JP3690501B2 - 3D modeling method - Google Patents

Description

[0001]
The present invention relates to a three-dimensional modeling method for constructing a three-dimensional model using a plurality of cross-sectional images of an object to be measured.
[0002]
[Prior art]
A conventional method of this type is disclosed in, for example, Japanese Patent Application Laid-Open No. 11-328442. This gave the vertex the luminance value (density) of each of the four pixels facing each other in the two adjacent cross-sectional images in the plurality of cross-sectional images obtained at intervals along the constant direction of the object to be measured. In this method, a cube or a rectangular parallelepiped is set, and a three-dimensional model is formed by an interpolation surface forming process using a marching cube method for generating a triangular surface based on a comparison result between a luminance value of each vertex and a threshold value.
[0003]
The marching cube method is described in detail in “Marching Cubes: A High Resolution 3D Surface Reconstruction Algorithm” (1987; Computer Graphics 21 (4); pp163-169) by WELorensen and HECline.
[0004]
According to such a three-dimensional modeling method, there is an advantage that a three-dimensional model can be easily configured by only computer processing without human intervention.
[0005]
[Problems to be solved by the invention]
However, in the above-described prior art, when the number of cross-sectional images is high and the number is large, the data amount of the obtained three-dimensional model increases in proportion to the data amount, and the processing time also increases. This is particularly noticeable because the marching cube method is processing in units of one voxel (one pixel of a cross-sectional image).
[0006]
This will be described below. Now, when a cross-sectional image is an X-ray CT image (hereinafter abbreviated as a CT image), and a single three-dimensional model is obtained using 500 general CT images of 512 × 512 pixels. Assume that the data amount is 250 MB.
[0007]
According to this, when a three-dimensional model is obtained using 1000 high-resolution CT images of 2048 × 2048 pixels, the three-dimensional model is (2048/512) × (2048/512) × Since (1000/500) = 32, the data amount is 32 times that of the three-dimensional model. It is assumed that the data amount representing the density of each pixel is the same.
[0008]
That is, a three-dimensional model obtained by using 1000 high-resolution CT images of 2048 × 2048 pixels has a huge data amount of 250 MB × 32 = 8000 MB, that is, 8 GB. This also means an increase in processing time, and the capacity of the recording medium in subsequent handling, for example, storage and recording of such a three-dimensional model, reuse or processing of the model by CAD, CAM, CAE, etc. It has been necessary to increase the time required for various operations.
[0009]
Therefore, it is conceivable to perform polygon reduction on the obtained three-dimensional model. Polygon reduction is a technique that reduces the number of polygons that make up the model while maintaining the model shape as much as possible (GARLAND, M. and HECKBERT, PS Surface Simplification using Quadric Error Metrics. Proceedings of SIGGRAPH 97. In Computer Graphics Proceedings, Annual Conference Series, 1997, ACM SIGGRAPH, pp.209-216, etc.), useful for reducing the amount of data.
[0010]
However, the polygon reduction process consumes many times, for example, four times as much memory as the data amount of the original model. For this reason, in order to perform polygon reduction processing on an 8 GB three-dimensional model, an expensive computer having 32 GB of memory is required, which is not practical.
[0011]
Furthermore, in a CT image of about 4000 × 4000 pixels that can be output by the current X-ray CT apparatus, if the data amount representing the pixel density is 2B (bytes), 4000 × 4000 × 2 = 32 MB of data. Amount. A three-dimensional model obtained by using 1000 sheets has a data amount of 32 MB × 1000 = 32 GB. In order to perform polygon reduction processing on this three-dimensional model, 32 GB × 4 = 128 GB of memory is consumed. Therefore, in order to realize the polygon reduction processing of such a scale, it is currently limited to a very large computer, and cannot be realized in reality.
[0012]
As described above, a three-dimensional model obtained by using 500 general CT images each having vertical and horizontal 512 × 512 pixels has a data amount of about 250 MB and a short processing time. However, in order to improve the measurement accuracy and the like of the obtained three-dimensional model, it is essential to increase the resolution and the number of CT images to be used.
[0013]
For this reason, conventionally, a high-resolution, large number of cross-sectional images can be used, in other words, even if the data amount of all cross-sectional images to be processed increases, a three-dimensional model with a small data amount of about 250 MB can be obtained. In addition, there has been a demand for the appearance of a three-dimensional modeling method that can be performed in a short time by a small computer.
[0014]
The present invention has been made in view of the above-described demands, and is capable of handling a relatively small amount of data and a resolution of a sectional image to be used, which is convenient for handling, regardless of an increase in the number of sectional images to be used. To provide a three-dimensional modeling method that can obtain a three-dimensional model that does not greatly deteriorate, and that can perform a process for obtaining the three-dimensional model in a short time by a small, low-cost computer. With the goal.
[0015]
[Means for Solving the Problems]
In order to achieve the above object, according to the first aspect of the present invention, a plurality of cross-sectional images obtained at intervals along a certain direction of an object to be measured can be obtained for each appropriate number of sheets without changing the arrangement thereof. Next, each group is subjected to a three-dimensional modeling process using the group of cross-sectional images constituting the group, and the obtained three-dimensional model part is adjacent to the three-dimensional model part adjacent to each group. The polygon reduction processing is performed separately except for the end face portion related to the joining with the three-dimensional model portion after the polygon reduction processing is combined according to the arrangement before the grouping and the shape of the end face portion from which the polygon reduction processing is removed. Thus, a single three-dimensional model is obtained , and polygon reduction processing is further performed on the single three-dimensional model .
[0016]
The invention according to claim 2 is characterized in that, in the invention according to claim 1, a three-dimensional modeling process based on the marching cube method is used for the three-dimensional modeling process .
[0018]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is an explanatory diagram of an embodiment of a three-dimensional modeling method according to the present invention, and is a flowchart in which a schematic diagram of execution contents is added to each step.
[0019]
As shown in this figure, first, in step 101, an arbitrary number of cross-sectional images that are the basis of the three-dimensional modeling are prepared. In this case, the multiple cross-sectional images are cross-sectional images obtained at intervals along a certain direction of the object to be measured.
[0020]
Here, 1000 CT images obtained at predetermined intervals were prepared. Each CT image is 2048 × 2048 pixels in length and width, and the data amount representing the density of each pixel is 2 bytes (total data amount 8.3 MB).
[0021]
In step 102, the 1000 CT images prepared in step 101 are grouped appropriately for each number without changing the arrangement. Each group g1, g2,..., GN includes at least a number of CT images that can be processed in units of groups by processing means (not shown) used in the subsequent processing. When a fraction occurs in grouping, the CT image of the fraction is assigned to the last group gN, for example.
[0022]
In step 103, the group of cross-sectional images grouped in step 102 is sent to the processing means to perform a three-dimensional modeling process, and a three-dimensional model (three-dimensional model portion) m1, m2, m2 for each group g1, g2,. ... get mN.
[0023]
Here, the grouped sectional image groups are sequentially sent to the processing means for each of the groups g1, g2,... GN, and a three-dimensional modeling process is performed for each group. This three-dimensional modeling process is performed by parallel processing by a single processing unit having a parallel processing function, or by parallel processing by a plurality of processing units, thereby speeding up the processing. In this case, the cross-sectional image group constituting one group may be processed in parallel, or a plurality of groups may be processed in parallel.
[0024]
In any case, all the data to be processed (8.3 MB × 1000 = 8.3 GB) is divided into groups, and in this case, the processing is divided into 1 / N. For example, a personal computer or a workstation can be used.
The three-dimensional modeling process is based on sequential processing for a plurality of pixels and cross-sectional images, so that parallel processing is easy.
[0025]
The three-dimensional modeling process is preferably a three-dimensional modeling process based on the marching cube method described above, that is, based on the marching cube method or to which this is applied. This is because three-dimensional modeling for each part on the premise of merging can be easily performed as described below.
[0026]
That is, the three-dimensional modeling process is a polygonal surface that forms a model surface based on a luminance distribution in a three-dimensional space (a rectangular parallelepiped formed by four opposing pixels of two cross-sectional images) arranged in a grid. The polygonal surface is generated in units of lattices. Further, in the marching cube method, the vertices of a triangular surface, which is a generated polygonal surface, are always arranged on a lattice (each side of a three-dimensional space arranged in a lattice shape). Therefore, according to the three-dimensional modeling process based on the marching cube method, the obtained three-dimensional model can be easily divided by using a line parallel to each side of the three-dimensional space arranged in a lattice as a boundary. .
[0027]
Therefore, by the reverse method, a plurality of divided three-dimensional models (three-dimensional model portions) can be easily combined. Therefore, in step 103, three-dimensional model parts m1, m2,... MN are obtained by three-dimensional modeling processing based on the marching cube method.
[0028]
As described above, since the three-dimensional modeling process for each part on the premise of merging is easy and parallel processing is also easy, in this embodiment, the first stage in the entire processing process Therefore, high-speed processing can be easily performed with a small and low-priced computer.
[0029]
In step 104, the obtained polygon reduction processing (for each model g1, g2,..., GN for each group g1, g2,. (Processing to reduce the number of polygons to be configured).
[0030]
In this step 104, the joint end face portion with the adjacent three-dimensional model part is excluded from the polygon reduction processing target.
Figure 2 is a view showing an enlarged joint end face portions mutually 3D model portion adjacent relates to a portion above the joint end face portions (bonding which is not a polygon reduction process shown denoted by the mesh drawing 21 End face portion) .
As described above, the joint end face portions 21 and 22 of the three-dimensional model portions m1, m2,..., MN are excluded from the polygon reduction processing target because of the guarantee of joining between the adjacent three-dimensional model portions after the polygon reduction processing. Because.
[0031]
In step 105, the three-dimensional model parts m1 ′, m2 ′,... MN ′ after the polygon reduction process are combined according to the arrangement before the grouping in step 102 and the shape of the end face part (end face shape) from which the polygon reduction process is removed. To obtain a single three-dimensional model M.
[0032]
As described above, in the polygon reduction processing in step 104, the joint end surface portions 21 and 22 (see FIG. 2) with the adjacent three-dimensional model portion are excluded from the polygon reduction processing targets. That is, the joint end surface portions 21 and 22 of the three-dimensional model portions m1 ′, m2 ′,... MN ′ are not processed at all, and the actual model (the three-dimensional model portions m1, m2,. mN end face shape), and the joining of adjacent three-dimensional model parts after the polygon reduction processing is guaranteed .
Therefore, the joining end surface portions 21 and 22 of the adjacent three-dimensional model parts are smoothly and appropriately joined, and the three-dimensional model parts m1 ′, m2 ′,.
[0033]
In step 106, polygon reduction processing is further performed on the single three-dimensional model (three-dimensional model immediately after combining) M obtained in step 105.
If the polygon reduction process is performed again immediately before the completion of the three-dimensional modeling, the end face parts 21 and 22 are also subjected to the polygon reduction process, and the end face parts 21 and 22 are also reduced in the three-dimensional model (model shape is reduced). While maintaining as much as possible, a three-dimensional model ( M ′ ) in which the number of polygons constituting the model is reduced is obtained. That is, the three-dimensional modeling according to the present embodiment is completed.
[0034]
Specifically, small polygons are concentrated and arranged in a complicated shape, in other words, a highly accurate three-dimensional model M ′ reflecting the resolution of a high-resolution CT image is relatively small and convenient for handling. It can be obtained with a data amount, for example, a data amount of about a general CT image (250 MB).
[0035]
Like the three-dimensional modeling process, the polygon reduction process can be easily performed in parallel, and the three-dimensional model parts m1 ′, m2 ′,... MN ′ can be easily combined. Therefore, in the present embodiment, high-speed processing can be easily performed with a small and low-cost computer not only from the first stage to the three-dimensional modeling process in the entire processing process but also to the final stage.
[0036]
In the above-described embodiment, an X-ray CT image is taken as an example of a cross-sectional image, but other cross-sectional images (tomographic images) such as an MRI image may be used. Further, it may be a cross-sectional image stored in a storage device, or may be a cross-sectional image sent in real time from various cross-sectional image generation apparatuses such as an X-ray CT apparatus or a communication line.
[0037]
In the present invention, since the cross-sectional image is a processing target, the type and size of the object to be measured that gives the cross-sectional image are not limited.
[0038]
【The invention's effect】
As described above, according to the present invention, when a three-dimensional model is configured using a plurality of cross-sectional images of the object to be measured, the plurality of cross-sectional images are appropriately grouped by number, and the cross-sectional images of each group are obtained. A three-dimensional modeling process is performed for each group to obtain a three-dimensional model portion. Thereafter, polygon reduction processing is performed on each three-dimensional model portion, and the three-dimensional model portion after the polygon reduction processing is combined according to the shape of the end face portion (end face shape) from which the arrangement before grouping and the polygon reduction processing are removed. Thus, a single three-dimensional model is obtained , and polygon reduction processing is further performed on the single three-dimensional model .
[0039]
That is, since the three-dimensional modeling process that requires a lot of processing time is performed for each of the grouped cross-sectional image groups, even if the amount of data and the number of cross-sectional images to be used increase, the small-scale (small size) , Low cost) can be done in a short time. In addition, since the polygon reduction process is also performed on a partial three-dimensional model (three-dimensional model part), it can be performed in a short time by a small computer as in the three-dimensional modeling process. Furthermore, these three-dimensional modeling processing and polygon reduction processing can be easily performed in parallel, and the processing speed can be increased from this point. Such an effect becomes more remarkable as the resolution and the number of cross-sectional images to be processed increase.
[0040]
Processing related to grouping and 3D model uniting other than 3D modeling processing and polygon reduction processing is significantly easier than 3D modeling processing and polygon reduction processing. Therefore, according to the present invention, high-speed processing can be easily performed with a small-scale computer over the entire process of three-dimensional modeling.
[0041]
Also, by performing polygon reduction processing, despite the increase in the amount of data and the number of cross-sectional images to be used, the resolution of the cross-sectional images to be used is relatively small and the amount of data that is convenient for handling is greatly impaired. It is possible to obtain a three-dimensional model without any. In particular, in the present invention, for the polygon reduction processing to be performed first, the end face portion related to the joint with the adjacent three-dimensional model portion is excluded from the object, thereby guaranteeing the joint between the adjacent three-dimensional model portions after the polygon reduction processing. As a result , the joining end face portions are joined smoothly and properly, and the three-dimensional model portions can be combined without any mismatch.
[0042]
By further performing polygon reduction processing on a single three-dimensional model, the polygonal reduction processing is performed on the end face portion that was previously excluded from the polygon reduction processing target, and the reduced data amount of the end face portion is also reduced. A three-dimensional model (a three-dimensional model in which the number of polygons constituting the model is reduced while maintaining the model shape as much as possible) is obtained. That is, the three-dimensional modeling according to the present invention is completed.
[0043]
Moreover, if the 3D modeling process based on the marching cube method is used for the 3D modeling process for each cross-sectional image group of each group, it becomes possible to easily combine the obtained 3D model parts, The processing can be further speeded up.
[Brief description of the drawings]
FIG. 1 is an explanatory diagram of an embodiment of a three-dimensional modeling method according to the present invention.
FIG. 2 is an enlarged view showing joint end surface portions of adjacent three-dimensional model portions.
[Explanation of symbols]
gN CT image group m1, m2, ... mN 3D model part m1 ', m2', ... mN '3D model part M after polygon reduction processing Single 3D model M' polygon (immediately after coalescence) 3D model after reduction processing

Claims (2)

A plurality of cross-sectional images obtained at intervals along a certain direction of the object to be measured are appropriately grouped for each number of sheets without changing the arrangement,
Next, for each group, a three-dimensional modeling process is performed using the group of cross-sectional images constituting the group,
The obtained 3D model part for each group is subjected to polygon reduction processing separately except for the end face part related to the joining with the adjacent 3D model part,
The three-dimensional model part after the polygon reduction processing is united according to the shape before the grouping and the shape of the end face part from which the polygon reduction processing has been removed to obtain a single three-dimensional model ,
A three-dimensional modeling method characterized by further performing polygon reduction processing on the single three-dimensional model . The three-dimensional modeling method according to claim 1, wherein a three-dimensional modeling process based on a marching cube method is used for the three-dimensional modeling process.

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