JP2002306480A - Image processing apparatus and method - Google Patents

Abstract

(57) [Summary] [Problem] For voxel data having a large volume such as a medical image, only a target organ and its surrounding image data are extracted from the data to newly create small volume data. Thus, an image processing apparatus capable of improving the efficiency of subsequent image processing and image storage is provided. SOLUTION: An outline of a target region of an organ in input data obtained by photographing an organ is recognized, a three-dimensional shape of the organ is calculated based on the outline, and then the smallest polyhedron including the organ is recognized. Is extracted as the minimum data, and the minimum data is stored together with the name of the organ and a label indicating the position in the living body.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to an image processing apparatus and method in medical image processing technology for handling voxel data and the like.

[0002]

2. Description of the Related Art Conventionally, most medical image data is a two-dimensional cross-sectional image of a living body. However, three-dimensional data can be acquired in the future with the development of imaging technology.

[0003] At this time, when two-dimensional data is conventionally expressed as three-dimensional voxel data directly combined,
The data size becomes enormous, and it takes time for data processing and data transfer. It is also assumed that a large-capacity recording medium is required for data storage.

[0004] Here, the expression using three-dimensional voxel data means that an object is expressed as a mass of a combination of small cubes of the same size. This small cube is called a voxel. It is excellent for expressing objects whose surface is not smooth, and any shape can be created by stacking voxels like blocks. On the other hand, the representation by voxel data requires a huge amount of data,
Not actively used. For example, 200 × 200 × 200
Requires 8 million voxels to represent the voxel region of Even if one voxel is represented by one byte,
Requires 8MB of memory. For this reason, it is mainly used in limited fields such as imaging of measurement data of a CT (Computed Tomography) scanner in the medical field.

[0005]

As described above, when handling three-dimensional voxel data in which conventional two-dimensional data is directly combined, the data size becomes enormous, and enormous processing and storage time is required. It takes.

However, in a medical image, the data area other than the target organ in the voxel data is often unnecessary because the imaging range is limited depending on the image acquisition means.

For example, FIG. 7 obtained by an ultrasonic echo or the like
For the voxel data like a rectangular parallelepiped in (a), the imaging range is conical as shown in FIG. 7 (b) due to the characteristics of the ultrasonic probe.

In addition, since the region of the target organ is often a part of the photographing range as shown in FIG. 7D, other parts as shown in FIG. 7C are unnecessary data regions. Often it is.

[0009] Therefore, from the voxel data, FIG.
If only the data including the target organ can be extracted as in the above, it is expected that the amount of data can be reduced and the subsequent data processing can be facilitated.

Therefore, in the present invention, the amount of data is reduced by extracting only the target organ and the surrounding image data and creating new data having a smaller capacity than the original data. Provided are an image processing apparatus that can easily perform processing and a method thereof.

[0011]

According to a first aspect of the present invention, there is provided a three-dimensional shape calculating means for calculating a three-dimensional shape of an object from a two-dimensional image of the object such as a living organ or a three-dimensional image. And minimum data calculating means for calculating minimum three-dimensional data including the object from the data of the three-dimensional shape of the object, and a minimum three-dimensional data of the calculated object.
And a data storage and output means for storing or outputting the dimensional data.

According to a second aspect of the present invention, the minimum data calculating means calculates a set of pixel values inside a polyhedron having a minimum size including the object, and defines the set as minimum three-dimensional data. The image processing apparatus according to claim 1, wherein:

According to a third aspect of the present invention, the three-dimensional shape calculating means includes a two-dimensional image generating means for generating a two-dimensional image from three-dimensional voxel data obtained by imaging the object; 3. An apparatus according to claim 1, further comprising: a contour extracting unit configured to extract a contour of the target object, and a reconstructing unit configured to reconstruct a three-dimensional shape of the target object from the extracted contour line. An image processing apparatus as described in the above.

According to a fourth aspect of the present invention, the data storage and output means stores minimum three-dimensional data of the object together with a label for identifying the position of the object in a living body. Item 4 is an image processing device according to any one of Items 1 to 3.

According to a fifth aspect of the present invention, there is provided a data acquisition means for acquiring a label indicating a position of an object in a living body together with the three-dimensional data of the object, according to the acquired label and the three-dimensional data of the object. Display means for displaying the object at a predetermined position on the living body.

The invention according to claim 6 is a three-dimensional shape calculating step of calculating a three-dimensional shape of the object from a two-dimensional image obtained by capturing an object such as a living organ or a three-dimensional image;
A minimum data calculation step of calculating minimum three-dimensional data including the object from the data of the three-dimensional shape of the object; and storing or outputting the calculated minimum three-dimensional data of the object. And a data storage output step.

According to a seventh aspect of the present invention, there is provided a three-dimensional shape calculating function for calculating a three-dimensional shape of the object from a two-dimensional image or a three-dimensional image obtained by capturing an object such as a living organ. A minimum data calculation function for calculating minimum three-dimensional data including the object from the three-dimensional shape data;
A program for an image processing method, wherein a computer implements a data storage and output function of storing or outputting the calculated minimum three-dimensional data of the object.

According to the present invention, when three-dimensional data is obtained, only the region data including the target organ in the data is extracted and stored as new data, so that the data amount can be reduced. Further, since the extracted data is data that can be classified for each organ, subsequent data processing can be easily performed.

[0019]

Embodiments of the present invention will be described below with reference to the drawings. In particular, an example of an ultrasonic image will be described.

(1) Configuration of Image Processing Apparatus 10 FIG. 1 is a block diagram showing a configuration of an image processing apparatus 10 according to one embodiment of the present invention.

The image processing apparatus 10 processes and displays image data obtained by various medical image diagnostic apparatuses (MRI, CT, ultrasonic diagnostic apparatus, etc.). As shown in FIG. An image processing unit 2 that processes stored image data, an image display unit 3 that displays a processed image on a monitor, and an input unit 4 that receives input from a user.

The image data storage unit 1 stores an image obtained by a medical image diagnostic apparatus such as an MRI, CT, ultrasonic diagnostic apparatus, or an image obtained by another image photographing apparatus.

The image processing unit 2 receives the image data output from the image data storage unit 1 as an input, creates a cross-sectional view from voxel data, calculates a contour of an object,
It is composed of an arithmetic unit of a computer that creates new data based on the calculation result, and each function of the processing described below is executed by a program.

The image display unit 3 presents the result calculated by the image processing unit 2 as an image, and is composed of, for example, a television monitor.

The input unit 4 is used when the user gives an instruction to the image of the target object displayed on the image display unit 3, and includes, for example, a keyboard and a mouse.

(2) Processing for Extracting Data of Object Next, a flow of performing data extraction processing of an object from input voxel data will be described.

(2-1) Automatic Extraction FIG. 2 is a flowchart showing the flow of processing for automatically extracting data of an object from input data.

As the target data, voxel data of the chest including the heart is acquired using, for example, an ultrasonic diagnostic apparatus.

The image data storage unit 1 stores the voxel data, and the image processing unit 2 extracts region data including the target organ, for example, data of only the heart region, from the stored data.

Then, based on the extracted voxel data, the image processing unit 2 extracts region data including the target organ.

After the extraction processing in the image processing unit 2 is completed, the image display unit 3 displays the heart as a three-dimensional image or a cross-sectional image on a monitor.

The image processing unit 2 can store the extracted data as new data in the image data storage unit 1.

(2-2) Processing for Extracting Data When User Designates Target Object FIG. 3 is a flowchart showing the flow of processing for extracting data when the user designates a target object for input data. It is.

In this case, after storing the voxel data, the image data storage unit 1 displays the input data on the monitor of the image display unit 3 as a three-dimensional image or a sectional image.

The user designates a target organ by using the input unit 4 such as a mouse or the like, and further designates a search range if necessary.

Then, based on the input result voxel data, the image processing unit 2 extracts region data including the target organ.

The extracted result is displayed on the monitor of the image display unit 3 as a three-dimensional image or a sectional image, and the image processing unit 2 can store the extracted data as new data in the image data storage unit 1. .

(3) Region Extraction Process in Image Processing Unit 2 Next, the image processing unit 2 performs a region extraction process based on the voxel data extracted or input as described above. Hereinafter, the flow will be described. Here, the “region extraction processing” is to calculate the contour of the target organ from the voxel data and reconstruct a three-dimensional shape from the calculated contour.

(3-1) Outline Here, the flow of three-dimensional shape reconstruction will be described. FIG.
Is a diagram for explaining the flow of reconstructing a three-dimensional shape.

For example, there are two methods for reconstructing the rectangular parallelepiped voxel data as shown in FIG.

The first method is to consider a plurality of slices parallel to a certain plane as shown in FIG. 4B, create a two-dimensional cross-sectional image with each slice, and apply contours to these two-dimensional images. This is a method for performing line extraction.

The second method considers radial slices centered on a certain axis as shown in FIG. 4C, creates a two-dimensional cross-sectional image with each slice, and applies these two-dimensional images to the slice images. This is a method of extracting a contour line.

When considering a slice as in the first method (FIG. 4B), an outline is extracted as shown in FIG. 4D, and the outline is extracted as shown in FIG. 4F. The three-dimensional shape is restored by arranging at the position.

Even when considering a slice as in the second method (FIG. 4 (c)), an outline is extracted as shown in FIG. 4 (c), and the outline is sliced as shown in FIG. 4 (f). To restore the three-dimensional shape.

As for a contour between slices, a contour of an adjacent slice may be interpolated.

The details of the three-dimensional shape reconstruction will be described later.

(3-2) Extraction of Contour Line from Cross-sectional Image of Each Slice An example of extraction of a contour line from a cross-sectional image of each slice will be described.

As for contour extraction, there are a method using an active contour, a method using region growing, and the like.

For example, when the active contour is used, a plurality of control points are arranged on the image as shown in FIG. The search proceeds such that reaches the edge.

The control points are 1, 2, 3,... As shown in FIG.
And the control points are connected in order to obtain the target contour.

In the search for an edge, when a point having a large luminance gradient is found near the control point, the control point is moved to that point.

After the control point is moved, for example, a constraint that "the contour connecting the control point is moved to a position where the contour line is not twisted and the smoothness is maintained" is given, and the position of the control point is corrected. There is also.

The search ends when the sum of the absolute values of the movement change amounts for all the control points becomes smaller than a predetermined threshold value.

If the area of the object occupying the voxel data is large, the search is automatically started by arranging the initial search point at the center of the sectional image as shown in FIG.

In addition, when the region where the object occupies in the voxel data is small, when the region is biased toward a certain portion of the voxel, or when there is a plurality of organs that can be considered as the object in the voxel data, the user can select the initial search point. Or a search range may be specified.

When the user designates an initial control point, a cross-sectional image obtained by cutting the voxel data at a certain cross-section is displayed on the image display device 3 as shown in FIG. 8A, and the user inputs the cross-sectional image. An initial control point and a search range are designated using the device of the unit 4 as shown in FIG.

When automatically setting an initial contour, a small circular initial contour centered on a point at the center of the cross-sectional image is generated to search for the contour.

When the user designates one point in the target organ in the image, a small circular initial contour centered on the designated point is generated, and the contour is searched.

Then, each control point has a large luminance gradient,
That is, the search is repeated so as to reach the edge. The search is also performed sequentially on the adjacent sections of the currently displayed section image, and finally is performed on the entire voxel data.

(3-3) Reconstruction of Three-Dimensional Shape After the contour search is completed, the contours are integrated based on the slice direction of the cross-sectional image to reconstruct the three-dimensional shape of the target organ.

For example, FIG. 9 shows a state of reconstruction when a slice image is radially formed as shown in FIG. 4E, which is the second method. It should be noted that, "_" in the following notation refers to the subscript, for example, "x_i" is the meaning of "x _i".

With reference to a section having voxel data,
Assuming that the final position in the sectional view of the j-th control point in the i-th slice is P (i, j) = (x_i, y_j), the three-dimensional position Q (i, j) = in the voxel data
(Xx_ij, yy_ij, zz_ij) is arg = (direction angle of slice) xx_ij = cos (arg) * (x_ij-widt
h_i / 2) + width_i / 2 yy_ij = y_ij zz_ij = sin (arg) * (x_ij-widt
h_i / 2) + width_i / 2.

Here, width_i is the width of the sectional view of the i-th slice.

By calculating this for all the control points, the three-dimensional position and shape of the target organ in the voxel data are calculated.

The image display section 3 can display the extracted contour shape and cross-sectional image, and can display the reconstructed three-dimensional shape using a wire frame model or a surface lettering model. Thus, the user can observe the display result and observe the state of the target organ.

The first method, that is, reconstruction in the case of creating slice images in parallel as shown in FIG.

(3-4) Others In the above processing, the three-dimensional voxel data is sliced into 2
Form a two-dimensional image, then extract the contours of the organs,
Although the three-dimensional shape is reconstructed again, the outline of the organ may be directly extracted from the three-dimensional voxel data instead.

(4) Extraction of only region data including organs After the reconstruction of the three-dimensional shape, only the region data including the target organ in the voxel data is extracted and stored as new data.

Here, the “region data including an organ” refers to a set of pixel values inside a polyhedron having the minimum size including the target organ portion.

FIG. 10 shows an example of a polyhedron including an object when the three-dimensional shape of the object is determined. The figure shows the relationship between the target existing area and the new three-dimensional data.

For example, vertical old_hei, horizontal old_w
A case will be described in which a polyhedron including a target organ is extracted as a rectangular parallelepiped from rectangular parallelepiped voxel data having id and depth old_dep (see the diagram on the left side of FIG. 10).

When N control points on the contour line of the target area are generated, the size of the rectangular parallelepiped of vertical new_hei, horizontal new_wid, and depth new_dep including the target area is new_wid = Max (x_ij) −Min (x_i)
j) new_hei = Max (y_ij) −Min (y_i)
j) new_dep = Max (z_ij) −Min (z_i
j) Here, Max (x_ij) is the horizontal length x_i of the control point.
j is the longest, and Min (x_ij) is the shortest of the horizontal lengths x_ij of the control points.

In this way, from the original voxel data, vertical new_hei, horizontal new_wid, depth new_d
Only the data of the rectangular parallelepiped region of ep can be extracted and stored in the image data storage unit 1 as new voxel data.

At the time of storage, the image data is stored together with a label indicating the position of the extracted target organ in the original voxel data and a label capable of identifying the name of the extracted target organ.

Here, in addition to storing the extracted data in a recording medium, the data may be transmitted to a server or the like at another location using a communication means.

(5) Example of Image Processing Apparatus that Performs Labeled Data Processing An example of an image processing apparatus that performs labeled data processing as described above will be described.

The image processing apparatus reads a label indicating where the extracted target organ was located in the original voxel data and a label capable of identifying the name of the extracted target organ together with the image data, and reads the label information. , The position of the target organ in the living body is displayed on the monitor. When there are a plurality of organ data, their positional relationship can be displayed.

The image processing apparatus can perform data processing using a label indicating the name of the target organ, or can search for desired data from a plurality of data.

As described above, according to the present invention, when three-dimensional voxel data is obtained, only the area data including the target organ in the voxel data is extracted and stored, so that the data amount can be reduced. Data processing can be facilitated.

[0080]

According to the present invention, a region of a target organ is automatically recognized in input voxel data such as a medical image or a desired region designated by a user is extracted. Only necessary data can be obtained from the voxel data.

Therefore, in the three-dimensional data processing which is expected to handle a huge amount of data in the future, only the necessary data can be extracted, so that the processing capacity can be improved and the efficiency of data storage can be improved. It can also be improved.

Further, the newly generated data has a smaller capacity than the original data and can be classified according to the type of the target organ, so that subsequent image management is easy.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of an image processing apparatus according to an embodiment of the present invention.

FIG. 2 is a flowchart illustrating a flow of image processing.

FIG. 3 is a flowchart illustrating a flow of image processing.

FIG. 4 is a diagram illustrating an example of three-dimensional shape reconstruction.

FIG. 5 is an example in which control points are arranged on an image.

FIG. 6 is an example of an initial control point.

FIG. 7 is a diagram illustrating a range occupied by a target area in voxel data.

FIG. 8 is an example of an initial control point designated by a user.

FIG. 9 is a diagram for describing reconstruction of a three-dimensional shape from a contour line of a cross-sectional view.

FIG. 10 is a diagram illustrating a polygon including a target organ.

[Explanation of symbols]

 1 image data storage unit 2 image processing unit 3 image display unit 4 input unit

Continued on the front page (51) Int.Cl. ⁷ Identification symbol FI Theme coat II (reference) G06T 7/60 250 G06T 7/60 250B 15/00 200 15/00 200 F term (reference) 4C301 BB13 EE20 JC13 KK16 KK26 KK30 LL14 5B057 AA07 AA09 BA05 BA07 BA24 CA13 CA16 CB13 CB16 CC03 CD14 CE09 CH08 CH18 DA08 DB03 DC14 DC16 5B080 AA17 BA02 5L096 AA09 BA06 BA13 CA01 CA24 EA28 EA35 EA37 FA06 FA46 FA69

Claims (7)

[Claims] 1. A three-dimensional shape calculating means for calculating a three-dimensional shape of an object from a two-dimensional image or a three-dimensional image of an object such as a living organ, and data of the three-dimensional shape of the object. A minimum data calculation unit that calculates minimum three-dimensional data including the object from the following; and a data storage output unit that stores or outputs the calculated minimum three-dimensional data of the object. An image processing apparatus characterized by the above-mentioned. 2. The method according to claim 1, wherein said minimum data calculating means calculates a set of pixel values inside a polyhedron having a minimum size including said object and sets the set as minimum three-dimensional data. The image processing device according to claim 1. 3. The two-dimensional image generating means for generating a two-dimensional image from three-dimensional voxel data obtained by capturing the object, the three-dimensional shape calculating means; and the object captured by the generated two-dimensional image The image processing apparatus according to claim 1, further comprising: a contour extracting unit configured to extract a contour of the object; and a reconstructing unit configured to reconstruct a three-dimensional shape of the object from the extracted contour line. . 4. The data storage and output means includes a label for identifying a position of the object in a living body,
4. The image processing apparatus according to claim 1, wherein the minimum three-dimensional data of the object is stored. 5. A data acquisition means for acquiring a label indicating a position of an object in a living body together with three-dimensional data of the object, and the object according to the acquired label and three-dimensional data of the object. An image processing apparatus comprising: a display unit configured to display a predetermined position on the living body. 6. A three-dimensional shape calculating step of calculating a three-dimensional shape of the object from a two-dimensional image or a three-dimensional image obtained by capturing an object such as a living organ, and data of the three-dimensional shape of the object. A minimum data calculation step of calculating minimum three-dimensional data including the object from the following; and a data storage output step of storing or outputting the calculated minimum three-dimensional data of the object. An image processing method characterized by the following. 7. A three-dimensional shape calculation function for calculating a three-dimensional shape of the target object from a two-dimensional image or a three-dimensional image of a target object such as a living organ, and data of the three-dimensional shape of the target object A minimum data calculation function for calculating minimum three-dimensional data including the object from the above, and a data storage output function for storing or outputting the calculated minimum three-dimensional data of the object, by a computer. A program for an image processing method which is realized.