WO2016137157A1

WO2016137157A1 - Medical imaging device and medical image processing method

Info

Publication number: WO2016137157A1
Application number: PCT/KR2016/001615
Authority: WO
Inventors: 남우현; 박용섭; 신영길; 이재성; 정진욱; 김지혜; 이용근
Original assignee: 삼성전자 주식회사; 서울대학교 산학협력단
Priority date: 2015-02-24
Filing date: 2016-02-17
Publication date: 2016-09-01
Also published as: KR102367133B1; KR20160103482A

Abstract

Disclosed are a medical image processing method and a medical imaging device therefor, the medical image processing method comprising the steps of: acquiring a three-dimensional medical image and a two-dimensional medical image, which indicate a blood vessel; determining a blood vessel region in the three-dimensional medical image, which corresponds to a partial region of the blood vessel in the two-dimensional medical image; and matching the blood vessel region to the partial region of the blood vessel in the two-dimensional medical image.

Description

Medical Imaging Device and Medical Image Processing Method

The present disclosure relates to a medical imaging apparatus and a medical image processing method for matching a 2D medical image and a 3D medical image.

The medical imaging apparatus is a device for acquiring an internal structure of an object as an image. The medical imaging apparatus photographs and processes structural details, internal tissues, and fluid flow in the body and is displayed to the user. A user such as a doctor may diagnose a medical condition and a disease of a patient using the medical image output from the medical imaging apparatus.

An X-ray apparatus as an example of a medical imaging apparatus is a medical imaging apparatus that acquires an internal structure of the human body by transmitting X-rays through the human body. The X-ray apparatus is simpler than other medical imaging apparatuses including an MRI apparatus, a CT apparatus, and the like, and has an advantage of obtaining a medical image of an object in a short time. Therefore, the X-ray apparatus is widely used for simple chest imaging, simple abdominal imaging, simple skeletal imaging, simple sinus imaging, simple neck soft tissue imaging and mammography.

Fluoroscopy is an image processing technique of acquiring an X-ray video by photographing an object in real time. The user may use fluoroscopy for the purpose of monitoring X-ray angiography or surgical procedures.

According to the embodiments, a medical imaging apparatus and a medical image processing method for matching a 2D medical image and a 3D medical image are provided.

According to a first aspect, a medical image processing method includes: obtaining a 3D medical image representing a blood vessel and a 2D medical image representing a blood vessel; Determining a blood vessel region in the 3D medical image corresponding to a portion of the blood vessel in the 2D medical image; And matching the blood vessel region to a partial region in the 2D medical image.

In addition, the partial region may include at least one of a region in which a contrast agent is administered in a blood vessel in a 2D medical image, a region of interest of a blood vessel in a 2D medical image, or a region in which a target is located in a blood vessel in a 2D medical image. It may be any one area.

The determining may include separating the three-dimensional blood vessel region from the three-dimensional medical image; Separating a partial region from the 2D medical image; And among the plurality of sub-vascular regions divided from the three-dimensional blood vessel region, determining the sub-vascular region having the highest similarity to the partial region as the blood vessel region.

Further, the determining may include performing parallel or rotational movement with respect to centerlines of each of the plurality of sub-vascular regions; Calculating a distance between centerlines of each of the plurality of sub-vascular regions that have been moved or rotated in parallel and a centerline of the partial region; And determining the sub-vascular region having the smallest distance from the partial region as the blood vessel region.

Further, the determining may include projecting centerlines of each of the plurality of sub-vascular regions in a two-dimensional plane; Calculating a distance between centerlines of each of the projected plurality of subvascular regions and a centerline of the partial region; And determining the sub-vascular region having the smallest distance from the partial region of the blood vessel as the blood vessel region.

In addition, the calculating may include generating a distance transform with respect to the centerline of the partial region; And calculating a distance between the centerlines of each of the projected plurality of sub-vascular regions and the centerline of the partial region by using the distance transformation.

In addition, the matching may include determining three-dimensional transformation information for matching the blood vessel region with the partial region; And matching the blood vessel region to a partial region in the 2D medical image based on the 3D transformation information.

The medical image processing method may further include: storing an image in which a blood vessel region is matched with a 2D medical image; And displaying the matched image.

In addition, the 3D medical image may be an image obtained through CT angiography before the procedure on the subject, and the 2D medical image may be x-ray angiography during the procedure on the subject. It may be an image acquired through.

According to a second aspect, a medical imaging apparatus includes: an image acquisition unit configured to acquire a 3D medical image representing a blood vessel and a 2D medical image representing a blood vessel; And a matching unit for determining a blood vessel region in the 3D medical image corresponding to the partial region of the blood vessel in the 2D medical image, and matching the blood vessel region to the partial region in the 2D medical image.

According to a third aspect, there is provided a computer readable recording medium having recorded thereon a program for implementing the above method.

According to the present embodiments, a 3D roadmap capable of correcting various movements of an object may be determined because a region of a blood vessel in a 3D medical image corresponding to a portion of the selectively imaged blood vessel may be determined and a matched image may be generated. ) Can be provided. In addition, since a partial region of the blood vessel selectively imaged through the registration image may be expressed as a 3D blood vessel structure, the convenience of the procedure for the subject may be improved.

1 is a block diagram of a medical imaging apparatus according to an exemplary embodiment.

2 is a block diagram of a medical imaging apparatus according to another exemplary embodiment.

FIG. 3 is a diagram for describing an exemplary embodiment in which the medical imaging apparatus extracts a center line of a 3D blood vessel region or a 3D blood vessel region from a 3D medical image.

4 and 5 are diagrams for describing an exemplary embodiment in which the medical imaging apparatus divides a 3D blood vessel region into a plurality of subvascular regions.

6 is a diagram for describing an example in which a medical imaging apparatus separates a partial region of a blood vessel from a 2D medical image, according to an exemplary embodiment.

FIG. 7 illustrates an embodiment in which the medical imaging apparatus determines a subvascular region having the highest similarity to a partial region of a blood vessel among a plurality of subvascular regions.

8 is a diagram for describing an embodiment of matching blood vessel regions in a 3D medical image to a 2D medical image, according to an exemplary embodiment.

9 is a diagram for describing a medical image processing method performed by a medical imaging apparatus, according to an exemplary embodiment.

10 and 11 illustrate X-ray apparatuses according to example embodiments.

FIG. 12 is a diagram illustrating a configuration of the communication unit of FIG. 11.

Advantages and features of the present disclosure, and a method of achieving them will be apparent with reference to the embodiments described below in conjunction with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below, but may be implemented in various forms, and only the present embodiments are disclosed so that the disclosure of the present disclosure is complete, and common knowledge in the art to which the present disclosure belongs. It is provided to fully inform the person having the scope of the invention, and the present disclosure is only defined by the scope of the claims.

Terms used herein will be briefly described, and the present disclosure will be described in detail.

The terms used in the present disclosure selected general terms widely used as far as possible in consideration of functions in the present disclosure, but may vary according to the intention or precedent of a person skilled in the art, the emergence of new technologies, and the like. In addition, in certain cases, there is also a term arbitrarily selected by the applicant, in which case the meaning will be described in detail in the description of the invention. Therefore, the terms used in the present disclosure should be defined based on the meanings of the terms and the contents throughout the present disclosure, rather than simply the names of the terms.

When any part of the specification is to "include" any component, this means that it may further include other components, except to exclude other components unless otherwise stated. In addition, the term "part" as used herein refers to a hardware component, such as software, FPGA or ASIC, and "part" plays certain roles. But wealth is not limited to software or hardware. The 'unit' may be configured to be in an addressable storage medium or may be configured to play one or more processors. Thus, as an example, a "part" refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, procedures, Subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays and variables. The functionality provided within the components and "parts" may be combined into a smaller number of components and "parts" or further separated into additional components and "parts".

As used herein, "image" may mean multi-dimensional data composed of discrete image elements (eg, pixels in a 2D image and voxels in a 3D image). Examples of the image may include an X-ray device, a computed tomography (CT) device, a magnetic resonance imaging (MRI) device, an ultrasound device, and a medical image of an object obtained by another medical device.

Also, herein, an "object" may be a person or an animal, or part of a person or an animal. For example, the subject may include at least one of organs, nerves, bones, and blood vessels, such as the liver, heart, uterus, brain, breast, and abdomen. In addition, the "object" may be a phantom. Phantoms are materials that are very close to the density and effective atomic number of an organism and also very close to the volume of an organism, and may include sphere phantoms with properties similar to the body.

In addition, in the present specification, the "user" may be a doctor, a nurse, a clinical pathologist, a medical imaging expert, or the like, and may be a technician who repairs a medical device, but is not limited thereto.

1 is a block diagram of a medical imaging apparatus 100 according to an exemplary embodiment.

As shown in FIG. 1, the medical imaging apparatus 100 may include an image acquisition unit 110 and a matching unit 120, according to an exemplary embodiment. In the medical imaging apparatus 100 illustrated in FIG. 1, only components related to the present exemplary embodiment are illustrated. Accordingly, it will be understood by those skilled in the art that other general purpose components may be further included in addition to the components shown in FIG. 1.

The image acquirer 110 acquires a 3D medical image and a 2D medical image representing a blood vessel, according to an exemplary embodiment. According to an embodiment, the image acquisition unit 110 performs computed tomography angiography (MRI angiography) or magnetic resonance angiography (MRI angiography) on the object, three-dimensional medical representation of the blood vessels in the object in three dimensions An image can be obtained. In addition, according to an exemplary embodiment, the image acquirer 110 may perform X-ray angiography on blood vessels in the object to acquire a 2D medical image representing the blood vessels in the object in two dimensions. In addition, according to an embodiment, the 2D medical image may be an X-ray video obtained through fluoroscopy. According to an embodiment, the 3D medical image may be acquired by the image acquisition unit 110 before the user performs the procedure on the object, and the 2D medical image is performed while the user performs the procedure on the object. It may be obtained by the image acquisition unit 110 in real time. In addition, according to an exemplary embodiment, the image acquisition unit 110 may acquire a 3D medical image and a 2D medical image representing blood vessels from the outside through a communication unit (not shown). In addition, according to an exemplary embodiment, the image acquirer 110 may acquire a 3D medical image and a 2D medical image stored in advance from a memory (not shown).

The matching unit 120 determines a blood vessel region in the 3D medical image corresponding to a portion of the blood vessel in the 2D medical image, according to an exemplary embodiment.

According to an embodiment, some regions of the blood vessels in the 2D medical image may be regions in which a contrast agent is administered in the blood vessels. For example, a user may inject a contrast agent into a blood vessel of an object, and the image acquirer 110 may perform an X-ray angiography test. As a result, the 2D medical image may include a portion of the blood vessel in which the contrast agent is added. It can be represented by some area. According to an embodiment, the partial region of the blood vessel in the 2D medical image may be a region of interest set by the user. In addition, according to an exemplary embodiment, a part of the blood vessel in the 2D medical image may be a region in which a target is located in the blood vessel. For example, when the user inserts the catheter into the blood vessel of the subject, a portion of the blood vessel may be an area where the catheter is located.

According to an embodiment, the matching unit 120 may separate or extract a 3D blood vessel region from a 3D medical image. That is, the matching unit 120 may separate or extract only the blood vessel region seen in three dimensions in the 3D medical image. Subsequently, the matching unit 120 may divide the separated three-dimensional blood vessel region into a plurality of sub-vascular regions.

According to an embodiment, the matching unit 120 may generate a graph corresponding to the 3D blood vessel region based on the branching point of the blood vessel. That is, the matching unit 120 may generate a graph showing a connection relationship between branch points of each blood vessel in the 3D blood vessel region. Subsequently, the matching unit 120 may divide the graph corresponding to the 3D blood vessel region into a plurality of regions according to a predetermined condition. An example of the predetermined condition may be a condition that the sum of the lengths of the branch points included in each of the plurality of areas is greater than a predetermined threshold. Accordingly, the matching unit 120 may divide the graph into a plurality of regions, so that the three-dimensional blood vessel region corresponding to the graph may be divided into a plurality of sub-vascular regions corresponding to the plurality of regions. A more specific embodiment will be described with reference to FIGS. 4 and 5 below.

According to an embodiment, the matching unit 120 may separate a portion of a blood vessel from a 2D medical image. That is, the matching unit 120 may separate only a part of the blood vessel seen in two dimensions in the two-dimensional medical image. Also, according to an embodiment, when the 2D medical image is a moving picture composed of a plurality of frames, the matching unit 120 may separate a partial region of the blood vessel based on the 2D medical images corresponding to the plurality of frames. Can be. For example, the matching unit 120 may refer to a partial region of the blood vessel shown in the 2D medical image corresponding to the next frame, and then may match the blood vessel from the 2D medical image corresponding to the current frame. Some areas can be separated.

According to an exemplary embodiment, the matching unit 120 may determine a sub-vascular region corresponding to a partial region of a blood vessel in the 2D medical image among a plurality of sub-vascular regions divided from the 3D blood vessel region. That is, the matching unit 120 may determine a sub-vascular region having the highest similarity to a partial region of the blood vessel among the plurality of sub-vascular regions.

According to an embodiment, the matching unit 120 may project the centerlines of each of the plurality of sub-vessels to a two-dimensional plane. According to an embodiment, the matching unit 120 may calculate a distance between centerlines of each of the plurality of sub-vascular areas projected on the 2D plane and a centerline of a part of the blood vessel in the 2D medical image. According to one embodiment, the matching unit 120 may calculate the closest distance to the center line of the partial blood vessel region for each of the points constituting the center line of any sub-vascular region, the matching unit 120 is a point The average value of the closest distances calculated for each of these may be determined as the distance between the centerline of any subvascular region and the centerline of some region of the blood vessel.

According to one embodiment, the distance between the centerline of any of the subvascular regions of the plurality of subvascular regions and the centerline of some regions of the blood vessels in the two-dimensional medical image is how to move or rotate the centerline of any subvascular region in three-dimensional space. Since the matching unit 120 may vary according to whether or not, the matching unit 120 may perform a parallel movement or a rotational movement with respect to the centerline of any sub-vascular region by a predetermined number of times by varying a numerical value within a preset range. Subsequently, the matching unit 120 may calculate the distance between the center line of any sub-vascular region that is parallel or rotated and the center line of the partial region of the blood vessel by a preset number of times, and as a result, the matching unit 120 may set the preset number of times. The distance having the lowest value among the calculated distances may be determined as the distance between the centerline of any subvascular region and the centerline of some region of the blood vessel. In addition, according to an exemplary embodiment, the matching unit 120 may store information of parallel movement or rotational movement of any sub-vascular region corresponding to the distance having the minimum value in the form of a matrix.

According to an exemplary embodiment, the matching unit 120 may further include a distance map for the centerline of the partial region of the blood vessel to calculate the distance between the centerlines of each of the plurality of subvascular regions and the centerline of the partial region of the blood vessel. A distance transform, such as a distance map or a distance field, may be generated. The distance transformation may be represented as an image according to an embodiment, and may include location information about the centerline of some regions of the blood vessel for each pixel in the image. Accordingly, the matching unit 120 may use the distance transformation with respect to the centerline of the partial region of the blood vessel and the centerlines of each of the plurality of subvascular regions, thereby forming the centerline between each of the plurality of subvascular regions and the centerline of the partial region of the blood vessel. Speed up calculations over distance.

According to an embodiment, the matching unit 120 may calculate a distance between centerlines of each of the plurality of subvascular regions and a centerline of a partial region of a blood vessel in the 2D medical image, and the plurality of subvascular regions Among these, it is possible to determine the sub-vascular region having the smallest distance from some region of the blood vessel. Accordingly, the matching unit 120 may determine the sub-vascular region having the smallest distance to the partial region of the blood vessel as the blood vessel region in the 3D medical image having the highest similarity with the partial region of the blood vessel. A more specific embodiment will be described with reference to FIG. 7.

According to an embodiment, the matching unit 120 may match the blood vessel region in the 3D medical image having the highest similarity with the partial region of the blood vessel in the 2D medical image to the 2D medical image. According to an embodiment, the matching unit 120 may determine the conversion information for matching the blood vessel region in the 3D medical image to a partial region of the blood vessel in the 2D medical image. An example of the transformation information may be a transformation matrix. According to one embodiment, the matching unit 120 is based on the information on the parallel or rotational movement that was performed for the sub-vascular region having the smallest distance to the partial region of the blood vessel among the plurality of sub-vascular region, A transformation matrix may be determined for matching sub-vascular regions in the 3D medical image to some regions of the blood vessels in the 2D medical image. That is, the matching unit 120 adds or subtracts an amount of change within a preset range for each value of the matrix representing the parallel movement or the rotational movement performed on the sub-vascular region, thereby making the blood vessel region in the 3D medical image two-dimensional. A transformation matrix can be determined for more precise registration with some regions of blood vessels in the medical image. Therefore, the matching unit 120 may match the blood vessel region in the 3D medical image having the highest similarity with the region of the blood vessel to the partial region of the blood vessel in the 2D medical image by using the determined transformation matrix. In addition, the matching unit 120 may generate a matching image in which blood vessel regions in the 3D medical image are matched to the 2D medical image.

In addition, according to an exemplary embodiment, the matching unit 120 may match a wider vessel region to a 2D medical image than a vessel region in a 3D medical image having the highest similarity with a partial region of the vessel according to a user's selection. have.

The

medical imaging apparatuses

100 and 200 may selectively determine a blood vessel region in a 3D medical image corresponding to a region of a blood vessel that is selectively contrasted, and generate a matched image, thereby allowing a 3D roadmap for correcting various movements of an object. ) Can be provided. In addition, since the

medical imaging apparatus

100 or 200 may express a partial region of the selectively contrasted blood vessel through a registration image, the

medical imaging apparatus

100 or 200 may improve the convenience of the procedure for the object.

2 is a block diagram of the medical imaging apparatus 200 according to another exemplary embodiment.

As illustrated in FIG. 2, the medical imaging apparatus 200 according to an embodiment may include an image acquirer 210, a matcher 220, a display 230, an inputter 240, and a storage 250. It may include. Since the contents described with reference to FIG. 1 may be applied to the image acquisition unit 210 and the matching unit 220, descriptions of overlapping contents will be omitted. In addition, each component included in the medical imaging apparatus 200 may be connected by various connection techniques 260 such as wired or wireless.

According to an exemplary embodiment, the display 230 may display a matched image generated by the matcher 220. For example, the display 230 may display a matched image, or display a user interface (UI) or a graphic user interface (GUI) related to function setting of the medical imaging apparatus 200.

The display unit 230 may include a liquid crystal display, a thin film transistor-liquid crystal display, an organic light-emitting diode, a flexible display, and a three-dimensional display. It may include at least one of a 3D display, an electrophoretic display. The medical imaging apparatus 200 may include two or more display units 230 according to the implementation form of the medical imaging apparatus 200.

According to an embodiment, the input unit 240 may receive a command for controlling the medical imaging apparatus 200 from a user. According to an exemplary embodiment, the input unit 240 may receive a command from the user to match a blood vessel region in the 3D medical image to the 2D medical image. In addition, according to an exemplary embodiment, the display 230 and the inputter 240 may provide a user with a user interface (UI) for manipulating the medical imaging apparatus 200. The display 230 may display a UI.

The storage unit 250 may store a 2D medical image or a 3D medical image acquired by the image acquirer 210, according to an exemplary embodiment. In addition, the matching image generated by the matching unit 220 may be stored.

FIG. 3 is a view for explaining an embodiment in which the

medical imaging apparatus

100 or 200 extracts a center line of a 3D blood vessel region or a 3D blood vessel region from a 3D medical image.

According to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may extract or separate a 3D blood vessel region 310 representing only a blood vessel region from a 3D medical image of an object. In addition, according to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may acquire the 3D blood vessel region 310 as a 3D medical image of the object.

In addition, the

medical imaging apparatus

100 or 200 may extract the center line 320 corresponding to the 3D blood vessel region 310 from the 3D blood vessel region 310 or the 3D medical image, according to an exemplary embodiment.

4 and 5 illustrate an embodiment in which the

medical imaging apparatus

100 or 200 divides a 3D blood vessel region into a plurality of subvascular regions.

According to an embodiment, the

medical imaging apparatus

100 or 200 may divide the 3D blood vessel region 310 into a plurality of

sub-vascular regions

412, 414, 416, 418, 420, and 422.

As illustrated in FIG. 5, the

medical imaging apparatus

100 or 200 may generate a graph 510 showing a connection relationship between branch points of respective blood vessels in the 3D blood vessel region 310 of FIG. 3. In addition, the

medical imaging apparatus

100 or 200 may generate a graph 510 indicating a connection relationship between branch points of respective blood vessels in the center line 320 corresponding to the 3D blood vessel region 310 of FIG. 3. That is, as shown in FIG. 5, the

medical imaging apparatus

100 or 200 determines 86 branch points of each blood vessel in the 3D blood vessel region 310 and generates a graph 510 indicating a connection relationship between the 86 branch points. Can be. Subsequently, the

medical imaging apparatus

100 or 200 may divide the graph 510 into a plurality of

regions

512, 514, 516, 518, 520, and 522 according to a predetermined criterion. According to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may provide an arbitrary area when the number of branch points in an area divided by a predetermined branch point or the sum of lengths between the branch points in an area is greater than a predetermined threshold value. May be determined as one region of the plurality of regions. Accordingly, the

medical imaging apparatus

100 or 200 may divide the graph 510 into a plurality of

regions

512, 514, 516, 518, 520 and 522. The

medical imaging apparatus

100 and 200 may include a plurality of three-dimensional blood vessel regions 310 corresponding to the graph 510. The

sub-vascular regions

412, 414, 416, 418, 420, and 422 may correspond to the

regions

512, 514, 516, 518, 520, and 522.

6 is a diagram illustrating an example in which the

medical imaging apparatus

100 or 200 separates a partial region of a blood vessel from a 2D medical image according to an exemplary embodiment.

The

medical imaging apparatus

100 or 200 may extract or separate a partial region 620 of the blood vessel from the 2D medical image 610 according to an exemplary embodiment. In addition, the

medical imaging apparatus

100 or 200 may extract the center line 630 corresponding to the partial region 620 of the blood vessel from the partial region 620 of the blood vessel.

FIG. 7 illustrates an embodiment in which the

medical imaging apparatus

100 or 200 determines a subvascular region having the highest similarity to a partial region of a blood vessel in a 2D medical image among a plurality of subvascular regions.

The

medical imaging apparatus

100 or 200 may extract

centerlines

712, 714, 716, 718, 720, and 722 from each of the plurality of

sub-vascular regions

412, 414, 416, 418, 420, and 422 of FIG. 4. That is, the

medical imaging apparatus

100 or 200 may extract

centerlines

712, 714, 716, 718, 720, and 722 corresponding to each of the plurality of

subvascular regions

412, 414, 416, 418, 420, and 422.

According to an embodiment, the

medical imaging apparatus

100 or 200 may determine a sub-vascular region corresponding to a partial region 620 of the blood vessel, and may include a center line 630 corresponding to the partial region 620 of the blood vessel and the plurality of sub-vascular vessels. The distance between the

centerlines

712, 714, 716, 718, 720, and 722 corresponding to each of the

regions

412, 414, 416, 418, 420, and 422 may be calculated. In addition, the

medical imaging apparatus

100 or 200 may perform parallel movement or rotational movement with respect to the

center lines

712, 714, 716, 718, 720, and 722 by a predetermined number of times by varying a numerical value within a preset range. Subsequently, the

medical imaging apparatus

100 or 200 may project each of the

center lines

712, 714, 716, 718, 720, and 722 that are parallel or rotated in a two-dimensional plane. Subsequently, the

medical imaging apparatus

100 or 200 may calculate the distance between each of the

centerlines

712, 714, 716, 718, 720, and 722 projected on the two-dimensional plane and the centerline 630 corresponding to the partial region 620 of the blood vessel by a predetermined number of times. The

imaging apparatus

100 or 200 may determine the center line 718 having the minimum distance from the center line 630 by comparing the distances calculated by a predetermined number of times. Therefore, the

medical imaging apparatus

100 or 200 may determine the sub-vascular region 418 corresponding to the center line 718 as the sub-vascular region most similar to the partial region 620 of the blood vessel.

In addition, according to an exemplary embodiment, the

medical imaging apparatus

100 or 200 generates a distance transform 705 for the center line 630 corresponding to a partial region 620 of the blood vessel, and converts the distance transform 705 and the

center lines

712, 714, 716, 718, 720, and 722. ) May facilitate calculation of the distance between the

centerlines

712, 714, 716, 718, 720, 722 and the centerline 630.

As described with reference to FIG. 7, the

medical imaging apparatus

100 or 200 according to an exemplary embodiment may include a sub-vessel as a blood vessel region within a three-dimensional medical image that is most similar to a partial region 620 of a blood vessel extracted from the two-dimensional medical image 610. Area 418 can be determined.

According to an embodiment, the

medical imaging apparatus

100 or 200 may match the sub-vascular region 418 to a partial region 620 of the blood vessel in the 2D medical image 610. Accordingly, the

medical imaging apparatus

100 or 200 may generate a registration image 810 in which the sub-vascular region 418 is matched to the 2D medical image 610.

According to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may determine a transformation matrix for matching the sub-vascular region 418 to a partial region 620 of the blood vessel in the 2D medical image 610. According to an embodiment, the

medical imaging apparatus

100 or 200 may determine a transformation matrix based on information on parallel movement or rotation movement that has been performed with respect to the center line 718. That is, the

medical imaging apparatus

100 or 200 subtracts the sub-vessel region 418 by subtracting a change amount within a preset range for each value of the matrix representing the parallel movement or the rotation movement performed with respect to the center line 718. A transformation matrix may be determined to more accurately match the partial region 620 of the blood vessel in the dimensional medical image 610. Therefore, the matching unit 120 may match the sub-vascular region 418 to the 2D medical image 610 using the determined transformation matrix.

9 is a diagram for describing a medical image processing method performed by the

medical imaging apparatus

100 or 200, according to an exemplary embodiment.

The method illustrated in FIG. 9 may be performed by each component of the

medical imaging apparatus

100 or 200 of FIG. 1 or 2, and overlapping descriptions thereof will be omitted.

In operation S910, the

medical imaging apparatus

100 or 200 acquires a 3D medical image and a 2D medical image representing blood vessels. According to an exemplary embodiment, the

medical imaging apparatus

100 or 200 performs a computed tomography angiography (CT angiography) or magnetic resonance imaging angiography (MRI angiography) on a subject, thereby displaying a three-dimensional representation of blood vessels in the subject in three dimensions. The medical image may be acquired. In addition, according to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may perform an X-ray angiography test on blood vessels in the object to acquire a 2D medical image representing the blood vessels in the object in two dimensions. Also, according to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may acquire a 3D medical image and a 2D medical image representing blood vessels from the outside. In addition, according to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may obtain a 3D medical image and a 2D medical image stored in advance from an internal memory.

In operation S920, the

medical imaging apparatus

100 or 200 determines a blood vessel region in the 3D medical image corresponding to a partial region of the blood vessel in the 2D medical image.

According to an embodiment, the

medical imaging apparatus

100 or 200 may separate or extract a 3D blood vessel region from a 3D medical image. That is, the

medical imaging apparatus

100 or 200 may separate or extract only a blood vessel region viewed in 3D from a 3D medical image. Subsequently, the

medical imaging apparatus

100 or 200 may divide the separated three-dimensional blood vessel region into a plurality of sub-vascular regions.

According to an embodiment, the

medical imaging apparatus

100 or 200 may generate a graph showing a connection relationship between branch points of respective blood vessels in the 3D blood vessel region. Subsequently, the

medical imaging apparatus

100 or 200 may divide the graph corresponding to the 3D blood vessel region into a plurality of regions according to a predetermined condition. An example of the predetermined condition may be a condition that the sum of the lengths of the branch points included in each of the plurality of areas is greater than a predetermined threshold. Accordingly, the

medical imaging apparatus

100 or 200 may divide the graph into a plurality of regions, and thus may divide the three-dimensional blood vessel region corresponding to the graph into a plurality of sub-vascular regions corresponding to the plurality of regions.

According to an embodiment, the

medical imaging apparatus

100 or 200 may separate or extract a partial region of a blood vessel from a 2D medical image. That is, the

medical imaging apparatus

100 or 200 may separate or extract only a portion of a blood vessel that appears in two dimensions in the two-dimensional medical image.

According to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may determine a sub-vascular region corresponding to a partial region of a blood vessel in the 2D medical image among a plurality of sub-vascular regions divided from the 3D blood vessel region. That is, the

medical imaging apparatus

100 or 200 may determine a subvascular region having the highest similarity to a partial region of the blood vessel among the plurality of subvascular regions.

According to an embodiment, the

medical imaging apparatus

100 or 200 may project centerlines of each of the plurality of sub vessels onto a two-dimensional plane. According to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may calculate a distance between centerlines of each of the plurality of subvascular regions projected on the 2D plane and a centerline of a partial region of the blood vessel. According to an embodiment, the

medical imaging apparatus

100 or 200 may calculate a distance closest to the centerline of the partial region of the blood vessel for each point constituting the centerline of the arbitrary sub-vascular region, and the medical imaging apparatus 100 or 200 ) May be determined as the distance between the centerline of any subvascular region and the centerline of some region of the vessel.

According to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may perform a parallel movement or a rotational movement with respect to the center line of an arbitrary sub-vascular region by a predetermined number of times by varying a numerical value within a preset range. Subsequently, the

medical imaging apparatus

100 or 200 may calculate the distance between the centerline of any sub-vascular region that is parallel or rotated and the centerline of the partial region of the blood vessel a predetermined number of times. The distance having the smallest value among the distances calculated by the set number of times may be determined as the distance between the centerline of any sub-vascular region and the center line of some region of the blood vessel.

According to an embodiment, the

medical imaging apparatus

100 or 200 may more easily calculate a distance between the centerline of each of the plurality of sub-vascular regions and the center line of the partial region of the blood vessel in the 2D medical image. A distance transform, such as a distance map or a distance field, may be generated. The distance transformation may be represented as an image according to an embodiment, and may include location information about the centerline of some regions of the blood vessel for each pixel in the image. Therefore, the

medical imaging apparatus

100 or 200 uses a distance transformation with respect to the centerline of the partial region of the blood vessel and a centerline of each of the plurality of subvascular regions, and thus, between the centerline of each of the plurality of subvascular regions and the centerline of the partial region of the blood vessel. Speed up calculations over distance.

According to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may calculate a distance between centerlines of each of the plurality of subvascular regions and a centerline of a portion of the blood vessel, and may determine the distance between the blood vessels among the plurality of subvascular regions. The sub-vascular region with the smallest distance to some region can be determined. Accordingly, the

medical imaging apparatus

100 or 200 may determine a sub-vascular region having the smallest distance to a partial region of the blood vessel as a blood vessel region in the 3D medical image having the highest similarity with the partial region of the blood vessel.

In operation S930, the

medical imaging apparatus

100 or 200 may match the blood vessel region with a portion of the blood vessel in the 2D medical image.

According to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may match the blood vessel region in the 3D medical image having the highest similarity with the partial region of the blood vessel in the 2D medical image to the 2D medical image. According to an embodiment, the

medical imaging apparatus

100 or 200 may determine transformation information for matching a blood vessel region in the 3D medical image to a partial region of the blood vessel in the 2D medical image. An example of the transformation information may be a transformation matrix. According to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may be configured to perform parallel movement or rotational movement based on information about a parallel movement or a rotational movement that has been performed with respect to a subvascular region having a minimum distance from a portion of a blood vessel among a plurality of subvascular regions. In addition, the transformation matrix for matching the sub-vascular region in the 3D medical image to a partial region of the blood vessel may be determined. That is, the

medical imaging apparatus

100 or 200 subtracts the amount of change within a preset range for each value of the matrix representing the parallel movement or the rotational movement performed with respect to the sub-vascular region, thereby reducing the blood vessel region in the 3D medical image by 2. A transformation matrix can be determined for more precise registration with some regions of blood vessels in the dimensional medical image. Accordingly, the

medical imaging apparatus

100 or 200 may match the blood vessel region in the 3D medical image having the highest similarity with the partial region of the blood vessel to the 2D medical image by using the determined transformation matrix. In addition, the

medical imaging apparatus

100 or 200 may generate a registration image in which blood vessel regions in the 3D medical image are matched to the 2D medical image.

In addition, according to an exemplary embodiment, the

medical imaging apparatus

100 or 200 may match a blood vessel region wider than a blood vessel region in a 3D medical image having the highest similarity with a portion of the blood vessel, to the 2D medical image according to a user's selection. Can be.

10 and 11 are views illustrating the X-ray apparatus 300 according to an embodiment.

The

medical imaging apparatuses

100 and 200 of FIGS. 1 and 2 may perform some or all of the functions performed by the X-ray apparatus 300 of FIGS. 10 and 11. The

image acquirers

110 and 210 of FIGS. 1 and 2 may correspond to at least one of the detector 108, the data acquisition circuit (DAS) 116, and the data transmitter 152 of FIGS. 10 and 11. . Also, the matching

units

120 and 220 of FIGS. 1 and 2 may correspond to the image processor 126 of FIG. 11. In addition, the display unit 230 of FIG. 2 may correspond to the display unit 153 of FIG. 11, the input unit 240 of FIG. 2 may correspond to the input unit 128 of FIG. 1, and the storage of FIG. 2. The unit 250 may correspond to the storage unit 124 of FIG. 11.

Referring to FIG. 10, the X-ray apparatus 300 may include a C-arm 102 having a C shape, and may continuously perform X-ray imaging for a predetermined time. An X-ray source 106 is provided at one end of the C-arm 102, and a detector 108 is provided at the other end of the C-arm 102. The C-arm 102 may connect the X-ray source 106 and the detector 108, and adjust the positions of the X-ray source 106 and the detector 108. Although not shown in FIG. 10, the C-arm 102 may be coupled to the ceiling, coupled to the floor, or coupled to both the ceiling and the floor. In addition, the X-ray apparatus 300 may further include a table 105 on which the object 10 may be located.

X-ray source 106 is configured to generate and irradiate X-rays. The detector 108 is configured to detect X-rays radiated from the X-ray source 106 and transmitted through the object 10. The medical image may be acquired based on the X-rays detected by the detector 108. In this case, the X-ray source 106 may rotate to radiate X-rays to the object 10. The X-ray source 106 may be rotated by the rotation of the C-arm 102, and the detector 108 may also detect X-rays passing through the object 10 while rotating together with the X-ray source 106.

The user may photograph the object 10 at various positions or at various angles by adjusting the positions of at least one of the C-arm 102 and the table 105. For example, the user may acquire a medical image by photographing the object 10 while rotating at least one of the C-arm 102 and the table 105 or moving up, down, left, and right. Accordingly, the user may more efficiently photograph the object 10 for a continuous time than the general fixed X-ray apparatus using the X-ray apparatus 300.

The X-ray apparatus 300 may be useful when it is necessary to acquire a plurality of X-ray images acquired in a continuous time or when an X-ray video should be obtained. For example, the X-ray apparatus 300 may be usefully used in medical procedures such as X-ray angiography, or surgery. If the doctor needs to examine the patient's patient precisely for the diagnosis of the vascular disease patient, the doctor continuously performs X-rays during the examination time. The vascular state of the patient is examined through a fluoroscopy image, which is an X-ray video obtained in real time. Therefore, in a medical procedure such as angiography, X-rays should be continuously irradiated to the subject during the procedure and a fluoroscopy image should be obtained.

For example, in the case of angiography, a guide wire may be installed at an object site and X-ray imaging may be performed, or X-ray imaging may be performed by injecting drugs using a thin needle or a catheter. You can proceed.

As another example, in the case of a surgical procedure, in performing a procedure by inserting a catheter, a stent, a needle, or the like into a body, a user such as a doctor should check whether the catheter is properly inserted into a target point of the subject. Therefore, the user may acquire a fluoroscopy image during the procedure, and proceed with the procedure while confirming the position of the target object such as a catheter through the obtained fluoroscopy image.

The X-ray apparatus 300 may include an Interventional X-ray, an Interventional Angiography C-arm X-ray, or a Surgical C-arm X-ray. have.

According to an embodiment, the X-ray apparatus 300 may acquire a 3D medical image representing 3D of blood vessels in the object. In addition, the X-ray apparatus 300 may perform an X-ray angiography test on blood vessels in the object to acquire a 2D medical image representing the blood vessels in the object in two dimensions. That is, the user may inject a contrast agent into the blood vessel of the object, and the X-ray apparatus 300 may perform an X-ray angiography test to acquire a 2D medical image showing a portion of the contrast medium in which the blood vessel is injected. . Also, the X-ray apparatus 300 may determine a blood vessel region in the 3D medical image corresponding to a partial region of the blood vessel in the 2D medical image. Subsequently, the X-ray apparatus 300 may match the blood vessel region in the 3D medical image to a partial region of the blood vessel in the 2D medical image.

Referring to FIG. 11, the X-ray apparatus 300 includes an X-ray source 106, a detector 108, and a C-arm 102 connecting the X-ray source 106 and the detector 108. In addition, the X-ray apparatus 300 may include a rotation driver 151, a data acquisition circuit 116, a data transmitter 152, a table 105, a controller 118, a storage 124, an image processor 126, and an input unit. 128, the display unit 153 and the communication unit 132 may be further included.

The object 10 may be located on the table 105. The table 105 according to some embodiments may move in a predetermined direction (eg, at least one of up, down, left, and right), and the movement may be controlled by the controller 118.

The X-ray source 106 and the detector 108 connected to the C-arm 102 and disposed to face each other have a predetermined field of view (FOV). If the X-ray source 106 and detector 108 are rotated by the C-arm 102, the FOV will change accordingly.

The X-ray apparatus 300 may further include an anti-scatter grid 114 positioned on the detector 108.

X-ray radiation that reaches the detector 108 includes attenuated primary radiation that forms a useful image, as well as scattered radiation that degrades the quality of the image. The anti-scattering grid 114 can be positioned between the patient and the detector (or photosensitive film) in order to transmit most of the main radiation and attenuate the scattered radiation.

For example, anti-scatter grids include strips of lead foil, solid polymer materials or solid polymers and fiber composite materials. It may be configured in the form of alternately stacked space filling material (interspace material) of. However, the shape of the anti-scattering grid is not necessarily limited thereto.

The C-arm 102 may receive a drive signal and power from the rotation driver 151 and rotate the X-ray source 106 and the detector 108 at a predetermined rotation speed.

The X-ray source 106 may generate and emit X-rays by receiving a voltage and a current from a power distribution unit (PDU) through a high voltage generator (not shown). When the high voltage generator applies a predetermined voltage (hereinafter referred to as a tube voltage), the X-ray source 106 may generate X-rays having a plurality of energy spectra corresponding to the predetermined tube voltage.

X-rays generated by the X-ray source 106 may be emitted in a predetermined form by a collimator 112.

The detector 108 may be positioned to face the X-ray source 106. The detector 108 may include a plurality of X-ray detection elements. The single X-ray detection element may form a single channel, but is not necessarily limited thereto.

The detector 108 may detect X-rays generated from the X-ray source 106 and transmitted through the object 10 and generate an electrical signal corresponding to the detected intensity of the X-rays.

The detector 108 may include an indirect method for converting radiation into light and a direct method detector for converting and detecting radiation into direct charge. The indirect detection unit may use a scintillator. In addition, the direct type detecting unit may use a photon counting detector. The data acquisition circuit 116 may be connected to the detector 108. The electrical signal generated by the detector 108 may be collected by the DAS 116. The electrical signal generated by the detector 108 may be collected by the data acquisition circuit 116 by wire or wirelessly. In addition, the electrical signal generated by the detector 108 may be provided to an analog / digital converter (not shown) through an amplifier (not shown).

Only some data collected from the detector 108 may be provided to the image processor 126 according to the slice thickness or the number of slices, or only some data may be selected by the image processor 126.

The digital signal may be provided to the image processor 126 through the data transmitter 152. The digital signal may be transmitted to the image processor 126 by wire or wirelessly through the data transmitter 152.

The controller 118 according to some embodiments may control the operation of each module included in the X-ray apparatus 300. For example, the controller 118 may include a table 105, a rotation driver 151, a collimator 112, a data acquisition circuit 116, a storage unit 124, an image processor 126, an input unit 128, and a display. Operations of the unit 153 and the communication unit 132 may be controlled.

The image processor 126 receives data (eg, raw data before processing) from the data acquisition circuit 116 through the data transmitter 152 to perform a process of pre-processing. Can be.

The preprocessing may include, for example, a process of correcting the sensitivity unevenness between the channels, a sharp reduction in signal strength, or a process of correcting the loss of a signal due to an X-ray absorber such as metal.

The data preprocessed by the image processor 126 may be referred to as raw data or projection data. Such projection data may be stored in the storage unit 124 together with photographing conditions (eg, tube voltage, photographing angle, etc.) when data is acquired.

The projection data may be a set of data values corresponding to the intensity of X-rays passing through the object. For convenience of description, the set of projection data acquired simultaneously at the same photographing angle for all channels is referred to as projection data set or measured data.

The storage unit 124 may include a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (SD, XD memory, etc.) and a RAM. ; Random Access Memory (Static Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory) magnetic memory, magnetic disk, optical disk It may include at least one type of storage medium.

In addition, the image processor 126 may acquire a reconstructed image of the object based on the acquired measurement data. The image processor 126 may obtain a reconstructed image obtained by imaging the ROI from the measured data. ROI is an area in which the X-ray apparatus 300 may reconstruct an image. Such a reconstructed image may be a 3D image. In other words, the image processor 126 may generate a 3D image of the object by using a cone beam reconstruction method based on the acquired measurement data.

External input for X-ray tomography conditions, image processing conditions, etc. may be received through the input unit 128. For example, X-ray tomography conditions may include a plurality of tube voltages, energy values of a plurality of X-rays, an imaging protocol selection, an image reconstruction method selection, an FOV region setting, an ROI region setting, a number of slices, a slice thickness, And image post-processing parameter settings. Also, the image processing condition may include a resolution of an image, attenuation coefficient setting for the image, a combination ratio setting of the image, and the like.

The input unit 128 may include a device for receiving a predetermined input from the outside. For example, the input unit 128 may include a microphone, a keyboard, a mouse, a joystick, a touch pad, a touch fan, a voice, a gesture recognition device, and the like.

The display unit 153 may display an image reconstructed by the image processor 126.

The transmission and reception of data, power, and the like between the above-described elements may be performed using at least one of wired, wireless, and optical communication.

The communication unit 132 may communicate with an external device, an external medical device, or the like through the server 134. Alternatively, the X-ray apparatus 300 may be connected to a workstation configured to control the X-ray apparatus 300 through the communication unit 132. This will be described later with reference to FIG. 12.

FIG. 12 is a diagram illustrating a configuration of the communication unit 133 of FIG. 11.

The communication unit 132 may be connected to the network 15 by wire or wirelessly to communicate with the external server 134, the medical device 136, the portable device 138, or the workstation 139. The communication unit 132 may exchange data with a hospital server or another medical device in a hospital connected through a PACS.

In addition, the communication unit 132 may perform data communication with the portable device 138 or the like according to a digital imaging and communications in medicine (DICOM) standard.

The communication unit 132 may transmit and receive data related to diagnosis of the object through the network 15. In addition, the communication unit 132 may transmit and receive a medical image obtained from the medical device 136, such as an MRI device, an X-ray device.

In addition, the communication unit 132 may receive a diagnosis history or a treatment schedule of the patient from the server 134 and use it for clinical diagnosis of the patient. In addition, the communication unit 132 may perform data communication not only with the server 134 or the medical device 136 in the hospital, but also with the portable device 138, the workstation 139, or the like of the user or the patient.

In addition, it is possible to send the equipment abnormality and quality control status information to the system administrator or service personnel through the network and receive feedback about it.

The workstation 139 may be located in a space physically separated from the X-ray apparatus 300. The X-ray apparatus 300 may be in a shield room and the workstation 139 may be in a console room. The shield room refers to a space in which the X-ray apparatus 300 is located to photograph an object, and may be variously referred to as a 'photography room', 'inspection room', or 'inspection room'. In addition, the console room is a space in which the user is located to control the X-ray apparatus 300 and means a space separated from the shield room. The console room and the shield room may be separated from each other through a shielding wall to protect the user from magnetic fields, radiation, RF signals, etc. transmitted from the shield room.

The device according to the embodiments described above includes a processor, a memory for storing and executing program data, a permanent storage such as a disk drive, a communication port for communicating with an external device, a touch panel, a key, a button, and the like. The same user interface device and the like. Methods implemented by software modules or algorithms may be stored on a computer readable recording medium as computer readable codes or program instructions executable on the processor. The computer-readable recording medium may be a magnetic storage medium (eg, read-only memory (ROM), random-access memory (RAM), floppy disk, hard disk, etc.) and an optical reading medium (eg, CD-ROM). ) And DVD (Digital Versatile Disc). The computer readable recording medium can be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion. The medium is readable by the computer, stored in the memory, and can be executed by the processor.

This embodiment can be represented by functional block configurations and various processing steps. Such functional blocks may be implemented in various numbers of hardware or / and software configurations that perform particular functions. For example, an embodiment may include an integrated circuit configuration such as memory, processing, logic, look-up table, etc. that may execute various functions by the control of one or more microprocessors or other control devices. You can employ them. Similar to the components that may be implemented as software programming or software elements, the present embodiment includes various algorithms implemented in C, C ++, Java (data structures, processes, routines or other combinations of programming constructs). It may be implemented in a programming or scripting language such as Java), an assembler, or the like. The functional aspects may be implemented with an algorithm running on one or more processors. In addition, the present embodiment may employ the prior art for electronic configuration, signal processing, and / or data processing. Terms such as "mechanism", "element", "means", "configuration" can be used widely and are not limited to mechanical and physical configurations. The term may include the meaning of a series of routines of software in conjunction with a processor or the like.

Specific implementations described in this embodiment are examples, and do not limit the technical scope in any way. For brevity of description, descriptions of conventional electronic configurations, control systems, software, and other functional aspects of the systems may be omitted. In addition, the connection or connection members of the lines between the components shown in the drawings by way of example shows a functional connection and / or physical or circuit connections, in the actual device replaceable or additional various functional connections, physical It may be represented as a connection, or circuit connections.

In this specification (particularly in the claims), the use of the term “above” and similar indicating terminology may correspond to both the singular and the plural. In addition, when a range is described, it includes the individual values which belong to the said range (if there is no description contrary to it), and it is the same as describing each individual value which comprises the said range in detailed description. Finally, if there is no explicit order or contrary to the steps constituting the method, the steps may be performed in a suitable order. It is not necessarily limited to the order of description of the above steps. The use of all examples or exemplary terms (eg, etc.) is for the purpose of describing technical concepts in detail and is not to be limited in scope by the examples or exemplary terms unless defined by the claims. In addition, one of ordinary skill in the art appreciates that various modifications, combinations and changes can be made depending on design conditions and factors within the scope of the appended claims or equivalents thereof.

Claims

Obtaining a 3D medical image representing a blood vessel and a 2D medical image representing the blood vessel;

Determining a blood vessel region in the 3D medical image corresponding to a portion of the blood vessel in the 2D medical image; And

And matching the blood vessel region with the partial region in the 2D medical image.
The method of claim 1,

The partial region,

At least one of a region to which a contrast agent is administered in a blood vessel in the 2D medical image, a region of interest of a blood vessel in the 2D medical image, or a region in which a target is located in a blood vessel in the 2D medical image Medical image processing method.
The method of claim 1,

The determining step,

Separating a 3D blood vessel region from the 3D medical image;

Separating the partial region from the 2D medical image; And

And among the plurality of sub-vascular regions divided from the three-dimensional blood vessel region, determining the sub-vascular region having the highest similarity to the partial region as the blood vessel region.
The method of claim 3, wherein

The determining step,

Performing parallel movement or rotational movement with respect to centerlines of each of the plurality of sub-vascular regions;

Calculating a distance between centerlines of each of the parallel and rotationally moved sub-vascular regions and a centerline of the partial region; And

And determining the sub-vascular region having the minimum distance from the partial region as the blood vessel region.
The method of claim 3, wherein

The determining step,

Projecting centerlines of each of the plurality of subvascular regions onto a two-dimensional plane;

Calculating a distance between centerlines of each of the projected plurality of subvascular regions and a centerline of the partial region; And

And determining the sub-vascular region having the minimum distance from the partial region as the blood vessel region.
The method of claim 5, wherein

The step of calculating the distance,

Generating a distance transform with respect to a centerline of the partial region; And

And calculating a distance between centerlines of each of the projected plurality of subvascular regions and a centerline of the partial region by using the distance transformation.
The method of claim 1,

The matching step,

Determining 3D transformation information for matching the vessel region with the partial region; And

And matching the blood vessel region to the partial region in the 2D medical image based on the 3D transformation information.
The method of claim 1,

Storing an image in which the vessel region is matched to the partial region in the 2D medical image; And

And displaying the matched image.
The method of claim 1,

The 3D medical image is an image obtained through CT angiography before the procedure for the subject, and the 2D medical image is obtained through X-ray angiography during the procedure for the subject. A medical image processing method, which is an image obtained.
An image acquisition unit configured to acquire a 3D medical image representing a blood vessel and a 2D medical image representing the blood vessel; And

And a matching unit for determining a blood vessel region in the 3D medical image corresponding to the partial region of the blood vessel in the 2D medical image, and matching the blood vessel region to the partial region in the 2D medical image.
The method of claim 10,

The partial region,

At least one of a region to which a contrast agent is administered in a blood vessel in the 2D medical image, a region of interest of a blood vessel in the 2D medical image, or a region in which a target is located in a blood vessel in the 2D medical image Medical imaging device.
The method of claim 10,

The matching part,

Separation of the three-dimensional blood vessel region from the three-dimensional medical image, Separation of the partial region from the two-dimensional medical image, Among the plurality of sub-vascular regions divided from the three-dimensional blood vessel region, the most similar to the partial region And determining a sub-vascular region as the blood vessel region.
The method of claim 12,

The matching part,

Performing parallel or rotational movement with respect to centerlines of each of the plurality of sub-vascular regions, and a distance between centerlines of each of the parallel and rotationally moved sub-vascular regions and a centerline of the partial region And calculating a sub-vascular region having the smallest distance from the partial region as the blood vessel region.
The method of claim 12,

The matching part,

Projecting centerlines of each of the plurality of subvascular regions on a two-dimensional plane, calculating a distance between centerlines of each of the projected plurality of subvascular regions and a centerline of the partial region, And determining the sub-vascular region having the minimum distance from the partial region as the blood vessel region.
A computer-readable recording medium having recorded thereon a program for executing the method of claim 1 on a computer.