WO2013129895A1

WO2013129895A1 - Three-dimensional virtual liver surgery planning system

Info

Publication number: WO2013129895A1
Application number: PCT/KR2013/001717
Authority: WO
Inventors: 유희천; 양샤오펑; 최영근; 이원섭; 조백환; 유희철
Original assignee: 포항공과대학교 산학협력단; 전북대학교산학협력단
Priority date: 2012-03-02
Filing date: 2013-03-04
Publication date: 2013-09-06

Abstract

The three-dimensional virtual liver surgery planning system, according to one embodiment of the present invention, comprises: a DICOM receiving module for receiving an abdominal CT volume dataset from a PACS server; a DICOM loading and noise-removing module for loading the received abdominal CT volume dataset and removing noise; a standard liver volume (SLV) estimation module for estimating a standard liver volume from the noise-removed abdominal CT volume dataset; a liver extraction module for extracting a three-dimensional liver region; a blood vessel extraction module for extracting a three-dimensional blood vessel region including the hepatic portal vein, the hepatic artery, the hepatic vein and the inferior vena cava (IVC); a tumor extraction module for extracting a three-dimensional tumor region; a liver division module for dividing the extracted three-dimensional liver region into a plurality of sections by a reference point, selected by a user or a spherical editing tool; and a liver surgery planning module for planning three-dimensional liver surgery using a cut plane, liver sections, or the spherical editing tool.

Description

【Specification】

[Name of invention]

3D Virtual Liver Surgery Planning System

Technical Field

The present invention relates to a three-dimensional virtual liver surgery planning system, a three-dimensional virtual liver surgery planning system that provides doctors with an effective method for safe and reasonable surgery.

Background Art

Safety between major resection relative residual capacity ^_(0/0 RLV) and total functional liver volume between - can be predicted by the ratio of the residual between the volume of the (TFLV, total liver functional liver volume = total liver volume of the volume of the tumor) .

For example, Schindl et al. (2005. Schindl, MJ, Redhead, DN, Fearon, KCH, Garden, OJ, Wigmore, S J. The value of residual liver volume as a predictor of hepatic dysfunction and infection after major liver resection. 54 (2), 289-296.) Show that over 90% of patients with normal liver function have a greater than 90% incidence of severe liver dysfunction after surgery, whereas% RLV is less than 27%. Reported a 13% incidence of liver dysfunction. Ferrero et al. (2007. Ferrero, A., Vigano, L., Polastri, R., Muratore, A., Eminefendic, H., Regge, D .. Capussotti, L. Postoperative liver dysfunction and future remnant liver: Where is the Results of a prospective study.World Journal of Surgery 31 (8), 1643-1651.) found that 119 patients had liver resection when% RLV was greater than 26.5% in patients with healthy liver, and For patients with impaired liver function, it was suggested to be safe when more than 31%.

Reasonable liver resection is required to be properly selected for the cutting position and orientation, and shape of the cross-cutting end face can be ^"plan By identifying the location of the tumor, taking into account the three vessels (portal vein, hepatic vein, and hepatic artery) structure between have. For safe and rational liver surgery, the three-dimensional virtual liver surgery system is designed to replace existing livers, remnants, and grafts, as well as visual information about the location and size of tumors, the structure of liver-related blood vessels, and liver compartments. Quantitative information on the volume of the liver should be provided. Most existing virtual surgical systems such as Rapidia (Infinitt Co., Ltd, South Korea), Voxar 3D (TOSHIBA Co., Japan), Syngovia (SIEMENS Co., Germany), and OsriX (Pixmeo Co., Switzerland) It does not provide specialized functions for surgery planning. In addition, this general virtual surgical system provides a level of functionality that surgeons lack clinically to plan for preoperative liver surgery. For example, the manual or semi-automated liver extraction provided by conventional virtual surgical systems requires a lot of processing time (more than 30 minutes) and requires considerable effort from the user. In addition, the general virtual surgery system does not provide a liver compartment discrimination function and liver surgery planning function.

[Detailed Description of the Invention]

[Technical problem]

In order to solve the problems of the background art and to plan the optimal liver surgery, (1) procedure-driven user interface, ( ² ) three-dimensional CT imaging, (3) volumetric calculation, (4) two-dimensional and three-dimensional To provide a 3D virtual liver surgery planning system that implements shape correction, (5) visualization technology, and (6) manipulation technique.

Technical Solution

The 3D virtual liver surgery planning system according to an embodiment of the present invention includes a digital imaging and communications in medicine (DICOM) receiving module that receives an abdominal computer tomography (CT) volume data set from a picture archiving and communication system (PACS) server. And a standard liver volume (SLV) from the DICOM loading and noise canceling models for loading and removing the received abdominal CT volume data set, and the multiple CT volume data set from which the noise is removed. A standard hepatic extrapolation module for estimating, hepatic extraction models for extracting a three-dimensional hepatic region connected with the standard hepatic extrapolation models, and a hepatic vein, hepatic artery, hepatic vein, and inferior vein vena cava, IVC) and the three-dimensional vessel region for extracting the vascular region, and the vascular extraction module, the three-dimensional tumor region, Tumor extraction modules for extracting the liver, liver segmentation module for dividing the extracted three-dimensional liver region into a plurality of compartments by a user-selected reference point or a sphere editing tool, and connected to the liver compartmentalization module, cutting plane, liver Block, or Includes a Liver Surgery Planning module that uses a spherical editing tool to perform a 3D liver plan.

It may further include a procedure-based user-friendly interface connected to each of the above.

The method may further include liver extraction correction models that interact with the liver extraction models and edit the extracted three-dimensional liver region.

The blood vessel extraction module may further include a blood vessel extraction correction module capable of editing the extracted three-dimensional vessel region.

The method may further include a tumor extraction correction module that interacts with the tumor extraction modules and edits the extracted three-dimensional tumor region.

It may further include hepatic compartmentalization correction modes which interact with the hepatic compartmentalization models and which can edit the segmented hepatic compartments.

The liver extracting hairs may perform a semi-automatic hybrid liver extraction method.

In the semi-automatic complex liver extraction method, a step of deriving an initial liver region by applying a fast marching level set method using a plurality of seed points selected from a plurality of CT slices by a user, Improving the derived first liver region through a threshold-based level set method, correcting the extracted liver region through a circle that can be scaled at a two-dimensional viewpoint, or at a three-dimensional viewpoint A correction step of correcting through an adjustable ball.

In the correcting step, the 3D viewpoint selection may be implemented using an integrated 3D viewpoint restoration button in which buttons of front, rear, left side, right side, top side, and bottom side are integrated.

The blood vessel extraction models may extract a three-dimensional region of the portal vein, hepatic artery, and hepatic vein by a region growing method using a threshold interval and seed points.

The region growing method may include loading a CT volume in which the extracted liver region is cut, editing the liver region through a spherical editing tool to include the blood vessel to be extracted, and editing the liver. CT into area Masking the volume, inputting a plurality of seed points selected by the user to the plurality of CT slices, and an initial threshold interval according to the intensity distribution of the data set of the masked CT volume finding an interval; generating a plurality of additional threshold intervals by finely adjusting a lower threshold and an upper threshold of the initial threshold interval; an initial threshold interval And extracting a plurality of blood vessel structures based on an additional threshold interval and providing the same with volume information in a three-dimensional view.

The user may further include editing the extracted blood vessel through a circular or spherical editing tool at a 2D or 3D viewpoint.

The liver compartmentalization step, forming a segment 1, dividing the liver into the left and right lobe, dividing the right lobe into an anterior and a posterior sector, the left lobe Dividing into medial sector (segment 4) and lateral sector; dividing the posterior sector into segment 6 and segment 7; anterior sector) may be configured to perform a step of dividing all segments into segment 5 and segment 8 and dividing the lateral sector into segment 2 and segment 3. .

Real-time volumetric calculations of the extracted liver, blood vessels, tumors, and liver compartments may be indicated.

Advantageous Effects

According to the three-dimensional virtual surgery procedure system according to an embodiment of the present invention, the user can easily extract the liver, blood vessels, and tumors according to the procedure, divide the liver compartment, and plan the surgery through a user-centered interface. have.

[Brief Description of Drawings]

The features and advantages of the invention may be apparent from the accompanying drawings and the detailed description. 1 is an overall configuration diagram of a three-dimensional virtual liver surgery planning system according to an embodiment of the present invention.

2 is an information processing flowchart of the liver extraction step of the three-dimensional virtual liver surgery planning system according to an embodiment of the present invention.

3 is an image photograph showing an example of selecting seed points for liver extraction in a liver extraction step of a 3D virtual liver surgery planning system according to an embodiment of the present invention.

4 is an image showing an example of editing the region of the liver extracted in the liver extraction step of the three-dimensional virtual liver surgery planning system according to an embodiment of the present invention through a three-dimensional ball (size) that can be adjusted in size It is a photograph. Figure 5 is a flow chart of blood vessel extraction in the liver extraction step of the three-dimensional virtual liver surgery planning system according to an embodiment of the present invention.

6A to 6F illustrate six candidate blood vessel candidates extracted based on various threshold intervals to allow a user to select the best extraction result in a 3D virtual liver surgery planning system according to an embodiment of the present invention. 6A and 6H are graphs and tables showing the volume of candidate vessel structure candidates.

FIG. 7 is a diagram exemplarily illustrating an integrated three-dimensional view restoration button having a color scheme in a three-dimensional virtual liver surgery planning system according to an embodiment of the present invention.

8 is a flowchart illustrating a three-step procedure based on a cutting plane for classifying liver compartments in a three-dimensional virtual liver surgery planning system according to an embodiment of the present invention.

9 is a flowchart illustrating a three-step procedure based on a spherical editing tool for classifying liver compartments in a three-dimensional virtual liver surgery planning system according to an embodiment of the present invention.

10 is a flowchart illustrating a liver compartment classification procedure in a 3D virtual liver surgery planning system according to an embodiment of the present invention.

11 illustrates a reference point used to classify the liver into the right lobe and the left lobe in a 3D virtual liver surgery planning system according to an embodiment of the present invention. Image is a picture.

12 is an image photograph showing a liver divided into a right lobe and a left lobe through a spherical editing tool in a 3D virtual liver surgery planning system according to an exemplary embodiment of the present invention.

FIG. 13A is an image photograph showing an example of a surgical plan through selecting a liver compartment to be cut in a 3D virtual liver surgery planning system according to an embodiment of the present invention, and FIG. 13B is a legend showing a volume and a color table of each compartment. .

14 is an image photograph showing an example of a surgical plan using a spherical editing tool in a three-dimensional virtual liver surgery planning system according to an embodiment of the present invention.

15A to 15F are image photographs showing an example of a procedure-driven user interface in a 3D virtual liver surgery planning system according to an embodiment of the present invention.

[Form for implementation of invention]

Hereinafter, with reference to the accompanying drawings will be described in detail to be easily carried out by those of ordinary skill in the art. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and like reference numerals designate like elements throughout the specification.

1 is an overall configuration diagram of a three-dimensional virtual liver surgery planning system according to an embodiment of the present invention.

The three-dimensional virtual liver surgery planning system according to the present embodiment includes: DICOM (Digital Imaging and Communications in Medicine) receiving modules (Ml), DICOM loading and noise removing modules (M2), standard liver volume estimation modules (M3), liver extraction Module (M4), vascular extraction modules (M5), tumor extraction modules (M6), liver compartmentalization module (M7), liver surgery planning modules (M8), and liver extraction correction modules (M4) ) Is connected, the vascular extraction modulus M5 is connected to the vascular extraction correction modulus M51, the tumor extraction modulus M6 is connected to the tumor extraction correction module M61, and the liver segmentation modulus M7 is the liver segmentation. The calibration module M71 is connected.

In the system according to this embodiment, first, hepatic artery phase, portal vein A computer tomography (CT) volume data set from phase and hepatic vein phase is input to the system. The DICOM receiving module Ml may receive CT volume data of various phases from a picture archiving and communication system (PACS) server and store it in a local storage. The DICOM loading and noise cancellation mode M2 loads the CT volume data set into the system to remove noise and registers the CT volume data set of each phase. liver volume (SLV) estimation models (M3) can provide standard liver volume (SLV) estimated through three regression models.

Liver extraction models M4 use a noise-free portal volume CT volume data set to extract liver areas. The extracted liver can be visualized as a two-dimensional and three-dimensional view on the CT image, and the user can freely edit the three-dimensional liver region at two and three-dimensional points through the liver extraction correction module M41. . The liver extraction module M4 also provides the function of calculating the volume of the extracted liver.

Blood vessel extraction module (M5) is a registered hepatic artery phase, portal vein phase, and hepatic vein image after noise is removed to extract four three-dimensional vessels (hepatic vein, hepatic artery, hepatic vein, and inferior vena cava) Use the CT volume data set of (phase) as input information. The extracted blood vessel may be visualized as a two-dimensional and three-dimensional view on the CT image, and the region of the extracted blood vessel may be effectively edited at the two-dimensional and three-dimensional views through the blood vessel extraction correction modules M51. The blood vessel extraction module M5 also provides the function of calculating the volume of the extracted blood vessel.

The system of this example provides tumor extraction modules M6 to extract tumors from a CT volume data set. The extracted tumor can be visualized as a two-dimensional and three-dimensional view on the CT image, and the user can effectively edit the region of the extracted tumor in both the two-dimensional and three-dimensional views through the tumor extraction correction module (M61). Can be. The tumor extraction modules (M6) also provide the function of calculating the volume of the extracted tumor.

The system of this embodiment classifies the extracted liver into several compartments. Liver compartmentalization modalities (M7) are provided. The liver segmentation module M7 provides an interactive method for the user to select a plurality of landmarks from a two-dimensional viewpoint on the CT image, wherein the selected reference points are the two-dimensional viewpoint and the three. It can be visualized in a dimensional view. The liver can be divided into sections based on cutting planes or spherical editing tools created by selected landmarks. The divided liver compartments can be visualized in a three-dimensional view, and a color scheme is provided to visualize the separated livers in different colors for each compartment. The hepatic compartmentalization models M7 provide an interactive way to adjust the color and transparency of each compartment and may also provide the ability to calculate the volume of each compartment. Liver compartmentalization may be corrected through liver compartmentalization correction models M71.

Finally, the hepatic surgical planning model (M8) uses the results of the previous models, provides information on the relative spatial relationships within the liver, blood vessels, tumors, liver compartments and liver compartments, and visualizes them in a three-dimensional perspective. Provides the ability to The surgical planning model M8 provides one or more cutting planes for cutting out the liver portion of the tumor, and can adjust the direction, position and shape of the cutting plane, and utilize the cutting planes or spherical editing tools. Provides the ability to cut liver compartments. In addition, the liver surgery planning model M8 may visualize and provide relative liver volume information in a three-dimensional view for effective surgery planning. The user can utilize the liver surgery plan model M8 via the user interface ₁ ; ₁ to perform the virtual liver surgery plan.

2 is an information processing flowchart of the liver extraction step of the three-dimensional virtual liver surgery planning system according to an embodiment of the present invention. The liver extracting hairs may perform a semi-automatic hybrid liver extraction method. That is, the initial liver region is automatically extracted based on the selected seed point, and then the 3D liver region is manually extracted through additional correction. It demonstrates in detail below.

First, the noise of the portal CT phase data set is removed (S41).

Second, a number of seed points can be placed in the area where the user (S42). Selected seed points may be indicated by red dots, for example. It is a good idea to select about five slices at the same interval from one CT volume data set. When the liver area is wide, it is necessary to select 7 to 15 seed points per slice, and when the liver area is narrow, 1 to 4 seed points per slice may be selected (see FIG. 3). Seed points can be selected to encompass the entire liver region, including the edges.

Third, the first liver region is derived through the fast marching level-set method (S43). If the derived first liver region is too wide to be extracted, the user may return to the seed point selection step and select seed points again.

Fourth, the initially formed liver region may be determined through a threshold-based level-set method (S45). If the extracted liver region is appropriate, the liver extraction operation may be terminated (S46). However, if the user wants to edit the extracted liver, the non-living part may be removed or the missing part may be restored through a circle or ball that can be adjusted in two-dimensional and three-dimensional views (S47). In other words, by providing a two-dimensional circle that can be adjusted or a three-dimensional ball that can be adjusted, the user can effectively remove an area other than the liver by clicking and dragging.

Figure 4 is possible to adjust the size of the extracted liver in three-dimensional view

This is an image of an example of using a three-dimensional ball to remove a part that is not a liver area.

Next, the step of smoothing the surface of the corrected liver region may be performed, and the volume of the liver extracted in the liver extraction step may be calculated and displayed on the screen.

Figure 5 is a flow chart of blood vessel extraction in the liver extraction step of the three-dimensional virtual liver surgery planning system according to an embodiment of the present invention.

First, the noise of the hepatic artery phase, portal vein phase, and hepatic vein phase CT volume data sets is removed (S51).

Secondly, the user can use the spherical editing tool based on the extracted liver area. The region including the blood vessel is masked (S52).

Third, the user selects a plurality of seed points in the blood vessel region of the 1 to 2 CT slices using the mouse (S53).

Fourth, after the initial threshold interval is automatically derived according to the intensity distribution of the masked CT image, five threshold intervals slightly different from the derived threshold interval are obtained. ) Are automatically determined (S54).

Fifth, the vascular structure is extracted through a region growing method based on six threshold intervals (S55). Thereafter, the extracted six vessel structure candidates are shown in three dimensions with volume information (S56). By checking whether there are satisfactory results among the six vascular structure candidates (S57), and if there are satisfactory results among the six vascular structure candidates, the user may select the result as the final result (S58) (FIGS. 6A to 6). 6h). However, if there is no satisfactory result among the six candidates, the user may repeat the blood vessel extraction procedure again from the seed point selection step (S53).

Finally, the user may correct the selected blood vessel structure at two and three dimensional views (S59). If the corrected result is satisfactory, the blood vessel extraction procedure is terminated. Otherwise, the correction procedure can be performed again.

7 illustrates an integrated three-dimensional viewpoint restoration button (A, P, S, I, L, and R) having a color scheme in a three-dimensional virtual liver surgery planning system according to an embodiment of the present invention. It is a figure shown normally. Two colors are available for the integrated buttons (light blue for the A, S, and L buttons, and yellow for the P, I, and R buttons). Each button has its own location, with the Α button on the front, the Ρ burrow on the back, the L burrow on the left, the R button on the right, the S button on the top, and the I button on the bottom. The user may select one of the integration buttons to restore the 3D viewpoint to a specific viewpoint.

That is, the integrated burner may be set to return to a specific direction at once when the direction or position is freely adjusted by the user on the 3D screen. For example, if you want to change the situation from the right side of the extracted 3D liver to the right side. Press to change the screen to view the liver from behind.

In addition, the color combination system assigns light blue for the left, top, front, and yellow for the right, bottom, and back in consideration of the positional meaning of each viewpoint, which allows the user to easily recognize the meaning of the button. It is to be utilized.

First, the liver can be divided into several compartments based on the vascular structure of the hepatic vein and portal vein by the Couinaud model. To divide a compartment, the user

Reference marks may be selected using a computer mouse on the 2D CT image (S701). The selected place may be represented by a red dot to indicate that it is selected as a reference point. At the same time, it is possible to indicate that the reference point is selected through the red sphere at the same position of the three-dimensional viewpoint.

Second, ^' to create a cutting plane passing through the previously selected reference points to partition the gaol (S702).

Third, the user may correct the divided liver compartment by adjusting the cutting plane (S703). The position and angle of the cutting plane can be adjusted freely by dragging at the three-dimensional viewpoint.

First, the extracted liver region is loaded and covered on the original CT image (S711).

Next, the liver compartments according to the Couinaud model are classified through the spherical editing tool (S712).

Finally, the classified liver region may be corrected as necessary through the spherical editing tool (S713).

FIG. 10 is a flow chart illustrating a liver compartment classification procedure in a 3D virtual liver surgery planning system according to an embodiment of the present invention, and FIG. An image image showing three reference points (middle hepatic vein, entrance of right portal vein, gallbladder fossa) used to distinguish the left lobe, and FIG. 12 is an extracted three-dimensional liver region extracted based on a CT image. The image is divided into a right lobe and a left lobe through a segmentation sphere.

First, segment 1 is formed (S721).

Second, the liver is a cutting plane or segmentation sphere (see FIG. 12) that passes through the middle hepatic vein, the entrance of right portal vein, and the gallbladder fossa (see FIG. 11). ) Are divided into right lobe and left lobe (S722).

Third, the right lobe can be divided into anterior sector and posterior sector along the postal vein (S723).

Previously, the left lobe can be divided into medial sector (segment 4) and lateral sector along the left vein (S724).

Fifth, the posterior sector may be divided into segment 6 and segment 7 according to the right posterior portal structure (S725).

Sixth, the anterior sector can be divided into segment 5 and segment 8 according to the right portal vein structure (S726).

Lastly, the lateral sector may be divided into segment 2 and segment 3 according to the left portal vein structure (S727).

The segments other than segment 1 in the liver segmentation procedure may be classified based on the structure of the portal vein and the hepatic vein by a cutting plane or a sphere editing tool generated based on a landmark.

Liver compartmentalization may be in whole or in part depending on the needs of the user.

FIG. 13A is an image photograph showing an example of a surgical plan by selecting a liver compartment to be cut in a 3D virtual liver surgery planning system according to an embodiment of the present invention, and FIG. 13B is a legend showing a volume and a color table of each compartment.

In this example, liver compartments, blood vessels, and tumors were visualized using 3D rendering techniques. You can hide the compartment where the tumor is located Can be removed effectively. In other words, during the stage of liver surgery, the tumor is located

Some of the three-dimensional liver compartments can be excised with one or more cutting planes defined by the user or with a spherical editing tool and removed by making the three-dimensional liver compartments with tumor fully transparent using checkboxes. It may be. In addition, the volume of the entire liver, the volume of the site to be resected, and the volume and ratio of the remaining liver after the ablation may be provided in real time on the 3D screen to assist the surgical planning.

Above _. In the stage of hepatic surgery planning, the hepatic section has a thickness of 2 mm, which is created by the sum of the cross section thickness of 1 mm and the cross section thickness of 1 mm. In other words, at the stage of liver surgery planning, a certain area between three dimensions is required, and a three-dimensional object having a thickness is generated to effectively visualize the cut surface. At this time, it can be taken to have a thickness of 2mm in total by taking 1mm in and out of the cutting surface.

The spherical editing tool allows the user to effectively remove the liver area where the tumor is located. The cut plane of the cut liver is seen at the three-dimensional viewpoint. In addition, volume information such as total liver volume and residual liver volume ratio (% 1 \) may be provided on a three-dimensional screen in real time to assist the liver compartment surgery planning.

15A to 15F are image photographs showing an example of a procedure-oriented user interface in a 3D virtual liver surgery planning system according to an embodiment of the present invention.

The user-oriented interface allows the user to easily extract liver, blood vessels and tumors according to the procedure, divide the liver compartments, and plan the surgery.

Although the preferred embodiments of the present invention have been described above, the present invention is not limited thereto, and various modifications and changes can be made within the scope of the claims and the detailed description of the invention and the accompanying drawings. Naturally, this also belongs to the scope of the present invention.

Claims

[Range of request]

[Claim 1]

A digital imaging and communications in medicine (DICOM) receiving module for receiving an abdominal computer tomography (CT) volume data set from a picture archiving and communication system (PACS) server;

DICOM loading and noise cancellation models for loading the received abdominal CT volume data set and removing noise;

A standard liver volume estimation module for estimating a standard liver volume (SLV) from the noise-removed plurality of CT volume data sets;

Liver extraction models connected to the standard liver volume estimation models to extract a three-dimensional liver region;

Blood vessel extraction models connected to the liver extraction models to extract a three-dimensional vessel region including a portal vein, a hepatic artery, a hepatic vein, and an inferior vena cava (IVC);

A tumor extraction model connected to the blood vessel extraction modules to extract a three-dimensional tumor region;

Liver partitioning models for dividing the extracted three-dimensional liver region into a plurality of sections by a user-selected reference point or a sphere editing tool; And

A liver surgery plan module connected to the liver compartment module to perform a three-dimensional liver surgery plan using a cutting plane, a liver compartment, or a spherical editing tool;

3D virtual liver surgery planning system comprising a.

[Claim 2]

The method of claim 1,

And a procedure-based, user-friendly interface coupled to each of the modules.

[Claim 3]

The method of claim 1,

And a liver extraction correction model that interacts with the liver extraction models and can edit the extracted three-dimensional liver region.

[Claim 4]

The method of claim 1,

3D virtual liver surgery planning system further comprising a blood vessel extraction correction modal to interact with the blood vessel extraction modalities, and to edit the extracted three-dimensional vessel region.

[Claim 5]

According to claim 1,

And a tumor extraction correction model that interacts with the tumor extraction models and is capable of editing the extracted three-dimensional tumor region.

[Claim 6]

The method of claim 1,

And a hepatic compartmentalization correction model that interacts with the hepatic compartmentalization models and is capable of editing the segmented hepatic compartments.

[Claim 7]

The method of claim 1,

The liver extraction model is a three-dimensional virtual liver surgery planning system capable of performing a semi-automatic hybrid (hybrid) liver extraction method.

[Claim 8]

The method of claim 7,

The semi-automatic complex liver extraction method,

Deriving an initial liver region by applying a fast marching level set method using a plurality of seed points selected from a plurality of CT slices by a user;

Improving the derived first hepatic region through a threshold-based level set method; And

A correction step of correcting the extracted liver region through a circle whose size can be adjusted at a two-dimensional viewpoint or through a ball which can be adjusted at a three-dimensional viewpoint; 3D virtual liver surgery planning system comprising a.

[Claim 9]

The method of claim 8,

In the correction step,

3D viewpoint selection is a 3D virtual liver surgery plan implemented using the integrated 3D viewpoint reconstruction button that integrates the front, back, left, right, top, and bottom buttons ^. system.

[Claim 10]

The method of claim 1,

The blood vessel extraction module,

A three-dimensional virtual liver surgery planning system that extracts three-dimensional regions of the portal vein, hepatic artery, and hepatic vein by a region growing method using threshold intervals and seed points.

[Claim 11]

The method of claim 10,

The region growing method,

Loading a CT volume on which the extracted liver region is loaded;

Editing the liver region with a sphere editing tool to include the blood vessel to be extracted;

Masking a CT volume to the edited liver region;

Receiving a plurality of seed points selected from a user in a plurality of CT slices;

Finding an initial threshold interval according to an intensity distribution of a data set of the masked CT volume;

Generating a plurality of additional threshold intervals by finely adjusting a lower threshold and an upper threshold of the initial threshold interval; And

Extracting a plurality of blood vessel structures based on an initial threshold interval and an additional threshold interval and providing the same with volume information in a three-dimensional view; 3D virtual liver surgery planning system comprising a.

[Claim 12]

The method of claim 11,

And a step of allowing the user to edit the extracted blood vessel through a circular or spherical editing tool at a two-dimensional or three-dimensional point of view.

[Claim 13]

The method of claim 1,

The liver compartmentalization module,

Forming segment 1;

Dividing the liver into left and right lobes;

Dividing the right lobe into an anterior sector and a posterior sector;

Dividing the left lobe into a medial sector (segment 4) and a lateral sector;

Dividing the posterior sector into segment 6 and segment 7;

Dividing the anterior sector into segment 5 and segment 8; And

The lateral sector is divided into segment 2 and segment

Dividing by three;

3D virtual liver surgery planning system configured to perform.

[Claim 14]

According to claim 11,

3D virtual liver surgery planning system showing the real-time volumetric calculation value of the extracted liver, blood vessels, tumors, and liver compartments.