JPH10108073A - Method and device for processing bone part image - Google Patents

Abstract

PROBLEM TO BE SOLVED: To indicate the change with respect to passage of time of an object, especially a bone beam, in a more easily observable state by respectively bone beam emphasizing the two image data of the different times of photographing and executing an energy subtraction processing. SOLUTION: The plural image data for respectively indicating the plural images of different photographing time periods are stored in a storage means 10, the two object image data (first X-ray image data S1 and second X-ray image data S2) to compare the with respect to passage of time change of the bone beam are read from the storage means 10 and the emphasis processing of the bone beam in a bone part tissue is respectively executed to the two image data S1 and S2 in a bone beam emphasis means 30. In a image-processing means 40, a positioning processing is executed, so as to obtain position correspondence between the image data S1' and S2' for which the emphasis processing is performed. Thereafter, a subtraction processing is performed for respective data for the pixels of the positions, corresponding to each other and difference data for indicating the with respect to passage of time change of the bone beam are obtained.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a bone image processing method and apparatus, and more particularly to a method for observing a change state of a trabecular bone of an object based on temporally different image data of the same object. The present invention relates to a trabecular bone image processing method and apparatus.

[0002]

2. Description of the Related Art In diagnosis and research using medical images such as radiation images and CT images, the same subject is photographed several times at different imaging points in order to examine the progression state or healing state of a lesion such as a tumor. It is often the case that the subject is photographed and the temporal change of the subject is determined from a plurality of images obtained in this way.

Conventionally, an observer such as a physician has compared a plurality of images at different photographing times recorded on an X-ray photographic film in order to judge the temporal change of the subject in this manner. As shown in, for example, Japanese Patent Application Laid-Open No. 1-107739, a medical image may be displayed on an image display means such as a CRT display device, but the situation is basically the same. That is, in this case, a plurality of images at different photographing times are simultaneously displayed or switched and displayed on the image display means, and an observer such as a doctor compares and observes the plurality of display images to determine a temporal change of the subject. Was like that.

However, when comparing a plurality of images as described above, if an observer such as a doctor is unfamiliar, it is sometimes difficult to understand the degree of change over time.

Therefore, the applicant of the present invention performs positioning of each of the images taken at two shooting times to be compared among the plurality of images at different shooting times on image data representing these images, By subtraction processing between the image data of the corresponding pixels, a difference between the two image data is obtained, and by displaying this difference data as a visible image, a temporal change between both photographing time points is displayed on the image display means. Has proposed a technique that allows an observer such as a doctor to easily and clearly observe the change over time of a subject (Japanese Patent Application No. 7-61).
No. 040, 7-61041).

[0006]

However, even with the above-mentioned technique by the present applicant, it is not possible to completely remove the aging of the soft tissue and the artifacts, so that the trabecular bone of the bone tissue particularly effective for diagnosing osteoporosis is used. There is a demand for a technique that makes it possible to observe changes over time as much as possible by eliminating the influence of soft tissues and the like as much as possible.

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and has as its object to provide a bone part image processing method and apparatus capable of showing a change over time of a subject, particularly a trabecular bone, in a more easily observable state. Is what you do.

[0008]

SUMMARY OF THE INVENTION A bone image processing method and apparatus according to the present invention are characterized in that image data representing two radiographic images of the same subject at different imaging time points are respectively enhanced by trabecular trabeculae, so that both imaging time points are obtained. Due to differences in beam hardening applied to images of bone tissue (including trabecular bone) due to changes in the thickness of soft tissue between the two, and differences in the position of soft tissue caused by differences in the shooting posture of the subject at the time of both shootings By reducing the soft tissue artifacts relatively and then performing an energy subtraction process, image data of a temporal change of the trabecular bone which is extremely less affected by the soft tissue is obtained.

That is, the bone part image processing method of the present invention comprises:
A plurality of image data representing images of a subject including a soft tissue and a bone tissue at different imaging times are stored in the image storage means. Each of the read images is subjected to a trabecular emphasis process on the bone tissue, and the read image data is subjected to a position correspondence between the two images. The subtraction process is performed for each of the data of the pixels at the corresponding positions between the two image data subjected to the emphasis processing after the position adjustment processing to indicate the temporal change of the trabecular bone. It is characterized in that difference data is obtained.

Here, when the image data of the two images to be compared is input from the outside, instead of the operation of reading these image data from the storage means, the two input image data are recognized. It may be an operation.

[0011] Further, as the above-mentioned alignment processing, when a predetermined alignment marker is imprinted upon capturing an image of a target, the processing is performed to match the marker, or a document Medical Imaging Technology (Medical Imaging Technology) ) Vol.11 No.3 July 1993 pp.373
Various known methods such as alignment processing by two-dimensional non-linear image deformation shown in FIGS.

The difference data thus obtained may be output to recording means, display means and the like.

It is also possible to apply, as the image data for each photographing time point, two image data respectively representing two images having different energy distributions photographed for energy subtraction processing at each photographing time point. . In this case, prior to performing the trabecular enhancement process, an energy subtraction process for extracting the bone tissue based on the two image data at each of the imaging times is performed to obtain bone image data. The trabecular bone enhancement data, the alignment processing, and the subtraction processing may be performed on the bone part image data obtained at each imaging time. However, when the image data stored in the image storage means is the bone image data obtained by performing the energy subtraction processing, it is not necessary to perform the energy subtraction processing again.

After the trabecular enhancement process and before the alignment process, each image data to be subjected to the alignment process is subjected to a smoothing process, and the smoothed image data is processed. It is desirable to perform a positioning process and a subtraction process. By performing the smoothing process before the alignment process, it is possible to reduce the artifact of the displacement of the trabecular bone caused by a slight difference in the photographing posture of the subject at both photographing times.

If the image data to be subjected to the trabecular enhancement is image data of a high density and high signal level, the trabecular enhancement is performed by a morphological operation represented by the following equation (1). It is preferable to apply a skeleton process based on

[0016]

(Equation 1)

On the other hand, when the image data to be processed is image data having a high luminance and a high signal level, a skeleton process based on a morphological operation represented by the following equation (2) is applied as the trabecular enhancement process. Is preferred.

[0018]

(Equation 2)

Here, the morphological operation (hereinafter, also referred to as morphological processing) and the skeleton processing will be described.

The morphology processing is to selectively extract only a specific image portion such as an abnormal shadow from an original image.
It is a process based on the algorithm of morphology (also called morphology or morphology), and has been studied as an effective method to detect microcalcification images, which is a characteristic form in breast cancer. It is not limited to the microcalcification image in such a mammogram.

In the morphological processing, processing using a structural element B corresponding to the size and shape of an image portion to be extracted is performed, and the extracted image is hardly affected by complicated background information. It does not distort.

That is, this method can detect the calcified image while maintaining the geometric information such as the size, shape, and density distribution better than the general differential processing.

Hereinafter, the outline of the morphological processing will be described.
An example in which the present invention is applied to detection of a microcalcification image in a mammogram will be described.

(Basic calculation of morphology) The morphology processing is generally developed as a set theory in an N-dimensional space. However, for intuitive understanding, a description will be given of a two-dimensional grayscale image.

The point of coordinates (x, y) is represented by a density value f
It is regarded as a space having a height corresponding to (x, y). Here, the density value f (x, y) is a high-luminance high-signal level signal having a larger image signal value as the density is lower (the brightness is higher when displayed on a CRT).

First, for simplicity, consider a one-dimensional function f (x) corresponding to a cross section of the two-dimensional gray image. The structuring element g used in the morphological operation is a symmetric function symmetric with respect to the origin as shown in the following equation (3).

[0027]

(Equation 3)

It is assumed that the value is 0 in the domain and the domain G is represented by the following equation (4).

[0029]

(Equation 4)

At this time, the basic form of the morphological operation is a very simple operation as shown in equations (5) to (8).

[0031]

(Equation 5)

That is, the dilation processing is performed in a range of ± m (a value determined according to the structural element B and corresponding to the mask size in FIG. 6) around the target pixel. Is a process of searching for a maximum value within the range (see FIG. 2A). On the other hand, an erosion process is a process of searching for a minimum value within a range of ± m around the pixel of interest. (See FIG. 2B). The opening process is a process of performing a dilation process after the erosion process, that is, a process of searching for a maximum value after searching for a minimum value.
ing) The process corresponds to a process of performing an erosion process after a dilation process, that is, a process of searching for a minimum value after searching for a maximum value.

That is, in the opening process, the density curve f (x) is smoothed from the low luminance side, and a convex density fluctuation portion (a portion higher in luminance than the surrounding portion) which fluctuates in a spatially narrower range than the mask size 2 m. (See FIG. 3C).

On the other hand, in the closing process, the density curve f (x) is smoothed from the high brightness side, and a concave density variation portion (a portion having a lower brightness than the surrounding portion) which fluctuates in a space narrower than the mask size of 2 m. (See FIG. 3D).

When the structural element g is not symmetrical with respect to the origin, the dilation operation shown in equation (5) is called Minkowski sum, and the erosion operation shown in equation (6) is called Minkowski difference.

Here, in the case of a signal having a high density and a high signal level, the higher the density, the higher the density, the higher the density f
Since the magnitude relationship is reversed with respect to the case where the image signal value of (x) is at the high luminance and high signal level, the dilation processing for the high density and high signal level signal and the erosion processing for the high luminance and high signal level (FIG. )), The erosion processing for the high-density high-signal level signal and the dilation processing for the high-brightness high-signal level (FIG. 10A) correspond to the opening processing for the high-density high-signal level signal. The closing process for a high-brightness high-signal level and the opening process for a high-brightness / high-signal level (FIG. 10C) match with the closing process for the high-brightness / high-signal level. .

In this section, the case of an image signal (luminance value) at a high luminance and high signal level will be described.

(Application to Calcified Shading Detection) For the detection of calcified shadows, a difference method of subtracting a smoothed image from an original image can be considered. It is difficult to distinguish calcified shadows from elongated non-calcified shadows (such as mammary glands, blood vessels, and mammary gland supporting tissues) using a simple smoothing method. A morphological filter represented by the following equation (9) based on the opening process has been proposed (“Extraction of microcalcification image by morphological filter using multiple structural elements”, IEICE Transactions D-II Vol. .J75-D-II No.7 P1170-1176 July 1992
Tsuki, "Basics of Morphology and Its Application to Mammogram Processing" MEDICAL IMAGING TECHNOLOGY Vol.12 No.1 Jan
uary 1994).

[0039]

(Equation 6)

Here, Bi (i = 1, 2,..., N) has a linear size of n pixels and n pixels (for example, in the case of FIG. 7, there are nine pixels in four directions and m = 9, n = 4) (these elements are collectively referred to as multiplexed structural elements in the m-pixel and n-directions). If the structuring element Bi is set to be larger than the calcified shadow to be detected, the processing by the above-described opening calculation causes a signal change portion finer than the structuring element Bi (an image portion in which the signal fluctuates in a narrow spatial range). The calcified shadow, which is a convex portion having a luminance value larger than that of the surroundings, is removed. On the other hand, a noncalcified shadow such as a shadow of an elongated mammary gland is longer than the structural element Bi, and if its inclination matches any of the four structural elements Bi, the opening process (the equation (9)) Even if the two-term operation is performed, it remains as it is. Therefore, a smoothed image obtained by the opening process (an image from which only calcified shadows have been removed)
Is subtracted from the original image f to obtain an image including only small calcified shadows. This is the concept of equation (9).

As described above, in the case of a signal having a high density and a high signal level, the density value of the calcified shadow is lower than that of the surrounding image portion, and the density value of the calcified shadow is lower than that of the surrounding portion. Since the signal change portion has a small concave shape, a closing process is applied instead of the opening process, and Expression (10) is applied instead of Expression (9).

[0042]

(Equation 7)

The closing processing of the equation (10), which is an example of the morphological operation, will be specifically described.

That is, according to the morphological operation on the density value Sorg which is the image signal of the high density and high signal level, for example, the density value Sor as shown by the solid line in FIG.
The maximum value processing (dilation processing) is performed on the image data having the distribution of g with the linear three-pixel structural element B as shown in FIG. S _i is converted to S _i ′ employing the maximum value S _{i + 1} among three pixels (determined by the structural element B) adjacent to each other with the target pixel as the center. By performing this calculation for all the pixels, it is converted into a maximum value signal indicated by a broken line in FIG.

Next, considering the minimum value processing (erosion processing) by the structural element B for the maximum value signal obtained by this maximum value processing, the pixel of interest indicated by the broken line in FIG. The maximum value signal S _i ′ is converted into S _i ″ (= S _i ) using the minimum value S _i−1 ′ among three pixels adjacent to each other with the target pixel as a center. , The distribution of the minimum value signal Sorg ″ after the maximum value processing is indicated by the dashed line in FIG. In the image signal indicated by the dashed line, the image portion where the signal fluctuates in a spatially narrower range than the structural element B with respect to the original solid line original image data disappears,
This indicates that an image portion which is a change portion of the signal value which fluctuates in a wider range spatially than the structural element B and an image portion having no change remain in the original shape. That is, the above process (closing process) acts as a process for smoothing the image density distribution from the high density side.

The value Smor obtained by subtracting the value obtained by the closing process (the value obtained by performing the maximum value process on Sorg and then performing the minimum value process) from the original image signal Sorg is: It represents an image portion which is a change portion of a signal value which fluctuates in a narrow spatial range and is erased by the above-described closing process.

Here, the image signal is originally a position (x, y) which is a two-dimensional element and a signal value f which is a third-dimensional element.
(X, y), but in the above description, a one-dimensional image signal distribution curve which appeared on a predetermined cross section of an image developed on two dimensions has been described for ease of understanding. .

Therefore, in practice, it is necessary to apply the above description to a two-dimensional image, and the multiple structural elements are used in order to correspond to the two-dimensional image.

Next, the skeleton processing based on the morphological operation will be described.

The skeleton processing is generally a skeleton of a figure (sk
eleton), and the skeleton can be regarded as a set of centers of disks inscribed in the figure. That is, for example, the skeleton of each figure (represented by a solid bold line) shown in FIGS. 9A to 9E is represented by a thick solid line.

Hereinafter, a case where the skeleton processing is performed by the above-described morphological operation will be described.
In this case, the skeleton processing is performed by the following equation (1) or (2).
Can be represented by

[0052]

(Equation 1)

[0053]

(Equation 2)

Here, the equations (1) and (2) are as described above.
This is due to the difference between representing the image as a high-density high-signal-level image signal or a high-luminance high-signal-level image signal. Expression (1) is applied to extract the skeleton of the image portion of (high luminance), while extracting the skeleton of the image portion of low luminance (high density) from the image represented by the image signal of high luminance and high signal level In this case, equation (2) is applied, and there is no substantial difference in the operation itself.

For example, on a negative film (high density and high signal level), the bone part has a lower density than other image parts, and the part where the trabecular bone exists has a lower density.
The portion that does not exist has a higher concentration. Accordingly, since this corresponds to performing skeleton processing on a trabecular bone which is a portion having a lower density than the surroundings, equation (1) may be applied.

Here, the structural element B in the equation (1) is a circle having a radius r, and a state is shown in which the skeleton processing has been performed on the figure shown in FIG. In the graphic shown in FIG. 10, the area outside the contour is a high density part, and the inside is the low density part.

First, the figure is subjected to erosion processing by the structural element B in the upper part of the figure. At λ = 0 (zero erosion processing by the structural element B), the figure does not change at all.

In λ = 1 (one erosion process using the structural element B), the figure is embedded inside the structural element B by the radius r.

In λ = 2 (two erosion processes by the structural element B), the portion of the figure projecting from the circle completely disappears.

By repeating the same operation, λ = N
-1 (N-1 times of erosion processing by structural element B)
And the figure is only a circle with a radius of r or less.

On the other hand, the middle part of the drawing shows the opening of each structural element B on the image subjected to the erosion processing (λ = 0, 1, 2,..., N-1, N) by the structural element B. This is a processed graphic.

The figure in which the figure in the middle of the figure is subtracted from the figure in the upper part of the figure in correspondence with the number of processes is the lower figure.

At λ = 1, it can be seen that the skeleton element of the portion protruding from the circle of the original figure is extracted, and at λ = N−1, the skeleton element of the circle of the original figure is extracted.

In this way, the original figure is subjected to the erosion processing, the opening processing is further performed, the processing times are subtracted correspondingly, and the union of the results is obtained by the expression (1). .

In equation (2), the level of density is effective for extracting a skeleton element from a figure inverted from that in equation (1). Dilation processing is performed on the original figure, and further closing processing is performed. , Deduct corresponding to the number of processing,
This means that a skeleton element is extracted by obtaining a union of the results.

As described above, by applying the skeleton processing based on the morphological operation represented by the equation (1) or (2) as the trabecular enhancement processing, the influence from the complicated background information is suppressed and the trabecular bone ( Or only the skeleton of the trabecular bone) can be effectively emphasized.

As the union set in the above formulas (1) and (2), the union set having only a relatively large value of n 1, that is, λ = 2, 3, excluding the case of n 1 = 0, 1 4,
By adopting the union of 5 or the like and displaying the skeletal elements obtained in this case, the change of the trabecular bone can be more easily seen, which is preferable. This is especially true when λ is 0 or 1.
Since noise components with extremely high spatial frequencies are also extracted,
This is because by removing these noise components from the union, an image with higher interpretation performance can be obtained. The same applies to the following inventions.

A bone image processing apparatus according to the present invention is an apparatus for performing the bone image processing method according to the present invention, and includes a subject including a plurality of soft tissues and bone tissues at different imaging times. Storage means for storing image data representing an image having a subject as a subject, reading means for reading out image data of two images to be compared from the storage means, and reading means for each of the read image data. Trabecular bone enhancement means for performing enhancement processing of trabecular bone in bone tissue, and performing alignment processing on these enhanced image data so that a positional correspondence can be obtained between the two images. Image processing means for performing subtraction processing for each of the data of the pixels at the corresponding positions between the two image data subjected to the emphasis processing to obtain difference data indicating a temporal change of the trabecular bone The is characterized in that it comprises.

Here, it is also possible to apply, to the image data at each photographing time point, two image data representing two images having different energy distributions, which are photographed at each photographing time point for energy subtraction processing, respectively. it can. In this case, the 2
Energy subtraction means for performing energy subtraction processing for extracting the bone tissue based on the two pieces of image data, wherein the trabecular enhancement means performs the bone subtraction processing on the bone image data obtained by the energy subtraction processing. If the image data stored in the image storage means is the bone image data obtained by performing the energy subtraction processing, the energy subtraction processing is performed again. You do not need to do
It is not necessary to further include the energy subtraction means.

Further, in order to reduce the artifact of the displacement of the trabecular bone due to the difference in the photographing posture, a smoothing processing means for performing a smoothing process on each image data to be subjected to the above-mentioned positioning process is further provided. It is preferable to adopt the configuration described above.

When the image data to be subjected to the trabecular enhancement processing by the trabecular enhancement means is image data of a high density and a high signal level, the trabecular enhancement processing is expressed by the equation (1). It is preferable to apply a skeleton process based on a morphological operation to be performed. On the other hand, when the image data to be processed is a high-brightness high-signal level image data, the trabecular bone enhancement process is expressed by the formula (2). It is preferable to apply a skeleton process based on the indicated morphological operation.

[0072]

According to the bone image processing method and apparatus of the present invention, the trabecular trabecula is emphasized on image data representing two radiographic images of the same subject at different photographing times, so that soft tissue between the two photographing times is obtained. Of soft tissue caused by differences in beam hardening applied to images of bone tissue (including trabecular bone) due to changes in the thickness of the soft tissue and the displacement of soft tissue caused by the difference in the shooting posture of the subject at the time of both shootings Is relatively reduced, and then the energy subtraction process is performed, so that image data of a temporal change of the trabecular bone which is extremely less affected by soft tissue can be obtained. Therefore, if the obtained image data is output as a visible image to a recording medium such as a film or a display means such as a CRT based on the obtained image data, it is possible to observe the temporal change of the trabecular bone which is extremely less affected by the soft tissue. it can.

Further, as the image data representing the radiation image, bone image data obtained by enhancing or extracting a bone tissue of a high energy image and a low energy image by energy subtraction processing can be used. The influence of the soft tissue can be suppressed as compared with the case where the data is used as it is.

After the trabecular enhancement process and before the alignment process, each image data to be subjected to the alignment process is subjected to a smoothing process, and the image data subjected to the smoothing process is processed. It is desirable to perform a positioning process and a subtraction process. By performing the smoothing process before the positioning process, it is possible to reduce the artifact of the displacement of the trabecular bone caused by a slight difference in the photographing posture of the subject between the two photographing times.

When the image data to be subjected to trabecular enhancement is image data of a high density and high signal level, the trabecular enhancement is expressed by equation (1) or (2). By applying the skeleton processing based on the morphology operation, it is possible to suppress the influence of complicated background information and effectively emphasize only the trabecular bone (or the skeleton of the trabecular bone).

[0076]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a specific embodiment of a bone image processing apparatus according to the present invention will be described with reference to the drawings.

FIG. 1 is a block diagram showing the configuration of the first embodiment of the bone image processing apparatus of the present invention, and FIG. 2 is a diagram showing the flow of operation of the bone image processing apparatus shown in FIG.

The illustrated bone image processing apparatus 100 stores a plurality of image data representing a plurality of images of different subjects at different imaging times, each of which is a subject including a soft tissue A and a bone tissue B. Means 10 and image data (first X-ray image data S1) of two images (first X-ray image P1 and second X-ray image P2) to be compared with each other in the trabecular change from the storage means 10. , The second X-ray image data S
2) reading means 20 for reading out 2)
Trabecular emphasis means 30 for performing an emphasis process on trabecular bone C in skeletal tissue B for each of the image data S1 and S2;
These emphasized image data S1 ′ and S2 ′ are
Positioning processing is performed so that a positional correspondence can be obtained between these two images, and between the two image data S1 ′ and S2 ′ that have undergone the positioning processing, pixels corresponding to the corresponding positions are obtained. The image processing unit 40 performs a subtraction process for each data to obtain difference data indicating a temporal change of the trabecular bone.

Here, as the trabecular enhancement means 30, as an example, a skeleton processing means based on a morphological operation for performing a skeleton processing based on a morphological operation represented by the following equation (1) is applied.

[0080]

(Equation 1)

FIG. 3 is a schematic diagram visualizing the manner in which changes over time are extracted by the operation of the bone image processing apparatus of the present embodiment.

Hereinafter, the bone image processing apparatus 100 of this embodiment will be described.
The operation of will be described.

The storage means 10 of the bone image processing apparatus 100 shown in FIG. 1 stores image data Si respectively representing a plurality of X-ray images Pi of the same subject photographed at different photographing times.
Is stored.

Here, the reading means 20 reads two image data sets S1 (first X.sup.1) which are input from, for example, a doctor or a radiological technologist or the like, and have different photographing times to be compared.
(Line image data) and S2 (second X-ray image data).

The read first X-ray image data S1
And the second X-ray image data S2 are input to the trabecular bone enhancing means 30. The trabecular enhancement means 30 converts the input first X-ray image data S1 and second X-ray image data S2 into the equation (1).
The skeleton process based on the morphological operation shown in (1) is performed, and the trabecular bone C of the bone tissue B is emphasized from each of the image data S1 and S2. The structural elements used in the morphological operation are set in advance to have a size suitable for extracting the skeleton of the trabecular bone.

The trabecular bone C is a spongy material that extends vertically and horizontally inside the bone. In the radiographic image, the spongy material that extends vertically and horizontally is imaged in multiple layers. By the skeleton processing, as shown in FIG. 3, only the spongy skeleton is extracted as an overlapping image. The first X-ray image P1 'represented by the emphasized first X-ray image data S1' and the second X-ray image P represented by the second X-ray image data S2 '
2 'is an image in which the soft tissue A is almost completely erased.

Next, this trabecular C is subjected to the first X
The line image data S1 'and the second X-ray image data S2' are input to the image processing means 40.

The image processing means 40 includes the trabecular enhancement means 30
The first X-ray image data S1 'and the second X-ray image data S2' which have passed through and the first X-ray image data S1 and the second X-ray image data S2 which do not pass through the trabecular enhancement means 30 are input.

Here, the image Pi represented by each image data Si stored in the storage means 10 is added to the image processing means 40.
, A marker D serving as an index for aligning the two images is printed.
30, the first X-ray image data S1 '
In the second X-ray image data S2 ', the marker D
Will be erased. Therefore, the image processing means 40 sets the marker D in the first X-ray image data S1 and the second X-ray image data S2 input without passing through the trabecular enhancement means 30
, Information for positioning (referred to as positioning information) is calculated based on the position of the first X-ray image data S1 'and the second X-ray image data S2' based on the positioning information.
And position.

Further, the first X-ray image data S1 'and the second X-ray image data S2' which have been subjected to the alignment are subjected to a subtraction process by the image processing means 40 for each data of the pixel at the corresponding position. Difference data ΔS ₁₂ indicating the temporal change of the trabecular bone is obtained.

The obtained difference data ΔS ₁₂ is output from the bone image processing apparatus 100 of the present embodiment to an image output device such as the image display device 200, and the visible image represented by the difference data ΔS ₁₂ , that is, the trabecular bone The change over time is displayed.

The displayed visible image is obtained by emphasizing the trabecular trabecules of the first X-ray image data S1 and the second X-ray image data S2, which are the original images, to change the thickness of the soft tissue between the two imaging times. It is possible to relatively reduce the soft tissue artifact caused by the difference in beam hardening given to the image of the trabecular bone and the displacement of the soft tissue caused by the difference in the photographing posture of the subject at the time of both photographing. By performing the subtraction processing based on the image where has relatively decreased,
The obtained image is very little affected by soft tissue.

Since the obtained image is the image data ΔS ₁₂ showing the temporal change of the trabecular bone, this image data ΔS ₁₂
Based on the S _12, the recording medium or CRT of the film such as
Is output as a visible image to a display means such as the like, since a change with time of the trabecular bone, which is extremely little affected by the soft tissue, is displayed, it is possible to obtain an image which is easy to diagnose and easy to observe.

Although the skeleton image processing apparatus of this embodiment uses skeleton processing means based on morphological operation as trabecular enhancement means, the skeleton image processing apparatus of the present invention is not limited to this mode. Various other means can be used that can emphasize

The positioning process in the image processing means is not limited to the method using markers as in the present embodiment, but the positioning process based on the two-dimensional non-linear image deformation described above (see Medical Imaging Technology Vol. 11).
No. 3, July 1993, pp. 373-374) and various other known methods can be applied.

FIG. 4 is a block diagram showing the structure of the second embodiment of the bone image processing apparatus according to the present invention. The illustrated bone image processing apparatus is different from the apparatus of the embodiment shown in FIG.
Smoothing means 50 between trabecular enhancement means 30 and image processing means 40
And the energy subtraction (abbreviated as “energy sub” in the figure) in place of the original image data (first X-ray image data S1 and second X-ray image data S2) as the image data to be processed by this apparatus. 1) except that the processed image data (refer to Japanese Patent Laid-Open No. 59-83486) is used (first energy subtraction image data and second energy subtraction image data). Is the same as

In the bone image processing apparatus according to the second embodiment, since the energy subtraction image data is to be processed, the soft tissue can be erased to some extent in advance, and the influence of artifacts or the like due to the soft tissue can be reduced. Further, it is possible to obtain image data indicating a reduced temporal change of the trabecular bone C.

The image data representing the trabecular bone C at each imaging time point obtained by the emphasis processing by the trabecular emphasis means 30 is subjected to smoothing processing by the smoothing means 50, so that It is also possible to reduce the trabecular artefacts caused by the displacement of the bone tissue caused by the difference in the photographing posture of the subject, and the image processing apparatus 40 between the trabecular weighted images in which such artifacts have been reduced.
By performing the subtraction process, image data indicating a temporal change of the trabecular bone which is more excellent in the observation and interpretation performance than the bone image processing apparatus of the first embodiment can be obtained.

As the smoothing processing by the smoothing means, various known methods such as unsharp mask processing (spatial filtering using a matrix) can be applied, and the same applies to the first embodiment. Can be applied.

In the second embodiment (FIG. 4), the configuration in the case where the image data stored in the storage means 10 is the energy sub-image data which has already been subjected to the energy subtraction processing has been described. A configuration in which the high-voltage image and the low-voltage image before the energy subtraction processing are stored in the storage unit 10 (third embodiment) may be adopted (see FIG. 5).

In the third embodiment, the trabecular bone enhancement processing, the smoothing processing, the positioning processing, and the subtraction processing are performed on the energy subtraction image data, but the stored image data is processed before the energy subtraction processing. Since the image data is image data, an energy subtraction processing means (abbreviated as “energy sub-means”) 60 is further provided in addition to the apparatus of the second embodiment. Based on the image and the low-voltage image, energy subtraction image data at each photographing time point is obtained, and the obtained trabecular bone enhancement processing, smoothing processing, positioning processing, and subtraction processing are performed on the obtained energy subtraction image data. Other configurations, operations, and effects are the same as those of the device of the second embodiment.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a configuration of a first embodiment of a bone image processing apparatus of the present invention.

FIG. 2 is a diagram showing a flow of operation of the bone image processing apparatus shown in FIG. 1;

FIG. 3 is a schematic view visualizing a state in which a change with time is extracted by the operation of the bone image processing apparatus of the embodiment shown in FIG. 1;

FIG. 4 is a block diagram showing a configuration of a second embodiment of the bone image processing apparatus of the present invention.

FIG. 5 is a block diagram showing a configuration of a third embodiment of the bone image processing apparatus of the present invention.

FIG. 6 is a diagram showing a basic operation of morphological processing;
(A) dilation processing, (B) erosion processing, (C) opening (openin)
g) processing, (D) closing processing

FIG. 7 is a diagram showing an example of a structural element Bi used for morphological processing;

FIG. 8 is a diagram specifically illustrating a closing process;

FIG. 9 is a diagram showing various figures and their skeletons.

FIG. 10 is a diagram specifically illustrating skeleton processing;

[Explanation of symbols]

 10 storage means 20 reading means 30 trabecular enhancement means 40 image processing means 50 smoothing means 60 energy subtraction processing means 100 bone image processing means 200 display device

Claims (14)

[Claims] 1. An image storage unit in which image data representing an image of a subject including a soft tissue and a bone tissue at different photographing points is stored from image storage means for storing two images to be compared. The image data is read out, and the read-out image data are subjected to the trabecular enhancement processing in the bone tissue, respectively, and the emphasized image data is positioned between the two images. The alignment processing is performed so that correspondence can be obtained. After the alignment processing, the subtraction processing is performed for each data of the pixel at the corresponding position between the two pieces of image data subjected to the enhancement processing, and A bone part image processing method, wherein difference data indicating a temporal change is obtained. 2. The image data for each photographing time point is composed of two image data respectively representing two images having different energy distributions photographed for energy subtraction processing at each photographing time point, and Prior to performing the emphasis processing, energy subtraction processing for extracting the bone tissue based on the two image data at each of the imaging time points is performed to obtain bone image data. 2. The bone image processing method according to claim 1, wherein the trabecular enhancement processing, the positioning processing, and the subtraction processing are performed on the obtained bone image data. 3. After the trabecular emphasis processing and before the alignment processing, each image data to be subjected to the alignment processing is subjected to a smoothing processing, and the image data subjected to the smoothing processing is subjected to a smoothing processing. 3. The bone image processing method according to claim 1, wherein the alignment processing and the subtraction processing are performed on the bone image. 4. The trabecular enhancement process is a skeleton process based on a morphological operation represented by the following equation (1), and an image to which the morphological operation is applied is represented by an image signal having a high density and a high signal level. The bone image processing method according to any one of claims 1 to 3, wherein the bone image processing method comprises: (Equation 1) 5. The bone image processing method according to claim 4, wherein the value of n1 in said equation (1) is 2 or more. 6. The trabecular enhancement process is a skeleton process based on a morphological operation represented by the following equation (2), and an image to which the morphological operation is applied is represented by an image signal of a high luminance and high signal level. The bone image processing method according to any one of claims 1 to 3, wherein the bone image processing method comprises: (Equation 2) 7. The bone image processing method according to claim 6, wherein the value of n1 in said equation (2) is 2 or more. 8. A storage means for storing image data representing a plurality of images of a subject including a soft tissue and a bone tissue at different imaging times, and two images to be compared from the storage means. Reading means for reading out image data of the above, trabecular enhancement means for performing trabecular enhancement processing on the bone tissue with respect to each of the read image data, , A position matching process is performed so that a position correspondence can be obtained between the two images, and after the position matching process, between the two pieces of image data that have been subjected to the emphasized process, for each data of a pixel at a corresponding position. Image processing means for performing subtraction processing to obtain difference data indicating a temporal change of the trabecular bone. 9. The image data for each photographing time point is composed of two image data representing two images having different energy distributions photographed for energy subtraction processing at each photographing time point, respectively. Further comprising energy subtraction means for performing energy subtraction processing for extracting the bone tissue based on the two image data at each point in time, wherein the trabecular bone emphasis means converts the bone image data obtained by the energy subtraction processing to The bone image processing apparatus according to claim 8, wherein the trabecular bone is enhanced. 10. The bone image processing apparatus according to claim 8, further comprising: a smoothing processing unit configured to perform a smoothing process on each image data to be subjected to the positioning process. 11. The trabecular enhancement processing by the trabecular enhancement means is a skeleton processing based on a morphological operation represented by the following equation (1), and an image to which the morphological operation is applied is an image having a high density and a high signal level. The bone image processing apparatus according to any one of claims 8 to 10, wherein the bone image processing apparatus is represented by a signal. (Equation 1) 12. The bone image processing apparatus according to claim 11, wherein the value of n1 in said equation (1) is 2 or more. 13. The trabecular enhancement processing by the trabecular enhancement means is a skeleton processing based on a morphological operation represented by the following equation (2), and an image to which the morphological operation is applied is an image having a high luminance and a high signal level. The bone image processing apparatus according to any one of claims 8 to 10, wherein the bone image processing apparatus is represented by a signal. (Equation 2) 14. The bone image processing apparatus according to claim 13, wherein the value of n1 in said equation (2) is 2 or more.