KR20120035237A - Image reconstruction method and apparatus for dts(digital tomosynthesis system) - Google Patents

Abstract

PURPOSE: An image reconstructing method and an image reconstructing device of a DTS(Digital Tomosynthesis System) are provided to remove a noise by efficiently processing X-ray projection image data with a back projection reconstruction method. CONSTITUTION: Projection image data about all voxels comprising an object is obtained(S10). Overlap image data is calculated by adding projection image data of each voxel(S20). N complementary image data is calculated by summing the projection image data of each voxel(S40). A difference between the overlap image data and the N complementary overlap image data is calculated(S41). A difference between the overlap image data and the sum of the above differences is calculated(S50).

Description

Image Reconstruction Method and Apparatus for Digital Tomosynthesis System (DTS)}

The present invention relates to an image reconstruction method and apparatus, and more particularly, to an image reconstruction method and apparatus of a digital tomosynthesis system (DTS).

A digital tomosynthesis system (DTS) is a device that reconstructs an image in three dimensions by using projection image data acquired at multiple angles within a limited angle. DTS uses a technique of improving the accuracy of analysis and diagnosis by separating the superimposed image of the subject to be three-dimensional spatially from the two-dimensional projection image. Recently, a lot of research is being carried out to apply this technology to the field of 3D Digital Breast Tomosynthesis (DBT).

The conventional two-dimensional X-ray mammography method detects an image depending on all X-ray attenuations existing in the space from the X-ray source to the detector, so that the lesion region of interest is overlapped by an object above or below the lesion. Accurate identification of lesions was difficult. Of course, using a three-dimensional diagnostic image using a computed tomography (CT) can eliminate this overlap, but CT must be taken from many angles, and one rotation around the subject, There are many limitations in areas such as breast cancer diagnosis in terms of irradiation dose and rotation angle.

In the field of DBT using DTS technology, it is recognized as a very meaningful and highly effective diagnostic technology in that it provides three-dimensional images close to CT while solving such limitations on radiation dose and rotation angle. Therefore, there is a need for an image reconstruction method and apparatus capable of providing accurate identification of lesions in the DBT field using DTS technology.

Accordingly, an object of the present invention is to provide an image reconstruction method and apparatus for a digital tomography imaging apparatus that can efficiently provide accurate identification of lesions.

First, to summarize the features of the present invention, in accordance with an aspect of the present invention for achieving the object of the present invention, the image reconstruction method in the digital tomography imaging apparatus, X-ray at a plurality (N) angle Projecting the object to obtain projection image data b _n for all voxels of a predetermined cube unit constituting the object by using X-ray detection means; Calculating total overlapping image data (X _ALL ) by summing projection image data of each voxel obtained at each of the plurality of angles; Calculating N complementary overlapping image data (X _n ) for each of the plurality of angles by adding projection image data of each voxel except the corresponding angle; Calculating a difference (d _n = X _ALL -Xn) between the entire overlapped image data and the N complementary overlapped image data; And calculating a difference between the total overlapping image data and the total sum of the differences.

The entire superimposed image data X _ALL may be calculated based on Equation 4, and the complementary superimposed image data X _n may be calculated based on Equation 5.

In addition, projection image data of all voxels of a predetermined cube unit constituting the object by using X-ray detection means by projecting an X-ray onto the object at a plurality of (N) angles according to another aspect of the present invention. The image reconstruction device included in the digital tomography imaging apparatus for acquiring (b _n ) may include a first image that calculates total overlapping image data X _ALL by summing projection image data of each voxel obtained at each of the plurality of angles. Synthesis unit; A second image synthesizer configured to calculate N complementary overlapping image data (X _n ) by summing projection image data of each voxel except the corresponding angle for each of the plurality of angles; A difference calculator configured to calculate a difference (d _n = X _ALL -Xn) between the entire overlapped image data and the N complementary overlapped image data; A difference total calculation unit calculating a total sum of the differences; And a subtractor configured to calculate a difference between the total overlapping image data and the total sum of the differences.

According to the image reconstruction method and apparatus of the digital tomography imaging apparatus according to the present invention, X-ray projection image data is effectively processed in an improved method of reverse projection reconstruction method to accurately identify the lesions from which noise such as bleeding phenomenon is removed. Can provide on-line images.

1 is a view for explaining a digital tomography apparatus according to an embodiment of the present invention.
2 is a view for explaining photographing from multiple angles of a digital tomography apparatus according to an embodiment of the present invention.
3 is a flowchart illustrating an image reconstruction method according to an embodiment of the present invention.
4 is an example of an image processing process in the image reconstruction method of FIG. 3.
5 is a block diagram of an image reconstruction apparatus according to an embodiment of the present invention.
6A is an example of a conventional image of a real object after image reconstruction.
6B is an example of an image of the present invention for a real object after image reconstruction.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Reference will now be made in detail to the preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the like elements throughout.

1 is a view for explaining a digital tomography apparatus according to an embodiment of the present invention.

In a digital tomography apparatus according to an embodiment of the present invention, a 3D image reconstruction algorithm is used for diagnosing breast cancer, and moves the X-ray source 110 at various angles to a diagnosis subject (for example, a breast). A method similar to the Cone-beam image reconstruction algorithm using the flat two-dimensional X-ray detector 120 to photograph X-ray images at various angles by projecting X-rays is used.

In the cone-beam imaging structure as described above, after the Cone-beam type X-ray starting at the n-th position of the X-ray source 110 passes through the object and attenuates, the two-dimensional X-ray detector 120 ) And a mathematical model of the projected image data b _n ) detected by applying the linear system theory is represented by Equation 1 or Equation 2.

[Equation 1]

A _n X = b _n

[Equation 2]

The three-dimensional space of the object can be modeled as being composed of voxels of a predetermined cube unit as shown in FIG. 1, where X is a matrix of X-ray luminance values in each voxel, and matrix A _n is a projection model. Although often used as a complex coefficient of, in a simplified model, the distance that an X-ray passes across an object is the X-ray from the nth position of the X-ray source to the corresponding element of the X-ray detector 120. This distance may be the distance passed through the corresponding voxel of the object. The position index n of the X-ray source is 1 ≦ n ≦ N. The matrix b _n representing the projection image data is a vector of two-dimensional projection image data projected onto each two-dimensional element (eg, PD: photo detection cell) of the X-ray detector 120.

Hereinafter, as shown in FIG. 2, the case where N = 3 will be described as an example. When the lesion of the object is in the A and B portions as shown in FIG. 2, the two lesion states appear as overlapped images when photographed in the direction 2, and the lesions of the A region appear to the left of the projection image when photographed in the direction 1, When shooting in direction 3, lesions in area B appear on the left side of the projection image. The DTS technology of the digital tomography imaging apparatus separates an object into three-dimensional space and analyzes the three-dimensional lesion even through an image superimposed on a two-dimensional projection image acquired at multiple angles through the X-ray detector 120. Make sure the location and condition are accurately diagnosed.

If the three-dimensional space of the object is modeled with 1,000 * 1,000 * 1,000 small voxels, then the variable X in the vector form has 1,000,000,000 elements, which is represented using the index, X-ray luminance at the voxel index j. The value can be expressed as X _j . The most widely used cone-beam image reconstruction algorithm is BP (Back-Projection), which can be simply expressed as shown in [Equation 3].

&Quot; (3) "

Here, 1≤n≤N, A _n [m, j] is an X-ray irradiated from the n-th position of the X-ray source 110 to the m-th element of the X-ray detector 120 to detect the j voxel of the object. The distance passed, b _n [m], is the projection image data detected at the m-th element of the X-ray detector 120 from the n-th position of the X-ray source 110, and r _n [m] is the X-ray source 110 X-rays are irradiated from the nth position of the X-ray detector to the mth element of the X-ray detector 120 to represent the total distance passing through the object.

According to the general reverse projection reconstruction method based on Equation 3, in a reconstructed image, an unnecessary object (eg, a part belonging to planes other than its own plane, that is, parts belonging to different cross sections of the object) , Blurring as shown in FIG. 6A due to noises not related to lesion detection may occur, thereby degrading image quality.

In the present invention, by improving the reverse projection reconstruction method of the X-ray projection image data, the image is effectively processed, thereby minimizing the noise such as inter-slices or inter-planes bleeding phenomenon, and accurately identifying the X-ray image for the lesion. We propose a method that can reconstruct a tomographic image to provide.

3 is a flowchart illustrating an image reconstruction method in a digital tomography imaging apparatus according to an embodiment of the present invention.

First, projection image data b _n for all voxels is obtained in the same manner as in FIG. 2 (S10). That is, X-rays are projected onto the object at a plurality of (N) angles to obtain projection image data b _n for all voxels of a predetermined cube unit constituting the object by using the X-ray detector 120. . For example, the projection image data b _n may be obtained by irradiating X-rays on a vertical position of the object and a position shifted 30 degrees left and right from the vertical position.

Next, by adding the projection image data b _n of each voxel obtained at each of the plurality of N angles as described above, the entire superimposed image data X _ALL may be calculated based on Equation 4 (S20). (X _ALL of FIG. 4 Reference).

&Quot; (4) "

일때의 투영 영상 데이터만을 이용하여 재구성한 영상을 Projection-Wise Contribution이라고 하고, 전체 중첩 영상 데이터(X_ALL)의 계산에 이를 이용한다. 전체 중첩 영상 데이터(X_ALL)은

을 구한 후, 모든 복셀 인덱스 j에 대하여

을 합산한 값 또는 이때 합산한 값을 N으로 나눈 값일 수 있다. Here, j is a voxel index, 1 ≦ n ≦ N, 1 ≦ _p ≦ N, and A _n [m, j], b _n [m], and r _n [m] are as described above. First, of the projection data sets acquired at the positions of N X-ray sources 110, n = p

The reconstructed image using only the projection image data at the time is called Projection-Wise Contribution, and is used to calculate the total overlapped image data (X _ALL ). All superimposed image data (X _ALL )

, Then for all voxel index j

It may be the sum of the sum or the sum of the sum of the values divided by N.

Next, for each of the plurality of N angles, the projection image data of each voxel except the corresponding angle may be summed to calculate N complementary overlapping image data X _n based on Equation 5 (S30). / S40). That is, X _{1 ,} X ₂ Calculate X _N (X _{1 ,} X _{2 ,} X _{3 in} FIG. 4) Reference).

[Equation 5]

Here, j is a voxel index, 1 ≦ n ≦ N, n ≠ p, and A _n [m, j], b _n [m], and r _n [m] are as described above. Projection-Wise Complementary Contribution (PWCC) is an image reconstructed from the set of projection image data obtained at the positions of the N X-ray sources 110 when n ≠ p, that is, except the projection image data at the corresponding angle. It is used to calculate N complementary overlapping image data X _n . In this case, when p = 0, it means back projection to the entire object voxel for image reconstruction.

Next, a difference (d _n = X _ALL -Xn) of each of the superimposed superimposed image data X _ALL and the N complementary superimposed image data X _{n in} operation S10 may be calculated (S31 / S41). That is, d _{1 ,} d _2, .. d _N are calculated (d _{1 ,} d _{2 , and} d ₃ of FIG. 4). Reference). In this case, for example, in d ₁ of FIG. 4, an image 410 of a lesion portion that may overlap due to an image of direction 1 may be removed, and in d ₂ of FIG. 4, a lesion that may overlap due to an image of direction 2 may be removed. The image 420 of the region may be removed, and in d ₃ of FIG. 4, the image 430 of the lesion region, which may overlap due to the image of direction 3, may be removed. The removed image is represented by white dots 410, 420, and 430.

)를 계산한다(S50) (도 4의

참조). 이와 같은 결과는 소정 프로세서에서 처리되어 LCD와 같은 디스플레이 수단을 통해 화면에 도 6b와 같은 영상으로 디스플레이할 수 있다. And finally, the difference between the total superimposed value of the total overlapping image data (X _ALL ) and the difference (d _n = X _ALL -Xn) (

) Is calculated (S50) (Fig. 4)

Reference). Such a result may be processed by a predetermined processor and displayed on the screen as an image as shown in FIG. 6B through a display means such as an LCD.

As such, the entire superimposed image data X _ALL includes all of the noises caused by inter-slices or inter-planes bleeding, which are spread to other layers by the projection image data set of each plane. In the present invention, when n ≠ p, that is, by using complementary overlapping image data (X _n ) excluding only projection image data at the corresponding angle, the layer bleeding phenomenon is not included at all. X-ray images were provided for more accurate lesion identification. In addition, in the present invention, by using N-1 complementary overlapping image data X _n for each voxel, the present invention has a feature of having a normal reconstruction value almost similar to that of the entire overlapping image data X _ALL .

5 is a block diagram of an image reconstruction apparatus 10 included in the digital tomography apparatus according to the embodiment of the present invention.

The image reconstruction apparatus 10 according to an embodiment of the present invention may include a first image synthesizer 11, a second image synthesizer 12, a difference calculator 13, a sum calculator 14, and a subtraction. And a portion 15. The components of the image reconstruction apparatus 10 may be implemented by hardware, software, or a combination thereof, and may be implemented so that any one element is included in another element.

을 구한 후, 모든 복셀 인덱스 j에 대하여

을 합산한 값 또는 이때 합산한 값을 N으로 나눈 값일 수 있다. Next, when the projection image data b _n for all voxels is obtained in the same manner as in FIG. 2, the first image synthesizing unit 11 projects the projection image of each voxel obtained at each of a plurality of (N) angles. The total overlapped image data X _ALL may be calculated based on the sum of the data b _n (see S20 of FIG. 3). All superimposed image data (X _ALL )

, Then for all voxel index j

It may be the sum of the sum or the sum of the sum of the values divided by N.

The second image synthesizing unit 12 sums the projection image data of each voxel excluding each of the plurality of angles (N), based on the N complementary overlapping image data X _n based on [Equation 5]. Can be calculated (see S30 / S40 of FIG. 3). That is, X _{1 ,} X ₂ Calculate X _N (X _{1 ,} X _{2 ,} X _{3 in} FIG. 4) Reference). In this case, when p = 0, it means back projection to the entire object voxel for image reconstruction.

The difference calculator 13 may calculate a difference d _n = X _ALL -Xn of each of the overlapping overlapping image data X _ALL and the N complementary overlapping image data X _{n as} described above (S31 of FIG. 3). / S41). That is, d _{1 ,} d _{2 ,} .. d _N is calculated (d _{1 ,} d _{2 ,,} d ₃ of FIG. 4). Reference). In this case, for example, in d ₁ of FIG. 4, an image 410 of a lesion portion that may overlap due to an image of direction 1 may be removed, and in d ₂ of FIG. 4, a lesion that may overlap due to an image of direction 2 may be removed. The image 420 of the region may be removed, and the image 430 of the lesion region, which may overlap due to the image of direction 3, may be removed in d ₃ of FIG. 4. The removed image is represented by white dots 410, 420, and 430.

)를 계산한다(도 3의 S50 참조).The sum calculator 14 calculates the total sum of the difference d _n = X _ALL -Xn, and the subtractor 15 calculates the total overlap image data X _ALL and the difference d _n = X _ALL −. The difference between the total sum of

) Is calculated (see S50 of FIG. 3).

Therefore, through this image reconstruction apparatus 10, when n ≠ p, that is, by using complementary overlapping image data X _n excluding only projection image data at a corresponding angle, all overlapping image data X _ALL By removing the inter-slices or inter-planes bleeding phenomenon, it is possible to provide a clear X-ray image of the lesion as shown in Figure 6b to be able to identify the lesion more accurately.

As described above, the present invention has been described by way of limited embodiments and drawings, but the present invention is not limited to the above embodiments, and those skilled in the art to which the present invention pertains various modifications and variations from such descriptions. This is possible. Therefore, the scope of the present invention should not be limited to the described embodiments, but should be determined not only by the claims below but also by the equivalents of the claims.

Image Reconstruction Device (10)
First image synthesizer 11
Second image synthesizing unit 12
Difference calculator (13)
Total calculation part (14)
Subtraction part (15)

Claims (6)

An image reconstruction method in a digital tomography imaging apparatus,
Projecting X-rays onto the object at a plurality of (N) angles to obtain projection image data b _n for all voxels of a predetermined cube unit constituting the object using X-ray detection means;
Calculating total overlapping image data (X _ALL ) by summing projection image data of each voxel obtained at each of the plurality of angles;
Calculating N complementary overlapping image data (X _n ) for each of the plurality of angles by adding projection image data of each voxel except the corresponding angle;
Calculating a difference (d _n = X _ALL -Xn) between the entire overlapped image data and the N complementary overlapped image data; And
Calculating a difference between the total overlapping image data and the total sum of the differences;
Image reconstruction method comprising a. The method of claim 1,
The all superimposed image data (X _ALL ),
Equations

Where j is the voxel index, 1 ≦ n ≦ N, 1 ≦ _p ≦ N, A _n [m, j] is the mth element of the X-ray detection means from the nth position of the X-ray source The distance X-rays were irradiated and passed through the voxel of the object, b _n [m], is the projection image data detected at the m-th element of the X-ray detection means from the n-th position of the X-ray source, r _n [m ] Is the total distance through which an X-ray is irradiated from the n-th position of the X-ray source to the m-th element of the X-ray detection means and passes through the object. The method of claim 1,
The complementary overlapping image data (X _n ),
Equation

Where j is a voxel index, 1≤n≤N, n ≠ p, A _n [m, j] is X from the nth position of the X-ray source to the mth element of the X-ray detection means The distance at which the ray is irradiated and passed through the j voxel of the object, b _n [m] is the projection image data detected at the mth element of the X-ray detection means from the nth position of the X-ray source, and r _n [m] is An image reconstruction method according to claim 1, wherein the X-ray is irradiated from the n-th position of the X-ray source to the m-th element of the X-ray detection means and passes through the object. Digital tomography which projects X-rays onto an object at multiple (N) angles and obtains projection image data b _n for all voxels in a given cube unit constituting the object by using X-ray detection means. In the image reconstruction device provided in the imaging device,
A first image synthesizer configured to calculate the total overlapped image data X _ALL by summing projection image data of each voxel obtained at each of the plurality of angles;
A second image synthesizer configured to calculate N complementary overlapping image data (X _n ) by summing projection image data of each voxel except the corresponding angle for each of the plurality of angles;
A difference calculator configured to calculate a difference (d _n = X _ALL -Xn) between the entire overlapped image data and the N complementary overlapped image data;
A difference total calculation unit calculating a total sum of the differences;
A subtraction unit for calculating a difference between the total overlapping image data and the total sum of the differences
Image reconstruction apparatus comprising a. The method of claim 4, wherein
The all superimposed image data (X _ALL ),
Equations

Where j is the voxel index, 1 ≦ n ≦ N, 1 ≦ _p ≦ N, A _n [m, j] is the mth element of the X-ray detection means from the nth position of the X-ray source The distance X-rays were irradiated and passed through the voxel of the object, b _n [m], is the projection image data detected at the m-th element of the X-ray detection means from the n-th position of the X-ray source, r _n [m ] Is the total distance through which an X-ray is irradiated from the n-th position of the X-ray source to the m-th element of the X-ray detection means and passes through the object. The method of claim 4, wherein
The complementary overlapping image data (X _n ),
Equation

Where j is a voxel index, 1≤n≤N, n ≠ p, A _n [m, j] is X from the nth position of the X-ray source to the mth element of the X-ray detection means The distance at which the ray is irradiated and passed through the j voxel of the object, b _n [m] is the projection image data detected at the mth element of the X-ray detection means from the nth position of the X-ray source, and r _n [m] is An image reconstruction apparatus, characterized in that the total distance passing through the object by X-rays irradiated from the n-th position of the X-ray source to the m-th element of the X-ray detection means.

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