JP2852795B2 - Digital radiation image signal processing device - Google Patents

Description

The present invention relates to a digital radiation image signal processing device,
More specifically, the present invention relates to an apparatus that can reduce the processing speed of an interpolation operation performed to change the number of pixels while ensuring image quality.

<Prior Art> Radiation images such as X-ray images are widely used for diagnosing diseases and the like. In order to obtain such X-ray images, X-rays transmitted through a subject are applied to a phosphor layer (fluorescent screen). A so-called radiograph, which is obtained by irradiating a visible light to thereby generate a visible light and irradiating the visible light to a film using a silver salt in the same manner as a normal photograph and developing the film, has been conventionally used.

However, in recent years, a method has been devised for directly taking out an image from the phosphor layer without using a film coated with a silver salt.

As this method, the radiation transmitted through the subject is absorbed by the phosphor, and then the phosphor is excited by, for example, light or heat energy, so that the radiation energy accumulated by the absorption by the phosphor is converted into fluorescence. There is a method of emitting an image and photoelectrically converting the fluorescence to obtain an image signal.

Specifically, for example, U.S. Pat.
JP-A-5-12144 discloses a radiation image conversion method using a stimulable phosphor and using visible light or infrared light as stimulating excitation light. This method uses a radiation image conversion panel in which a stimulable phosphor layer is formed on a support, and irradiates the stimulable phosphor layer of the conversion panel with radiation transmitted through a subject.
A latent image is formed by accumulating radiation energy corresponding to the radiation transmittance of each part of the subject, and thereafter, the radiation energy is emitted by scanning the photostimulable layer with photostimulated excitation light, and this is emitted. The optical signal is photoelectrically converted to obtain a radiation image signal.

The radiation image signal thus obtained may be used as it is or after being subjected to image processing, to a silver halide film, CRT
Etc. and visualized, but often digitized for computer image processing. Further, the digitized radiation image signal is stored in an image storage device such as a semiconductor storage device, a magnetic storage device, an optical disk storage device, and a magneto-optical storage device. In some cases, it is output to a silver halide film, a CRT or the like and visualized.

Also, the silver halide film on which the radiation image is recorded is irradiated with light from a light source such as a laser or a fluorescent lamp to obtain the transmitted light of the silver halide film, and the transmitted light is photoelectrically converted to obtain a radiation image signal. There are also ways to digitize.

As a configuration of the device for obtaining a digital radiation image signal from a silver halide film that has recorded a radiation image as described above,
A structure in which a light beam is one-dimensionally scanned on a silver halide film, and at the same time, the silver halide film is conveyed in a direction perpendicular to the scanning direction, and transmitted light is detected by a photodetector provided on a side opposite to the light source. Or, a silver halide film on which a radiation image is recorded is attached to the side of a transparent drum containing a light source, and at the same time as the drum is rotated, an aperture for guiding transmitted light to a photodetector is rotated by the rotation axis of the drum. , And the like.

<Problems to be Solved by the Invention> By the way, in the diagnosis based on the radiographic image, there are cases where it is desired to enlarge the image to a larger size or reduce the size to a smaller size and reproduce the image. It is a common practice to increase or decrease the number of pixels by interpolation, which is an operation of discretizing at a smaller or larger sampling pitch after conversion to a continuous signal (Japanese Patent Laid-Open No. 63-175575, etc.). reference).

In such an interpolation operation, it is preferable to perform a higher-order interpolation operation so that high image quality can be maintained even after the number of pixels is changed. However, in this case, the interpolation operation becomes complicated and the calculation time becomes longer. Therefore, if a low-order interpolation operation, which is relatively easy to calculate, is performed to shorten the calculation time, the image quality will be degraded.

However, especially in the case of X-ray images for disease diagnosis, etc., there is a transparent region where radiation does not actually pass through the human body,
Although it is useless to perform a higher-order interpolation calculation on such a region, conventionally, various interpolation calculation expressions are used in the interpolation calculation on the radiation image signal, but the interpolation calculation expression is used in one image. Because it was uniform ("Restor
ing Spline Interpolation of CT Images '' IEEE TRANSA
CTION ON MEDICAL IMAGING, VOL.MI-2, NO.3, SEPTEMBER
1983), it was not possible to reduce the processing time of the interpolation operation while ensuring the image quality.

The present invention has been made in view of the above problems, and includes, in an image, a region where high-order interpolation is performed to maintain high image quality and a region where low-order interpolation is performed to reduce the calculation time. It is an object of the present invention to provide a processing device that can achieve both image quality assurance and reduction in calculation time by dividing.

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

In FIG. 1, the interpolation calculation means changes the number of pixels by performing interpolation calculation on pixel data of a digital radiation image.

Further, the image dividing means divides the image before the interpolation calculation into a plurality of regions based on the histogram of the pixel data and / or profile information. Then, the interpolation calculation formula changing means changes the interpolation calculation formula in the interpolation calculation means for each of a plurality of regions of the image divided by the image dividing means.

<Operation> According to the digital radiation image processing apparatus having such a configuration, when performing an interpolation operation for changing the number of pixels, for example, a medical image is required for diagnosis based on the histogram of pixel data and / or profile information. Since the interpolation formulas are changed for each area by dividing them into areas and areas that are not so, high-order interpolation calculations with an emphasis on image quality can be performed according to the image area, and low-order interpolation calculations can be performed to shorten the calculation time. Interpolation can be performed, and the calculation time can be reduced while ensuring the required image quality.

<Examples> Examples of the present invention will be described below.

FIG. 2 shows an embodiment of a radiographic image information recording / reading apparatus including a digital radiographic image signal processing apparatus according to the present invention, which is applied to a chest radiography of a human body for medical use. .

Here, the radiation source 1 is controlled by the radiation control device 2 and irradiates a radiation (generally, an X-ray) toward a subject (a human chest or the like) M. The recording and reading device 3 includes a conversion panel 4 on a surface facing the radiation source 1 with the subject M interposed therebetween.
The conversion panel 4 accumulates energy according to the radiation transmittance distribution of the subject M with respect to the irradiation radiation amount from the radiation source 1 in the photostimulable layer, and forms a latent image of the subject M there.

The conversion panel 4 has a photostimulable layer provided on a support by vapor deposition of a photostimulable phosphor or application of a photostimulable phosphor paint, and the photostimulable layer blocks adverse effects and damage due to the environment. To be covered or covered by a protective member. As the stimulable phosphor material, for example, JP-A-61-1
Materials such as those disclosed in 72091 or JP-A-59-75200 are used.

A light beam generator (gas laser, solid-state laser, semiconductor laser, etc.) 5 generates a light beam whose emission intensity is controlled, and the light beam reaches a scanner 6 via various optical systems, where it is deflected. Then, the optical path is further deflected by the reflecting mirror 7 and guided to the conversion panel 4 as stimulating excitation scanning light.

The light collector 8 has a light collecting end which is an optical fiber positioned close to the conversion panel 4 on which the stimulating excitation light is scanned, and is proportional to the latent image energy from the conversion panel 4 scanned by the light beam. The photostimulable light having the light emission intensity is received. Reference numeral 9 denotes a filter that passes only light in the photostimulated emission wavelength region from the light introduced from the light collector 8, and the light that has passed through the filter 9 enters the photomultiplier 10 and corresponds to the incident light. The current signal is photoelectrically converted into a current signal.

The output current from the photomultiplier 10 is a current / voltage converter 11
After being converted to a voltage signal by the amplifier and amplified by the amplifier 12, the A / D
Digital data (digital radiation image signal) by converter 13
Is converted to Then, the digital data is sequentially stored in the image memory 14.

Reference numeral 15 denotes a CPU that performs an interpolation operation on the radiation image information (image data) stored in the image memory 14 and performs various image processing (eg, gradation processing, frequency processing, movement, rotation, etc.) suitable for diagnostic purposes. , Statistical processing, etc.), and the image data subjected to the image processing is stored in the image memory 14 again.

Reference numeral 16 denotes an interface for transmitting a radiation image signal in the image memory 14 to the printer 17. Reference numeral 18 denotes a read gain adjusting circuit, which adjusts the light beam intensity of the light beam generator 5, the gain of the photomultiplier 10 by adjusting the power supply voltage of the photomultiplier high-voltage power supply 19, and the current / voltage converter. 11 and amplifier 12 gain adjustment, and
The input dynamic range of the A / D converter 13 is adjusted, and the reading gain of the radiation image signal is adjusted comprehensively.

The image memory 14, the CPU 15, and the interface 16 are more specifically configured as shown in FIG.

That is, the digital radiation image signal from the A / D converter 13 is processed by the image dividing unit 28 as an image dividing unit to divide the image into a plurality of regions in accordance with the pixel data, The gradation processing is performed by the processing unit 22, and the image data after the gradation processing is temporarily stored in the line memory 21 constituting the image memory 14.

The interpolation calculation unit 26 as the interpolation calculation means is a line memory.
The pixel data after the gradation processing stored in 21 is compared with the image dividing unit
By comparing with the position information on the boundary of the image area determined in 28, the switch SW is switched, and the interpolation work 25
Is controlled by the control logic 23 as a work area for calculation, and an interpolation calculation is performed using an interpolation calculation formula determined for each image region divided by the image division unit 28. The pixel data after the interpolation calculation is stored in the output line memory 27 constituting 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 one of the areas is subjected to the nearest neighbor interpolation processing that does not require the operation. Is not provided with an interpolation calculation unit, but an interpolation calculation unit 26 'may be provided here.
At 23, the interpolation formula may be changed for each area.

Further, in FIG. 3, although the interpolation processing is performed after the gradation processing is performed, the order may be reversed.

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

The digital radiation image signal that has been subjected to the gradation processing and the interpolation calculation stored in the output line memory 27 is output to the sprinter 17 via the interface 16 and is hard-copyed. Is configured, for example, as shown in FIG.

The connection via the interface 16 is a CRT
Or a storage device (filing system) such as a semiconductor storage device.

In the printer 17 shown in FIG. 4, the digital radiation image signal read out from the line memory 27 through the interface 16 is first subjected to various signal correction processes in the signal correction circuit 31 through the buffer memory 30. Later, D / A converter 3
It is converted to an analog signal by 2. Then, in order to modulate the laser beam according to the analog signal, the D / A converter 3
The output of 2 is input to the converter drive circuit 33, and the modulator drive circuit 33 outputs a drive voltage corresponding to the output level of the D / A converter 32 to the optical modulator. The light modulator 34 modulates the laser light emitted from the laser light source 35 in accordance with the image signal level based on the drive voltage, and the modulated laser light is rotated by a motor (not shown). The light is reflected by the 36 polygonal reflecting surfaces and is distributed in the main scanning direction.

The reflected light from the deflecting mirror 36 passes through the fθ lens 37 and is adjusted to a constant scanning speed, and the scanning light is received by a recording medium (photosensitive material) 38 conveyed in the sub-scanning direction, so that recording is performed. Recording a two-dimensional radiographic image on the medium 38,
Thereafter, by developing the recording medium 38, a hard copy of the digital radiation image can be obtained.

Next, an embodiment 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 embodiment, a radiographic image signal (2048 pixels × 2464 pixels) on the side of a normal human chest obtained using the recording and reading device 3 shown in FIG. Into two regions (image region 1, image region φ).

That is, first, a histogram of the entire image is obtained, and as shown in FIG. 5, a threshold value St for separating a signal value group having a peak at a level closest to the maximum signal value in the histogram and a signal value other than the threshold value St is set. Set.

Here, as shown in FIG. 6, the threshold St divides a transparent part (a region with a small amount of image information) and a human body transparent part (a region with a large amount of image information) in the image of the normal human chest side surface. Threshold.

Next, one line of image data (X direction shown in FIG. 6)
By determining whether or not the pixel data exceeds the threshold value St, the image area φ is a set of pixels exceeding the threshold value St.
Boundary pixels (X ₁₁ , 1), (X ₁₂ , 1) as shown in FIG. 6 for separating (a transparent portion) and an image area 1 (a human body transparent portion) which is a set of pixels equal to or less than the threshold St. ), (X ₂₁ , 2) (X ₂₂ ,
2), ... are detected. At the same time as the image decomposition processing, data conversion is performed on each pixel data using a gradation conversion curve set based on the histogram, and an appropriate gradation processing is performed to generate an image signal O (I). Obtained.

Then, the image signal O (I) after the gradation processing was subjected to interpolation processing to obtain an image signal A (I) whose image size was enlarged to 4096 pixels × 4928 pixels. The interpolation calculation for the pixel enlargement was performed by changing the interpolation calculation expression as follows by using the two image areas 1 and φ divided in advance based on the histogram as described above.

Image area φ → Nearest neighbor interpolation Image area 1 → Cubic convolution interpolation That is, for the image area φ which is a part without radiation, the nearest neighbor interpolation in which the image quality degradation cannot be avoided but the operation time is short is short. For the image area 1 which is a human body transmission part, the calculation time is longer than that of the nearest neighbor interpolation, but the cubic convolution interpolation which is a higher-order interpolation calculation that can suppress the deterioration of the image quality is performed. In this way, image quality deterioration in parts necessary for diagnosis is suppressed, and simple interpolation calculation is performed in parts not related to diagnosis to shorten the calculation time.

Next, the image signal A of the first embodiment obtained by performing the interpolation operation by changing the interpolation operation expression according to the image areas 1 and φ in this manner.
(I) was converted to a 14 inch × using a printer 17 shown in FIG.
Print and hard copy on 17-inch silver halide film
CA (I) was obtained.

On the other hand, as a comparative example 1 in which the image signal O (I) obtained in the same manner as in the first embodiment is divided into an image area as a comparative example 1 in which the image signal A (I) subjected to the interpolation operation processing according to the present invention is divided. Without performing the nearest neighbor interpolation over the entire image area, an image signal P (I) of 4096 × 4928 pixels, which is twice the number of pixels, is obtained.
(I) was printed on a silver halide film in the same manner as in the first embodiment to obtain a hard copy CP (I).

Further, as a comparative example 2 to be compared with the first embodiment, the image signal O (I) obtained in the same manner as the first embodiment is obtained by dividing the image signal O (I) over the entire image area without dividing the image area. Convolution interpolation is performed to obtain an image signal Q (I) of twice the number of pixels of 4096 pixels × 4928 pixels, and the image signal Q (I) is formed on a silver halide film in the same manner as in the first embodiment. Printing was performed to obtain a hard copy CQ (I).

The hard copy CA (I) of the first embodiment according to the present invention obtained as described above and the hard copy CP (I), CQ (I) obtained as a comparison object of the hard copy CA (I) Visual comparison of the image quality resulted in the results shown in Table 1.

That is, the hard copy CA (I) of the first embodiment and the hard copy CQ (I) of the second comparative example in which cubic convolution interpolation is performed over the entire area have good image quality, The hard copy CP (I) of Comparative Example 1 subjected to nearest neighbor interpolation had remarkably poor image quality. This is because in the first embodiment and the comparative example 2, the diagnosis area is processed by the same higher-order interpolation calculation, whereas the diagnosis order is the lower-order interpolation which is the lower-order interpolation for the entire image area. When the neighbor interpolation is performed, the pixel is doubled by the interpolation, so that a block of 2 pixels × 2 pixels stands out in a mosaic shape on the human body image.

Table 1 shows the image signal A of the first embodiment.
(I), the time required for the interpolation calculation for obtaining the image signal P (I) of Comparative Example 1 and the image signal Q (I) of Comparative Example 2 are indicated by relative values, and Example 1 is a comparative example. Although the calculation time is longer than 1, the calculation time is shorter than that of Comparative Example 2.

As described above, it is necessary for diagnosis by performing interpolation calculation that is easy to calculate for the part without radiation, and performing high-order interpolation that can suppress image quality degradation for the part that passes through the human body necessary for diagnosis. The time required for the interpolation calculation can be shortened while ensuring a high image quality.
It can be said that this is an overall superior interpolation calculation process as compared with 1 and 2.

Next, as a second embodiment according to the present invention, an image signal O (I) is obtained in the same manner as in the first embodiment, and this image signal O (I) is obtained.
Regarding (I), the interpolation operation was changed in the image area φ, 1 as follows, and the image size was doubled to 4096 pixels × 4928 pixels to obtain the image signal B (I).

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 (I ) Got. Note that the β is a bell-spline point spread function F
It is a positive real number β that determines (ω, β), and it is known that the spatial frequency characteristic after interpolation can be enhanced or attenuated according to the change of β. When the bell-spline interpolation operation is used as described above, the above β is set to 0.4 <β ≦
It is preferred to be about 1.5.

Also, since the bell-spline interpolation (β = 0.7) is used for the image area 1 in the second embodiment, the bell-spline interpolation (β = 0.7) is applied to the entire image area as a comparative example 3 to double. The image signal R (I) of 4096 pixels × 4928 pixels, which is the number of pixels, is obtained, and the image signal R (I) is printed on a silver halide film in the same manner as in the first embodiment.
(I) was obtained.

And the hard copy CB (I), CR (I) and
The image quality of the hard copy CP (I) of Comparative Example 1 was compared by visual evaluation, and the results shown in Table 2 were obtained. In visual image quality evaluation, CB (I) and CR
Although the image quality of (I) is good, the image quality of CP (I) by nearest neighbor interpolation is remarkably inferior to the above two hard copies. This is the nearest
This is because the 2 × 2 pixel block becomes noticeable in a mosaic shape on the human body image due to the twice enlargement of the pixel by the neighbor interpolation, and in the processing time shown in the same manner as in Table 1, the second Example B (I) is a comparative example
Although longer than 1P (I), the processing time was shorter than that of Comparative Example 3R (I).

As described above, also in the second embodiment, the processing time of the interpolation calculation is reduced without deteriorating the image quality, and the overall processing is superior to the comparative examples 1 and 3.

Further, as a third embodiment, an averaging profile is created from a radiation image signal (2048 pixels × 2464 pixels) on the side of the normal human chest obtained using the recording and reading device 3 shown in FIG. , The image area was divided into two (image area 1, image area φ).

That is, as shown in FIG. 7, an averaging profile in the horizontal direction (X direction) is obtained, and an image area φ having a small amount of image information corresponding to a flat portion of the averaging profile and a large amount of image information corresponding to other portions are included. It was set boundary pixel column X ₁ and X ₂ to separate the image area 1 to the silos. The boundary pixel rows X ₁ and X ₂ are located in an image area on the left side in FIG. 7 of the boundary pixel row X ₁ and an image area (image area φ) on the right side in FIG. 7 of the boundary pixel row X ₂ . not contain at least the body transparent portion is in the region surrounded by the boundary pixel column X ₁ and X ₂ (image area 1), also includes a directly irradiated portion will include all human image region, the image region φ Although not related to diagnosis, the image region 1 includes a region that needs diagnosis.

Next, each pixel data was subjected to data conversion using a gradation conversion curve set based on the averaging profile, and was subjected to appropriate gradation processing to obtain an image signal O (II).

The image signal O (II) is subjected to an interpolation operation, and is enlarged to a double image size of 4096 pixels × 4928 pixels.
Although was obtained (II), it was here, to change the interpolation calculation equation as follows in the image region φ and the image area 1 divided into boundary the boundary pixels X ₁ and X _2.

Image area φ → Nearest neighbor interpolation Image area 1 → Linear interpolation Next, the image signal A (II) is transferred to the printer 17 shown in FIG.
Was used to print on a 14 inch × 17 inch silver halide film to obtain a hard copy CA (II).

On the other hand, as a comparative example 4 of the third embodiment, the image signal O
Nearest neighbor interpolation is performed on the entire image area of (II) to obtain an image signal P (II) of 4096 pixels × 4928 pixels, which is printed on a silver halide film in the same manner as in Example 3, and a hard copy CP (II) was obtained.

Further, as Comparative Example 5, an image signal Q (II) of 4096 pixels × 4928 pixels was obtained by performing linear interpolation on the entire image area of the image signal O (II). Printing on film yielded a hardcopy CQ (II).

Then, the hard copy CA (II), CP (II), CQ (I
The image quality of I) was compared by visual evaluation. As shown in Table 3, the image quality of CA (II) and CQ (II) was good, and the image quality of CP (II) was better than others. It was significantly inferior. This is because CP (II) enlarged the pixel twice by nearest neighbor interpolation.
This is because a block of pixels × 2 pixels stands out on the mosaic.

Further, as shown in the relative processing time in Table 3, in the third embodiment as well, the processing time was shortened in spite of the good image quality, and the interpolation was superior to Comparative Examples 4 and 5 in total. Operations can be performed.

Next, as a fourth embodiment, the image signal obtained in the same manner as in the third embodiment O (II), the image region φ divided by the boundary pixels X ₁ and X _2, in the following manner 1 By changing the interpolation formula, an image signal B (II) of 4096 pixels × 4928 pixels was obtained.

Image area φ → Nearest neighbor interpolation Image area 1 → Cubic convolution interpolation The image signal B (II) is printed on a silver halide film in the same manner as in the third embodiment, and a hard copy CB (I
I got.

On the other hand, as a comparison object of the fourth embodiment, the image signal O (II) is subjected to cubic convolution interpolation over the entire image area, thereby doubling the image signal R (II) of 4096 pixels × 4928 pixels. (Comparative Example 6) was obtained 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 (II).

The image quality of the hard copy CB (II), CP (II), and CR (II) was compared by visual evaluation. As shown in Table 4, the image quality of CB (II) and CR (II) Is good, but the image quality of CP (II) is
2 pixels x 2 by 2 times enlargement of pixels by neighbor interpolation
The block of the pixel was remarkably inferior because it was conspicuous in a mosaic shape. Further, as shown in Table 4, the processing time of the interpolation calculation is different from that of the fourth embodiment B (II) in the comparative example 4P.
Although it was longer than (II), the calculation time could be shortened compared to Comparative Example 6R (II) in which the image quality was at the same level.

Note that the nearest neighbor interpolation, bell-spline interpolation, linear interpolation, and cubing convolution interpolation used in the above-described interpolation calculations are all known interpolation functions (“Restoring Spline Interpolation of CT”).
Images '' IEEE TRANSACTION ON MEDICAL IMAGING, VOL.M
I-2, NO.3, SEPTEMBER 1983, `` Cubic Convolution for
Digital Image Processing IEEE TRANSACTION ON ACOUS
TICS, AND SIGNAL PROCESSING, VOL.ASSP-29, NO.6 1981
Etc.).

As is clear from Tables 1 to 4, according to the present embodiment, an image is preliminarily obtained based on pixel data before interpolation in a diagnostic region (a region containing a large amount of image information) and a radiation-free region (image information is not included). And a high-order interpolation calculation formula such as bell-spline interpolation, linear interpolation, cubic convolution interpolation, etc., which can reduce the image quality although it takes a long calculation time for the diagnosis region. For the transparent region (or outside of the irradiation field), a relatively low-order interpolation calculation formula such as nearest neighbor interpolation or linear interpolation, which has a short calculation time although the image quality is deteriorated, is selected. The processing time required for the interpolation calculation can be reduced while suppressing deterioration, and the efficiency of diagnosis is improved.

In addition, the detection of the area for changing the interpolation formula is performed as follows.
As shown in the above embodiment, whether to perform the gradation processing simultaneously
Alternatively, if the information (histogram, profile) necessary for determining the gradation processing condition is collected at the same time, the processing time can be further reduced.

Further, as described in JP-A-58-67240, prior to the so-called "book reading" of obtaining radiation image information from a radiation image conversion panel using a stimulable phosphor, excitation light of low energy is applied. When performing “read ahead” using the “read ahead” image information, the area may be determined based on the “read ahead” image information, and may be applied to the “read ahead” image. Further, the human body image region may be further divided into a plurality of regions to divide the region into three or more regions.

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

Further, the digital radiation image signal subjected to the interpolation operation according to the present invention may be immediately copied by the printer 17 as described above. However, the digital radiation image signal may be reproduced on a CRT or temporarily stored in a filing system. Then, when necessary, the data may be read out and hard-copied or displayed on a CRT.

<Effects of the Invention> As described above, according to the present invention, in an interpolation calculation performed for pixel change, an image is divided into a plurality of regions based on information of a histogram and / or a profile, and particularly in a medical image. A portion necessary for diagnosis can be accurately extracted, and the interpolation calculation formula is converted for each of the divided regions. In an area having a small amount of image information, such as a blank portion, the processing time can be reduced by performing a low-order interpolation operation. Therefore, in the process of changing the number of pixels by the interpolation operation, both securing the image quality and shortening the processing time can be achieved. In particular, the radiation image for diagnosing a disease has the effect of improving the efficiency of diagnosis.

[Brief description of the drawings]

FIG. 1 is a block diagram showing the configuration of the present invention, FIG. 2 is a system block diagram showing one embodiment of the present invention, and FIG.
FIG. 4 is a detailed system block diagram of a portion for performing an interpolation operation in the system shown in FIG. 4, FIG. 4 is a system block diagram showing the configuration of the printer shown in FIG. 2, and FIG. FIG. 6 is a diagram illustrating an example of a histogram used, FIG. 6 is a diagram illustrating image division using the histogram illustrated in FIG. 5, and FIG. 7 is a diagram illustrating image division using a profile in the embodiment. FIG. 14 ... Image memory, 15 ... CPU, 16 ... Interface, 17 ... Printer, 21, 27 ... Line memory, 22 ...
Tone processing unit, 23 Control logic, 24 Comparison unit, 25
... Interpolation work, 26 ... Interpolation calculation unit, 28 ... Image division unit

──────────────────────────────────────────────────続 き Continued on front page (58) Field surveyed (Int.Cl. ⁶ , DB name) G06T 3/40 H04N 1/387 101-1/393

Claims (1)

(57) [Claims] 1. A digital radiation image signal processing device for interpolating a radiation image signal composed of digital data for each pixel to change the number of pixels, comprising: Interpolation calculating means for changing; an image dividing means for dividing an image before the interpolation calculation into a plurality of areas based on the histogram and / or profile information of the pixel data; and a plurality of areas of the image divided by the image dividing means. A digital radiation image signal processing apparatus, comprising: an interpolation calculation expression changing means for changing an interpolation calculation expression in the interpolation calculation means every time.