separate the containing image region l.The boundary pixel columns X1 and X2 correspond to the image region and the boundary pixel column X2 to the left of the boundary pixel column X1 in FIG. The image area on the right in FIG. 7 (image area φ) does not include at least the transparent part of the human body, and the area surrounded by the boundary pixel rows X1 and X2 (image area 1) also includes a transparent part. Although the image area φ is an area unrelated to diagnosis, the image area 1 includes an area necessary for diagnosis.

Next, each pixel data was subjected to the above-mentioned averaging blowdown conversion and appropriate gradation processing to obtain an image signal 0 (■).

This image signal 0 (■) is subjected to interpolation calculation and enlarged to twice the image size of 4096 pixels x 4928 pixels to obtain image signal A (II).
The interpolation calculation formula was changed as follows for image area φ and image area 1, which are divided with X2 as the boundary.

Image area φ → Nearest neighbor interpolation Image area l → Linear interpolation Next, the image signal A (II) is printed on a 14 inch x 1 inch silver halide film using the printer 17 shown in FIG. Copy CA (II) was obtained.

On the other hand, as a fourth comparative example of the third embodiment, an image signal ○(
Nearest neighbor interpolation is applied to the entire image area of I[) to produce an image signal P of 4096 pixels x 928 pixels.
(I[) was obtained and printed on a silver salt film in the same manner as in Example 3 to obtain a hard copy CP (■).

Further, as Comparative Example 5, linear interpolation was performed on the entire image area of the image signal 0 (■5p) to obtain an image signal Q (II) of 4096 pixels x 928 pixels, and this was carried out in the same manner as in Example 3. A hard copy CQ (II) was obtained by printing on a silver halide film.

And the above hard copy CA (II), CP
Regarding the image quality of '(II) and CQ(II),
When a comparison was made by visual evaluation, as shown in Table 3, the image quality of both CA(In) and CQ(I[) was good, and the image quality of CP(II) was significantly inferior to the others.

This is because CP (I) or nearest neighbor interpolation is used to expand the pixels by 2 times, so 2 pixels x
This is because the two-pixel block stands out on the mosaic.

Table 3 In addition, as shown in the relative processing time in Table 3, the processing time was shortened in the third example as well, although the image quality was good, and overall it was superior to Comparative Examples 4 and 5. Interpolation calculations can be performed.

Next, as a fourth example, for the image signal 0 (II) obtained in the same manner as in the third example, interpolation calculation is performed in the image area φ,1 divided by the boundary pixels X1 and X2 as follows. By changing the formula, an image signal B (It) of 4096 pixels x 928 pixels was obtained.

Image area φ → Nearest neighbor interpolation Image area l → Cubic convolution interpolation Then, the image signal B (I[) is printed on a silver halide film as in the third embodiment, and a hard copy CB is obtained.
(I[) was obtained.

On the other hand, as a comparison target for the fourth embodiment, the image signal 0 (II) is subjected to cubic convolution interpolation over the entire image area, and the image signal R (II) is twice as large as 4096 pixels x 928 pixels. ) (Comparative Example 6), and the image signal R(II) was printed on a silver halide film in the same manner as in Example 4 to obtain a hard copy CR(I[).

Hard copy CB (In), CP (II)
) and CR(It) were compared by visual evaluation, and as shown in Table 4, CB(It)
Although the image quality of both F) and CR(I[) is good,
On the other hand, the image quality of CP (It) was significantly inferior because the 2-pixel x 2-pixel blocks stood out in a mosaic pattern due to the doubling of pixels by nearest neighbor interpolation. Regarding the processing time of the interpolation calculation, as shown in Table 4, the fourth example B (■) is different from the comparative example 4P (II
), but the image quality is at the same level as Comparative Example 6
The computation time can be reduced compared to R(I[).

Table 4 Note that the nearest neighbor interpolation, Peruvian spline interpolation, linear interpolation, and cubic convolution interpolation used in each interpolation operation shown above are all known interpolation functions (rRestoringSpline I
terpolation of CT Ima
gesJ IEEEETRANSACTION ON M
EDICAL IMAGING, VOL, MI-2, N
O, 3゜SEPTEMBER1983, rcubic
Convolution for Digital Im
ageProcessing IEEE TRANS
ACTION 0NACUSTIC3, AND 5I
GNAL PROCESSING, VOL, ASSP
-29°NO, 61981, etc.).

As is clear from Tables 1 to 4 above, according to this embodiment, images are preliminarily divided into diagnostic areas (areas containing a lot of image information) and radiation areas (image information For diagnosis areas, Peruvian spline interpolation is used to divide the diagnostic area into areas with a small amount of image data (areas with a small amount of image data).

High-order interpolation calculation formulas such as linear interpolation and cubic convolution interpolation are selected.On the other hand, the nearest method is used for the radiation area (or outside of irradiation), which reduces the calculation time although the image quality deteriorates. Since a relatively low-order interpolation calculation formula such as neighbor interpolation or linear interpolation is selected, it is possible to reduce the processing time required for interpolation calculations while suppressing deterioration of image quality, and improve diagnostic efficiency.

Note that the detection of the area for changing the interpolation calculation formula may be performed at the same time as the gradation processing, as shown in the above embodiment, or may be performed using information necessary to determine the gradation processing conditions (histogram, If this is done at the same time as the profile), the processing time can be further reduced.

In addition to dividing the area in which the interpolation formula needs to be changed based on the histogram or profile as described above, it is also possible to divide the area by calculating the contour in the image based on the differential value of pixel data or thinned out pixel data. Moreover, as described in Japanese Patent Application Laid-Open No. 58-67240, a low-energy When performing "pre-reading" using excitation light, the area may be determined based on the "pre-reading" image information, and it may be applied to the "main reading" image. Furthermore, patterns for dividing an image into multiple regions may be stored in advance, and in this case, it is also possible to store multiple division patterns in advance and allow the operator to select from among them. Furthermore, the human body image area may be further divided into a plurality of areas, thereby dividing the area into three or more areas.

In this example, a system for obtaining a digital radiation image using a stimulable phosphor or a system for obtaining a digital radiation image signal by photoelectrically converting the transmitted light of a silver halide film on which a radiation image is recorded is used. However, the configuration for obtaining digital radiation image signals is not limited.

Further, the digital radiation image signal subjected to the interpolation calculation according to the present invention may be immediately hard-copied by the printer 17 as described above, but it may be reproduced on a CRT or temporarily stored in a filing system. read it out and make a hard copy when necessary, or copy it to a CR
It may be displayed on T.

<Effects of the Invention> As explained above, according to the present invention, in the interpolation calculation performed for pixel change, the image is divided into multiple areas and the interpolation calculation formula is changed in each area. In areas that contain a large amount of image information, high-order interpolation calculations are performed to ensure image quality, while in areas with little image information, such as radiation spots, low-order interpolation calculations are performed to reduce processing time. Therefore, it is possible to both ensure image quality and shorten processing time in the process of changing the number of pixels by interpolation calculation, and this has the effect of improving diagnostic efficiency, especially in radiographic images for disease diagnosis.

[Brief explanation of drawings]

Fig. 1 is a block diagram showing the configuration of the present invention, Fig. 2 is a system block diagram showing an embodiment of the invention, and Fig. 3 is a block diagram showing the configuration of the present invention.
FIG. 4 is a system block diagram showing the configuration of the printer shown in FIG. 2. FIG. 5 is a detailed system block diagram of the part that performs interpolation calculations in the illustrated system. FIG. FIG. 6 is a diagram showing an example of the histogram used; FIG. 6 is a diagram for explaining image segmentation using the histogram shown in FIG. 5; FIG. It is a line diagram. 14... Image memory 15... CPU 16
...Interface 17...Printer 21
．． 27... Line memory 22... Gradation processing section
23... Control logic 24... Comparison section 25.
...Interpolation work 26...Interpolation calculation section 28...
・Image division part

Claims (1)

[Scope of Claims] A digital radiation image signal processing device that changes the number of pixels by performing an interpolation calculation on a radiation image signal consisting of digital data for each pixel, the processing device changing the number of pixels by performing an interpolation calculation on the pixel data of the digital radiation image. interpolation calculation means for changing the interpolation calculation means; image division means for dividing the image before the interpolation calculation into a plurality of regions; and interpolation for changing the interpolation calculation formula in the interpolation calculation means for each of the plurality of regions of the image divided by the image division means. 1. A digital radiation image signal processing device comprising: arithmetic expression changing means; and a digital radiation image signal processing device.