JP2004313736A - Apparatus, method and program for medical image processing - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an apparatus, a method and a program for medical image processing capable of extracting a tubular tissue such as a blood vessel exactly from a medical image. <P>SOLUTION: An image processing apparatus 300 acquires three-dimensional data from a modality 100 and designates the starting point and the end point of a blood vessel to be extracted. The image processing apparatus 300 designates cross sectional regions of the blood vessel sequentially from the starting point. The image processing apparatus 300 sequentially acquires, at each of the designated cross sectional regions of the blood vessel, the areas of images that appear in response to the change of the threshold values. The image processing apparatus 300 images a cross section of the blood vessel at each of the cross sectional regions on the basis of acquired rate of change of the image areas. The image processing apparatus 300 finds the center of the each imaged cross section of the blood vessel and acquires a three-dimensional path that designates the longitudinal center line of the subject blood vessel. The image processing apparatus 300 generates various kinds of images that show the subject blood vessel on the basis of the acquired three-dimensional path and displays the list of the images on a display apparatus. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to a medical image processing apparatus, a medical image processing method, and a program for generating a three-dimensional medical image used for image diagnosis and the like, and particularly to a medical image processing apparatus suitable for displaying a tubular tissue such as a blood vessel, The present invention relates to a medical image processing method and a program.

  2. Description of the Related Art Conventionally, for example, image diagnosis in which a tomographic (slice) image of a human body is captured by a modality (imaging apparatus) such as a CT scanner or an MRI apparatus to diagnose a disease or the like has been performed. In addition, a method of generating a three-dimensional image of a predetermined organ or organ from a captured tomographic image and performing a diagnosis has been established, which contributes to precise and accurate diagnosis. In particular, a diagnosis using a three-dimensional image of a coronary blood vessel around the heart is useful for early detection of a heart disease and the like.

  In such three-dimensional image diagnosis, diagnosis is often performed by extracting an observation target region. In this case, a predetermined region is generally extracted by a method called “segment division”. . However, for example, when segmenting a tubular tissue such as a blood vessel (particularly a coronary blood vessel around the heart), it has been difficult to extract only a target blood vessel.

  A technique for segmenting a vascular tissue is described in, for example, Patent Document 1. Here, a “binary mask” composed of a pixel value indicating a region of interest (ie, a target vascular tissue) and a pixel value indicating a region outside the region of interest is formed to distinguish vascular tissue from other tissues. ing.

  In the method using a binary mask as described above, once the pixel value indicating the target tissue is determined, it is determined based on the value. In this case, if there is only the target blood vessel in the discrimination area, the extraction is performed without any problem. However, usually, other tissues (blood vessels, organs, organs, and the like) are often close to each other. Particularly when targeting coronary vessels around the heart, the heart and many other vessels are in close proximity. Since the constituents of these nearby objects are almost the same as the target blood vessel, the pixel values indicating them are also similar. When such similar pixel values are close to each other, the binary mask method may process these values as one value, and the target blood vessel cannot be accurately extracted. Was.

  Also, when coronary blood vessels generated from the heart are imaged based on CT values acquired by an imaging device such as a CT scanner, generally, the brightness of the image gradually decreases as the blood vessels extend from the blood vessel generation point. . In other words, it can be said that the approximation that the pixel value transitions substantially linearly according to the distance from the blood vessel occurrence point is established. According to this characteristic, a method of extracting a target blood vessel using a “multi-value mask” that linearly transitions and applies pixel values from a blood vessel generation portion to the extraction end has been considered. However, when the heart or another blood vessel is close to the target blood vessel or when there is an abnormal site on the blood vessel, the pixel value indicating the target blood vessel does not simply transition linearly. Therefore, even if an image is formed simply by linearly transitioning pixel values, an image in which the target blood vessel and a nearby object are combined or the target blood vessel is cut may be an image that can contribute to accurate diagnosis. It was difficult to get.

In addition, for example, Patent Literature 2 discloses a method of detecting a blood vessel part by detecting an average density near a point of interest, but in a case where a heart or another blood vessel is close to a target blood vessel. However, it is difficult to accurately extract a blood vessel part even by such a method because a useful concentration value cannot be obtained.
JP-A-2002-282235 (pages 4 to 5) JP-A-8-89501 (page 6)

  The present invention has been made in view of the above circumstances, and has as its object to provide a medical image processing apparatus, a medical image processing method, and a program capable of accurately extracting a tubular tissue such as a blood vessel.

In order to achieve the above object, a medical image processing apparatus according to a first aspect of the present invention includes:
A medical image processing apparatus that generates a medical image using three-dimensional volume data indicating the inside of a living body,
A cross-sectional area specifying unit that specifies a plurality of areas including a cross section of a predetermined tubular tissue indicated by the three-dimensional volume data;
Using the three-dimensional volume data included in each cross-sectional area specified by the cross-sectional area specifying unit, an imaging unit that images a cross-section of the tubular tissue included in the cross-sectional area,
A center specifying unit that specifies three-dimensional volume data indicating a center position of an image indicating a cross section of the tubular tissue;
A center line specifying unit that specifies the three-dimensional volume data indicating the longitudinal center line of the tubular tissue based on the three-dimensional volume data indicating the center position of the tube cross section in each cross-sectional area specified by the center specifying unit; ,
It is characterized by having.

In order to achieve the above object, a medical image processing apparatus according to a second aspect of the present invention includes:
A medical image processing apparatus that generates a medical image using three-dimensional volume data indicating the inside of a living body,
At a plurality of positions on a predetermined tubular tissue indicated by the three-dimensional volume data, an orthogonal cross-sectional area designation that is orthogonal to the longitudinal direction of the tubular tissue at each position and specifies a region including a cross section of the tubular tissue at the position Department and
Using the three-dimensional volume data included in each orthogonal cross-sectional area specified by the orthogonal cross-sectional area specifying unit, an imaging unit that images a cross section of the tubular tissue included in the orthogonal cross-sectional area,
A center specifying unit that specifies three-dimensional volume data indicating a center position of an image indicating a cross section of the tubular tissue;
A center line specifying unit that specifies the three-dimensional volume data indicating the longitudinal center line of the tubular tissue based on the three-dimensional volume data indicating the center position of the tube cross section in each orthogonal cross section area specified by the center specifying unit. When,
It is characterized by having.

In order to achieve the above object, a medical image processing device according to a third aspect of the present invention includes:
A medical image processing apparatus that generates a medical image using three-dimensional volume data indicating the inside of a living body,
A three-dimensional region specifying unit that specifies a predetermined three-dimensional region at a plurality of positions on a predetermined tubular tissue indicated by the three-dimensional volume data;
An imaging unit configured to image a cross section of the tubular tissue included in the three-dimensional region, using the three-dimensional volume data included in each of the three-dimensional regions specified by the three-dimensional region specification unit;
A center specifying unit that specifies three-dimensional volume data indicating a center position of an image indicating a cross section of the tubular tissue;
A center line specifying unit that specifies the three-dimensional volume data indicating the longitudinal center line of the tubular tissue based on the three-dimensional volume data indicating the center position of the tube cross section specified by the center specifying unit;
It is characterized by having.

In the medical image processing apparatus,
The three-dimensional volume data may include at least three-dimensional coordinate information and characteristic information indicating a predetermined characteristic at each coordinate indicated by the three-dimensional coordinate information. In this case,
It is preferable that the imaging unit visualizes a cross section of the tubular tissue on an image by imaging using the characteristic information corresponding to a predetermined condition.

The imaging unit,
A condition changing unit that changes the predetermined condition;
An image attribute detection unit that detects an image attribute that changes according to the condition change,
Based on the detected change of the image attribute, it is preferable that the apparatus further comprises an manifestation determining unit that determines whether or not the cross section of the tubular tissue has been manifested on the image.
in this case,
The image attribute may indicate an area of the image,
The image attribute detection unit,
Detecting an image area that changes in accordance with the condition change, and detecting a change in the image area in accordance with the condition change, based on the detected area;
It is preferable that the manifestation determination unit determines whether or not a cross section of the tubular tissue has been manifested on an image based on the detected area change.

  The manifestation determination unit is configured such that when the image appearing at the center of the cross-sectional area falls within the cross-sectional area, and when the area change is maximized, the cross-section of the tubular tissue is visualized on the image. It is desirable to determine that it has been done.

The orthogonal cross-sectional area designating section,
A provisional direction determination unit that provisionally determines the traveling direction for specifying the next orthogonal cross-sectional area,
Based on the center position of the tubular tissue specified in the orthogonal cross-sectional area specified immediately before, based on the provisional direction determined by the provisional direction determination unit, parallel to the longitudinal direction of the tubular tissue in the orthogonal cross-sectional area, A parallel section area designating section for designating one or more areas including a longitudinal section of the tubular tissue;
A traveling direction determining unit that detects a center position of the longitudinal section included in the designated parallel sectional region, and determines a traveling direction for designating a next orthogonal sectional region based on the detected center position; , Is preferably further provided, in this case,
A region orthogonal to the traveling direction determined by the traveling direction determination unit can be designated as the next orthogonal cross-sectional region.

  Further, the three-dimensional region specifying unit can determine the position of the next three-dimensional region to be specified based on the three-dimensional volume data indicating the center line of the tubular tissue specified by the center line specifying unit. .

It is desirable that the center line specifying unit specifies the center line of the tubular tissue as three-dimensional path data. In this case,
It is preferable that the image processing apparatus further includes an image creating unit that creates an image indicating the tubular tissue based on the three-dimensional path data specified by the center line specifying unit.

in this case,
The image creation unit,
Create a plurality of types of images showing the tubular tissue, an image calculation unit that calculates the relative positional relationship between each image,
A plurality of created images are displayed in a list on a predetermined display device, and the positional relationships on each display image are associated with each other based on the relative positional relationship between the images calculated by the image calculation unit. And a display control unit for displaying.

In order to achieve the above object, a program according to a fourth aspect of the present invention includes:
A computer is caused to function as the medical image processing apparatus.

  According to such an apparatus, when generating a three-dimensional medical image in image diagnosis or the like, by extracting the center line (for example, three-dimensional path data) of a tubular tissue such as a blood vessel, the accurate shape of the tubular tissue can be obtained. Images can be generated. In addition, since the coordinate information of the center line can be specified, a plurality of types of images (for example, three-dimensional images, two-dimensional path data, two-dimensional images (MPR images and CPR images), etc.) showing the target tubular tissue can be specified. Can be displayed in a list on the display device in association with each other.

In order to achieve the above object, a medical image processing method according to a fifth aspect of the present invention includes:
Using a computer, a medical image processing method for generating an image showing a tubular tissue inside the living body,
Obtaining three-dimensional volume data indicating the inside of the living body;
Based on an arbitrary point specified on the tubular tissue indicated by the three-dimensional volume data, sequentially specifying a cross-sectional area including a cross section of the tubular tissue along the tubular tissue;
Detecting a center position of the tubular tissue in each of the designated cross-sectional areas,
Acquiring three-dimensional path data indicating a center line of the tubular tissue based on the detected center position;
Generating and displaying an image indicating the tubular tissue based on the acquired three-dimensional path data;
It is characterized by having.

In the medical image processing method,
The step of designating the cross-sectional area includes:
Based on the designated arbitrary point, it is possible to specify the cross-sectional area by sequentially specifying a region orthogonal to the longitudinal direction of the tubular tissue along the tubular tissue,
Or
The sectional area can be designated by sequentially designating a predetermined three-dimensional area based on the designated arbitrary point along the tubular tissue.

In the medical image processing method,
The step of detecting the center position includes:
Setting a threshold value for predetermined characteristic information included in the three-dimensional volume data;
Imaging each cross-sectional area using characteristic information corresponding to the set threshold,
By changing the threshold, it is desirable to further comprise the step of making a tube cross section of the tubular tissue appear on an image, and in this case,
By detecting the center position of the image showing the revealed tube section, the center position of the tube section can be detected.

in this case,
The step of detecting the center position is based on a change in an image area that changes in accordance with the change in the threshold value, and it is preferable to determine whether or not a cross section of the tubular tissue has been exposed on the image,
further,
The image appearing at the center of the cross-sectional area is within the cross-sectional area, and, when the change in area according to the change in the threshold is maximized, the cross-section of the tubular tissue has become apparent. It is desirable to determine.

In the medical image processing method,
The step of generating and displaying an image indicating the tubular tissue includes generating a plurality of types of images of the tubular tissue based on the three-dimensional path data, and displaying all or any of the generated images in a predetermined manner. It is desirable to list on the device, in this case,
In the step of generating and displaying the image indicating the tubular tissue, the positional relationship on each of the images displayed in the list can be associated with each other and dynamically linked on the display image.

  In this case, in the step of generating and displaying the image indicating the tubular tissue, at least a three-dimensional image and a two-dimensional image of the tubular tissue can be created as the plurality of types of images.

  Here, for example, a CPR (Curved Planer Reconstruction) image may be created as the two-dimensional image. In this case, at least the positional relationship between the created three-dimensional image and the created CPR image is displayed in association with each other. Is desirable.

Also,
Generating and displaying an image showing the tubular tissue,
Converting the three-dimensional path data into two-dimensional path data;
Preferably, the method further comprises associating the three-dimensional path data with the converted two-dimensional path data.
It is desirable to display at least a list of images based on the three-dimensional path data and images based on the converted two-dimensional path data.

  Further, predetermined supplementary information may be acquired and displayed as a list together with the generated images.

  According to such a method, when generating a three-dimensional medical image in image diagnosis or the like, by extracting the center line (for example, three-dimensional path data) of a tubular tissue such as a blood vessel, an accurate shape of the tubular tissue is extracted. Images can be generated. In addition, since the coordinate information of the center line can be specified, a plurality of types of images (for example, three-dimensional images, two-dimensional path data, two-dimensional images (MPR images and CPR images), etc.) showing the target tubular tissue can be used. ) Can be displayed in a list on the display device in association with each other.

In order to achieve the above object, a program according to a sixth aspect of the present invention includes:
The present invention is characterized by causing a computer to execute each step of the medical image processing method.

  According to the present invention, in generating a medical image, a tubular tissue such as a blood vessel can be accurately extracted, and a plurality of types of images representing the tubular tissue can be displayed as a list in association with each other.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the following embodiment, a case where the present invention is applied to three-dimensional image diagnosis in a predetermined medical facility (hereinafter, referred to as “medical facility H”) will be described as an example.

  FIG. 1 is a diagram illustrating a configuration of an image diagnostic system according to an embodiment of the present invention. As illustrated, the diagnostic imaging system 1 according to the present embodiment includes a communication network 10, a modality 100, a control terminal 200, and an image processing device 300.

  The communication network 10 is a communication network that interconnects the control terminal 200 and the image processing apparatus 300 in the medical facility H and mediates information transmission between them, such as DICOM (Digital Imaging and Communications in Medicine). Mediating information transmission based on a predetermined communication protocol.

  Next, the modality 100 will be described. The modality 100 is an imaging device that images the inside of a human body, and is, for example, a CT scanner (computer tomography device), helical CT, MRI (magnetic resonance imaging device), PET (positron tomography device), or the like. In the present embodiment, a CT scanner that captures a tomographic image of the inside of a human body using X-rays is adopted as the modality 100.

  In the present embodiment, the modality 100 (CT scanner) is controlled by a control terminal 200 to be described later, and a tomographic image (inside a living body) of a patient, a patient, or the like (hereinafter, referred to as a “patient”). (Slice). Here, in the present embodiment, since a CT scanner is employed as the modality 100, information indicating a tomographic image includes a CT value, which is an X-ray absorption coefficient, and the like. The modality 100 and the control terminal 200 are connected based on a predetermined medical image communication standard such as DICOM (Digital Imaging and Communications in Medicine).

  Next, the control terminal 200 will be described. The control terminal 200 includes a predetermined information processing device such as a workstation, controls the operation of the connected modality 100, and obtains captured image data (original data) obtained by imaging by the modality 100. The configuration of the control terminal 200 will be described with reference to FIG.

  FIG. 2 is a block diagram showing a configuration of the control terminal 200. As shown, the control terminal 200 includes a control unit 210, a communication control unit 220, an input control unit 230, an output control unit 240, a program storage unit 250, and a storage unit 260.

  The control unit 210 includes, for example, a CPU (Central Processing Unit) and a predetermined storage device (RAM (Random Access Memory)) serving as a work area, and controls each unit of the control terminal 200. Each process described below is executed based on a predetermined operation program stored in the program storage unit 250.

  The communication control unit 220 includes, for example, a predetermined communication device such as a predetermined NIC (Network Interface Card), connects the control terminal 200 to the modality 100 and the communication network 10, and connects the modality 100 and the image processing device 300 to each other. Perform communication.

  The input control unit 230 is connected to a predetermined input device 23 such as a keyboard or a pointing device, receives an instruction to the control unit 210 input from the input device 23, and transmits the instruction to the control unit 210.

  The output control unit 240 is connected to a predetermined output device 24 such as a display device or a printer, and outputs the processing result of the control unit 210 to the output device 24 as needed.

The program storage unit 250 includes a predetermined storage device such as a hard disk device or a ROM (Read Only Memory), and stores various operation programs executed by the control unit 210. The operation program stored in the program storage unit 250 includes, in addition to an arbitrary OS (Operating System: basic software) that controls the basic operation of the control terminal 200, a program for realizing each process described later in cooperation with the OS. It is assumed that the following operation programs (1) and (2) are stored. Processing by the control terminal 200 described later is realized by the control unit 210 executing these operation programs.
(1) “Modality control program”: a program for controlling the modality 100 (2) “Communication program”: a program for controlling the communication control unit 220 to perform communication with the modality 100 and communication via the communication network 10

  The storage unit 260 includes, for example, a storage device such as a RAM (Random Access Memory) and a hard disk device, and stores captured image data acquired from the modality 100.

  Here, the “captured image data” (original data) obtained from the modality 100 indicates “three-dimensional volume data” of the captured area. The three-dimensional volume data includes coordinate system information in the area and characteristic information in each coordinate. “Characteristic information” is information that, when used for image generation, indicates characteristics (for example, lightness, saturation, color tone, etc.) of pixels (pixels, voxels) constituting the image. In the present embodiment, since a “CT scanner” is used as the modality 100, “CT value” is used as the characteristic information. Here, the “CT value” is a value indicating the X-ray absorption coefficient. When an image is generated using the CT value as a pixel value, a difference in CT value appears as a difference in brightness on the image. Accordingly, by using the “captured image data” acquired from the modality 100, for example, a tomographic image (slice image) as shown in FIG. 3 can be obtained.

  Such a tomographic image can be captured as a stack of a plurality of parallel two-dimensional images as illustrated, and can also be captured as one three-dimensional area in which these are integrated. That is, not only can each of the stacked two-dimensional images be extracted, but also an arbitrary region can be designated from the entire three-dimensional region. Here, as a method of designating an arbitrary plane, for example, a technique such as MPR (Multi Planer Reconstruction) is known. That is, as shown in FIG. 4A, an arbitrary plane in the three-dimensional volume data can be designated. As a method of specifying an arbitrary curved surface, for example, a method such as CPR (Curved Planer Reconstruction) is known. That is, as shown in FIG. 4B, an arbitrary curved surface in the three-dimensional volume data can be designated.

  Next, the image processing apparatus 300 will be described. The image processing device 300 includes, for example, a predetermined information processing device such as a workstation, and generates a three-dimensional diagnostic image (medical image) using captured image data (three-dimensional volume data) acquired from the control terminal 200. Is what you do. The configuration of the image processing device 300 will be described below with reference to FIG.

  FIG. 5 is a block diagram illustrating a configuration of the image processing apparatus 300. As illustrated, the image processing device 300 includes a control unit 310, a communication control unit 320, an input control unit 330, an output control unit 340, a program storage unit 350, and an image storage unit 360. .

  The control unit 310 includes, for example, a CPU (Central Processing Unit) and a predetermined storage device (RAM (Random Access Memory) or the like) serving as a work area, and controls each unit of the image processing device 300. , Based on a predetermined operation program stored in the program storage unit 350.

  The communication control unit 320 includes a predetermined communication device such as a predetermined NIC (Network Interface Card), connects the image processing device 300 to the communication network 10, and performs communication with the control terminal 200 and the like.

  The input control unit 330 is connected to a predetermined input device 33 such as a keyboard or a pointing device, and receives an instruction to the control unit 310, information recorded in each database, and the like input from the input device 33. The information is transmitted to the control unit 310.

  The output control unit 340 is connected to a predetermined output device 34 such as a display device or a printer, and outputs a processing result of the control unit 310 to the output device 34 as needed.

The program storage unit 350 is configured from a predetermined storage device such as a hard disk device or a ROM (Read Only Memory), and stores various operation programs executed by the control unit 310. The operation program stored in the program storage unit 350 includes, in addition to an arbitrary OS (Operating System: basic software) that controls the basic operation of the image processing apparatus 300, various processes described later in cooperation with the OS. It is assumed that the following operation programs (1) to (3) are included. The processing by the image processing device 300 described later is realized by the control unit 310 executing these operation programs.
(1) “Communication program”: a program that controls the communication control unit 320 and communicates with the control terminal 200 and the like via the communication network 10 (2) “DB control program”: a program (3) that controls the image storage unit 360 ) “Image processing program”: a program for performing image processing on captured image data acquired from the control terminal 200

  The image storage unit 360 includes, for example, a rewritable storage device such as a semiconductor storage device or a hard disk device, and stores data acquired by each process described later, a generated three-dimensional diagnostic image, and the like.

  Hereinafter, each process in the present embodiment will be described with reference to the drawings. In the present embodiment, the center line of a desired blood vessel is extracted from the three-dimensional volume data acquired by the modality 100 by the diagnostic imaging system 1 to which the present invention is applied, and an image indicating the blood vessel is generated. And

  FIG. 6 is a flowchart for explaining “blood vessel image generation processing” for generating a blood vessel image in the image diagnostic system 1 to which the present invention is applied. As shown in the figure, in generating a blood vessel image in the image diagnostic system 1, “imaging processing” (step S100), “blood vessel extraction processing” (step S300), and “medical image generation / display processing” (step S500) are sequentially performed. Be executed. Hereinafter, the details of each of these processes will be described with reference to the drawings.

  First, the “imaging processing” according to the present embodiment will be described with reference to the flowchart shown in FIG. This processing is for acquiring a tomographic image (slice) inside the human body of the examinee or the like in cooperation with the modality 100 and the control terminal 200. The operation will be mainly described below mainly on the operation of the control terminal 200.

  In executing the imaging operation, first, predetermined imaging condition information is set in the control terminal 200 (step S101). Here, various imaging conditions such as designation of an imaging target area and the use of a contrast agent are set.

  The control terminal 200 controls the modality 100 according to the imaging conditions set in step S101 (step S102). That is, the modality 100 performs an imaging operation based on the imaging conditions under the control of the control terminal 200. As a result, the modality 100 acquires captured image data (three-dimensional volume data) in the set imaging region.

  When the imaging operation of the modality 100 ends, the control terminal 200 acquires captured image data from the modality 100 (step S103), stores the data in the storage unit 260 (step S104), and ends the process.

  Next, “blood vessel extraction processing” according to the present embodiment will be described with reference to the flowchart shown in FIG. In this processing, the center line of a desired blood vessel is extracted as three-dimensional path data using the image data acquired in the “imaging processing” by the image processing apparatus 300. In the present embodiment, an example in which a coronary blood vessel near the heart is to be extracted will be described below.

  First, the image processing apparatus 300 acquires target captured image data (three-dimensional volume data) from the control terminal 200 via the communication network 10 (step S301).

  Next, the control unit 310 displays a two-dimensional image based on the captured image (three-dimensional volume data) acquired in step S301 on the output device 34 (display device), and extracts a blood vessel to be extracted (hereinafter, “target blood vessel Vt”). ") Is specified (step S302). Here, an operator such as a doctor operates the input device 33 to specify an extraction start point and an extraction end point on the displayed two-dimensional image.

  FIG. 9A shows an example of the two-dimensional image displayed here. Here, an image showing an arbitrary two-dimensional plane in the imaging region obtained by the MPR or the like is displayed on the output device 34. That is, by displaying light and shade based on the difference in CT values included in the three-dimensional volume data, the region is imaged. Here, the image processing apparatus 300 changes the display position and the angle as needed by displaying the three-dimensional volume data corresponding to the position and the direction specified by the operation of the input device 33 by the operator. When a blood vessel is to be imaged, a contrast agent is usually used to increase the CT value of blood, and as a result, the blood vessel portion is displayed relatively bright as shown in FIG. . The operator operates the input device 33 to change the display screen so that the blood vessel cross section at the extraction start point of the target blood vessel Vt is displayed. The operator uses the input device 33 to specify the center of the displayed cross section (hereinafter, referred to as “start point SP”). Similarly, the center of the cross section at the extraction end point (hereinafter, referred to as “end point EP”) is designated.

  When the start point SP is specified in step S302, the control unit 310 of the image processing apparatus 300 specifies the three-dimensional coordinates. Then, based on the specified coordinate values, a region in which the cross section of the starting point SP is located at the center, and a region perpendicular to the longitudinal direction of the target blood vessel Vt at that position (hereinafter, referred to as an “orthogonal cross-sectional region SR”) Is specified (step S303).

Here, FIGS. 9B and 9C show examples of the positional relationship between each point specified in step S302, the target blood vessel Vt, and the orthogonal cross-sectional area SR specified in step S303. FIG. 9B is a diagram schematically showing the positional relationship between the target blood vessel Vt, the designated start point SP and end point EP, and the orthogonal cross-sectional area SR ₀ designated by the start point SP. ) is a schematic view showing the position of the target vessel Vt in the cross section perpendicular region SR _0. When the start point SP · end point EP on the target vessel Vt is specified (FIG. 9 (b)), the cross section perpendicular to region SR ₀ as the start point SP is located at the center is designated (FIG. 9 (c)).

In the present embodiment, the orthogonal cross-sectional area SR is sequentially designated from the start point SP to the end point EP by the processing described later. Therefore, the orthogonal cross-sectional area specified by the start point SP position is referred to as “orthogonal cross-sectional area SR ₀ ”, and the orthogonal cross-sectional area specified by the end point EP is referred to as “orthogonal cross-sectional area SR _n ”. That is, the orthogonal cross-sectional areas SR _{0 to} SR _n are sequentially designated by the processing described later.

After holding the coordinate values of the start point SP and the end point EP specified in step S302 in a predetermined storage area such as a work area, the control unit 310 moves in any direction based on the positions of the start point SP and the end point EP. It is determined whether to extract the target blood vessel Vt. Then, based on the discriminated direction (traveling direction), either surface traveling direction side of the cross section perpendicular to region SR ₀ (hereinafter referred to as "main surface") to determine whether it is. The control unit 310 determines a direction perpendicular to the determined main surface as a “provisional traveling direction” (step S304). The provisional traveling direction is determined in each of the orthogonal cross-sectional areas SR _{0 to} SR _n by the following processing. Therefore, in the following description, the provisional traveling directions corresponding to the respective orthogonal cross-sectional areas SR _{0 to} SR _n are described as “provisional directions DirA _{0 to} DirA _n ”.

That is, in step S304, the provisional direction DirA ₀ as shown in FIG. 9B is determined.

When the provisional direction is determined, the control unit 310, based on the determined provisional direction, determines the next specified orthogonal cross-sectional area SR (here, the orthogonal cross-sectional area SR ₁ that is the area following the orthogonal cross-sectional area SR ₀ ). Is performed (step S320) to determine the designated position. The “traveling direction determination process” will be described with reference to the flow shown in FIG.

The control unit 310 starts from the start point SP specified in step S302, and is parallel to the provisional direction (here, the provisional direction DirA ₀ ), and includes two regions (hereinafter, referred to as “intersections”) including the longitudinal section of the target blood vessel Vt at the position. One is referred to as “parallel cross-sectional area PR1” and the other is referred to as “parallel cross-sectional area PR2” (step S321). In this embodiment, each time the orthogonal cross-sectional area SR is sequentially specified, the parallel cross-sectional areas PR1 and PR2 are also specified by the following processing. Therefore, hereinafter, the orthogonal cross-sectional area SR ₀ to SR _n each parallel sectional areas corresponding to the respective "parallel sectional area PR1 ₀ ~PR1 _n", referred to as "parallel sectional area PR2 ₀ ~PR2 _n". Schematically shows the positional relationship between the parallel sectional area PR1 _0, PR2 ₀ in FIG. 11.

11 (a) is a parallel sectional area PR1 _0, the positional relationship between the cross section perpendicular to region SR ₀ and the starting point SP schematically shown, FIG. 11 (b), the parallel sectional area PR2 _0, orthogonal cross-sectional area SR ₀ and a positional relationship between the start point SP shown schematically, FIG. 11 (c), the cross section perpendicular region SR _0, in which the positional relationship between the parallel sectional area PR1 _0, PR2 ₀ shown schematically.

Due to the perpendicular direction to provisional direction DirA ₀ on the main surface of the orthogonal cross-section area SR _0, as shown in FIG. 11 (a) ~ (c) , parallel sectional area PR1 ₀ and PR2 ₀ also, the cross section perpendicular region SR ₀ Perpendicular to the main surface of The control unit 310, a region specifies that these parallel sectional area PR1 ₀ and PR2 ₀ are orthogonal to each other. Here, parallel sectional area PR1 ₀ and PR2 ₀ is in contact with the main surface of the cross section perpendicular to regions SR _0, the side portions are in contact is intended to be on the starting point SP. Thus, the parallel sectional areas PR1 ₀ and PR2 ₀ becomes comprise a longitudinal section of the target vessel Vt in the region.

Here, the control unit 310 imaged using volume data thus designated parallel sectional area PR1 ₀ and PR2 in ₀ (step S322). That is, an image showing the longitudinal section of the target blood vessel Vt as shown in FIGS. 12A and 12B (hereinafter, referred to as “longitudinal image”) is acquired.

If the target blood vessel Vt extends linearly, blood vessel extraction can be performed by processing along the tentative traveling direction DirA perpendicular to the main surface of the orthogonal cross-sectional region SR. Since the image is stretched while changing the direction, the acquired longitudinal image is not always parallel to the temporary traveling direction DirA ₀ as shown in FIG. Therefore, the provisional traveling direction DirA ₀ is corrected to the actual stretching direction based on the acquired longitudinal image.

First, the control unit 310 obtains the center position of each of the longitudinal images acquired in step S322 (step S323). That is, FIG. 12 (a), (b) , and calculates the position of the center C1 ₀ · C2 _0. Here, for example, by using a technique such as "flood-fill (Flood Fill)", it recognizes a longitudinal image in the parallel sectional area PR1 _{0-PR2 0,} determine the centers C1 _{0-C2 0.} Note that the following processing, since obtaining the center position in each of the parallel sectional area PR1 ₀ ~PR1 _n and parallel sectional area PR2 ₀ ~PR2 _n, hereinafter, "parallel sectional area PR1 ₀ ~PR1 _n", "parallel sectional area PR2 ₀ ~PR2 _n "respective centers corresponding to" center C1 ₀ to C1 _n ", referred to as" C2 ₀ -C2 _n ".

Next, the control unit 310 obtains an actual stretching direction vector using each center position obtained in step S323 (step S324). Here, for example, by calculating a formula shown in FIG. 13, it is possible to obtain a stretching direction vector from the orthogonal sectional area SR ₀ of the target vessel Vt.

By such a vector operation, the direction DirB ₀ which is the actual stretching direction as shown in FIG. 14A can be obtained. That is, the provisional traveling direction DirA ₀ is corrected to the traveling direction DirB ₀ . Hereinafter, the direction determined in this way is referred to as “determined traveling direction DirB”. Also, determine the traveling direction DirB is the following process, since it is determined in each of the orthogonal cross-sectional area SR ₀ to SR _n, the corresponding determined traveling direction DirB described as "determined traveling direction DirB ₀ ~DirB _n".

The control section 310 sets the determined traveling direction DirB ₀ thus determined as the traveling direction for determining the position of the next designated cross-sectional area (ie, the orthogonal cross-sectional area SR ₁ ) from the orthogonal cross-sectional area SR _0. , the next time the traveling direction setting, i.e., a work area to store as an interim traveling direction in the process of determining the direction of extension of the cross section perpendicular to regions SR ₁ until the next cross section perpendicular region SR ₂ (step S325), the cross section perpendicular to region The “traveling direction determination process” in SR ₀ ends.

Returning to the “blood vessel extraction processing” flow in FIG. 8, the control unit 310 determines the next orthogonal cross-sectional area SR (in this case, the orthogonal cross-sectional area SR ₁ ) orthogonal to the determined traveling direction DirB ₀ obtained in step S325, It is designated by the same processing as S303 (step S305). That is, the cross section perpendicular to regions SR ₁ as shown in FIG. 14 (b) is specified. Here, the distance from the previously specified cross-sectional area to the next cross-sectional area is arbitrarily set according to, for example, the processing capability of the image processing apparatus 300 and desired accuracy.

Orthogonal sectional area SR ₁ designated in step S305 is because it is the direction perpendicular to the determined direction of travel DirB ₀ from the starting point SP is the center of the cross section perpendicular region SR ₀ immediately before, the orthogonal cross-sectional area SR, which is newly specified ₁ also becomes a cross-sectional direction of the region of likewise target vessel Vt and SR _0, the center of the cross section in the substantially central is to be located.

Here, for example, as shown in FIG. 9C, when only a blood vessel cross section exists in the orthogonal cross section region SR, the blood vessel cross section and its center can be easily extracted, but FIG. As shown in (), the target blood vessel Vt in the designated orthogonal cross-sectional area SR is often close to the heart HT or close to a blood vessel Vx other than the target blood vessel Vt. For example, in the orthogonal cross-sectional area SR where the target blood vessel Vt is close to the heart HT (“orthogonal cross-sectional area SR _ex1 ” in the figure), as shown in FIG. A portion of the heart HT will be included. Further, in the orthogonal cross-sectional area SR where the other blood vessel Vx is close to the target blood vessel Vt (“orthogonal cross-sectional area SR _ex2 ” in the figure), as shown in FIG. In addition, the cross section of the blood vessel Vx is included.

  In such a case, in order to determine the cross section of the target blood vessel Vt and its center, it is conceivable to image the cross sectional area. That is, an image may be formed based on the CT value in the cross-sectional area, and the cross-section of the target blood vessel Vt may be extracted as an image. Here, the CT value is an X-ray absorption coefficient acquired by the modality 100 (CT scanner), and the value is predetermined depending on the substance, for example, “water: 0”, “air: −1000”. . Therefore, when imaging the cross section of the target blood vessel Vt, only the blood vessel is imaged by imaging the pixel (pixel) corresponding to the CT value corresponding to the constituent material of the blood vessel (blood, blood vessel wall, contrast agent, etc.). Is imaged and can be extracted. However, when the heart and other blood vessels are close to the target blood vessel, the substances constituting them are almost the same as those of the target blood vessel Vt, so that the difference in CT value is extremely small. Therefore, even if such a cross-sectional area is imaged, the cross-section of the target blood vessel Vt is integrated with the cross-sections of the adjacent heart HT and other blood vessels Vx as shown in FIGS. As a result, the cross section and the center of the target blood vessel Vt cannot be recognized.

  Therefore, the control unit 310 distinguishes such a slight difference in the CT value, makes the cross-section of the target blood vessel identifiable, reveals the cross-section, and detects the center thereof (step S340). Execute This blood vessel center detection processing will be described with reference to the flowchart shown in FIG. Here, the range (range) of CT values (hereinafter, referred to as “target CT value range”) used when imaging the target region is changed, and an image showing a cross section of the target blood vessel Vt is made to be apparent. Find the center.

First, the control unit 310 sets a range (range) of “threshold” used to change the target CT value range (hereinafter, referred to as “threshold range”) (step S341). That is, in this embodiment, in the following processing, for changing the target CT value range by changing the threshold value indicating the lower limit of the "target CT value range", the variation range of the threshold value (minimum threshold th _min ~ First, the maximum threshold th _max ) is defined.

  Here, the "target CT value range" indicates a range of CT values to be targeted when imaging the inside of a target living body (human body). As described above, the CT value is predetermined according to the substance. When the inside of the human body is to be imaged as in the present embodiment, the organs, organs, blood (contrast agent), bones, and the like are to be imaged. It is predetermined as a CT value range. Then, since the threshold is changed within the target CT value range determined in this way, the threshold range is also the same as the target CT value range.

  Further, as described above, the “threshold” in the present embodiment indicates the lower limit of the target CT value range. That is, when a certain threshold is specified, all CT values equal to or higher than the CT value corresponding to the threshold are targeted. Therefore, among the three-dimensional volume data constituting the area, coordinates where the CT values included in the “target CT value range” are the characteristic information are to be imaged. For example, when the threshold range (target CT value range) is “0 to 1000” and a threshold “100” is set, the coordinates using the CT values included in the range of “100 to 1000” as the characteristic information are It is imaged.

When an image is formed using a CT value, which is an X-ray absorption coefficient, a difference in CT value appears as a difference in brightness. At this time, for example, an image is formed by binary data in which a pixel having a CT value to be imaged as characteristic information is “1” and a pixel having other CT values as characteristic information is “0”. In the present embodiment, it is assumed that the CT value of blood is increased by using a contrast agent during imaging. Also, “imaging” refers to imaging with binary data as described above. Hereinafter, processing in the orthogonal cross-sectional area SR _ex2 (FIG. 15) in which another blood vessel Vx is close to the target blood vessel Vt will be described as an example.

First, the control unit 310 sets the minimum threshold th _min set in step S341 as the threshold th (step S342), and _sets a pixel in the orthogonal cross-sectional area SR _ex2 having a CT value with the threshold th as a lower limit as characteristic information. Is imaged (step S343). When the threshold value th is the minimum threshold value th _min , the applied CT values correspond to all the CT values corresponding to the threshold range (the minimum threshold value th _min to the maximum threshold value th _max ). Here, in step S341, since the width of the CT values can be imaged through the living body is a threshold value range, when the threshold value th is a minimum threshold value th _min, as shown in FIG. 18 (a), of the target vessel Vt sectional and Not only a cross section of the adjacent blood vessel Vx, but also a portion including other tissues and the like around the cross section is imaged.

Also, in the image of FIG. 18A, in the one-dimensional area in the X direction passing through the center of the area (the area of “X0 to X1” in “X-X ′” in the figure), it corresponds to the set threshold. The distribution of pixels having the following CT values can be expressed as a graph G1 shown in FIG. Here, the horizontal axis indicates one-dimensional area coordinates (X0-X1) in the orthogonal cross-sectional area SR _ex2 , and the vertical axis indicates CT values. Since the CT value of the target blood vessel Vt and the adjacent blood vessel Vx is relatively high due to the use of the contrast agent, two peaks appear in the graph curve of the graph G1. That is, each of these peaks indicates a cross section of the target blood vessel Vt and the adjacent blood vessel Vx. The hatched portion in the graph curve indicates a distribution of pixels having a CT value corresponding to the threshold value th (in this case, the minimum threshold value th _min ). Hereinafter, the graph G1 will be referred to as needed when describing the relationship between the threshold value that changes by the processing described later and the target pixel at that time.

Next, the control unit 310 specifies the range of the image appearing at the center position of the orthogonal cross-sectional area SR _{ex2 in} the image obtained in step S343 (step S344). As described above, in the present embodiment, since the image is formed by using the binary data, a pixel region having a CT value corresponding to the threshold value appears clearly as shown in FIG. Shaded area).

  At this time, depending on the target cross-sectional area, for example, as shown in FIG. 19A, a plurality of pixel areas having a CT value corresponding to the threshold value may exist. In the present embodiment, pixel regions having the same contour are recognized and treated as one unit by a method such as “Flood Fill” (hereinafter, referred to as “unit image”). ). That is, in the example of FIG. 19A, two unit images “unit image 1” and “unit image 2” appear.

Therefore, in step S344, control unit 310 specifies the range of the unit image appearing at the center position of orthogonal cross-sectional area SR _ex2 . Here, the “range” corresponds to the outline of the unit image. That is, as shown in FIG. 19B, the outline of a unit image (hereinafter, referred to as “center unit image”) over the center (“+” in the figure) of the region is specified. That is, in FIG. 19B, the line segment indicated by the thick line is specified as the range (contour) of the center unit image.

The control unit 310 determines whether or not the range of the center unit image specified in step S344 _falls within the orthogonal cross-sectional area SR _ex2 (step S345). In other words, it is determined whether or not the range of the center unit image extends outside the area of the orthogonal cross-sectional area _SRex2 . Here, for example, by determining whether or not the contour identified in step S344 is in _contact with any side of the orthogonal cross-sectional area SR _ex2 , it is determined whether or not the center unit image is within the area. Determine. In the case of FIG. 19B, since a part of the outline of the center unit image is in _{contact with} the upper side and the right side of the orthogonal cross-sectional area SR _ex2 , it is determined that the center unit image is not included in the area. In other words, the center unit image are those which extend to the outside of the orthogonal cross-sectional area SR _ex2, it indicates that a portion of which appears in the cross section perpendicular region SR _ex2.

  The control unit 310 associates the determination result with the threshold value at that time, and records it as “threshold attribute information” in a predetermined storage unit (for example, a work area or an image storage unit 360) (step S345).

  Next, the control unit 310 obtains the area of the center unit image specified in step S344, associates the value with the threshold value at that time, and records the value in a predetermined storage unit as “threshold attribute information” (step S346).

Thereafter, the control unit 310, a threshold value th is sequentially changed until the maximum threshold value th _max, the process of step S343~S346 at each threshold (Step S347: No, S348). That is, the threshold value th is sequentially increased from the minimum threshold value th _min to the maximum threshold value th _max , and for each threshold value, (1) imaging, (2) identification of the center unit image, and (3) determination and recording of the range of the center unit image , (4) calculate and record the area of the center unit image. Thus, the threshold attribute information recorded in steps S345 and S346 is recorded in the predetermined storage unit, for example, as a “threshold attribute table” as shown in FIG. The increment rate of the threshold value th (that is, the lower limit value of the target CT value range) is arbitrary, and is arbitrarily set according to, for example, the processing capability of the image processing apparatus 300 and desired accuracy. In the present embodiment, the threshold th is incremented by “+1” for ease of explanation.

The control unit 310 images the cross section of the target blood vessel Vt based on the area change (image attribute) in order to detect the center of the target blood vessel Vt in the orthogonal cross-sectional area SR _ex2 using the “threshold attribute information”. The “vascular cross-section clarification process” (step S360) to be clarified above is executed. This “vascular cross section revealing process” will be described with reference to the flowchart shown in FIG.

First, the control unit 310 obtains the “area value” from the threshold attribute table shown in FIG. 20, and obtains the area distribution of the center unit image in the threshold range (step S361). Here, for example, by plotting each area value, a graph G2 showing the area distribution as shown in FIG. 22 can be obtained. In the graph G2, the horizontal axis indicates the threshold th (the minimum threshold th _min to the maximum threshold th _max ), and the vertical axis indicates the area of the center unit image. As shown in the figure, the area value of the center unit image decreases as the threshold value th transitions from the minimum threshold value th _min to the maximum threshold value th _max . This is because the target CT value range is narrowed in accordance with the transition of the threshold, so that the area of the region to be imaged is also reduced.

  The control unit 310 obtains the area change rate of the center unit image (step S362). Here, for example, the area distribution obtained in step S361 is defined by a piecewise continuous function, and the area change rate can be obtained by differentiating the piecewise continuous function.

  Next, the control unit 310 refers to the threshold attribute table and excludes the threshold when the central unit image does not fall within the area (step S363). This is because the target blood vessel cross-section has a substantially circular shape and is located at the center of the orthogonal cross-sectional area, so that an image whose contour is clear (a visualized image) extends outside the area. Because it cannot be reached.

Further, as shown in the graph G2 of FIG. 22, in the process of increasing the threshold value th (that is, narrowing the target CT value range), the area of the center unit image may decrease rapidly. In the example of the graph G2, the area sharply decreases when the threshold value changes from th _a to th _{a + 1} and when the threshold value changes from th _{b to} th _{b + 1} . Here, the transition from “th _{a to} th _{a + 1} ” is when the center unit image that has been extended to the outside of the area range has fallen into the area due to the decrease in the area. The transition from “th _{b to} th _{b + 1} ” is the time when the central unit image is revealed as showing the cross section of the target blood vessel Vt. 23 and 24 as examples of the former case, and FIGS. 25 and 26 as examples of the latter case.

FIG. 23A shows an example of an image obtained at the threshold th _a , and FIG. 23B shows a graph G1 representing a pixel distribution in a one-dimensional area (X0-X1) at the threshold th _a. It is shown. FIG. 24A shows an image obtained at the threshold th _{a + 1} , and FIG. 24B shows a pixel distribution in the one-dimensional area (X0-X1) at the threshold th _{a + 1.} 6 is a graph G1 shown in FIG.

As shown in FIG. 23A, at the time of the threshold th _a , the contour of the central unit image is in contact with the side of the orthogonal cross-sectional area. Further, as shown in FIG. 23B, the pixel distribution (hatched portion) at the threshold value th _a is over X1, which is the end of the one-dimensional area. Then, as shown in FIG. 24 (b), when the threshold value is changed from th _a to th _{a + 1} , the pixel distribution moves away from X1 at the end of the one-dimensional area. That is, as shown in FIG. 24A, the central unit image that has been in contact with the side of the orthogonal cross-sectional area until now fits in the area. At this time, since a gap is generated between the contour of the center unit image and the side of the orthogonal cross-sectional area, the area of the center unit image is significantly reduced, and the change as shown in the graph G2 (FIG. 22) occurs. Appear.

On the other hand, FIG. 25 (a) shows an image obtained when the threshold value th _b, FIG. 25 (b) is a graph showing the pixel distribution in the one-dimensional area (X0-X1) when the threshold value th _b G1 It is shown. Table Moreover, FIG. 26 (a) shows an image obtained when the threshold value th _{b + 1,} FIG. 26 (b) shows a pixel distribution in a one-dimensional area (X0-X1) when the th _{b + 1} 13 shows a graph G1 obtained.

As shown in FIG. 25 (a), at the time of the threshold th _b, the center unit image is both cross-section of the vessel Vx proximate the target vessel Vt is an image that integrates. Further, as shown in FIG. 25 (b), the threshold th _b may correspond to a valley between two peaks appearing in the graph curve, that is, the pixel distribution containing both peaks both. Then, as shown in FIG. 26 (b), when the transition threshold from th _b to th _{b + 1,} pixel distribution is divided into each of the two peaks. In other words, as shown in FIG. 26A, the central unit image that previously shows both the cross section of both the target blood vessel Vt and the adjacent blood vessel Vx is divided into two, and one is a cross section of the target blood vessel Vt. And the other is a unit image showing the cross section of the blood vessel Vx. That is, the cross section of the target blood vessel Vt is made obvious. Here, since the area change of the central unit image is detected in this processing, the area of the unit image indicating the blood vessel Vx is reduced from the area of the central unit image, and the graph G2 (FIG. ).

  In this processing, since it is to identify that the cross section of the target blood vessel Vt has been exposed on the image, it is possible to determine whether or not the cross section of the target blood vessel Vt has been exposed by detecting the sudden decrease in the area as described above. it can. However, depending on differences in various conditions such as the location of the cross-sectional area and the shape of the central unit image, the area change when the central unit image fits within the area rather than the area change when the blood vessel cross section becomes apparent May be larger. Therefore, even if a location where the area change rate is maximized within the threshold range is detected, it is not always possible to detect the appearance of the blood vessel cross section. Therefore, the control unit 310 refers to the “threshold attribute table” in step S363, excludes the threshold when the contour of the central unit image extends outside the cross-sectional area, and determines that the area change is the largest among the excluded thresholds. The threshold value is determined (step S364).

In the example of the graph G2 in FIG. 22, the threshold range that has been excluded is shown as a non-target area (NG area). Here, a large area change occurs during the transition from the threshold th _a to th _{a + 1} , but since the threshold th _a is a threshold corresponding to an NG area, it is excluded from detection targets. Therefore, the threshold value at which the change in the area is maximum among the threshold values th _{a + 1} to th _max , that is, the threshold value th _{b + 1} is detected. Here, when the area change rate is obtained by the above “differentiation of the piecewise continuous function”, the threshold when the minimum differential value is obtained can be set as the “threshold that maximizes the area change”.

The control unit 310 sets the threshold specified in step S364 as the lower limit, and images the pixels corresponding to the CT value range with the threshold th _max as the upper limit, thereby forming the target blood vessel as illustrated in FIG. An image in which the cross section of Vt has become apparent is acquired (step S365), and the flow returns to the “vessel center detection processing” shown in FIG.

  When the central unit image indicating the cross section of the target blood vessel Vt that has been revealed in step S365 is obtained, the control unit 310 recognizes the shape of the central unit image by a technique such as flood fill, for example. Then, the correct center position is determined (step S349). That is, in step S305, each of the orthogonal cross-sectional regions SR is specified such that the cross section of the target blood vessel Vt is located substantially at the center thereof. However, the center of the target blood vessel Vt is obtained from the imaged cross section of the target blood vessel Vt. The center can be determined accurately. Here, since the orthogonal cross-sectional area SR is an area specified for a part of the three-dimensional volume data, if a specific position is determined, the position is specified as coordinate system information of the three-dimensional volume data. be able to. That is, the center position of the blood vessel in the cross-sectional area can be obtained as coordinate system information (x, y, z). After determining the blood vessel cross-sectional center in the cross-sectional area, the control unit 310 returns to the flow of the “blood vessel extraction process” illustrated in FIG.

Control unit 310 performs the processes described above in each of the orthogonal cross-sectional area SR ₀ to SR _n (Step S306: No). That is, the coordinate system information of the blood vessel center position in each of the orthogonal cross-sectional regions SR sequentially specified based on the traveling direction determined in the traveling direction determination processing is acquired. In the description of the moving direction determination process, because of the initial process as an example, it is assumed to correct and decide the traveling direction relative to the center of the cross section perpendicular to regions SR _0, vascular central position in the blood vessel extraction process If determined, the traveling direction is determined based on the determined blood vessel center position.

When the control unit 310 determines the blood vessel center in the orthogonal cross-sectional area SR _n at the end point EP specified in step S302 as a result of sequentially performing the above-described processes (step S306: Yes), the control unit 310 Based on the coordinate system information of the blood vessel center acquired in the cross-sectional area, a three-dimensional path indicating the longitudinal center line of the target blood vessel Vt is acquired (step S307). That is, since the cross-sectional center position is acquired as coordinate system information, the center line of the target blood vessel Vt can be specified as a path connecting the centers. Therefore, a path of the center line from the start point SP to the end point EP (hereinafter, referred to as “path P _Vt ”) as shown in FIG. 27 is obtained. The control unit 310 of the image processing apparatus 300 generates and displays various medical images using the path P _Vt acquired in this manner (step S500: FIG. 6).

In the “blood vessel extraction processing”, since the path P _Vt which is the vector information of the center line of the target blood vessel Vt has been obtained, the control unit 310 of the image processing apparatus 300 performs arbitrary three-dimensional image processing along the path P _Vt. By performing (for example, volume rendering), a three-dimensional image showing a coronary blood vessel as shown in FIG. 28 can be generated. That is, since the path data of the center line has been obtained in the "blood vessel extraction processing", for example, even in a portion where the blood vessel diameter is small, a three-dimensional image can be formed without being cut. In addition, as described above, according to the “blood vessel extraction process”, even when the heart or other blood vessels are close to each other, the center of the target blood vessel can be accurately detected. Even for a coronary blood vessel that has been difficult to image, an accurate three-dimensional image as shown in FIG. 28 can be generated.

In addition, since the path P _Vt acquired in the “blood vessel extraction processing” is vector data, various conversions and processings can be easily performed. That is, the path P _Vt is “three-dimensional path data” composed of three-dimensional coordinate system data, but is converted into “two-dimensional path data” by the control unit 310 of the image processing apparatus 300 performing a predetermined calculation or the like. After conversion, each blood vessel can be displayed as a linear two-dimensional image (tree view). In addition, it can be associated with a medical image of another format created using the three-dimensional volume data acquired by the modality 100. That is, a plurality of medical images of different display formats (coordinate systems) can be simultaneously displayed for the same target, and their positions on each image can be associated with each other.

  FIG. 29 shows an example of such an image display. The display screen in this example has a plurality of display areas (left, center, right) as shown in the figure, and the output device 34 (in this case, the display device in this case) is controlled by the control unit 310 and the output control unit 340. Display devices) display medical images in different display formats (coordinate systems). For example, in the left area, a “three-dimensional image” of the heart and coronary vessels is displayed in the upper part, and “two-dimensional path data” converted from the three-dimensional path data is displayed in the lower part. Here, it is assumed that an image indicating a three-dimensional path can be displayed on the three-dimensional image in a superimposed manner. That is, when a blood vessel displayed as a three-dimensional image is designated on the three-dimensional image by a pointer such as a cursor, for example, the three-dimensional path of the blood vessel is displayed on the three-dimensional image of the designated blood vessel. Is done.

  The conversion into the two-dimensional path data is performed by converting the three-dimensional path data into the two-dimensional path data while maintaining the topology (connection branching relation) to obtain a tree view. Here, since a coronary blood vessel or the like can be represented as a so-called acyclic graph having a branch point, even when such a blood vessel is represented by a two-dimensional path, it can be represented without crossing branches. . Further, by obtaining the blood vessel length from the three-dimensional path data, the positional relationship on the three-dimensional path and the two-dimensional path can be easily associated.

  Therefore, for example, when a certain blood vessel is designated on the three-dimensional image in the upper part of the screen, the three-dimensional path of the blood vessel is displayed on the three-dimensional image, and the two-dimensional path indicating the blood vessel is highlighted in the lower part of the screen. And so on. That is, since the position information (node) on both images is relatively associated with each other by the operation of the control unit 310, for example, a pointer displayed on a three-dimensional image and a pointer displayed on a two-dimensional path image are displayed. The linked pointers are linked to each other, and it is possible to display such that the other pointer moves in response to the movement of one pointer.

  Here, the three-dimensional volume data acquired by the modality 100 can include, for example, various measurement data in addition to the coordinate system information and the CT value. By using such measurement data, for example, numerical information such as a blood flow rate and a blood vessel diameter can be obtained. These pieces of information can be associated not only with the three-dimensional path data, but also with two-dimensional path data obtained by converting the three-dimensional path data. Therefore, by acquiring these measurement data as parameters, the control unit 310 can explicitly display a difference in a blood vessel diameter, a blood flow rate, and the like on each image. For example, on the two-dimensional path screen, it is possible to change the display color of a part where the blood vessel diameter is equal to or smaller than a predetermined threshold value and change the display color to another part.

  Usually, it is said that there is a high probability that an abnormality occurs in a portion where the blood vessel diameter is small, but it is suitable for grasping the spatial positional relationship of the blood vessel in a three-dimensional image, but it is generated on the blood vessel. There is a disadvantage that it is difficult to find an abnormal part or a part with a small diameter. Therefore, by displaying the two-dimensional path data having the above-described display form simultaneously with the three-dimensional image, it is possible to determine the position of the blood vessel in which the abnormal part or the thin part is located in the two-dimensional path. It can be recognized on the screen and the location can be confirmed as the actual position on the three-dimensional image.

  Further, as shown in FIG. 29, for example, a CPR (Curved-Planer Reconstruction) image of the target blood vessel is displayed in the upper and middle stages of the central display area. The CPR is for designating an area of three-dimensional volume data with an arbitrary curved surface. For example, by designating a curved surface region along a blood vessel, a longitudinal cross section of the blood vessel can be displayed on one screen. In the example of FIG. 29, the image of “CPR non-linear mode” is displayed on the upper stage, and the image of “CPR linear mode” is displayed on the lower stage. In the “non-linear mode”, the designated curved surface region is directly imaged, and in the “linear mode”, the designated curved surface region is pseudo-expanded and the target blood vessel is displayed as a linear image. .

  The coordinate information in the CPR image displayed here is also associated with the three-dimensional path data and the two-dimensional path data by the operation of the control unit 310. Therefore, for example, when one of a three-dimensional image and a two-dimensional path for a desired blood vessel is designated, a CPR image of the designated blood vessel is displayed in the central area. Further, when the pointer is moved on the three-dimensional image, the pointer on the CPR image also moves accordingly. Conversely, when the pointer is moved on the CPR image, the pointer on the three-dimensional image is moved accordingly. Further, as described above, since various information can be included in the volume data, the control unit 310 creates a graph or the like based on such information and displays it in the lower part. In this graph, for example, various types of information at positions indicated on the images can be displayed in a graph. For example, when a plurality of locations on a blood vessel are designated on the CPR image, information such as a blood vessel diameter and a stenosis rate at each designated location is graphed and displayed for comparison.

  In the right region, an MPR image showing a blood vessel cross section is displayed. The coordinate information on the MPR image is also correlated with the coordinate information of another image by the operation of the control unit 310. Therefore, for example, when a plurality of locations on a blood vessel are designated on the CPR image, a cross section of the blood vessel at the designated location is displayed.

  Since the position information on all images displayed in this way is linked to each other, specifying a position on any image will explicitly display the corresponding position on other images, so A plurality of images having different formats (coordinate formats) can be displayed in a list and referred to, and the positional relationship can be uniquely grasped. Therefore, for example, it is possible to use the two-dimensional path data and the CPR image to find an abnormal part at the time of diagnosis, and to confirm the actual position by referring to the three-dimensional image when performing an operation on the part. -It can contribute to improvement of treatment accuracy.

  As described above, according to the image diagnostic system 1 according to the embodiment of the present invention, when an image of a tubular tissue such as a blood vessel is generated, the cross section of the blood vessel is visualized by changing the threshold value in each cross sectional area. Therefore, the center line can be accurately extracted even when the CT value changes in the middle of the tube due to a change in the blood vessel diameter or an abnormal site, for example. Therefore, it is possible to obtain a good image without being shredded. In addition, since the center of the cross section is detected by visualizing the cross section of the blood vessel in each cross-sectional area, the center line of the target blood vessel can be accurately determined even when other organs or the like having similar CT values are close to each other. Can be extracted. In addition, since the center line of the target blood vessel can be acquired as path data, it can be mutually linked with a plurality of types of medical images having different display formats, and these medical images can be displayed simultaneously. Therefore, particularly useful medical image display can be realized for diagnosis and treatment of coronary vessels near the heart.

In the “blood vessel extraction processing” in the above embodiment, the orthogonal cross-sectional area SR _ex2 shown in FIG. 15 (when another blood vessel Vx is close to the target blood vessel Vt) has been described as an example. Even in the illustrated orthogonal cross-sectional area SR _ex1 (that is, when the heart HT is close to the target blood vessel Vt), a cross section of the target blood vessel Vt can be accurately extracted similarly. This is because the present invention changes the target CT value range in each of the acquired cross-sectional areas, thereby detecting the center of the blood vessel when the blood vessel cross-section becomes apparent. This is because they can be distinguished sharply. Therefore, the cross-sectional center of the target blood vessel Vt is accurately detected even if other organs or tissues are close to each other as long as the area includes the cross-section of the target blood vessel Vt, without being limited to the illustrated orthogonal cross-sectional areas SR _ex1 and SR _ex2. can do.

  In this case, the method of designating the region including the cross section of the target blood vessel Vt is arbitrary. For example, the cross sectional region of the target blood vessel Vt may be specified by specifying a predetermined three-dimensional region (space region). In this case, for example, as shown in FIG. 30A, an arbitrary point AP on the target blood vessel Vt (for example, “start point SP” specified in step S302 of “blood vessel extraction processing” (FIG. 8)) is specified. The three-dimensional coordinates of the arbitrary point AP are specified, and a cubic three-dimensional area having the arbitrary point AP as the center of gravity CP (hereinafter, referred to as “cube area CR”) is specified. Since the target blood vessel Vt is tubular, it comes into contact at two places on the surface of the cubic region CR (hereinafter, the contact on the upstream side in the traveling direction is referred to as “contact EG1”, and the contact on the downstream side is referred to as “contact EG2”. "). Then, among the surfaces constituting the cubic region CR, the surface including the contact point EG1 is referred to as a “cross-sectional region SRa”, and the surface including the contact point EG2 is referred to as a “cross-sectional region SRb”. The identification of. That is, by executing the above-described “blood vessel center detection processing” (FIG. 17) on the cross-sectional areas SRa and SRb, three-dimensional coordinates indicating the cross-sectional center of the target blood vessel Vt at the contact points EG1 and EG2 can be specified.

  Since the three-dimensional coordinates of the center of gravity CP and the contact points EG1 and EG2 are specified, for example, as shown in FIG. 30 (b), the unit three-dimensional path data in the cubic region CR connecting the center of gravity CP and the contact point EG2 ( Hereinafter, “unit path UP” can be obtained. That is, it is possible to obtain three-dimensional path data for the target blood vessel Vt included in the cubic region CR. Here, the unit path UP may be, for example, one connecting two points of the contact point EG1 and the contact point EG2, or connecting three points of the contact point EG1, the center of gravity CP, and the contact point EG2. Is also good.

Then, the next three-dimensional area can be designated based on the “unit path UP” obtained in this manner. For example, as shown in FIG. 31A, the next cubic region CR2 may be designated by using the terminal point UP1e of the unit path UP1 of the previously designated cubic region CR1 as the center of gravity CP2. Alternatively, as shown in FIG. 31 (b), the next cubic region CR2 is designated by setting the center of gravity CP1 of the previously designated cubic region CR1 and the midpoint UP1m of the terminal UP1e of the unit path UP1 as the center of gravity CP2. Good. A plurality of unit paths UP can be obtained by sequentially designating the cubic region CR in this manner. Based on such a plurality of unit paths UP, the path P _Vt of the center line from the start point SP to the end point EP is obtained. Can be obtained.

  Note that the arbitrary point AP is not the center of gravity of the cubic region CR, but, for example, as shown in FIG. 32A, the cubic region CR is designated as the center of one surface of the cubic region CR (hereinafter, referred to as “center CP”). You may. In this case, as shown in FIG. 32 (b), among the surfaces constituting the cubic region CR, the surfaces in contact with the target blood vessel Vt are set as the cross-sectional regions SRa and SRb, and the tube cross-section and the center thereof can be specified. Since the contact point EG1 in this case is the same as the arbitrary point AP (the center of gravity CP), "extraction of the pipe section" and "identification of the section center" may be performed for the contact point EG2. Then, a three-dimensional path connecting the center of gravity CP and the contact point EG2 can be referred to as a “unit path UP”.

  The shape of the designated three-dimensional area (space area) is not limited to the cube as described above, and may be any shape. For example, a rectangular parallelepiped shape as shown in FIG. 33 (a), a triangular pyramid shape as shown in FIG. 33 (b), a spherical shape as shown in FIG. 34 (a), or a spherical shape as shown in FIG. 34 (b) In addition to such a cylindrical shape, for example, the shape may be an elliptical shape, a barrel shape, or a torus (annular tube surface).

  Further, the designation of such a “three-dimensional region” may be combined with the designation of the “orthogonal cross-sectional region” exemplified in the above embodiment. For example, the “orthogonal cross-sectional area” may be used for the start point SP and the end point EP, and the “three-dimensional area” may be used between the start point SP and the end point EP.

  In the above-described embodiment, the start point SP and the end point EP (arbitrary points) are specified on the two-dimensional image showing the cross section of the blood vessel by the operator operating the input device 33. Not limited to For example, it may be specified on various images (that is, a three-dimensional image, a CPR image, or the like) generated in the “medical image generation / display processing”. Alternatively, the arbitrary point may be specified by a program executed by the image processing apparatus 300 or an instruction from another apparatus connected to the image processing apparatus 300, etc., without depending on the operation of the operator. Further, in the above embodiment, both the start point SP and the end point EP are specified, but one of the start point SP and the end point EP may be specified. In this case, the “traveling direction” may be specified by an instruction from an operator or a program. Further, in the above-described embodiment, the extraction is terminated by designating the orthogonal cross-sectional area SR at the end point EP. However, the present invention is not limited to this. For example, a threshold value for a blood vessel diameter is set, and the blood vessel diameter is set to a predetermined value or less. The extraction may be terminated when it becomes.

  Further, in the “vascular cross section revealing process” of the above-described embodiment, the threshold at which the area change is maximum in the threshold range excluding the NG value is detected in advance, but the method of detecting the threshold at which the blood vessel cross section becomes visible is It is not limited to this. For example, when there is a large area change a plurality of times, the roundness of the center unit image obtained in each case is obtained, and the threshold when the image with the highest roundness is obtained is set as the “threshold for making the blood vessel cross section visible. ".

  In the above embodiment, the appearance of the blood vessel cross section is determined by focusing on the area change. However, the attention target item is not limited to this. For example, the roundness, the center of gravity, and the outer peripheral length are determined based on the change. Is also good.

In the above embodiment, the threshold value indicating the lower limit value of the “target CT value range” is changed, but the setting of the threshold value is arbitrary. For example, it may indicate the upper limit of the “target CT value range”. Further, in the above embodiment, changing the threshold from the minimum threshold value th _min up to the threshold th _max, is not how the change is optional, for example, be varied from a maximum threshold th _max to the minimum threshold value th _min Good. Further, in the above embodiment, the “target CT value range” is gradually narrowed by changing the threshold. However, the present invention is not limited to this. For example, the “target CT value range” is gradually expanded. The manifestation may be determined.

  In the “traveling direction determination process” in the above embodiment, the traveling direction is determined by designating two parallel cross-sectional areas in each orthogonal cross-sectional area, but the method of determining the traveling direction is not limited to this. That is, any method can be used as long as it can appropriately determine the direction in which the vehicle should proceed. In the case where the method exemplified in the above embodiment is used, the number of designated parallel cross-sectional areas is not limited to “2” and is arbitrary. That is, the traveling direction may be corrected and determined based on the longitudinal images in one parallel cross-sectional area, or the traveling direction may be corrected and determined based on the longitudinal images in three or more parallel cross-sectional areas. You may. Also, when obtaining the longitudinal direction image, the target revealing method used in the above-mentioned "vascular cross section revealing process" can be used. That is, when other tissues are close to the target blood vessel Vt, they are also included in the parallel cross-sectional area, but by making the longitudinal cross-section similar to the above-described blood vessel cross-section, The center position can be accurately detected.

  In the above embodiment, a case where a CT scanner is used as the modality 100 and, therefore, a case where a CT image is used has been described as an example. However, as described above, the modality 100 that can be used is arbitrary, and accordingly, the modality that is used is used. An image (for example, an MR image or an ultrasonic image) corresponding to the device may be used.

  In the above embodiment, blood vessels such as coronary blood vessels are particularly extracted. However, any tubular tissue (tubular organ, luminal organ) can be extracted. For example, trachea, intestine, nerve, etc. Can be extracted.

  In the above-described embodiment, in the “medical image generation / display processing”, an example has been described in which a three-dimensional image, a two-dimensional path, a CPR image, a graph, and an MPR image are displayed on the same screen. The type of image and the number of images to be displayed at one time are arbitrary. Further, the image processing apparatus 300 according to the above embodiment may have only a function of acquiring a centerline path of a tubular tissue, for example. In this case, the image processing device 300 may provide the obtained three-dimensional path data to another image generation device, and generate various images there. Further, for example, the modality 100, the control terminal 200, or the like may have some or all of the functions of the image processing apparatus 300 according to the above-described embodiment relating to the above-described processing. That is, each function of the image processing device 300 may be realized by a single device, or may be realized by cooperation of a plurality of devices.

  The image processing apparatus 300 according to the above-described embodiment can be constituted not only by a dedicated device but also by a general-purpose computer device such as a personal computer. In this case, the image processing apparatus 300 can be configured by installing a part or all of the program for realizing each of the above processes in a general-purpose computer device and executing the program under control of an OS or the like. In this case, the program distribution form is arbitrary. For example, it can be distributed via a communication medium (such as the Internet) by being superimposed on a carrier wave as well as being stored and distributed on a recording medium such as a CD-ROM.

  As described above, according to the present invention, in generating a medical image, a tubular tissue such as a blood vessel can be accurately extracted, and a plurality of types of images showing the tubular tissue are displayed in a list in association with each other. Can be.

FIG. 1 is a diagram schematically illustrating a configuration of an “image diagnostic system” according to an embodiment of the present invention. FIG. 2 is a block diagram illustrating a configuration of a “control terminal” illustrated in FIG. 1. FIG. 3 is a diagram for explaining a tomographic image (slice image) acquired by the control terminal shown in FIG. 2. FIGS. 7A and 7B are diagrams for explaining a method of designating an arbitrary area of three-dimensional volume data, wherein FIG. 9A shows an example of “MPR” and FIG. 9B shows an example of “CPR”. FIG. 2 is a block diagram illustrating a configuration of an “image processing device” illustrated in FIG. 1. It is a flowchart for demonstrating the "blood vessel image generation process" concerning embodiment of this invention. 7 is a flowchart for explaining “imaging processing” shown in FIG. 6. FIG. 7 is a flowchart for explaining “blood vessel extraction processing” shown in FIG. 6. 9A and 9B are views for explaining a cross-sectional area obtained by the blood vessel extraction processing shown in FIG. 8, wherein FIG. 9A shows an example of a cross-sectional image displayed for specifying a start point, and FIG. And (c) schematically illustrates the positional relationship between the acquired cross-sectional area and the blood vessel cross-section. FIG. 9 is a flowchart for describing “traveling direction determination processing” in the blood vessel extraction processing shown in FIG. 8. 11A is a diagram for explaining a parallel cross-sectional area specified in the traveling direction determination processing shown in FIG. 10, where FIG. 11A schematically illustrates a positional relationship of one of the specified parallel cross-sectional areas, and FIG. FIG. 4 schematically illustrates the positional relationship of the other of the designated parallel cross-sectional regions, and FIG. 4C schematically illustrates the positional relationship between both of the designated parallel cross-sectional regions and the orthogonal cross-sectional region. It is a figure which shows the example of the longitudinal direction image acquired in the traveling direction determination process shown in FIG. 10, (a) shows the example of the longitudinal direction image acquired in one parallel cross section area, (b) is the other. 5 shows an example of a longitudinal image acquired in a parallel cross-sectional area. FIG. 11 is a diagram illustrating an example of a calculation formula used for vector calculation in the traveling direction determination process illustrated in FIG. 10. 11A and 11B are diagrams for explaining processing in the traveling direction determination processing shown in FIG. 10, where FIG. 11A schematically illustrates a relationship between a provisional traveling direction and a determined traveling direction, and FIG. 2 schematically shows an orthogonal cross-sectional area to be formed. It is a figure which illustrates typically the positional relationship about a target blood vessel, (a) typically illustrates the positional relationship between the orthogonal cross-sectional area designated about a target blood vessel, and the heart and other blood vessels which are close to the target blood vessel. , (B) schematically illustrates the positional relationship between the target blood vessel and the heart in one orthogonal cross-sectional area illustrated in (a), and (c) illustrates the positional relation in the other orthogonal cross-sectional area illustrated in (a). The positional relationship between a target blood vessel and other blood vessels is schematically illustrated. FIG. 16 is a diagram schematically illustrating an example of an image when an orthogonal cross-sectional area illustrated in FIG. 15 is imaged, wherein FIG. 15A illustrates an example of an image of the area illustrated in FIG. ) Shows an example of an image of the area illustrated in FIG. It is a flowchart for demonstrating "the blood vessel center extraction process" concerning embodiment of this invention. 18A and 18B are diagrams for explaining the blood vessel center extraction process illustrated in FIG. 17, wherein FIG. 17A illustrates an example of an image when a minimum threshold is set, and FIG. 3 shows a graph illustrating a pixel distribution in an original area. It is a figure for demonstrating the blood-vessel center extraction process shown in FIG. 17, (a) is a figure for demonstrating a term "unit image", (b) is a term "center unit image" and "a unit image. It is a figure for explaining "range." FIG. 18 is a diagram illustrating an example of a “threshold attribute table” created in the blood vessel center extraction process illustrated in FIG. 17. It is a flowchart for demonstrating "the blood-vessel cross-section visualization process" concerning embodiment of this invention. 22 is a graph showing a change in the area of a central unit image detected in the blood vessel cross-section clarification processing shown in FIG. 21. 22A and 22B are diagrams for explaining a change in an image in the blood vessel cross-section revealing process illustrated in FIG. 21, where FIG. 21A illustrates an example in which a central unit image extends outside an orthogonal cross-sectional area, and FIG. It is a graph which shows the relationship between the threshold value and the pixel distribution at that time. 22A and 22B are diagrams for explaining a change in an image in the blood vessel cross-section revealing process illustrated in FIG. 21, where FIG. 21A illustrates an example in which a central unit image falls within an orthogonal cross-sectional area, and FIG. 6 is a graph showing a relationship between a threshold value and a pixel distribution at the time. 22A and 22B are diagrams for explaining a change in an image in the blood vessel cross-section clarification processing illustrated in FIG. 21, wherein FIG. (B) is a graph showing the relationship between the threshold value and the pixel distribution at that time. 22A and 22B are diagrams for explaining a change in an image in the blood vessel cross-section visualization processing illustrated in FIG. 21, where FIG. 22A illustrates an example of a center unit image when a cross-section of a target blood vessel is realized, and FIG. 7 is a graph showing the relationship between the threshold value and the pixel distribution at that time. FIG. 22 is a diagram schematically illustrating a three-dimensional path acquired in the blood vessel cross-section visualization processing illustrated in FIG. 21. FIG. 7 is a diagram illustrating an example of a three-dimensional image generated by “medical image generation / display processing” illustrated in FIG. 6. FIG. 7 is a diagram illustrating a display example of an image generated by “medical image generation / display processing” illustrated in FIG. 6. It is a figure for explaining the case where a “3D area” is used for section area designation in an embodiment of the present invention, and (a) is an example of a positional relationship between an arbitrary point on a target blood vessel and a specified cubic area. (B) shows an example of a cross-sectional area in a designated cubic area and an obtained unit path. FIG. 31A is a diagram for explaining a method of sequentially designating the cubic regions shown in FIG. 30, wherein FIG. An example in which the middle point is set as the center of gravity of the next cubic region is schematically shown. FIG. 31 is a diagram for explaining another method of designating the cubic region shown in FIG. 30, where (a) shows an example of the positional relationship between an arbitrary point on the target blood vessel and the designated cubic region, and (b) shows 5 shows an example of a cross-sectional area in a specified cubic area and an obtained unit path. FIG. 31 is a diagram illustrating another example of the three-dimensional region illustrated in FIG. 30, where (a) illustrates a rectangular parallelepiped spatial region and (b) illustrates a triangular pyramid spatial region. FIG. 31 is a diagram illustrating another example of the three-dimensional region illustrated in FIG. 30, where (a) illustrates a spherical space region and (b) illustrates a columnar space region.

Explanation of reference numerals

DESCRIPTION OF SYMBOLS 1 Image diagnostic system 10 Communication network 100 Modality 200 Control terminal 300 Image processing device

Claims (25)

A medical image processing apparatus that generates a medical image using three-dimensional volume data indicating the inside of a living body,
A cross-sectional area specifying unit that specifies a plurality of areas including a cross section of a predetermined tubular tissue indicated by the three-dimensional volume data;
Using the three-dimensional volume data included in each cross-sectional area specified by the cross-sectional area specifying unit, an imaging unit that images a cross-section of the tubular tissue included in the cross-sectional area,
A center specifying unit that specifies three-dimensional volume data indicating a center position of an image indicating a cross section of the tubular tissue;
A center line specifying unit that specifies the three-dimensional volume data indicating the longitudinal center line of the tubular tissue based on the three-dimensional volume data indicating the center position of the tube cross section in each cross-sectional area specified by the center specifying unit; ,
A medical image processing apparatus comprising: A medical image processing apparatus that generates a medical image using three-dimensional volume data indicating the inside of a living body,
At a plurality of positions on a predetermined tubular tissue indicated by the three-dimensional volume data, an orthogonal cross-sectional area designation that is orthogonal to the longitudinal direction of the tubular tissue at each position and specifies a region including a cross section of the tubular tissue at the position Department and
Using the three-dimensional volume data included in each orthogonal cross-sectional area specified by the orthogonal cross-sectional area specifying unit, an imaging unit that images a cross section of the tubular tissue included in the orthogonal cross-sectional area,
A center specifying unit that specifies three-dimensional volume data indicating a center position of an image indicating a cross section of the tubular tissue;
A center line specifying unit that specifies the three-dimensional volume data indicating the longitudinal center line of the tubular tissue based on the three-dimensional volume data indicating the center position of the tube cross section in each orthogonal cross section area specified by the center specifying unit. When,
A medical image processing apparatus comprising: A medical image processing apparatus that generates a medical image using three-dimensional volume data indicating the inside of a living body,
A three-dimensional region specifying unit that specifies a predetermined three-dimensional region at a plurality of positions on a predetermined tubular tissue indicated by the three-dimensional volume data;
An imaging unit configured to image a cross section of the tubular tissue included in the three-dimensional region, using the three-dimensional volume data included in each of the three-dimensional regions specified by the three-dimensional region specification unit;
A center specifying unit that specifies three-dimensional volume data indicating a center position of an image indicating a cross section of the tubular tissue;
A center line specifying unit that specifies the three-dimensional volume data indicating a longitudinal center line of the tubular tissue based on the three-dimensional volume data indicating the center position of the tube section specified by the center specifying unit;
A medical image processing apparatus comprising: The three-dimensional volume data includes at least three-dimensional coordinate information and characteristic information indicating a predetermined characteristic at each coordinate indicated by the three-dimensional coordinate information,
The imaging unit, by imaging using the characteristic information corresponding to a predetermined condition, to make a cross section of the tubular tissue visible on an image,
The medical image processing apparatus according to claim 1, wherein: The imaging unit,
A condition changing unit that changes the predetermined condition;
An image attribute detection unit that detects an image attribute that changes according to the condition change,
Based on the detected change of the image attribute, further comprising: a visualization determination unit that determines whether or not the cross section of the tubular tissue has been visualized on an image.
The medical image processing apparatus according to claim 4, wherein: The image attribute indicates an area of the image,
The image attribute detection unit,
Detecting an image area that changes in accordance with the condition change, and detecting a change in the image area in accordance with the condition change, based on the detected area;
The manifestation determination unit determines, based on the detected area change, whether or not the cross section of the tubular tissue has been manifested on an image.
The medical image processing apparatus according to claim 5, wherein: The manifestation determination unit is configured such that when the image appearing at the center of the cross-sectional area falls within the cross-sectional area, and when the area change is maximized, the cross-section of the tubular tissue is visualized on the image. Determine that
The medical image processing apparatus according to claim 6, wherein: The orthogonal cross-sectional area designating section,
A provisional direction determination unit that provisionally determines the traveling direction for specifying the next orthogonal cross-sectional area,
Based on the center position of the tubular tissue specified in the orthogonal cross-sectional area specified immediately before, based on the provisional direction determined by the provisional direction determination unit, parallel to the longitudinal direction of the tubular tissue in the orthogonal cross-sectional area, A parallel section area designating section for designating one or more areas including a longitudinal section of the tubular tissue;
A traveling direction determining unit that detects a center position of the longitudinal section included in the designated parallel sectional region, and determines a traveling direction for designating a next orthogonal sectional region based on the detected center position; And further comprising
Designate a region orthogonal to the traveling direction determined by the traveling direction determination unit as the next orthogonal cross-sectional region,
The medical image processing apparatus according to claim 2, wherein: The three-dimensional region specifying unit determines a position of a three-dimensional region to be specified next based on three-dimensional volume data indicating a center line of the tubular tissue specified by the center line specifying unit.
The medical image processing apparatus according to claim 3, wherein: The center line specifying unit specifies a center line of the tubular tissue as three-dimensional path data,
The medical image processing apparatus further includes an image creating unit that creates an image indicating the tubular tissue based on the three-dimensional path data identified by the center line identifying unit.
The medical image processing apparatus according to claim 1, wherein: The image creation unit,
Create a plurality of types of images showing the tubular tissue, an image calculation unit that calculates the relative positional relationship between each image,
A plurality of created images are displayed in a list on a predetermined display device, and the positional relationships on each display image are associated with each other based on the relative positional relationship between the images calculated by the image calculation unit. And a display control unit for displaying.
The medical image processing apparatus according to claim 10, wherein:   A non-transitory computer-readable storage medium storing a program for causing a computer to function as the medical image processing apparatus according to claim 1. Using a computer, a medical image processing method for generating an image showing a tubular tissue inside the living body,
Obtaining three-dimensional volume data indicating the inside of the living body;
Based on an arbitrary point specified on the tubular tissue indicated by the three-dimensional volume data, sequentially specifying a cross-sectional area including a cross section of the tubular tissue along the tubular tissue;
Detecting a center position of the tubular tissue in each of the designated cross-sectional areas,
Acquiring three-dimensional path data indicating a center line of the tubular tissue based on the detected center position;
Generating and displaying an image indicating the tubular tissue based on the acquired three-dimensional path data;
A medical image processing method comprising: The step of designating the cross-sectional area includes:
Based on the specified arbitrary point, to specify the cross-sectional area by sequentially specifying a region orthogonal to the longitudinal direction of the tubular tissue along the tubular tissue,
14. The medical image processing method according to claim 13, wherein: The step of designating the cross-sectional area includes:
Specifying the cross-sectional area by sequentially specifying a predetermined three-dimensional area based on the specified arbitrary point along the tubular tissue;
15. The medical image processing method according to claim 13, wherein: The step of detecting the center position includes:
Setting a threshold value for predetermined characteristic information included in the three-dimensional volume data;
Imaging each cross-sectional area using characteristic information corresponding to the set threshold,
By changing the threshold value, the step of visualizing a tube cross section of the tubular tissue on an image, further comprising:
By detecting the center position of the image showing the revealed tube section, the center position of the tube section is detected,
The medical image processing method according to any one of claims 13 to 15, wherein: The step of detecting the center position is based on a change in an image area that changes in accordance with the change in the threshold value, and determines whether or not a cross section of the tubular tissue has been exposed on the image.
17. The medical image processing method according to claim 16, wherein: The step of detecting the center position, the image appearing at the center of the cross-sectional area, is contained in the cross-sectional area, and, when the change in area according to the change of the threshold value is the maximum, Determine that the cross section of the tubular tissue has become apparent,
The medical image processing method according to claim 17, wherein: The step of generating and displaying an image indicating the tubular tissue includes generating a plurality of types of images of the tubular tissue based on the three-dimensional path data, and displaying all or any of the generated images in a predetermined manner. List on the device,
The medical image processing method according to any one of claims 13 to 18, wherein: The step of generating and displaying an image indicating the tubular tissue is associated with the positional relationship on each image displayed in the list, and dynamically linked on the display image,
20. The medical image processing method according to claim 19, wherein: The step of generating and displaying an image indicating the tubular tissue includes creating, as the plurality of types of images, at least a three-dimensional image and a two-dimensional image of the tubular tissue.
21. The medical image processing method according to claim 19, wherein: In the step of generating and displaying the image indicating the tubular tissue, a CPR (Curved Planer Reconstruction) image is created as a two-dimensional image, and at least the positional relationship between the created three-dimensional image and the CPR image is associated with each other. indicate,
22. The medical image processing method according to claim 21, wherein: Generating and displaying an image showing the tubular tissue,
Converting the three-dimensional path data into two-dimensional path data;
Associating the three-dimensional path data with the converted two-dimensional path data.
At least displaying a list of images based on the three-dimensional path data and images based on the converted two-dimensional path data,
The medical image processing method according to any one of claims 19 to 22, wherein: The step of generating and displaying an image indicating the tubular tissue acquires predetermined supplementary information and causes a list to be displayed together with the generated images.
The medical image processing method according to any one of claims 19 to 23, wherein: A program causing a computer to execute each step of the medical image processing method according to claim 13.

Images