KR20020041277A - 3-dimentional multiplanar reformatting system and method and computer-readable recording medium having 3-dimentional multiplanar reformatting program recorded thereon - Google Patents

Abstract

PURPOSE: A 3-dimensional MPR(Multi-Planer Reconstruction) system is provided to directly reconstruct a multi-planer image from a 3-dimensional image, and to generate an automatic structure through the reconstructed 3-dimensional multi-planer image, thereby displaying a section as a line type of a reference image to obtain a section image. CONSTITUTION: An input/storage unit(100) inputs volume data having a density value of a stereo structure from an exterior, and stores the volume data. An optional multi-planer image reconstructor(200) 3-dimensionally displays a spacial distribution of the stereo structure based on the volume data, and makes a displayed 3-dimensional image a reference image, enabling a user to directly reconstruct the image, then displays a multi-planer image on an ROI(Region Of Interest) of the reference image. A display(300) displays the 3-dimensional image corresponding to the volume data, and displays the 3-dimensional image corresponding to the ROI. An input unit(400) supplies a drawing tool for specifying the ROI on the displayed 3-dimensional image, and adapts to a drawing request by the drawing tool to supply a request signal to the optional multi-planer image reconstructor.

Description

3D multidimensional image reconstruction system and method and a computer readable recording medium storing the same.

The present invention relates to a three-dimensional multi-dimensional image reconstruction system and method and a computer-readable recording medium storing the three-dimensional multi-dimensional image reconstruction, and more specifically, to generate and visualize a multi-dimensional reconstruction image from the three-dimensional reference image of the three-dimensional human structure A multidimensional image reconstruction system and method, and a computer readable recording medium storing the same.

In general, three-dimensional image reconstruction is a technique of displaying a cross section to be obtained from a reference image in the form of a line on the reference image to obtain a corresponding cross section image.

In the 3D multi-dimensional image reconstruction system, vertical (Coronal, Sagittal, Axial) images of the entire volume are used as reference images, and vertical, horizontal, and diagonal lines are provided as display interfaces of the reconstructed surface. Here, the diagonal line is rotatable to display the reconstructed surface at any angle.

Such a 3D image reconstruction system is widely used in medical imaging techniques (hereinafter referred to as 3D medical imaging technique). In particular, the 3D medical imaging technique generates a 3D image from a series of 2D medical images obtained from CT and MRI. Say that. Diagnosis using only a series of two-dimensional images has the disadvantage that it is difficult to obtain an overall three-dimensional effect and it is impossible to observe an arbitrary cross section.However, using three-dimensional medical imaging technique, it is possible to determine the exact position of the affected area and make the surgical method more realistic. Predictably.

In general, reconstructing arbitrary multi-sided images in a program that visualizes CT or MRI data obtained from a medical device in three dimensions plays an important role in medical diagnosis.

However, existing three-dimensional visualization programs provide multi-sided reconstruction from two-dimensional images, as shown in FIG.

However, since they can obtain images only in the direction perpendicular to the three-dimensional axis, it is difficult to extract an accurate reconstructed surface for human organs having an inclined shape.

In addition, since the reconstructed surface can be displayed only in a straight form, it is impossible to extract a cross section along a desired organ.

Therefore, the technical problem of the present invention is to solve the problem of providing a multi-sided image reconstruction in the conventional two-dimensional image, an object of the present invention is to directly reconstruct the multi-sided image from the three-dimensional image, reconstructed three-dimensional multi-dimensional reconstruction An object of the present invention is to provide a 3D multi-dimensional image reconstruction system for generating an automatic anatomical structure through an image.

In addition, another object of the present invention is to provide a method for reconstructing a multi-dimensional image directly from a three-dimensional image, to generate an automatic anatomical structure through the reconstructed three-dimensional multi-dimensional reconstruction image.

Another object of the present invention is to provide a computer-readable recording medium storing the above-described three-dimensional multi-dimensional image reconstruction method.

1 is a diagram illustrating a conventional multi-sided image reconstruction (MPR) screen.

2 is a view for explaining a 3D multi-dimensional image reconstruction system according to an embodiment of the present invention.

3 is a flowchart illustrating a 3D multi-dimensional image reconstruction method according to an embodiment of the present invention.

4A shows an example of a reconstruction screen using a straight interface according to the present invention, FIG. 4B shows an example of a reconstruction screen using a curved interface according to the present invention, and FIG. 4C shows a reconstruction using a free curve according to the present invention. An example of a surface display screen is shown.

FIG. 5 illustrates a result of extracting a cross section using the straight line interface of FIG. 4A.

FIG. 6 illustrates a result of extracting a cross section using the curved interface of FIG. 4B.

FIG. 7 illustrates a result of extracting a reconstructed surface using the free curve of FIG. 4C.

8 is a flowchart illustrating a 3D multi-dimensional image reconstruction method according to another embodiment of the present invention.

9 is a result of displaying a distance obtained by summing the distance for each section to a curve having a control point.

10 is a flowchart illustrating a 3D multi-dimensional image reconstruction method according to another embodiment of the present invention.

11 shows an example of site setting through a multi-faceted reconstruction image

<Description of the symbols for the main parts of the drawings>

100: input / storage unit 200: random side image reconstruction unit

210: reference image processor 220: converter

230: reconstruction unit 300: display unit

400: input unit

The three-dimensional multi-dimensional image reconstruction system according to one feature for realizing the above object of the present invention,

An input / storing unit that receives volume data storing density values of three-dimensional structures having predetermined characteristics from outside and stores the volume data;

The spatial distribution of the three-dimensional structure is displayed as a 3D image based on the volume data stored in the input / storage unit, and the user can directly reconstruct the image by using the displayed 3D image as a reference image. An arbitrary multi-sided image reconstructing unit which processes to display a multi-sided image of a predetermined ROI displayed on the image;

A display unit configured to display a 3D image corresponding to volume data stored in the input / storage unit, and to display a 3D image corresponding to a predetermined ROI set by a user; And

And an input unit that provides a drawing tool so that a user can designate a predetermined region of interest on the displayed 3D image, and adapts a drawing request by the drawing tool to provide a request signal to the arbitrary screen reconstruction unit.

In addition, a three-dimensional multi-dimensional image reconstruction method according to one feature for realizing another object of the present invention, in the three-dimensional multi-dimensional image reconstruction method for processing to be able to display any multi-sided image of a predetermined region of interest of the reference image ,

(a) displaying a shape of a corresponding section as an image mode to be viewed by a user's operation is input on the projected three-dimensional reference image;

(b) As a predetermined region of interest is input in the form of any straight line, a curve, or a free curve by a user on the shape of the corresponding cross section to be displayed, it becomes a standard of image generation from the cross-sectional shape. Extracting one or more sample points;

(c) converting the extracted one or more sample points into three-dimensional coordinates, respectively;

(d) multiplying the normal vector of the projection plane by the inverse of the visible matrix to generate a three-dimensional multi-sided image extraction direction vector; And

(e) generating a multi-faceted image by moving forward using the generated three-dimensional multi-faceted image extraction direction vector from each sample point and obtaining a value corresponding to a unit voxel, and displaying the generated multi-faceted image It is made, including.

Here, the step (e),

Calculating each section distance by integrating section by section using a curve equation passing through each control point; And summing and storing the calculated interval distances by summing the curve lengths from the origin to the corresponding control point in the order of the control points.

In addition, the above step (e),

Providing a drawing tool such as an ellipse, a free curve, a rectangle, or the like for representing a region of interest; Arranging the density values belonging to the inside of the boundary of the region of interest in ascending order; And generating the aligned density values as density values corresponding to the respective control points of the opacity transition function.

In addition, the step (a),

Extracts and arranges each point of a straight line representing a plane such as a horizontal plane, a vertical plane, a slope, and stores a sample point, creates a curve with a plurality of control points input by the user, and generates a curve. The curved multi-sided image mode for observing the cross-sectional shape on the basis of the, and the free-formed multi-sided image mode for observing the cross-sectional shape based on the curve arbitrarily drawn by the user. At this time, the generation of the curve is obtained by the function of the curve from the input control points, and the coordinates of the points by calculating the coordinates of the points by substituting values of a predetermined interval to the parameters, and then connected the curves by a predetermined line segment between the points It is preferable to generate, and it is preferable that the curve function uses a Hermit curve.

In addition, the step (b) is characterized in that the sample point is extracted for each unit length from a straight line representing the plane selected by the user when the shape of the displayed cross section is a basic multi-image mode.

In addition, in the step (b), when the shape of the cross section to be displayed is curved, the direction unit vector of the corresponding line segment is obtained using the length and the direction vector of each line segment, and the direction unit vector at one end of the line segment. Another feature is the extraction of points while advancing as much.

In addition, in the step (b), when the shape of the cross section to be displayed is the free-form surface image mode, the direction unit vector of the corresponding line segment is obtained using the length and the direction vector of each line segment, and the direction at one end point of the line segment is obtained. Another feature is the extraction of points while advancing by unit vectors.

Further, the conversion to the three-dimensional coordinates of step (c) preferably multiplies the inverse of the visible matrix A by the coordinates on the projection plane of each sample point.

In addition, a computer-readable recording medium storing a three-dimensional multi-dimensional image reconstruction method according to one feature for realizing another object of the present invention is processed to display an arbitrary multi-sided image of a predetermined region of interest of a reference image. In the three-dimensional multi-dimensional image reconstruction method for

(a) displaying a shape of a corresponding section as an image mode to be viewed by a user's operation is input on the projected three-dimensional reference image;

(b) As a predetermined region of interest is input in the form of any straight line, a curve, or a free curve by a user on the shape of the corresponding cross section to be displayed, it becomes a standard of image generation from the cross-sectional shape. Extracting one or more sample points;

(c) converting the extracted one or more sample points into three-dimensional coordinates, respectively;

(d) multiplying the normal vector of the projection plane by the inverse of the visible matrix to generate a three-dimensional multi-sided image extraction direction vector; And

(e) generating a multi-faceted image by moving forward using the generated three-dimensional multi-faceted image extraction direction vector from each sample point and obtaining a value corresponding to a unit voxel, and displaying the generated multi-faceted image It is made, including.

According to such a three-dimensional multi-dimensional image reconstruction system and method and a computer-readable recording medium storing the three-dimensional image reconstruction system, it is possible to directly display an arbitrary reconstruction surface in the three-dimensional image to provide direct information, and also to infer the lesions estimated in the three-dimensional image. It is possible to obtain the reconstruction surface by directly displaying on the 3D image without having to confirm through 2D multi-dimensional image reconstruction, and overcome the limitations of the existing reconstruction method limited to the axis.

In addition, the summation distance is displayed on an interface by a user input device such as a mouse to provide numerical information as well as a three-dimensional image may be re-extracted using the multi-dimensional image extracted as a result.

In addition, the user can save the hassle of expressing directly to the opacity transition function for the area that you want to see, and if you mark the site you want to see on the reconstruction screen, you can automatically create the opacity transition function to see the site you want to see have.

Then, embodiments will be described so that those skilled in the art can easily implement the present invention.

2 is a view for explaining a 3D multi-dimensional image reconstruction system according to an embodiment of the present invention.

Referring to FIG. 2, a three-dimensional multi-dimensional image reconstruction system according to an exemplary embodiment of the present invention includes an input / storage unit 100, an arbitrary multiple-image reconstruction unit 200, a display unit 300, and an input unit 400.

The input / storage unit 100 receives volume data storing density values of three-dimensional structures having predetermined characteristics from the outside and stores the three-dimensional image reconstruction for processing.

The random multi-faceted image reconstructor 200 includes a reference image processor 210, a converter 220, and a reconstructor 230, based on the volume data stored in the input / storage unit 100. A 3D image is displayed, and a 3D image is displayed as a reference image, so that the user can directly reconstruct the image, and display a multi-sided image of a predetermined region of interest displayed on the reference image.

In more detail, the reference image processing unit 210 processes to display the 3D reference image from the volume data stored in the input / storage unit 100, and is input by the user through the input unit 400. The region of interest is inputted and processed in the form of a predetermined straight line, a curve, a free curve, or the like on the reference image.

The conversion unit 220 extracts three-dimensional coordinates corresponding to each point from two-dimensional position data of each point constituting a straight line, curve, or free curve on the reference image input to the reference image processing unit 210. do.

The reconstructor 230 obtains image information from the 3D image by using the 3D coordinates corresponding to the respective points obtained by the converter 220 and the visible vector of the desired face image, and reconstructs the image information from the volume data. The image is changed into a 3D multi-dimensional image corresponding to the specified predetermined ROI.

The display unit 300 displays a corresponding 3D image of the reference image, that is, volume data stored in the input / storage unit 100, and displays a 3D multi-dimensional image corresponding to a predetermined ROI set by the user. The 3D image corresponding to the volume data is preferably displayed on one side of the screen, and the 3D image corresponding to the ROI is preferably displayed on the other side of the screen.

The input unit 400 provides various drawing tools to allow a user to designate a predetermined region of interest on the corresponding reference image, preferably a 3D image, to be displayed. That is, the request signal is provided to the arbitrary screen image reconstruction unit 200 by adapting to the drawing request of the user input through a mouse or the like.

3 is a flowchart illustrating a three-dimensional multi-dimensional image reconstruction method according to an embodiment of the present invention, in particular a flowchart for explaining a multi-dimensional image reconstruction in a three-dimensional image.

4A shows an example of a reconstruction screen using a straight interface according to the present invention, FIG. 4B shows an example of a reconstruction screen using a curved interface according to the present invention, and FIG. 4C shows a reconstruction using a free curve according to the present invention. An example of a surface display screen is shown.

FIG. 5 illustrates a result of extracting a cross section using the straight line interface of FIG. 4A, FIG. 6 illustrates a result of extracting a cross section using the curve interface of FIG. 4B, and FIG. 7 shows the result of FIG. 4C. The result of extracting the reconstructed surface using the free curve is shown.

Referring to FIG. 3, first, as shown in FIGS. 4A to 4C, a 3D reference image is displayed (step S105). In the state where three-dimensional volume data is projected onto a two-dimensional plane, in order to obtain a desired cross section, a cross section to be viewed must first be drawn on a three-dimensional reference image. Modules for inputting information about these cross sections are a Basic MPR module, a Curve MPR module, and a free draw MPR module.

First, the Basic MPR (Basic MPR) module basically provides a horizontal line, a vertical line, and a diagonal line representing a horizontal plane, a vertical plane, and a slope on a three-dimensional reference image.

The horizontal plane and the vertical plane cannot be rotated, and only the parallel plane can be moved in the normal vector direction of each plane, and the slope can be moved parallel to the normal vector direction, and the normal vector of the screen can also be rotated about the axis. Do. The straight lines representing each have the same operation. The user can observe the shape of the desired cross section by selecting each straight line or moving or rotating it with the mouse.

In addition, the Curve MPR module generates a curve from control points given to a user input and observes the shape of the cross section according to the curve. For the generation of the curve passing through the control point, first obtain the function of the curve from the input control points using Hermitite equation and calculate the coordinates of the points by substituting a certain interval value into the parameter. Express the curve by connecting the points between the points.

In addition, the free draw MPR module can observe the shape of the cross section based on an arbitrary curve drawn by a user.

In other words, it is checked whether the basic MPR is selected by the user (step S110), and when the basic MPR is selected, each point of a straight line representing the selected plane is extracted and arranged (step S110). S112), the sample points on which the corresponding MPR image, preferably the basic MPR image is generated, are stored (step S114). Here, the basic MPR is preferably composed of an axial image, a sagittal image, and a coronal image.

The sample point is a point on a straight line (or curve) drawn (or selected) on the 3D reference image by the user, and constitutes one side of the final MPR image. In the case of the basic MPR described above, the storage of sample points is solved by extracting certain sample points every unit length from a straight line representing a plane selected by the user.

If the basic MPR is not selected in step S110, it is checked whether a curve MPR consisting of a series of control points is selected (step S120), and if the curve MPR is selected, the input control points are used. The Hermit curve equation is calculated (step S122), and the sample points are stored by equally extracting points between the control points using the Hermit curve equation described above (step S124).

In the case of the above-mentioned curve MPR, the sample points are stored by extracting the points for each unit length from each line segment because the points used to draw the curve are connected by line segments. In this method, the direction unit vector of the line segment is obtained using the length and the direction vector of each line segment, and the point is extracted by advancing the direction unit vector from one end point of the line segment. After extraction from one segment, do the same for the next segment.

If the curve MPR is not selected in step S120, it is checked whether or not the free curve MPR (FreeDraw MPR) consisting of a series of points drawn by the user is selected (step S130). In step S110, when the free curve MPR is selected, the extracted extraction points are interpolated and arranged (step S132), and the sample points are stored (step S134).

In the case of the above-mentioned free curve MPR, the storage of the sample points is also composed of line segments between the series of points obtained when the curve is drawn by the mouse. Thus, the sample points may be extracted for each unit length in the same manner as in the case of the curved MPR.

After the above-described steps S114, S124, and S134, the current viewing information is obtained (step S140), and in order to generate an MPR image directly from the three-dimensional volume data, the two-dimensional sample point obtained in the above process is converted into three-dimensional (step S150). More specifically, in order to convert the two-dimensional sample point into three-dimensional, the inverse of the visible matrix A may be multiplied by the coordinates of each point. That is, P_3 = A ^ -1 P_2. Where P ₃ is the coordinate converted in three dimensions of the sample point, and P ₂ is the coordinate on the projection plane of the sample point.

Subsequently, after obtaining image information based on each sample point (step S160), a corresponding MPR image is generated, and the generated MPR image is displayed as shown in FIGS. 5 to 7 (step S170).

In more detail, when the sample point is converted into three-dimensional coordinates, an MPR image is obtained using the sample point as a starting point. In this case, it is necessary to set a direction in which the image is obtained in the three-dimensional coordinate space. In other words, if there is a starting point and a direction, one line of MPR image can be generated for each sample point. Here, the direction is set by multiplying (0,0,1), which is the normal vector of the projection plane, with the inverse of the visible matrix, as in the three-dimensional transformation of the sample point.

From each sample point, a value corresponding to a unit voxel is obtained by moving forward using the direction vector obtained above. Do this for all sample points to get an MPR image.

In the above, as a feature of the present invention, a series of processes for describing the reconstruction of the multi-sided image in the 3D image has been described. As another feature of the present invention, the summation distance information using the multi-sided image may be extracted. More specifically, in the case of reconstructing a multifaceted image using a curve having a control point, in order to satisfy a desire to know a distance between or between sections, a summation distance according to a section in the three-dimensional multifaceted image reconstruction system according to the present invention. It provides a function to display on the screen.

Next, a brief description will be given with reference to FIG.

8 is a flowchart illustrating a 3D multi-dimensional image reconstruction method according to another embodiment of the present invention. In particular, FIG. 8 is a flowchart illustrating a measurement of a summation distance in a 3D image.

Referring to FIG. 8, first, as the control point is input by the user (step S201), the count is increased (step S220). Then, the integral value of one step is added (step S230), and it is checked whether the count value is less than 20 (step S240).

That is, each section distance is obtained by integrating section by using the equation of the curve passing through each control point, and the sum of the lengths of the curves from the origin to the control point in the order of the control points is shown next to the control point. Equation is as follows.

If the curve by the parameter u is (x (u), y (u)), the length L of the curve is as shown in the following equation.

Becomes

Here, the Hermite curve, which is easy to define as a control point, has a small amount of calculation, and can display a smooth curve despite a small amount of calculation, is used.

Therefore, since it is difficult to perform the static fraction in actual code, the length is obtained by using the divisional quadrature method by increasing the value of u by 0.05 by dividing the parameter u having a value from '0' to '1' by 20. At this time, in order to reduce the error, the final result is calculated by arithmetic average of the sum of the upper sum and the lower sum.

In addition, integral length calculations can be performed while editing curves or adding new control points, making it easy to see the cumulative length of a curve that has changed each time you edit a curve or add a new control point.

If it is determined in step S240 that the count value is less than 20, it is fed back to step S220. If it is determined that the count value is 20, the length is displayed as shown in FIG. 9 (step S250). In this case, the count value may be adjusted by the user.

9 is a result of displaying a distance obtained by summing the distance for each section to a curve having a control point. The user can know the total and interval distances from this information.

In the above, as another feature of the present invention, a series of processes for extracting summation distance information using a multi-faceted image have been described. As another feature of the present invention, an automatic anatomical structure is drawn by drawing a region of interest in a 3D multi-faceted reconstructed image. You can also create one, as described below.

In general, three-dimensional reconstructed images show arbitrary cross-sections of the structure, so they have more information about the area to be viewed than two-dimensional slices of CT or MRI.

Therefore, in another embodiment of the present method, since the 3D multi-dimensional reconstruction image is provided, the multi-dimensional reconstruction image including the anatomical structure to be extracted is displayed, and then, the ROI is set on the structure, and the density value corresponding to the portion is obtained. We can automatically generate an appropriate opacity transition function by analyzing

In particular, various drawing tools, such as ellipses, free curves, rectangles, etc., are provided for ROI representation.

The method of generating the opacity transition function for automatically representing anatomical structures through the ROI is based on the opacity transition of density values of 5%, 25%, 70%, and 90% when the density values within the ROI boundary are arranged in ascending order. Generated as the density value corresponding to each control point of the function (trapezoid). At this time, the percentage (%) corresponding to each control point can be adjusted by the user. This will be described in detail with reference to FIG. 10 to which the above procedure is attached.

10 is a flowchart illustrating a 3D multi-dimensional image reconstruction method according to an embodiment of the present invention. In particular, FIG. 10 is a flowchart illustrating an automated process of extracting a region of interest (ROI) from a 3D image.

Referring to FIG. 10, first, a 3D multi-dimensional reconstructed image is generated (step S310).

Next, the structure to be viewed by the user is expressed as an ROI (step S320), and the density values inside the ROI are aligned (step S330). At this time, the sorting is preferably sorted in ascending order.

Subsequently, density values corresponding to 5, 25, 70, and 90% are determined as the control points of the opacity transition function (step S340). Of course, it is obvious that the density value for determining the control point of the opacity transition function is not limited to 5, 25, 70, and 90%.

An opacity transition function is then generated (step S350).

11 shows an example of site setting through a multi-faceted reconstruction image. Create a 3D multi-dimensional reconstructed image as shown in the diagram and draw the desired area in ROI. 11 is an example represented by a circle. In this way, the corresponding opacity transition function is drawn as shown in the lower left of the figure, and the corresponding visualization result is shown in the visualization screen on the upper left.

The three-dimensional multi-dimensional image reconstruction method according to the present invention described above can be modified and applied in various forms within the scope of the technical idea of the present invention and is not limited to the preferred embodiment. For example, the input unit may use not only a mouse but also a light pen, a keyboard, or various input devices. In addition to a system for medical image processing, the input unit may be used in the field of design and construction of a building having a three-dimensional structure such as an automobile, a ship, and a building. A wide range of applications is possible.

Although the above has been described with reference to a preferred embodiment of the present invention, those skilled in the art will be able to variously modify and change the present invention without departing from the spirit and scope of the invention as set forth in the claims below. It will be appreciated.

As described above, according to the present invention, in the multi-image reconstruction apparatus that plays an important role in medical diagnosis, the region of interest is directly added to the 3D image by overcoming the limitation of the 2D reconstruction function provided by the existing system. Marking can help you make an intuitive diagnosis, which can be a big help in making a more accurate diagnosis.

In addition, the three-dimensional multi-dimensional image reconstruction according to the present invention provides an important guide role for identifying the lesion of the patient, and in particular, directly displayed on the three-dimensional image while overcoming the limitations of the two-dimensional reconstruction function provided by the existing software. By doing so, it can be helpful for the intuitive diagnosis and help to find and diagnose the correct lesion.

In addition, in the case of a curve having a control point, a sum of distances can be provided for each section to provide numerical information of the lesion, and a method of re-extracting a 3D image by displaying a region of interest shows an image of a desired section instead of a numerical value. Direct input can be used to provide easier operation.

In addition, the automatic visualization of anatomical structures through the ROI of the three-dimensional multi-faceted reconstruction screen can solve the existing hassle that the user must adjust the opacity transition function.

Claims (15)

An input / storing unit that receives volume data storing density values of three-dimensional structures having predetermined characteristics from an external device and stores the volume data; The spatial distribution of the three-dimensional structure is displayed as a 3D image based on the volume data stored in the input / storage unit, and the user can directly reconstruct the image by using the displayed 3D image as a reference image. An arbitrary multi-sided image reconstructing unit which processes to display a multi-sided image of a predetermined ROI displayed on the image; A display unit configured to display a 3D image corresponding to volume data stored in the input / storage unit, and to display a 3D image corresponding to a predetermined ROI set by a user; And An input unit that provides a drawing tool to enable a user to designate a predetermined region of interest on the displayed 3D image, adapts to a drawing request by the drawing tool, and provides a request signal to the arbitrary screen reconstruction unit. 3D multi-dimensional image reconstruction system comprising a. The image processing apparatus of claim 1, wherein the random face reconstructing unit comprises: Processing to display the 3D reference image from the volume data stored in the input storage means, and receiving and processing a predetermined region of interest in the form of predetermined straight or curved data on the reference image through the input means. A reference image processor; A transformation unit for extracting three-dimensional coordinates of each point from two-dimensional position data of each point constituting an arbitrary straight line or curve on the reference image input to the reference image processor; And And extracting data of each part of the image using the three-dimensional coordinates of each point obtained by the converting unit and a visible vector of a desired multi-dimensional image, and reconstructing the reconstructing unit to reconstruct the data of the respective parts into a multi-sided image of the predetermined region of interest. 3D multi-dimensional image reconstruction system. In the three-dimensional multi-dimensional image reconstruction method for processing to be able to display any multi-sided image of the predetermined region of interest of the reference image, (a) displaying a shape of a corresponding section as an image mode to be viewed by a user's operation is input on the projected three-dimensional reference image; (b) As a predetermined region of interest is input in the form of any straight line, a curve, or a free curve by a user on the shape of the corresponding cross section to be displayed, it becomes a standard of image generation from the cross-sectional shape. Extracting one or more sample points; (c) converting the extracted one or more sample points into three-dimensional coordinates, respectively; (d) multiplying the normal vector of the projection plane by the inverse of the visible matrix to generate a three-dimensional multi-sided image extraction direction vector; And (e) generating a multi-faceted image by moving forward using the generated three-dimensional multi-faceted image extraction direction vector from each sample point and obtaining a value corresponding to a unit voxel, and displaying the generated multi-faceted image 3D multi-dimensional image reconstruction method comprising a. The method of claim 3, wherein step (e) Calculating each section distance by integrating section by section using a curve equation passing through each control point; And Storing and displaying the calculated distance of each interval by summing the curve lengths from the origin to the corresponding control point in the order of the control points. 3D multi-dimensional image reconstruction method further comprising. The method of claim 3, wherein step (e) Providing a drawing tool such as an ellipse, a free curve, a rectangle, or the like for representing a region of interest; Aligning density values belonging to boundaries within the ROI; And And generating the aligned density values as density values corresponding to the respective control points of the opacity transition function. The method of claim 3, wherein step (a) comprises: Extracts and arranges each point of a straight line representing a plane such as a horizontal plane, a vertical plane, a slope, and stores a sample point, creates a curve with a plurality of control points input by the user, and generates a curve. 3. The method of claim 6, The generation of the curve, Obtaining a function of the curve from the input one or more control points, by substituting values of a predetermined interval to the parameters to calculate the coordinates of the points, and connecting the points between the predetermined line segments to generate a curve 3D multi-dimensional image reconstruction method. 8. The method of claim 7, wherein the curve function uses a Hermitian curve equation. The method of claim 3, wherein step (b) comprises: 3. The method of claim 3, wherein the sample points are extracted for each unit length from a straight line representing a plane selected by the user when the shape of the cross section to be displayed is a basic polygonal image mode. The method of claim 9, wherein step (b) comprises: When the shape of the displayed cross-section is curved, in the image mode, the direction unit vector of the corresponding line segment is obtained using the length and the direction vector of each line segment, and the point is extracted by advancing the direction unit vector from one end point of the line segment. 3D multi-dimensional image reconstruction method. The method of claim 9, wherein step (b) comprises: When the shape of the displayed cross section is the free-form multi-face image mode, the direction unit vector of the corresponding line segment is obtained using the length and the direction vector of each line segment, and the point is extracted by advancing the direction unit vector from one end of the line segment. 3D multi-dimensional image reconstruction method characterized in that. The method of claim 3, wherein the conversion to the three-dimensional coordinates of step (c), A multidimensional image reconstruction method comprising multiplying the inverse of the visible matrix A by the coordinates on the projection plane of each sample point. A computer-readable recording medium storing a three-dimensional multi-faceted image reconstruction method for processing to display an arbitrary faceted image of a predetermined region of interest of a reference image, the method comprising: (a) displaying a shape of a corresponding section as an image mode to be viewed by a user's operation is input on the projected three-dimensional reference image; (b) As a predetermined region of interest is input in the form of any straight line, a curve, or a free curve by a user on the shape of the corresponding cross section to be displayed, it becomes a standard of image generation from the cross-sectional shape. Extracting one or more sample points; (c) converting the extracted one or more sample points into three-dimensional coordinates, respectively; (d) multiplying the normal vector of the projection plane by the inverse of the visible matrix to generate a three-dimensional multi-sided image extraction direction vector; And (e) generating a multi-faceted image by moving forward using the generated three-dimensional multi-faceted image extraction direction vector from each sample point and obtaining a value corresponding to a unit voxel, and displaying the generated multi-faceted image A computer-readable recording medium storing a three-dimensional multi-dimensional image reconstruction method comprising a. The method of claim 13, wherein step (e) Calculating each section distance by integrating section by section using a curve equation passing through each control point; And Storing and displaying the calculated distance of each interval by summing the curve lengths from the origin to the corresponding control point in the order of the control points. The computer-readable recording medium storing the three-dimensional multi-dimensional image reconstruction method further comprising. The method of claim 13, wherein step (e) Providing a drawing tool such as an ellipse, a free curve, a rectangle, or the like for representing a region of interest; Arranging the density values belonging to the inside of the boundary of the region of interest in ascending order; And And generating the aligned density values as density values corresponding to the respective control points of the opacity transition function.