JP3370797B2 - Image superposition method and energy subtraction method - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a radiation image superimposing method for performing addition processing of a plurality of image signals carrying radiation image information of the same subject, and a plurality of image signals carrying radiation image information of the same subject. The present invention relates to an energy subtraction method for performing the subtraction process of.

[0002]

2. Description of the Related Art An image signal is obtained by reading a recorded radiation image, and after subjecting this image signal to appropriate image processing,
Image reproduction and recording are performed in various fields.
For example, an X-ray image is recorded using a film having a low gamma value designed to be suitable for later image processing, and the X-ray image is read from the film on which the X-ray image is recorded and converted into an electric signal. By performing image processing on this electric signal (image signal) and reproducing it as a visible image on a copy photograph or the like, a system capable of obtaining a reproduced image with good image quality performance such as contrast, sharpness, and graininess is provided. It has been developed (see Japanese Patent Publication No. 61-5193).

In addition, the applicant of the present invention has proposed radiation (X-ray, α
Ray, β-ray, γ-ray, electron beam, ultraviolet ray, etc.), a part of this radiation energy is accumulated, and when excitation light such as visible light is subsequently irradiated, the stimulated emission light of a light amount corresponding to the accumulated energy is emitted. Stimulable phosphor that emits light (stimulable phosphor)
Using, the radiographic image of a subject such as a human body is once photographed and recorded on a sheet-shaped stimulable phosphor, and the stimulable phosphor sheet is scanned with excitation light such as laser light to generate stimulated emission light.
A radiation recording / reproducing system that photoelectrically reads the obtained stimulated emission light to obtain an image signal, and outputs a radiation image of a subject as a visible image on a recording material such as a photographic light-sensitive material or a CRT based on the image signal. Have already been proposed (Japanese Patent Laid-Open Nos. 55-12429, 56-11395, 55-0163472,
56-164645, 55-116340, etc.).

On the other hand, the superposition processing of radiation images has been conventionally known (see, for example, JP-A-56-11399).
Generally, radiation images are used for diagnostic purposes and other purposes, but in using them, it is required to satisfactorily detect minute radiation absorption differences of a subject. The degree of this detection in the radiographic image is called contrast detectability or simply detectability. The higher the detectability, the higher the diagnostic performance.
It can be said that the radiographic image has high practical value. Therefore, in order to improve the diagnostic performance, it is desired to increase this detectability, but the biggest obstacle factor is various noises.

For example, in the radiation image recording system using the above-mentioned stimulable phosphor sheet, the following noise is recognized in the step of recording and reading the radiation image on the stimulable phosphor sheet and reading it out. .

(1) Quantum noise of radiation (2) Noise due to nonuniform phosphor coating distribution or phosphor particle distribution of the stimulable phosphor sheet (3) Exhaustion of images stored and recorded on the stimulable phosphor sheet Noise of excitation light to be emitted (4) Noise of stimulated emission light emitted from the stimulable phosphor sheet, which is collected and detected (5) Electric noise superposition processing in the system that amplifies and processes electric signals This is a method of significantly reducing these noises and making it possible to clearly observe even a slight radiation absorption difference of the object in the final image, that is, a method of greatly improving the detectability. The general method and operation of the superposition processing are as follows.

A radiographic image is photographed (recorded) on a plurality of recording media, and a plurality of image signals obtained by reading the plurality of recording media are superimposed. By this,
The various noises mentioned above can be reduced. That is, since the noises (1) to (5) of the above-mentioned stimulable phosphor sheet often show different distributions for each sheet image, each noise is averaged by superimposing the images of these sheets. Then, the noise is not noticeable in the image subjected to the superposition processing. That is, an image signal with a good S / N can be obtained. The same can be said when the radiation image recorded on the X-ray film is read. More specifically, noise (1) to (5) is mostly noise that can be approximated by Poisson statistics, and one of the dominant factors is the noise that is particularly dominant in radiation images (1) Radiation noise is an example. Is. Here, assuming that the noise can be approximated by Poisson statistics, the two radiation images have the same signal S.
If we have ₁ , S ₂ and noise N ₁ , N ₂ ,
The magnitude of the signal and the noise when two images are superimposed is as follows: the signal is S ₁ + S ₂ and the noise is

[0008]

[Equation 1]

[0009] On the other hand, considering S / N which is one index showing the detectability of radiation images, the S / N of each image before superposition is S ₁ / N ₁ and S ₂ / N ₂ , respectively, The S / N is

[0010]

[Equation 2]

The S / N ratio is improved. Further, by weighting each signal when performing the superposition processing, it is possible to optimize the S / N improvement.

Conventionally, in order to actually carry out this superposition processing, for example, when a stimulable phosphor sheet is used,
Two stimulable phosphor sheets are placed on top of each other in the cassette to photograph the subject, and the two stimulable phosphor sheets are sequentially subjected to the same reading process as the normal reading process to obtain two sets of image signals. The method of getting is used.

On the other hand, subtraction processing of radiation images has been conventionally known. This subtraction of the radiation image means that two radiation images photographed under different conditions are photoelectrically read to obtain a digital image signal,
It is a method of subtracting these digital image signals by making each pixel of both images correspond to each other, and obtaining a difference signal for extracting a specific structure in the radiographic image. By using the difference signal thus obtained, It is possible to reproduce the radiation image in which only the specific structure is extracted.

There are basically the following two methods for this subtraction processing. That is, (1) a specific structure is extracted by subtracting (subtracting) the image signal of the radiation image in which the contrast agent is not injected from the image signal of the radiation image in which the specific structure is emphasized by the injection of the contrast agent. The so-called temporal subtraction processing, and (2) irradiating the same subject with radiation having different energy distributions, or irradiating the two radiation detecting means with radiation after passing through the subject by changing the energy distribution state, As a result, images having different specific structures are made to exist between two radiographic images, and then the image signals of the two radiographic images are appropriately weighted and then subtracted (subtract) to obtain the specific structures. This is a so-called energy subtraction process for extracting the image.

In the radiation image information recording / reproducing system using the above-mentioned stimulable phosphor sheet, the radiation image information recorded on the sheet is directly read in the form of an electric image signal, so that this system is used. According to this, it becomes possible to easily perform the subtraction processing as described above. In order to perform energy subtraction processing using this stimulable phosphor sheet, for example, two stimulable phosphor sheets are image-recorded (captured) so that the image information of a portion corresponding to a specific structure is different. Specifically, specifically, the 2Shot method in which imaging is performed twice using two types of radiation having different energy distributions, and, for example, two stimulable phosphor sheets on which radiation transmitted through a subject is overlapped (these are There is known a 1-shot method in which both sheets are irradiated with radiation having different energy distributions by simultaneously irradiating the sheets with each other.

Further, as a method for photoelectrically reading the above-mentioned stimulated emission light, the photoelectric reading means described above is arranged on both sides of the stimulable phosphor sheet, and the excitation light is applied only on both sides or one side of the stimulable phosphor sheet. And a double-sided condensing reading method for photoelectrically reading the stimulated emission light emitted by this excitation light scanning from both sides of the stimulable phosphor sheet (for example, JP-A-55-87970). reference). In such a double-sided condensing reading method, one radiation image is accumulated and recorded on the stimulable phosphor sheet, and the stimulated emission light is condensed from both sides of the stimulable phosphor sheet. The light collection efficiency is improved and the S / N ratio is further improved.

In the double-sided condensing reading method disclosed in JP-A-55-87970, a stimulable phosphor sheet is mounted on a transparent holder, and photoelectric reading means are arranged above and below the stimulable phosphor sheet. That is, in the photoelectric reading means arranged above the holder, the stimulated emission light emitted from the surface of the stimulable phosphor sheet is read, and in the photoelectric reading means arranged below the holder, the back surface of the stimulable phosphor sheet is read. The stimulated emission light emitted from the device is read.

[0018]

In order to obtain the image signal for performing the above-mentioned superposition, it is necessary to record a radiation image on a plurality of stimulable phosphor sheets which are superposed. On this occasion,
The image signal obtained from the stimulable phosphor sheet at a position far from the radiation source contains image information in the low frequency band like the image signal obtained from the upper sheet closest to the radiation source. Compared with the above, the frequency dependence of the high frequency band is low, the image information is small in the high frequency band, and the noise component due to the influence of scattered light is increased. Therefore, if the image signals obtained from the upper and lower sheets are subjected to the same weighting and addition as it is, the image quality is improved in the low frequency band of the added image signals, but noise components are also included in the high frequency band. Since the image is emphasized, the image quality is deteriorated. The same applies to the case of the image signal obtained from the upper side of the sheet and the image signal obtained from the lower side of the sheet obtained by the method of reading the image signal from both sides of the above-mentioned one stimulable phosphor sheet. The image quality may be degraded. Furthermore, even in the image signal for which the energy subtraction described above is performed, the ratio of the noise component differs depending on the frequency band of the image signal, and therefore when the subtraction process is performed between the image signals, the difference signal The noise component may increase.

In view of the above circumstances, the present invention provides a method of superimposing a radiation image and an energy subtraction method capable of obtaining a higher quality image with less noise components in the above-mentioned superimposed image and energy subtracted image. The purpose is.

[0020]

According to a first image superimposing method of the present invention, signals between pixels corresponding to a plurality of image signals having different frequency characteristics for carrying radiation images of the same subject are provided. In a radiographic image superimposing method in which each image signal is multiplied by a predetermined weighting coefficient and addition is performed to obtain an addition signal, a weighting coefficient of a frequency component having a low signal-to-noise ratio is signaled according to the frequency characteristic of each image signal. It is characterized in that it is made relatively smaller than the weighting coefficient of the frequency component having a high noise ratio.

The second image superimposing method according to the present invention is the same as the first image superimposing method according to the present invention.
Fourier transform is applied to each image signal to decompose each image signal into a Fourier transform coefficient signal for each of a plurality of frequency bands, and a weighting coefficient is changed for each Fourier transform coefficient signal to obtain a Fourier transform coefficient signal for each Fourier transform coefficient signal. An image is superposed by performing addition to obtain an addition Fourier transform coefficient signal for each frequency band, and performing inverse Fourier transform on the addition Fourier transform coefficient signal.

Furthermore, a third image superimposing method according to the present invention is the same as the first image superimposing method according to the present invention, wherein each of the image signals is converted into a multi-resolution space, and each of the image signals is converted into a plurality of frequency bands. For each conversion coefficient signal, the weighting coefficient is changed for each conversion coefficient signal, the conversion coefficient signals are added to obtain an addition conversion coefficient signal for each frequency band, and the addition conversion coefficient signal is obtained. It is characterized in that the images are superimposed by performing the inverse conversion.

Here, the conversion into a multi-resolution space is a conversion that decomposes an image signal into signals of a plurality of frequency bands by a filter shorter than that of Fourier transform such as wavelet transform and sub-band transform.

The wavelet transform will be described here.

The wavelet transform has been recently developed as a method of frequency analysis, and has been applied to stereo pattern matching, data compression, etc. (OLIVIER RIOUL and MARTIN VETTERLI; Wavelets a
nd Signal Processing, IEEESP MAGAZINE, P.14-38, OCTOB
ER 1991, Stephane Mallat; Zero-Crossings of a Wavel
et Transform, IEEE TRANSACTIONS ON INFORMATION THEO
RY, VOL.37, NO.4, P.1019-1033, JULY 1991).

This wavelet transform uses a function h as shown in FIG. 22 as a basis function.

[0027]

[Equation 3]

In the equation, the signal is converted into a frequency signal for each of a plurality of frequency bands, so that the problem of false vibration unlike the Fourier transform does not occur. That is, if the filtering process is performed by changing the period and reduction ratio of the function h and moving the original signal, it is possible to create a frequency signal adapted to a desired frequency from a fine frequency to a coarse frequency. For example, as shown in Figure 23, the signal So
The wavelet transform of rg and the inverse wavelet transform for each frequency band and the signal Sorg as shown in Fig. 24.
Looking at a signal obtained by performing a Fourier transform on each frequency band and performing an inverse Fourier transform on each frequency band, the wavelet transform can obtain a frequency signal in a frequency band corresponding to the vibration of the original signal Sorg as compared with the Fourier transform. That is, in the Fourier transform, the frequency band 7 corresponding to the part B of the original signal Sorg
In the wavelet transform, vibration is generated in the portion B ′ of the original signal Sorg, whereas in the portion A ′ of the frequency band W7 corresponding to the portion A of the original signal Sorg in the wavelet transform, vibration is not generated similarly to the original signal. Become.

A fourth image superimposing method according to the present invention is the same as the third image superimposing method according to the present invention.
It is characterized in that the conversion into the multi-resolution space is performed by the above-mentioned wavelet conversion.

Further, a fifth image superimposing method according to the present invention is the image superimposing method according to the first, third or fourth image superimposing method according to the present invention, which is reached according to the part of the subject included in the radiation image. It is characterized in that the weighting coefficient of a portion having a large dose is made relatively larger than that of a portion having a small reaching dose.

Furthermore, a sixth image superimposing method according to the present invention is the same as the above-mentioned first to fifth image superimposing methods according to the present invention. Of the stimulable phosphor sheet is scanned with excitation light to convert the radiation image into stimulated emission light, and the stimulated emission light obtained from both sides of the stimulable phosphor sheet is read photoelectrically. It is characterized by being obtained.

Further, in a seventh image superimposing method according to the present invention, each of the image signals is an analog image signal, and a filter having a weight for changing the frequency characteristic of the image signal for all of the analog image signals. Thus, all of the analog image signals are filtered, and the respective analog image signals after the filtering are added to superimpose the images.

Further, in the eighth image superimposing method according to the present invention, each of the image signals is an analog image signal, and a frequency characteristic of the desired analog image signal among the analog image signals is changed. It is characterized in that the desired analog image signal is filtered by a filter having a weight that causes the image to be superimposed by adding the filtered analog image signal and the other analog image signal. It is a thing.

Further, a ninth image superimposing method according to the present invention is the same as the first to eighth image superimposing methods according to the present invention, wherein the plurality of image signals are stored in two radiographic images. The fluorescent image is obtained by scanning each of the fluorescent phosphor sheets with excitation light to convert the radiation image into stimulated emission light and photoelectrically reading the stimulated emission light.

Furthermore, the present invention can be applied to energy subtraction, and the first energy subtraction method according to the present invention is such that at least a part of images obtained by radiation having different energy distributions transmitted through the same subject. Information of a plurality of image signals obtained by detecting a plurality of different radiographic images are obtained by multiplying each image signal by a predetermined weighting coefficient between the signals of pixels corresponding to each other In an energy subtraction method for obtaining a difference signal forming an image of a specific structure, a weighting coefficient of a frequency component having a low signal-to-noise ratio is set to a frequency component having a high signal-to-noise ratio in accordance with a frequency characteristic of each image signal. It is characterized in that it is made relatively smaller than the weighting coefficient.

A second energy subtraction method according to the present invention is the above-described energy subtraction method of the first subject, wherein Fourier transform is performed on each of the image signals to obtain Fourier transform coefficients for each of a plurality of frequency bands. The signal is decomposed into signals, the weighting coefficient is changed for each Fourier transform coefficient signal, the Fourier transform coefficient signals are subtracted to obtain a subtracted Fourier transform coefficient signal for each frequency band, and the subtracted Fourier transform coefficient signal is obtained. The difference signal is obtained by performing an inverse Fourier transform.

Furthermore, a third energy subtraction method according to the present invention is the same as the first energy subtraction method according to the present invention, wherein each of the image signals is converted into a multi-resolution space, and each of the image signals is divided into a plurality of frequency bands. The conversion coefficient signal is decomposed, the weighting coefficient is changed for each conversion coefficient signal, the conversion coefficient signal is subtracted to obtain a subtraction conversion coefficient signal for each frequency band, and the subtraction conversion coefficient signal is inversely converted. By doing so, the difference signal is obtained.

Further, a fourth energy subtraction method according to the present invention is characterized in that, in the third energy subtraction method according to the present invention, the conversion into the multi-resolution space is performed by a wavelet transform.

Further, a fifth energy subtraction method according to the present invention is the first, third or fourth energy subtraction method according to the present invention, in which the dose reached is large depending on the part of the subject included in the radiation image. The feature is that the weighting coefficient of the region is made relatively larger than that of the region having a small reaching dose.

Further, in the sixth energy subtraction method according to the present invention, each of the image signals is an analog image signal, and all of the analog image signals are:
Characterized in that the difference signal is obtained by filtering all the analog image signals with a filter having a weight that changes the frequency characteristics of the image signal and subtracting each analog image signal after the filtering. Is.

In the seventh energy subtraction method according to the present invention, each of the image signals is an analog image signal, and the frequency characteristic of the desired analog image signal among the analog image signals is changed. The difference signal is obtained by filtering the desired analog image signal with a filter having a weight and subtracting the analog image signal after the filtering from the other analog image signal. is there.

[0042]

According to the image superimposing method of the present invention, in the above-described radiographic image superimposing method, the weighting coefficient of the frequency component having a low signal-to-noise ratio is set in accordance with the frequency characteristics of each image signal. The added image signal has a high signal-to-noise ratio over the entire frequency band because it is made relatively small compared to the weighting coefficient of the frequency component with a high ratio, and this added image signal must be reproduced. As a result, a high quality superimposed image can be obtained.

Specifically, by performing a Fourier transform on each image signal to decompose each image signal into a Fourier transform coefficient signal for each of a plurality of frequency bands and performing weighted addition as described above, The weighting coefficient of the frequency component having a low signal-to-noise ratio can be made relatively smaller than the weighting coefficient of the frequency component having a high signal-to-noise ratio, whereby a high-quality superimposed image can be obtained.

Further, by converting each image signal into a multi-resolution space such as wavelet transform or sub-band transform and decomposing each image signal into transform coefficient signals for a plurality of frequency bands to obtain an addition signal, Since the image signal can be decomposed into a plurality of frequency bands with the short filter as described above, the configuration of the device for implementing the present invention can be simplified.

Furthermore, the image signal for each frequency band obtained by converting the image signal into the multi-resolution space as described above is an image signal obtained by reducing the image signal before conversion. Therefore, by performing histogram analysis for each converted signal, it is possible to know the arrival dose of the part included in the image signal, and the weighting coefficient of the image signal representing the part with the larger arrival dose is assigned to the part with the smaller arrival dose. Since it can be made relatively large, a higher quality image can be obtained.

Further, each image signal is an analog image signal, and all or desired analog image signals are filtered by a filter having a weight that changes the frequency characteristic of the image signal, thereby obtaining the analog image signal. Weighting is performed on the desired frequency band of, and by reproducing the added signal obtained by adding the image signals after this filtering, similar to the above-described Fourier transform, wavelet transform, or subband transform, A superimposed image can be obtained.

Further, in the case of obtaining an image signal by condensing both sides of the stimulable phosphor sheet as described above, the image signal obtained from the lower side of the sheet (the side farther than the radiation source) or the sheets are superposed. When the radiation image is recorded, the high-frequency component of the image signal obtained from the side far from the radiation source contains many noise components such as scattered light, so the high-frequency component of the image signal obtained from this lower sheet is high. By making the weighting coefficient by which the frequency component is multiplied smaller than the weighting coefficient by which the high frequency component of the image signal obtained from the upper sheet is multiplied, it is possible to obtain a superposition signal with reduced noise components.

Further, the above-mentioned processing for changing the weighting coefficient of the image signal for each frequency band can be applied to the energy subtraction processing, and the signal-to-noise ratio is low depending on the frequency characteristic of each image signal to be subtracted. By making the weighting coefficient of the frequency component relatively smaller than the weighting coefficient of the frequency component having a high signal-to-noise ratio, the subtracted image signal has a small noise component ratio. A high-quality subtraction image can be obtained by reproducing the signal.

[0049]

Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 shows two stimulable phosphor sheets 4A, 4
It is a figure which shows the state which irradiates the radiation 2 which permeate | transmitted the same to-be-photographed object 1 to B.

As shown in FIG. 1, the first stimulable phosphor sheet 4A and the second stimulable phosphor sheet 4B are arranged so as to overlap with each other, and the radiation source 3 is driven to emit the radiation 2. As a result, the radiation 2 transmitted through the subject 1 is applied to the first and second stimulable phosphor sheets 4A and 4B,
The radiation image information of the subject 1 is accumulated and recorded in the stimulable phosphor sheets 4A and 4B.

Next, these two stimulable phosphor sheets 4 are used.
A radiation image is read from A and 4B by an image reading means as shown in FIG. 2, and an image signal representing the radiation image is obtained. First, while moving the stimulable phosphor sheet 4A in the direction of arrow Y by the sub-scanning means 9 such as an endless belt,
The laser light (excitation light) 11 from the laser light source 10 is deflected by the scanning mirror 12 to perform main scanning on the sheet 4A in the X direction. By this excitation light scanning, the stimulable phosphor sheet 4
From A, stimulated emission light 13 having a light amount corresponding to the stored and recorded radiation image information is emitted. The stimulated emission light 13 enters the inside of the light guide 14 from one end surface of the light guide 14 formed by molding a transparent acrylic plate, and travels through the light guide 14 while repeating total reflection, and the photomultiplier. The light is received by (photomultiplier tube) 15. This photo multiplier
An output signal S _A corresponding to the amount of stimulated emission light 13, that is, the above-mentioned image information, is output from 15.

The output signal S _A is logarithmically amplified by the logarithmic amplifier 16 and then input to the A / D converter 17 to be converted into a digital image signal S ₁ . This image signal S ₁
Are stored in a storage medium 18 such as a magnetic disk. Next, in the same manner, another stimulable phosphor sheet 4
The recorded image information of B is read out, an output signal S _B indicating the image information is obtained, logarithmically amplified by a logarithmic amplifier 16, and then input to an A / D converter 17 to obtain a digital image signal S ₂ . The converted image signal S ₂ is converted into the storage medium 18
Memorized in.

Next, the image signal S thus obtained is obtained.
_A superposition process is performed using ₁ and S ₂ . FIG. 3 is a diagram showing an outline of an apparatus for performing this superposition processing. First, from the image file 18A and the image file 18B in the storage medium 18,
The image signals S ₁ and S ₂ are read out and input to the wavelet transform means 19. The wavelet transforming means 19 wavelet transforms the two input image signals S ₁ and S ₂ and decomposes them into transform coefficient signals for each of a plurality of frequency bands.
The details of the wavelet transform will be described below.

FIG. 4 is a diagram showing details of the wavelet transform for the image signals S ₁ and S ₂ . Here, the wavelet transform of the image signal S ₁ will be described for simplicity.

In the present embodiment, the orthogonal wavelet transform in which each coefficient of the wavelet transform is orthogonal is performed, which is described in the above-mentioned document of Marc Antonini et al.

As shown in FIG. 4, filtering processing is performed in the main scanning direction of the image signal S ₁ by the functions g and h obtained from the basic wavelet function. That is,
The filtering processing for each column of pixels arranged in the main scanning direction by such functions g and h is performed while shifting each pixel in the sub scanning direction to obtain the wavelet transform coefficient signals Wg0 and Wh0 of the original image data Sorg in the main scanning direction. It is what you want.

Here, the functions g and h are uniquely obtained from the basic wavelet function. For example, the function h
Is shown in Table 1 below. It should be noted that in Table 1, the function h'represents a function used when performing inverse wavelet transform on image data that has been subjected to wavelet transform. Further, as shown in the following equation (4), the function g is obtained from the function h ', and the function g'for performing the inverse wavelet transform is obtained from the function h.

[0059]

[Table 1]

G ′ = (− 1) ⁿ h g = (− 1) ⁿ h ′ (4) Thus, the wavelet transform coefficient signals Wg 0, W
When h0 is obtained, the wavelet transform coefficient signal Wg0,
For Wh0, pixels in the main scanning direction are thinned out every other pixel, and the number of pixels in the main scanning direction is halved. Then, the wavelet transform coefficient signals Wg0 and Wh0 from which this pixel is thinned out.
Filtering processing is performed by the functions g and h in the respective sub-scanning directions, and wavelet transform coefficient signals WW _U0 and W
Obtain V _U0 , VW _U0 and VV _U0 .

Next, the wavelet transform coefficient signal W
With respect to W _U0 , WV _U0 , VW _U0, and VV _U0 , the pixels in the sub-scanning direction are thinned out every other pixel, and the number of pixels in the sub-scanning direction is halved. As a result, the respective wavelet transform coefficient signals VV _U0 , WV _U0 , VW _U0 , WW
The number of pixels of _U0 is 1/4 of the number of pixels of the image signal S ₁ . Next, filtering processing is performed in the main scanning direction of the wavelet transform coefficient signal VV _{U0 by} the functions g and h.

[0062] That is, the function g, the filtering process for each one row of pixels aligned in the main scanning direction is performed while one pixel at a time Shifts in the sub-scanning direction by h, the main scanning direction of the wavelet transform factor signals of the wavelet transform factor signals VV _u0 Wg1 And Wh1.

Here, the wavelet transform coefficient signal VV _U0
Since the number of pixels in both main and sub directions is half that of the original image data, the image resolution is half that of the original image data. Therefore, by performing a filtering process on the wavelet transform coefficient signal VV _U0 with the functions g and h, the wavelet transform coefficient signal representing a frequency component lower than the frequency component represented by the wavelet transform coefficient signal VV _U0 among the frequency components of the original image data. Wg1, Wh1
Is required.

In this way, when the wavelet transform coefficient signals Wg1 and Wh1 are obtained, for the wavelet transform coefficient signals Wg1 and Wh1, pixels in the main scanning direction are thinned out every other pixel, and the number of pixels in the main scanning direction is further reduced to 1. / 2 Next, the wavelet transform coefficient signals Wg1 and Wh1 are filtered in the sub-scanning direction by the functions g and h to obtain wavelet transform coefficient signals WW _U1 and W1.
Obtain V _U1 , VW _U1 and VV _U1 .

Next, the wavelet transform coefficient signal W
For W _U1 , WV _U1 , VW _U1 , and VV _U1 , the pixels in the sub-scanning direction are thinned out every other pixel, and the number of pixels in the sub-scanning direction is halved.
And perform the process. As a result, the number of pixels of each wavelet transform coefficient signal WW _U1 , WV _U1 , VW _U1 , VV _U1 becomes 1/16 of the number of pixels of the image signal S ₁ .

Thereafter, in the same manner as described above, filtering processing is performed by the functions g and h in the main scanning direction of the wavelet transform coefficient signal VV _U1 from which pixels have been thinned, and the main wavelet transform coefficient signal obtained is further processed. Pixels in the scanning direction are thinned out, and the wavelet transform coefficient signal obtained by thinning out the pixels is filtered in the sub-scanning direction by the functions g and h to obtain the wavelet transform coefficient signal W.
W _U2 , WV _U2 , VW _U2 , VV _U2 are obtained.

By repeating such wavelet transform N times, wavelet transform coefficient signals WW _U0 -W
W _UN , WV _{U0 to} WV _UN , VW _{U0 to} VW _UN , and VV _UN
To get Here, the wavelet transform factor signals obtained by the wavelet transform of the N-th WW _N, WV _N, V
W _N, VV _N are the original as compared with the image data is the number of pixels in the main sub each direction (1/2) because it is a ^N, each wavelet transform factor signal has a low enough frequency bands N is large, the original It becomes the data representing the low frequency component of the frequency component of the image data.

Therefore, the wavelet transform coefficient signal WW _Ui (i = 0 to N, the same applies hereinafter) represents a change in the frequency of the image signal S ₁ in both the main and sub directions. The larger i is, the lower the frequency of the signal becomes. . The wavelet transform coefficient signal WV _Ui represents the change in the frequency of the image signal S _{1 in} the main scanning direction, and the larger i is, the lower the frequency signal becomes. Further, the wavelet transform coefficient signal VW _Ui is the image signal S ₁
Represents the change in frequency in the sub-scanning direction, and the larger i is, the lower the frequency signal becomes.

FIG. 5 shows a wavelet transform coefficient signal for each of a plurality of frequency bands. Note that FIG.
For convenience, the state up to the state in which the third wavelet transform is performed is represented by. In FIG. 5, the wavelet transform coefficient signal WW _{3 is} (1/1)
2) It has been reduced to ³ .

[0070] Similarly, also subjected to wavelet transform on the image signal S _2, a plurality of the wavelet transform factor signals WW _L0 ~WW _LN of each frequency band, WV _L0 ~WV _LN,
Obtain VW _{L0 to} VW _LN and VV _LN .

The wavelet transform coefficient signal obtained by subjecting the image signals S ₁ and S ₂ to the wavelet transform in this way is input to the weighting superposition means 20. The weighting superimposing means 20 performs weighting processing by making the weighting coefficient of the frequency band having a low signal-to-noise ratio relatively smaller than the weighting coefficient of the frequency band having a high signal-to-noise ratio. First, the determination of the weighting coefficient will be described.

The image signals S ₁ and S ₂ obtained from the two stimulable phosphor sheets 4A and 4B are shown in FIGS. 6 (a) and 6 (b), respectively.
MTF (Modulation Transfer Function,
Frequency-dependent characteristic). Here, the MTF is obtained by photographing a CTF chart (Contrast Transfer Function Chart), and represents the magnitude of the resolution of the image signal for each frequency band. That is, as shown in FIG. 6 (a), the MTF of the image signal S ₁ obtained from the upper stimulable phosphor sheet 4A near the radiation source.
1 is large up to the high frequency band, the image signal S ₁ has information up to the high frequency band, but as shown in FIG. 6 (b), it is obtained from the stimulable phosphor sheet 4B on the lower side far from the radiation source. In the image signal S ₂ , the MTF 2 on the high frequency band side is smaller than that of the image signal S _1, and the amount of information in the high frequency band is small. This is because the information in the high frequency band of the image signal S ₂ includes noise such as scattered radiation at the time of imaging, and further, the thin information on the high frequency band side is blurred because it is far from the radiation source. Is represented. Therefore, the weighting coefficient of each wavelet transform coefficient signal is changed according to this MTF, and each wavelet transform coefficient signal is added. Here, a method of determining the weighting coefficient of each wavelet transform coefficient signal will be described.

First, in addition to the frequency characteristics MTF1 and MTF2 of each image signal shown in FIGS. 6A and 6B, the frequency characteristics of noise of each image signal as shown in FIGS. 7A and 7B are shown. Winer1,2
Ask for. Here, Winer1 and Winer2 are obtained by obtaining the variance for each frequency of the noise image signal obtained by the image pickup apparatus described above, that is, the image obtained by performing the image pickup without placing the subject. That is, looking at the Winer 1, the noise image signal Image (X
Regarding 1),

[0074]

[Equation 4]

The plots of RMS ² obtained by the above for each frequency are Winers 1 and 2 shown in FIGS. 7 (a) and 7 (b).

Here, the index DQE is defined by the following equation (6).

[0077]

[Equation 5]

Equation (6) indicates that the higher the DQE, the better the image quality. Further, the DQE is obtained for each frequency.

Next, image signals Image 1 (X), Im for each frequency band obtained when the above MTFs 1, 2 are obtained.
age 2 (X) is added by (add (t) = t × Image 1 (X) + (1-t) × Image 2 (X) (7), and t is 0 for the added image signal add (t). ~
By changing up to 1, multiple added image signals add
get (t). Then, for each added image signal add (t), D
QE is calculated and plotted with t on the horizontal axis and DQE on the vertical axis. FIG. 8 is obtained for each of a plurality of frequency bands,
It is a figure showing the relationship between t and DQE. As shown in Fig. 8 (a), the frequency band is 1 cycle / mm (1c / mm in Fig. 8).
mm), the DQE becomes maximum at t = 0.5. In addition, as shown in Fig. 8 (b), the frequency band is 2 cycles /
When the frequency is 3 mm / mm, t = 0.7, and when the frequency band is 3 cycles / mm, t = 0.9 and the DQE, respectively.
Is the maximum.

As described above, the weighting table as shown in FIG. 9 can be obtained by plotting t at which the DQE becomes maximum for each frequency band. Based on the weighting table as shown in FIG. 9, the above-mentioned wavelet transform coefficient signals are added.

That is, regarding the wavelet transform coefficient signal for each frequency band, WW _i = t · WW _Ui + (1-t) WW _Li WV _i = t · WV _Ui + (1-t) WV _Li (8) Weighted addition is performed by VW _i = t · VW _Ui + (1-t) VW _Li VV _i = t · VV _Ui + (1-t) VV _Li . For example, when the addition coefficient signal WW ₁ of the frequency band is obtained, the coefficient signal WW _L1 has much noise and a small amount of information as compared with the coefficient signal WW _U1 , so the value of t is increased. That is, the coefficient signal WW ₁ is obtained by WW ₁ = 0.8 × WW _U1 + 0.2 × WW _L1 (9) The addition coefficient signal WV
₁ and VW ₁ may be obtained by the same weighting as in the case of obtaining WW _{1 of the} addition coefficient signal.

On the other hand, the wavelet transform coefficient signal WW ₁
In the case of obtaining the addition coefficient signal WW ₂ in the lower frequency band than the coefficient signal WW _L2 , even if the coefficient signal WW _L2 is compared with the coefficient signal WW _U2 , there is no noise as much as the coefficient signal WW _{L1 and the} amount of information is small. Is set to about 0.6, and an addition coefficient signal WW ₂ is obtained by WW ₂ = 0.6 × WW _U2 + 0.4 × WW _L2 (10) Addition coefficient signal W
V ₂ and VW ₂ may be obtained by the same weighting as in the case of obtaining the addition coefficient signal WW ₂ .

The wavelet transform coefficient signal WW ₂
When the addition coefficient signal WW ₃ in the lower frequency band is obtained, the coefficient signals WW _L2 and WW _U2 have substantially the same information, so the value of t is set to 0.5, and WW ₃ = 0.5 × WW _The addition coefficient signal WW ₃ is obtained by _U3 + 0.5 × WW _L3 (11) Addition coefficient signal W
V ₃ and VW ₃ may be obtained by the same weighting as in the case of obtaining the addition coefficient signal WW ₃ .

Further, the wavelet transform coefficient signal WW
Than ₃ in the case of obtaining the addition coefficient signals WW ₄ ~WW _N of the low frequency band, the coefficient signal WW _U4 ~WW _UN, WW _L4
.About.WW _LN have approximately the same information, the addition coefficient signals WW _{4 to} WW _N may be obtained with the value of t being 0.5.

By thus determining the weighting coefficient, it is possible to determine the optimum weighting coefficient for each frequency regardless of the characteristics of the MTF and Winer of the original image.

As described above, the weighting superposition means 20
In the addition wavelet transform coefficient signals WW _{1 to} WW
_{N, WV 1 ~WV N, VW} 1 ~VW N, VV 1 ~VV N
Then, the addition wavelet transform coefficient signal is subjected to the inverse wavelet transform in the inverse wavelet transform means 21. The details of the inverse wavelet transform will be described below.

FIG. 10 is a diagram showing details of the inverse wavelet transform.

[0088] As shown in FIG. 10, first, the addition wavelet transform factor signals _{VV N, VW N, WV N} , the WW _N performs processing spacing of one pixel among pixels arranged in the sub-scanning direction (in the figure Displayed as × 2). Followed by different function h 'is the function h described above the addition wavelet transform factor signal VV _N this spaced in the sub-scanning direction, different from the function g described above the addition wavelet transform factor signal VW _N in the sub-scanning direction Filtering processing is performed by the function g '. That is, the function g ', h' addition by the wavelet transform factor signals VV _N, filtering processing for each pixel of a row aligned in the sub-scanning direction VW _N in the main scanning direction is performed while Shifts pixel by pixel, the addition wavelet transform factor signal VV _N, to obtain an inverse wavelet transform factor signal VW _N, obtain the inverse wavelet transform factor signals WhN 'by adding to 2 times this.

The function for performing the wavelet transform and the function for performing the inverse wavelet transform are different from each other for the following reason. Wavelet transform and inverse wavelet transform have the same function,
That is, it is difficult to design orthogonal functions, and it is necessary to loosen any of the conditions of orthogonality, continuity, function shortness, and symmetry. Therefore, a function that satisfies other conditions is selected by relaxing the orthogonality condition.

As described above, in the present embodiment, the functions h and g for performing the wavelet transform and the functions h'and g'for performing the inverse wavelet transform are different from each other in biorthogonal manner. Thus, the addition wavelet transform factor signal VV _i, V
By performing the inverse wavelet transform on W _i , WV _i , and WW _i with the functions h ′ and g ′, the added signals of the image signals S ₁ and S ₂ can be completely restored.

[0091] On the other hand, in parallel with this, the function h 'the addition wavelet transform factor signal WV _N in the sub-scanning direction,
The addition wavelet transform factor signal WW _N performs filtering processing by the function g 'in the sub-scanning direction, to obtain an inverse wavelet transform factor signals of the addition wavelet transform factor signal WV _N ,, WW _N, adds it twice to be To obtain the inverse wavelet transform coefficient signal WgN '.

Next, the inverse wavelet transform coefficient signal W
With respect to hN 'and WgN', a process of spacing one pixel between pixels arranged in the main scanning direction is performed. Thereafter, the inverse wavelet transform coefficient signal WhN 'is filtered in the main scanning direction by the function h', and the inverse wavelet transform coefficient signal WgN 'is filtered in the main scanning direction by the function g', and the inverse wavelet of the wavelet transform coefficient signals WhN 'and WgN' is obtained. A transform coefficient signal is obtained, and this is doubled and added to obtain an addition inverse wavelet transform coefficient signal VVN _-1 '.

Then, the addition inverse wavelet transform coefficient signal VVN _-1 'and the addition wavelet transform coefficient signal VW are added.
_{For N-1} , WVN _-1 , and WWN _-1 , processing is performed to leave an interval of one pixel between pixels arranged in the sub _- scanning direction. Thereafter, the addition inverse wavelet transform coefficient signal VVN _-1 'is filtered in the sub _- scanning direction by the above-mentioned function h', and the addition wavelet transform coefficient signal VWN _-1 is filtered in the sub _- scanning direction by the above-mentioned function g '. That is, the function g ′,
Addition wavelet transform coefficient signal V by h '
V _N-1 ′ and VW _N-1 are subjected to filtering processing for each row of pixels arranged in the sub _- scanning direction while shifting each pixel in the main scanning direction, and the added wavelet transform coefficient signal V
V _N-1 to obtain a ', to give the inverse wavelet transform factor signal VW _N-1, the inverse wavelet transform factor signals WhN-1 by adding to 2 times this'.

On the other hand, in parallel with this, the added wavelet transform coefficient signal WVN _-1 is filtered in the sub _- scanning direction by the function h ', and the added wavelet transform coefficient signal WW _N-1 is filtered in the sub _- scanning direction by the function g'. was carried out, the addition wavelet transform factor signals _{WV N-1, WW N-} 1 to obtain an inverse wavelet transform factor signals, summing the inverse wavelet transform factor signals by adding and doubling this WgN-
Get 1 '.

Next, the inverse wavelet transform coefficient signal W
1 between pixels lined up in the main scanning direction for hN-1 'and WgN-1'
Performs a process for spacing pixels. Thereafter, the inverse wavelet transform coefficient signal WhN-1 'is filtered in the main scanning direction by the function h', and the inverse wavelet transform coefficient signal WgN-1 'is filtered in the main scanning direction by the function g', and the wavelet transform coefficient signal WhN-1 'is obtained. , WgN-1 'of inverse wavelet transform coefficient signals are obtained, and this is doubled and added to obtain an added inverse wavelet transform coefficient signal VVN _-2 '.

Thereafter, the sequential addition inverse wavelet transform coefficient signal VV _i ′ (i = −1 to N) is created, and finally the addition inverse wavelet transform coefficient signal VV ₋₁ ′ is obtained. The final addition inverse wavelet transform coefficient signal VV _-1 ′ becomes the addition image signal Sadd of the image signals S ₁ and S ₂ .

The wavelet transform coefficient signal VV _-1 ′ thus obtained is subjected to predetermined image processing by the image processing means 22 and used for reproduction of the radiation image by the reproduction means 23.

The reproducing means may be a display means such as a CRT or a recording device for performing optical scanning recording on the photosensitive film.

In this way, the two image signals S ₁ and S
Wavelet transform ₂ to obtain the wavelet transform coefficient signal for each frequency band, for the wavelet transform coefficient signal for each frequency band, the image obtained from the upper stimulable phosphor sheet for the coefficient signal in the high frequency band The noise component contained in the image signal obtained from the lower stimulable phosphor sheet is reduced by making the signal weighting factor larger than the weighting factor of the image signal obtained from the lower stimulable phosphor sheet. Since the added wavelet transform coefficient signals thus obtained are obtained, it is possible to obtain a high-quality reproduced image in which noise components are reduced by reproducing the added signals obtained by performing inverse wavelet transform on each added wavelet transform coefficient signal. it can.

In the above-described embodiment, the functions h and h'for performing the wavelet transform shown in Table 1 are used, but the functions are not limited to these, and Tables 2 and 3 shown below are used. You may use what is shown in.

[0101]

[Table 2]

[0102]

[Table 3]

In addition to this, any function may be used as long as it is a function capable of performing wavelet transformation, and for example, a function which is not symmetric but orthogonal and is not symmetrical may be used.

Further, as shown in Tables 1, 2, and 3, n
Not only the function symmetrical about the axis of = 0, but n = 0
The wavelet transform may be performed using a function that is asymmetric with respect to the axis of. When the wavelet transform is performed using the left-right asymmetric function as described above, the inverse wavelet transform is performed by using the function obtained by inverting the left-right function of the wavelet-transformed function with respect to the axis of n = 0. That is, with respect to the left-right asymmetric functions g and h, the functions g ′ and h ′ that perform the inverse wavelet transform are: g [n] = g ′ [− n] h [n] = h ′ [− n] (12) However, [-n] represents left-right inversion.

It becomes:

[0106] Further, in the embodiment described above, but by decomposing the image signal S _1, S ₂ to the transform factor signals of the plurality of frequency bands by the wavelet transform, the image signal S _1, S ₂ by the sub-band transform You may make it decompose | disassemble into the conversion coefficient signal of several frequency bands. The sub-band transform is that the wavelet transform sequentially obtains transform coefficient signals for each of a plurality of frequency bands by filtering the image signal with one kind of function, while the image signal is filtered with a plurality of functions having different periods. By this, the conversion coefficient signal for each of a plurality of frequency bands is obtained by one-time processing.

For example, in the above-described embodiment, the image signal is filtered by the functions g and h to obtain the image signal for each of a plurality of frequency bands, but the sub-band conversion is as shown in FIG. Image signal S
_{When 1} is sub-band transformed, the periods of functions g and h are 2
Multiple times, 4 times, ... ²ⁿ times multiple frequencies g ₁ ,
_{h 1 ,, g 2, h 2} , ......, g N, h N by the image signals S ₁ a filtering process multiple coefficient signals WW _U1 ~WW _UN for each frequency band by, WV _U1 ~WV _{UN,
VW U1 ~VW UN, VV U1 ~VV} UN can be obtained, also factor signal WW _L1 ~WW _LN for a plurality of frequency bands for the image signal S ₂ in the same manner, WV _L1 ~WV _LN, VW
_{L1 ~VW LN,} it is possible to obtain the VV _L1 ~VV _LN.

Then, with respect to the coefficient signals for each frequency band thus obtained, the weighting coefficient is changed for each frequency band as in the case of the above-mentioned wavelet transform, and the weighted addition of coefficient signals is performed for each frequency band. The addition coefficient signal is obtained by performing the inverse subband conversion of the addition coefficient signal, and the addition signal Sadd with weighted addition can be obtained as in the case of the wavelet transform.

Further, in the above-mentioned embodiment, the image signal is converted into the image signal for each of a plurality of frequency bands by the wavelet transform and the sub-band conversion. The image signal may be converted into the image signal.
However, the Fourier transform needs to use a filter having a long multiple frequency band as shown in FIG. 12, and even if the fast Fourier transform method is used, the image signal can be decomposed by a short filter. The conversion can simplify the configuration of the device for implementing the present invention.

Since the frequency-dependent characteristics of the obtained image differ depending on the radiation dose applied to the stimulable phosphor sheet described above, the central dose at the time of reading is obtained from the reading device and the addition ratio held for each dose is added. You may make it determine the addition ratio of the image signal for every frequency band with reference to a table.

The transform coefficient signal obtained by the above-mentioned wavelet transform or subband transform is an image signal obtained by reducing the original image signal.
The transform coefficient signal obtained by wavelet transforming or subband transforming the image signal obtained by photographing the human chest is
As shown in Fig. 13, it looks like a reduced image of the original image. In such a chest image, the target of observation is the lung field (the lung field 30 at the position corresponding to the coefficient signal WW ₁ ) at each conversion coefficient with which the dose reaching the stimulable phosphor sheet is large. . Further, as described above, the frequency-dependent characteristic of the image also differs depending on the amount of radiation applied to the stimulable phosphor sheet. Therefore, the transform coefficient signal obtained by the wavelet transform or the subband transform is subjected to, for example, histogram analysis or the like to obtain the radiation dose of each part in the image, and the weighting coefficient of the transform coefficient signal representing the part having a large reaching dose. Is made larger than the conversion coefficient signal representing a region having a small arrival dose, an image excellent in observation and interpretation can be obtained. That is, the reaching dose is obtained for each conversion coefficient signal, and the weighting coefficient is increased for the coefficient signal corresponding to the pixel in the lung field portion having the large reaching dose. For example, in the coefficient signal WW _U1 shown in FIG. 13, the superposition ratio with the coefficient signal WW _L1 is 2: 1 for the lung field 30, and 1: 1 for the part 31 other than the lung field 3D.
As described above, the weighting coefficient for the lung field 30 having a large arrival dose, which is an important observation area, may be further weighted to add the coefficient signals.

As described above, by changing the weighting coefficient at the time of addition depending on the part of the image signal, it is possible to obtain an addition signal in which the weighting coefficient is changed for each arrival dose, which is more suitable for observation and interpretation. It is possible to obtain high quality images.

Further, in the above-described embodiment, as shown in FIG. 1, radiation images are accumulated and recorded on the two stimulable phosphor sheets 4A and 4B, and the image signals obtained from the respective sheets 4A and 4B are recorded. Although the addition is made, as shown in FIG. 14, the radiation image of the subject 1 is accumulated and recorded on one stimulable phosphor sheet 4A, and as shown in FIG. The image signals to be superposed may be obtained from The details of this double-sided reading will be described below.

The stimulable phosphor sheet 4A has endless belts 9a and 9b rotated by a motor (not shown).
Placed on top. Above the sheet 4A, a laser light source 10 that emits laser light 11 that is excitation light and the laser light
A rotary polygon mirror 12 is arranged which is rotated by a motor (not shown) for reflecting and deflecting 11 and for main scanning the sheet 4A. Furthermore, above the position where the laser beam 11 is scanned, a focusing guide 14a for focusing the stimulated emission light emitted by the scanning of the laser beam 11 from above is arranged closely, and below the position. Is a light guide for collecting stimulated emission light from below.
14b is arranged perpendicular to the seat 4A. Photomultipliers (photomultiplier tubes) 15a and 15b for photoelectrically detecting the stimulated emission light are connected to the light collecting guides 14a and 14b, respectively. This photomultiplier 15a, 15b
Are connected to logarithmic amplifiers 16a and 16b, and the logarithmic amplifiers 16a and 16b are connected to A / D converters 17a and 17b, and the A / D converters 17a and 17b are connected to a storage device 18.

The stimulable phosphor sheet 4A on which the radiation image of the subject is stored and recorded is set on the endless belts 9a and 9b. The stimulable phosphor sheet 4A set at this predetermined position is conveyed (sub-scanned) in the arrow Y direction by the endless belts 9a and 9b. On the other hand, the laser light 11 emitted from the laser light source 10 is reflected and deflected by the rotary polygon mirror 12 which is driven by a motor (not shown) and rotates at a high speed in the arrow direction, enters the sheet 4A, and the sub-scanning direction (direction of arrow Y).
The main scanning is performed in the direction of the arrow X, which is substantially vertical. From the portion of the sheet 4A irradiated with the laser light 11, the stimulated emission light 13a, 13b having a light amount corresponding to the radiation image information accumulated and recorded.
(Here, the stimulated emission lights 13a and 13b are respectively emitted from the sheet 4A.
Of the upper and lower parts of) are shown). The stimulated emission light 13a is guided by a light collecting guide 14a and photoelectrically detected by a photomultiplier (photomultiplier tube) 15a. The stimulated emission light 13a that has entered the focusing guide 14a from the entrance end face advances through the inside of the focusing guide 14a by repeating total reflection, is emitted from the exit end face, is received by the photomultiplier 15a, and represents a radiation image. The photomultiplier 15a converts the amount of the stimulated emission light 13a into an electric signal. Similarly, the stimulated emission light 13b is guided by the light collecting guide 14b and photoelectrically detected by the photomultiplier (photomultiplier tube) 15b.

The analog output signal S _A output from the photomultiplier 15a is logarithmically amplified by the logarithmic amplifier 16a and input to the A / D converter 17a, where it is converted into a digital image signal S ₁ and stored in the storage medium. Entered in 18. Similarly, the analog output signal S _B output from the photomultiplier 15b is logarithmically amplified by the logarithmic amplifier 16b and input to the A / D converter 17b, where it is converted into a digital image signal S ₂ and stored. It is input to the medium 18. These two
The two image signals S ₁ and S ₂ are decomposed into coefficient signals for a plurality of frequency bands by wavelet transform, sub-band transform or Fourier transform, and obtained from the upper side of the stimulable phosphor sheet 4A as in the above-mentioned embodiment. Image signal S
The weighting coefficient of the coefficient signal of the high frequency band of ₁ is set to be larger than the weighting coefficient of the coefficient signal of the high frequency band of the image signal S ₂ obtained from the lower side of the stimulable phosphor sheet 4A. The coefficient signals for each are added, and the added coefficient signals are subjected to inverse wavelet transform, inverse subband transform, or inverse Fourier transform. By reproducing the added signal thus obtained, it is possible to obtain a high-quality reproduced image in which noise components are reduced as in the above-described embodiment.

In the above-described double-sided reading embodiment,
Although the stimulable phosphor sheet 4A is scanned by the laser light 11 generated from one laser light source 10,
However, the present invention is not limited to this, and as shown in FIG. 16, laser light sources 10a and 10b and rotating polygon mirrors 12a and 12b are provided on the front surface side and the back surface side of the stimulable phosphor sheet 4A, respectively. Laser light 11a, 11 on both sides of 4A
Two image signals may be obtained by scanning b and reading the stimulated emission light.

When the image signals S ₁ and S ₂ obtained by the double-sided reading embodiment are subjected to the wavelet transform and the sub-band transform, the coefficient depends on the part of the image signal as in the above-mentioned embodiment. It is possible to change the weighting coefficient at the time of adding signals, thereby obtaining a signal in which the weighting coefficient is changed for each arrival dose of the image signal, and it is possible to obtain a high-quality image with more excellent observation and interpretation suitability. it can.

In the above embodiment, the A / D
Converter 17, 17a, digitized image signals S _1, S ₂ wavelet transform on the 17b, the weighting of the low frequency components of the signal-to-noise ratio in accordance with the frequency characteristics of the image signals S _1, S ₂ by a Fourier transform The coefficient is processed to be relatively smaller than the weighting coefficient of the frequency component having a high signal-to-noise ratio, but the processing is not limited to this, and is shown in FIG. 2, FIG. 15 or FIG. Accumulative phosphor sheets 4A, 4B by radiation image reading device
The above processing may be performed on the analog output signals S _A and S _B obtained from the above.

An embodiment in which the above processing is performed on the analog output signals S _A and S _B will be described below.

FIG. 17 is a diagram for explaining an embodiment in which the above processing is applied to the analog output signals S _A and S _B.
As shown in FIG. 17, the stimulable phosphor sheet 4 is formed by the radiation image reading apparatus shown in FIG. 2, FIG. 15 or FIG.
The analog output signals S _A and S _B obtained from A and 4 _B are input to the logarithmic converters 16a and 16b. Logarithmic converter 16a,
The output signals S _A and S _B logarithmically amplified in 16b are input to the frequency processing circuits 40a and 40b. Frequency processing circuit 4
In 0a and 40b, the following processing is performed.

Here, in the case of obtaining an image signal by condensing light from both sides of the stimulable phosphor sheet as described above, the image signal obtained from the lower side of the sheet (the side farther than the radiation source) or the sheets are superposed. The high-frequency component of the image signal obtained from the side farther from the radiation source when a radiation image is recorded by this method contains many noise components such as scattered light. By making the weighting coefficient for multiplying the high frequency component smaller than the weighting coefficient for multiplying the high frequency component of the image signal obtained from the upper sheet, it is possible to obtain the superposition signal in which the noise component is reduced. Therefore, in the frequency processing circuit 40a, the filtering processing for emphasizing the high frequency components of the output signal S _A is performed by the filter shown in FIG. 18, and in the frequency processing circuit 40b, the filtering processing shown in FIG.
A filtering process for reducing the high frequency components of the output signal S _B is performed. Since the output signals S _A and S _B are analog signals, the filtering process is performed only in the main scanning direction of the output signals S _A and S _B.

In this way, the frequency processing circuits 40a, 40a
The output signals S _A , S that have been frequency processed at b
_B has the A / D converters 17a, 17b whose error due to aliasing has been removed by the aliasing removal filters 41a, 41b.
It is input to b and converted into digital image signals S ₁ and S ₂ . The digital image signal S obtained in this way
₁ and S ₂ are added, and the added signal Sadd is subjected to predetermined image processing in the image processing means in the same manner as in the above-described embodiment, and is reproduced as a visible image in the reproducing means.

The filters shown in FIGS. 18 and 19 are added signals Sa when digital image signals S ₁ and S ₂ are added.
In order to maximize the DQE of dd, the addition ratio is S _A : S _B = 0.5: 0.5 at 1 cycle / mm, 0.7: 0.3 at 2 cycles / mm, and 0.9: 0.1 at 3 cycles / mm. Is set to. This means that the frequency processing circuit 40b for performing the filtering process on the output signal S _B and the aliasing removal filter 41
The response of means such as b indicates that the high frequency component of the output signal S _B of about 3 cycles / mm may be about 20% as compared with the low frequency component (1 cycle / mm). Therefore, the means for processing the output signal S _B , such as the frequency processing circuit 40b and the aliasing removal filter 41b, can be sufficiently processed by a circuit having a narrower processable band than the means used in the ordinary reading device. Become.

In this way, the analog output signals S _A , S
Processing of relatively small compared to the weighting coefficient of the output signal S _A, a high frequency component weighting coefficients of low frequency components of the signal to noise ratio of the signal to noise ratio in accordance with the frequency characteristics of the S _B against _B By performing the above-mentioned processing, as in the case of performing the above-mentioned processing on the digital image signals S ₁ and S ₂ ,
The added signal has a high signal-to-noise ratio over the entire frequency band, and by reproducing the added signal, a high-quality superimposed image can be obtained. Further, by sufficiently reducing the high frequency component of the output signal S _B , the cutoff frequency of the aliasing removal filter 41b can be lowered, and the aliasing at the time of A / D conversion by the A / D converter 17b is further improved. It can be reduced. further,
Since the parts constituting the log amplifier and the aliasing removal filter of the output signal S _B do not require high speed processing so much, inexpensive parts such as operational amplifiers and transistors which cannot perform high speed processing can be used. The cost can be reduced.

The analog output signals S _A and S described above are used.
_{In the} embodiment for processing _B , frequency processing is performed by the frequency processing circuits 40a and 40b, but the logarithmic amplifiers 16a and 16b and the aliasing elimination filter are used.
By changing the frequency characteristics of 41a and 41b, the high frequency components of the output signal S _A may be emphasized and the high frequency components of the output signal S _B may be reduced, as is done in the aliasing removal filters 41a and 41b. It is a thing.

Further, the analog output signals S _A and S described above are
_{In the} embodiment in which _{B is} processed, both analog output signals S _A and S _B are processed, but the present invention is not limited to this, and one of the analog image signals is processed. Alternatively, frequency processing may be performed, and the processed analog output signal and the unprocessed analog output signal may be digitally converted and added.

In the above-described embodiment, when two image signals are superposed, the image signals are decomposed into coefficient signals for each of a plurality of frequency bands and weighted, but the present invention is not limited to this. However, weighting can be performed as described above even when performing energy subtraction that takes the difference between two image signals. Hereinafter, weighting of the image signal for performing energy subtraction will be described.

FIG. 20 shows two stimulable phosphor sheets 4A and 4A.
FIG. 2 is a diagram showing an imaging device for performing so-called one-shot energy subtraction in which the radiation 2 that has passed through the same subject 1 is irradiated to B with different energies. That is, the first stimulable phosphor sheet 4A is arranged closer to the radiation source 3, and the second stimulable phosphor sheet 4B is arranged at a slight distance from the first stimulable phosphor sheet 4A.
A radiation energy conversion filter 5 made of a copper plate is arranged between A and 4B to drive the radiation source 3.
As a result, a radiation image of the subject 1 is generated on the first stimulable phosphor sheet 4A by the radiation 2 including so-called soft rays, while on the second stimulable phosphor sheet 4B, the radiation image of the subject 1 is generated by the radiation 2 in which the soft rays are removed. Accumulated and recorded. At this time, the positional relationship of the subject 1 is the same between the stimulable phosphor sheets 4A and 4B.

In the above-described manner, radiation images having different image information of at least a part of the subject 1 are recorded on the two stimulable phosphor sheets 4A and 4B.

Next, these two stimulable phosphor sheets 4 are used.
A radiation image is read from A and 4B by the image reading means as shown in FIG. 2 described above, and digital image signals S ₁ and S ₂ representing the image are obtained. Obtained image signals S ₁ , S ₂
Are stored in the storage medium 18.

Next, subtraction processing is performed using the digital image signals S ₁ and S ₂ obtained as described above. FIG. 21 is a diagram showing an outline of this subtraction process. First, the image signals S ₁ and S ₂ are read from the image file 18A and the image file 18B in the storage medium 18 and input to the wavelet transform means 30. The wavelet transform means 30 wavelet transforms the two input image signals S ₁ and S ₂ and decomposes them into image signals for each of a plurality of frequency bands, as in the above-described embodiment of superposition. Thereby, the wavelet transform coefficient signals WW _{U0 to} WW _UN , WV _{U0 to} WV _UN , VW _{U0 to} V obtained from the image signal S ₁
W _UN and VV _UN and wavelet transform coefficients obtained by the image signals S ₂ signals WW _L0 ~WW _LN, WV _L0 ~
Obtaining WV _LN, VW _L0 ~VW _LN and VV _LN.

The wavelet transform coefficient signal thus obtained is input to the weighted subtraction means 31. The weighted subtraction means 31 performs the subtraction processing by making the weighting coefficient of the frequency band having a large noise component relatively smaller than the weighting coefficient of the frequency band having a small noise component. here,
The information in the high frequency band of the image signal S ₂ includes noise such as scattered radiation at the time of shooting, and further, the information on the high frequency band side is blurred due to the fact that the information is high in the two image signals S 2.
₁ and S ₂ have the frequency characteristics as shown in FIGS. 6 (a) and 6 (b) described above. Therefore, the two image signals S ₁ , S ₂
The weighting coefficient when performing the subtraction processing of is determined according to the weighting table as shown in FIG. 9 described above, and the subtraction processing of each wavelet transform coefficient signal is performed based on this weighting coefficient.

That is, for the wavelet transform coefficient signal for each frequency band, WW _i = t · WW _Ui − (1-t) WW _Li WV _i = t · WV _Ui − (1-t) WV _Li (13) Weighted subtraction processing is performed by VW _i = t · VW _Ui − (1-t) VW _Li VV _i = t · VV _Ui − (1-t) VV _Li .

The weighting subtraction means 31 subtracts the subtraction coefficient signals WW _{1 to} WW _N and WV _{1 to} W.
V _N, VW ₁ ~VW _N, the VV ₁ ~VV _N is obtained,
Inverse wavelet transform means 32 subjects each subtraction coefficient signal to inverse wavelet transform in the same manner as in the above-described superimposing embodiment. The subtraction signal subjected to the inverse wavelet transform is input to the image processing means 33, subjected to predetermined image processing, and then input to the reproducing means 34 to be reproduced as a visible image.

In this way, the two image signals S ₁ , S
Wavelet transform ₂ to obtain the wavelet transform coefficient signal for each frequency band, for the wavelet transform coefficient signal for each frequency band, for the high frequency band coefficient signal, the image signal obtained from the upper stimulable phosphor sheet By making the weighting coefficient of (1) larger than the weighting coefficient of the image signal obtained from the lower stimulable phosphor sheet, a subtraction signal with reduced noise is obtained, and by reproducing this, the noise component is reduced. It is possible to obtain a reproduced image of high quality.

In the embodiment of the subtraction processing described above, the subtraction should be performed by one shooting.
The so-called one-shot method for obtaining _two image signals S ₁ and S ₂ at the same time has been described, but the present invention is not limited to this and the two stimulable phosphor sheets are imaged using two types of radiation having different energy distributions. Also in the case where the subtraction processing is performed on the image signal obtained by the so-called two-shot method, the obtained image signal is decomposed into coefficient signals for a plurality of frequency bands, and the weighted subtraction processing is performed on the coefficient signals for each frequency band. It may be applied. The weighting coefficient in this case is an MTF obtained by the energy distribution of two types of radiation when a radiation image is stored and recorded on two storage phosphor sheets.
It may be determined based on the above.

Further, in the above-described embodiment, the image signal is converted into the image signal for each of a plurality of frequency bands by the wavelet transform, but the image signal is converted for each of a plurality of frequency bands by the sub-band transform and the Fourier transform. The image signal may be converted into the image signal.
However, since the Fourier transform needs to use a filter having a plurality of long frequency bands as shown in FIG. 12, for example, a wavelet transform and a subband transform that can decompose an image signal with a short filter implement the present invention. The configuration of the device for doing so can be simplified.

The coefficient signal obtained by the above-mentioned wavelet transform or sub-band transform is an image signal obtained by reducing the original image signal. For example, an image signal obtained by photographing a human chest is As shown in FIG. 13, the transform coefficient signal subjected to the wavelet transform or the sub-band transform is like an image obtained by reducing the original image. Therefore, it depends on the part of the image signal as in the above-described superimposing example. Then, the weighting coefficient at the time of subtraction processing may be changed. As a result, it is possible to obtain a subtraction signal that is weighted differently for each arrival dose of the image signal, and it is possible to obtain a high-quality image that is more suitable for observation and interpretation.

Further, also in the embodiment for performing the energy subtraction described above, after the analog image signals S _A and S _B are frequency-processed by the filters shown in FIGS. 18 and 19 as shown in FIG. Alternatively, S _A and S _B may be digitally converted, and the subtraction processing may be performed on the digitally converted image signals S ₁ and S ₂ .

Further, both analog output signals S _A and S _B
In addition to processing the analog image signal, one of the analog image signals is subjected to frequency processing, and the processed analog output signal and the unprocessed analog output signal are digitally converted to perform subtraction processing. May be.

[Brief description of drawings]

FIG. 1 is a diagram for explaining recording of a radiation image on a stimulable phosphor sheet in an example of an image superimposing method according to the present invention.

FIG. 2 is a diagram showing an apparatus for reading a radiation image from a stimulable phosphor sheet.

FIG. 3 is a diagram showing an outline of an apparatus for performing superposition.

FIG. 4 is a diagram showing details of wavelet transform.

FIG. 5 is a diagram showing a wavelet transform coefficient signal.

FIG. 6 is a diagram showing an MTF of an image signal.

FIG. 7 is a diagram showing a Wiener spectrum of an image signal.

FIG. 8 is a diagram showing DQE in a plurality of frequency bands.

FIG. 9 is a diagram showing a weighting table.

FIG. 10 is a diagram showing details of inverse wavelet transform.

FIG. 11 is a diagram showing details of subband conversion.

FIG. 12 is a diagram showing a filter for performing a Fourier transform.

FIG. 13 is a diagram showing coefficient signals obtained by wavelet transform or subband transform.

FIG. 14 is a diagram showing a state in which a radiation image of one stimulable phosphor sheet is accumulated and recorded.

FIG. 15 is a diagram showing an apparatus for reading a radiation image from both sides of a stimulable phosphor sheet.

FIG. 16 is a diagram showing another device for reading a radiation image from both sides of a stimulable phosphor sheet.

FIG. 17 is a diagram for explaining an example in which frequency processing is performed on an analog output signal.

FIG. 18 is a diagram showing a filter that performs frequency processing on the output signal S _A.

FIG. 19 is a diagram showing a filter that performs frequency processing on the output signal S _B.

FIG. 20 is a diagram for explaining recording of a radiation image on a stimulable phosphor sheet in an example of the energy subtraction method according to the present invention.

FIG. 21 is a diagram showing an outline of an apparatus for performing energy subtraction.

FIG. 22 is a diagram showing a basic wavelet function used for wavelet transform.

FIG. 23 is a diagram for explaining a wavelet transform.

FIG. 24 is a diagram for explaining a Fourier transform.

[Explanation of symbols]

1 subject 2 radiation 3 radiation sources 4A, 4B storage phosphor sheet 10 laser light source 11 Laser light 12 mirror 13, 13a, 13b stimulated emission light 14, 14a, 14b Light guide 15,15a, 15b Photomultiplier 16, 16a, 16b Logarithmic converter 17, 17a, 17b A / D converter 18 Storage medium 19,30 Wavelet transform means 20 Weighted superposition means 21,32 Inverse wavelet transform means 22, 33 Image processing means 23,34 Regeneration means 40a, 40b Frequency processing means 41a, 41b Alias removal filter

─────────────────────────────────────────────────── ─── Continuation of front page (51) Int.Cl. ⁷ Identification code FI G06T 5/00 A61B 6/00 350S H04N 5/325 G06F 15/62 390A 15/68 350 (56) Reference JP-A-5- 232608 (JP, A) JP 2000-147698 (JP, A) JP 60-222034 (JP, A) JP 59-83486 (JP, A) JP 58-163340 (JP, A) Kai 56-11399 (JP, A) (58) Fields investigated (Int.Cl. ⁷ , DB name) G03B 42/02

Claims (16)

(57) [Claims] 1. A plurality of image signals having different frequency characteristics that carry radiation images of the same subject are multiplied by a predetermined weighting coefficient between the signals of pixels corresponding to each other, and addition is performed. In a method of superimposing radiographic images to obtain a signal, a weighting coefficient of a frequency component having a low signal-to-noise ratio is relatively compared to a weighting coefficient of a frequency component having a high signal-to-noise ratio in accordance with the frequency characteristics of each image signal. A method for superimposing images, which is characterized in that 2. A Fourier transform is applied to each of the image signals to decompose each image signal into a Fourier transform coefficient signal for each of a plurality of frequency bands, and a weighting coefficient is changed for each Fourier transform coefficient signal. The image is superposed by adding the Fourier transform coefficient signals to obtain an added Fourier transform coefficient signal for each frequency band, and performing an inverse Fourier transform on the added Fourier transform coefficient signal.
The described image superposition method. 3. Each of the image signals is converted into a multi-resolution space, the image signals are decomposed into transform coefficient signals for each of a plurality of frequency bands, and a weighting coefficient is changed for each transform coefficient signal. 2. The image superimposition according to claim 1, wherein the conversion coefficient signals are added to obtain an addition conversion coefficient signal for each frequency band, and the addition conversion coefficient signals are inversely converted to superimpose the images. Method. 4. The image superimposing method according to claim 3, wherein the conversion into the multi-resolution space is performed by a wavelet transform. 5. The weighting coefficient of a portion having a large arriving dose is set to be relatively larger than that of a portion having a smaller arriving dose according to the portion of the subject included in the radiation image. The image superimposing method according to any one of 3 and 4. 6. Each of the image signals is an analog image signal, and for each of the analog image signals, a filter having a weight that changes the frequency characteristic of the image signal,
2. The image superimposing method according to claim 1, wherein all the analog image signals are filtered and the analog image signals after the filtering are added to superimpose the images. 7. Each of the image signals is an analog image signal, and a desired analog image signal of the analog image signals is selected by a filter having a weight that changes a frequency characteristic of the image signal. The image superimposing method according to claim 1, wherein the analog image signals are filtered, and the analog image signals after the filtering are added to the other analog image signals to superimpose the images. 8. The plurality of image signals are converted into stimulated emission light by scanning excitation light on both sides or one side of a single stimulable phosphor sheet on which a radiation image is stored and recorded, 8. The image superimposing method according to claim 1, which is obtained by photoelectrically reading stimulated emission light obtained from both sides of the stimulable phosphor sheet. 9. The plurality of image signals are converted into stimulated emission light by converting the radiation image into stimulated emission light by scanning excitation light with each of two stimulable phosphor sheets on which a radiation image is stored and recorded. The image superimposing method according to any one of claims 1 to 7, which is obtained by photoelectrically reading emitted light. 10. A plurality of image signals obtained by detecting a plurality of radiation images in which at least some image information obtained by radiations having different energy distributions transmitted through the same subject are different from each other. In an energy subtraction method for obtaining a difference signal that forms an image of the specific structure of the subject by performing a subtraction by multiplying each image signal by a predetermined weighting coefficient between signals of corresponding pixels, An energy subtraction method, characterized in that a weighting coefficient of a frequency component having a low signal-to-noise ratio is made relatively smaller than a weighting coefficient of a frequency component having a high signal-to-noise ratio according to frequency characteristics. 11. A Fourier transform is applied to each of the image signals to decompose each image signal into a Fourier transform coefficient signal for each of a plurality of frequency bands, and a weighting coefficient is changed for each Fourier transform coefficient signal. 11. The subtraction Fourier transform coefficient signal is subtracted to obtain a subtraction Fourier transform coefficient signal for each frequency band, and the difference signal is obtained by inverse Fourier transforming the subtraction Fourier transform coefficient signal. Energy subtraction method. 12. The image signal is converted into a multi-resolution space, the image signal is decomposed into a plurality of conversion coefficient signals for each frequency band, and a weighting coefficient is changed for each conversion coefficient signal. 11. The energy subtraction method according to claim 10, wherein a subtraction conversion coefficient signal for each frequency band is obtained by performing subtraction of the conversion coefficient signal, and the difference signal is obtained by inversely converting the subtraction conversion coefficient signal. 13. The energy subtraction method according to claim 12, wherein the conversion into the multi-resolution space is performed by a wavelet transform. 14. The weighting coefficient of a portion having a large arriving dose is set to be relatively larger than that of a portion having a smaller arriving dose in accordance with the portion of the subject included in the radiation image. The energy subtraction method according to any one of 12 and 13. 15. Each of the image signals is an analog image signal, and for each of the analog image signals, a filter having a weight that changes the frequency characteristic of the image signal,
2. The difference signal is obtained by filtering all the analog image signals and subtracting each analog image signal after the filtering.
The energy subtraction method described in 0. 16. The image signals are analog image signals, and a desired analog image signal of the analog image signals is set to a desired one by a filter having a weight that changes a frequency characteristic of the image signal. 11. The energy subtraction method according to claim 10, wherein the difference signal is obtained by filtering an analog image signal and subtracting the analog image signal after the filtering from the other analog image signal.