JP2007202957A - Wall motion measuring device and medical image diagnostic apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide technique which can evaluate the wall motion of the heart based on a heart image acquired by various kinds of medical image diagnostic apparatuses. <P>SOLUTION: The trait point designation processing section 3 of a wall motion measuring device 1 designates trait points in the image areas Ci of the coronary arteries extracted from each of two or more heart images Gi. An identification information grant processing section 4 gives identification information to each designated specifying point. A trait point verification section 51 performs the verification of the trait points of heart images Gi, G(i+1) of a continuous frame by reference to the given identification information. A displacement calculation section 53 computes displacement between frames in the heart images Gi, G(i+1) about the compared trait points. An indication section 57 indicates the heart image for indication in which indication color according to the computed displacement between the frames is designated. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a wall motion measuring apparatus and a medical image diagnostic apparatus for evaluating a motion state of a heart.

  Evaluation of heart wall motion (contraction, dilation) is widely used for diagnosis of the heart's operating state. For example, it is used for diagnosis of a disease state by comparing the wall motion state of a healthy person and a patient, and for confirming a surgical result by comparing the wall motion state before and after surgery.

  Patent Document 1 discloses a conventional device used for evaluation of heart wall motion. This apparatus obtains image data representing information in the subject, extracts a plurality of feature points whose position movement can be traced based on the image data, tracks the movement of the feature points, and tracks the tracking of the feature points. A specific physical parameter is calculated based on the result. This apparatus performs the process on the ultrasonic image formed by the ultrasonic diagnostic apparatus.

  In recent years, it has been developed in response to requests to evaluate heart wall motion based on CT images formed by X-ray CT (Computed Tomography) devices and MRI images formed by MRI (Magnetic Resonance Imaging) devices. Is underway.

  For example, Patent Document 2 discloses an invention for evaluating heart wall motion based on CT images. According to the present invention, a heart contour is extracted from a plurality of heart images obtained continuously in time series, a predetermined feature point is determined from the heart contour, and the feature points in the plurality of heart images are associated with each other. It is configured to calculate the momentum of the point and determine whether or not the heart wall motion is abnormal using fuzzy reasoning based on the momentum of the feature point.

  Patent Document 3 discloses an invention for evaluating heart wall motion based on an MRI image. The present invention uses an electrocardiogram-synchronized cine magnetic resonance imaging method of the heart, and performs variability dependent filter (V-filter) processing on the cine MRI image, and differential processing is performed on the image after the V-filter processing. In addition, a thinning process is performed to form a boundary between the intraventricular blood and the myocardial intima to determine the volume of the intraventricular lumen, and to obtain a time-varying curve of the intraventricular lumen volume in each cross section of the heart. It is configured to perform Fourier series approximation on the time change curve of the volume, and evaluate the heart wall motion using the intraventricular volume curve and the differential curve of the intraventricular volume curve approximated by the Fourier series. .

JP 2003-250804 A JP 2005-237555 A JP 2005-270491 A

  However, the inventions described in Patent Documents 2 and 3 perform evaluation based on the contour motion of the heart image (motion of feature points set on the contour). Only evaluation is possible. Therefore, in these inventions, it is difficult to effectively evaluate the wall motion in the region other than the contour of the heart image.

  It is also possible to evaluate wall motion based on heart images acquired by various types of medical image diagnostic devices, such as 4D CT images and MRI images (3D moving images) that have recently attracted attention. Technology is demanded.

  This invention is made in view of such a situation, and provides the technique which can evaluate the wall motion of the heart based on the heart image acquired by various types of medical image diagnostic apparatuses. It is aimed.

  Another object of the present invention is to provide a technique capable of evaluating wall motion over a wide range of cardiac images.

  In order to achieve the above object, the invention according to claim 1 is a wall motion measuring apparatus for measuring a state of wall motion of a heart based on a plurality of heart images forming a moving image of the heart, For each of the plurality of heart images, a feature point designating unit that designates at least a feature point in the image area of the coronary artery, and the designated feature points based on two or more heart images of the plurality of heart images And an information presenting means for presenting wall motion information indicating the change state of the position.

  According to a sixteenth aspect of the present invention, there is provided an image acquisition means for acquiring a plurality of heart images forming a moving image of the heart, and a coronary artery image for extracting a coronary artery image region from each of the acquired plurality of heart images. Based on extraction means, feature point designation means for designating at least feature points in the image area of the extracted coronary artery for each of the plurality of heart images, and two or more heart images of the plurality of heart images And an information presenting means for presenting wall motion information indicating a change state of the position of the designated feature point.

  The wall motion measuring device according to the present invention designates a feature point in at least an image area of a coronary artery for each of a plurality of heart images forming a moving image of the heart, and two or more of the plurality of heart images. Based on the image, it is configured to present wall motion information indicating a change state of the position of the feature point. Therefore, according to this wall motion measuring apparatus, it is possible to evaluate the wall motion of the heart based on the heart images acquired by various types of medical image diagnostic apparatuses.

  Further, since the displacement state of the feature point designated in the coronary artery distributed over a wide range of the surface of the heart can be grasped, it is possible to evaluate the wall motion over the wide range of the heart image.

  According to the medical image diagnostic apparatus of the present invention, a plurality of heart images that form a moving image of the heart are acquired and a coronary artery image region is extracted, and at least a feature point is specified in the coronary artery image region, It is configured to present wall motion information indicating a change state of the position of the feature point based on two or more heart images of the heart images. Therefore, the wall motion can be evaluated over a wide range of the heart image.

  An example of a preferred embodiment of a wall motion measuring apparatus and a medical image diagnostic apparatus according to the present invention will be specifically described with reference to the drawings.

  The wall momentum measuring apparatus according to the present invention has a function of designating a feature point in an image region of a coronary artery in each heart image for each of a plurality of heart images forming a moving image of the heart. And about the feature point designated with respect to two or more heart images of these multiple heart images, the wall motion information indicating the change state of the position of the feature points in the two or more heart images is presented. It is configured. In particular, it is configured so that the state of wall motion in various parts of the heart can be easily grasped by displaying the change state of the positions of a plurality of feature points in different colors.

  The medical image diagnostic apparatus according to the present invention captures a medical image (moving image) of the heart of a subject such as an X-ray CT apparatus, an MRI apparatus, an ultrasonic diagnostic apparatus, a nuclear medicine diagnostic apparatus (PET, SPECT, etc.). It is a medical image diagnostic apparatus in any possible form. And it has the function to extract the image area | region of a coronary artery from the several heart image which forms the image | photographed moving image of the heart, and has the same function as the wall motion measuring apparatus which concerns on this invention.

<First Embodiment>
[Device configuration]
First, the wall motion measuring apparatus according to the present invention will be described. The block diagram shown in FIG. 1 represents an example of the overall configuration of the wall motion measuring apparatus.

  A wall motion measuring apparatus 1 shown in FIG. 1 is connected to a network installed in a medical institution, for example. A medical image diagnostic apparatus 1000 and a database 2000 are connected to this network.

  The medical image diagnostic apparatus 1000 is an arbitrary form of medical image diagnostic apparatus such as an X-ray CT apparatus, an MRI apparatus, an ultrasonic diagnostic apparatus, and a nuclear medicine diagnostic apparatus. The number of installed medical image diagnostic apparatuses 1000 is not limited to one, and a plurality of the same or various types of medical image diagnostic apparatuses can be installed.

  The database 2000 also has a large-capacity storage device (such as a hard disk drive) that stores medical information such as medical images acquired by the medical image diagnostic apparatus 1000, and a computer program that manages the medical information stored in the storage device. It is comprised including. As this database 2000, for example, a database incorporated in a medical information system such as PACS (Picture Archiving and Communication System), RIS (Radiology Information System), or HIS (Hospital Information System) can be applied.

  The wall motion measuring apparatus 1 can execute a process described later on a moving image of the heart directly input from the medical image diagnostic apparatus 1000, or can be described later on a moving image of the heart stored in the database 2000. It is also possible to execute the process. This moving image is a four-dimensional heart image composed of a plurality of three-dimensional heart images.

  Note that the three-dimensional image means a pseudo three-dimensional image displayed on a two-dimensional display screen of a display (described later). Examples of the three-dimensional image include a pseudo three-dimensional image generated by rendering volume data obtained by an X-ray CT apparatus or an MRI apparatus.

  A predetermined coordinate system is set for the medical image formed by the medical image diagnostic apparatus 1000. In the three-dimensional image, for example, the z coordinate is set in the body axis direction of the subject, the x coordinate is set in one direction on a plane orthogonal to the z coordinate, and the x coordinate and the z coordinate are orthogonal. The y direction is set as the direction. Hereinafter, description will be made assuming that such a coordinate system is set in advance.

  This wall motion measuring device 1 includes a computer. This computer is provided with a microprocessor such as a CPU and MPU, a RAM, a ROM, a hard disk drive, a display such as an LCD and a CRT, an input operation device such as a mouse and a keyboard, and a communication device such as a LAN card and a modem. .

  The computer hard disk drive stores in advance a computer program that causes the wall motion measuring apparatus 1 to execute processing described later. The computer program is stored in a server on the network, and the wall motion measuring device 1 can read out the computer program to execute processing described later.

  The wall motion measuring apparatus 1 includes a coronary artery extraction processing unit 2, a feature point designation processing unit 3, an identification information addition processing unit 4, a wire model creation unit 38, a feature point matching unit 51, a disappearance feature point processing unit 52, and a displacement calculation unit 53. , A feature point mapping unit 54, an interpolation processing unit 55, a display color designating unit 56, and a display unit 57. Hereinafter, each of these components will be specifically described.

[Coronary Artery Extraction Processing Unit]
The coronary artery extraction processing unit 2 analyzes a heart image input from the medical image diagnostic apparatus 1000 (or database 2000; the same applies hereinafter), and extracts an image area of the coronary artery. The coronary artery extraction processing unit 2 includes a microprocessor that executes image analysis in accordance with the computer program.

  An example of a heart image input from the medical image diagnostic apparatus 1000 is shown in FIG. A heart image Gi shown in the figure is one of a plurality of heart images that form a moving image representing the pulsation of the heart. The medical image diagnostic apparatus 1000 captures a heart moving image by capturing a plurality of heart images (still images) Gi (i = 1 to n) at a predetermined imaging interval (frame rate). get. Each heart image Gi is an image representing a state of a moving heart in a certain time phase.

  In the heart image Gi, the image area Ci of the coronary artery is expressed with a brightness and color different from those of other image areas (particularly the peripheral area of the coronary artery). The coronary artery extraction processing unit 2 extracts the image area Ci of the coronary artery by analyzing the luminance and color of the heart image.

  For example, the coronary artery extraction processing unit 2 first determines the root position ci of the coronary artery in the image area Ci of the coronary artery. The coronary artery is a blood vessel that branches from the base of the aorta and stretches around the surface layer of the heart, and supplies blood to the myocardium. The coronary artery extraction processing unit 2 specifies the root position of the aorta (the user may specify it manually), and analyzes the pixel value (pixel value) in the vicinity of the specified position to determine the root position ci of the coronary artery. Extract. At this time, the coronary artery extraction processing unit 2 extracts one or both of the root position of the right coronary artery (the root position ci on the left side in FIG. 2) and the root position of the left coronary artery (the root position ci on the right side in FIG. 2). Do.

  Next, the coronary artery extraction processing unit 2 selects a pixel (coordinate value) having a pixel value substantially equal to the extracted root position ci of the coronary artery from pixels forming the heart image Gi, so that an image region of the coronary artery Ci is extracted. By tracing the pixels of the extracted image region Ci, the blood flow direction of the coronary artery can be specified. The blood flow direction is obtained for each pixel of the image area Ci of the coronary artery, for example.

  FIG. 3 shows an image area Ci of the coronary artery extracted from the heart image Gi. The coronary artery extraction processing unit 2 extracts the coronary artery image regions C1 to Cn for each of the plurality of heart images G1 to Gn. The extracted image data of the coronary artery image area Ci (pixel data of each pixel (coordinate values and pixel values)) is input to the feature point designation processing unit 3, the identification information addition processing unit 4, and the erasure feature point processing unit 52, respectively. Is done. At this time, together with the image data of the image area Ci of each coronary artery, data specifying the pixel corresponding to the root position ci of the coronary artery (root position specifying data) and data specifying the blood flow direction of blood flowing in the coronary artery (blood (Flow direction specifying data) may be input.

[Feature Point Specification Processing Unit]
The feature point designation processing unit 3 performs a process of designating feature points in the image areas C1 to Cn of a plurality of coronary arteries extracted by the coronary artery extraction processing unit 2. The feature point means a characteristic part in the image area Ci of the coronary artery. As an example of the feature point, there are a branch position and a tip position of a coronary artery (described later). In addition, the bending position of the coronary artery can be used as a feature point. This feature point designation processing unit 3 corresponds to an example of “feature point designation means” of the present invention.

  The feature point designation processing unit 3 of this embodiment includes a root position extraction unit 31, a blood vessel tracking unit 32, a cross section detection unit 33, a cross section determination unit 34, a branch position extraction unit 35, a tip position extraction unit 36, and a feature point designation unit 37. It is comprised including. Each of these units is configured to include a microprocessor or the like that executes processing to be described later according to the above computer program. Hereinafter, each of these parts will be described in detail.

(Root position extraction unit)
The root position extraction unit 31 performs a process of extracting the root position ci of the coronary artery in the coronary artery image region Ci for each of the coronary artery image regions C1 to Cn. The root position extraction unit 31 extracts the root position ci in the image area Ci of each coronary artery based on, for example, the image data input from the coronary artery extraction processing unit 2 and the root position specifying data. The root position extraction unit 31 corresponds to an example of “root position extraction unit” of the present invention.

(Blood vessel tracking part)
For each of the coronary artery image regions C1 to Cn, the blood vessel tracking unit 32 performs processing for tracking the coronary artery image region Ci in the direction of blood flow starting from the root position ci of the coronary artery extracted by the root position extraction unit 31. Do.

  The blood vessel tracking unit 32 performs the coronary artery tracking processing based on the image data input from the coronary artery extraction processing unit 2 and the blood flow direction specifying data. For example, first, the blood flow direction at the root position ci is specified based on the blood flow direction specifying data, and an expression of a plane orthogonal to the blood flow direction is obtained, and an intersection region (almost) of the plane and the blood vessel wall of the coronary artery is obtained. To be circular). Then, the center position of the intersection area (the center of the circle, the center of gravity of the planar figure surrounded by the intersection area, etc.) is obtained, and the center position is set as the starting pixel of the tracking process.

  Next, the blood vessel tracking unit 32 specifies a pixel located in the blood flow direction in the pixel that is the starting point of the root position ci based on the blood flow direction specifying data, and specifies a pixel located in the blood flow direction in the pixel. Then, the image area Ci of the coronary artery is traced along the blood flow direction by sequentially performing the processes of. Note that, at each stage of tracking, it is also possible to obtain the intersection area and track its center position.

  It is also possible to perform a thinning process on the coronary artery image area Ci, and to execute the tracking process of the coronary artery image area Ci along the pixels forming the thinned image. The blood vessel tracking unit 32 corresponds to an example of the “blood vessel tracking means” of the present invention.

(Cross section detector)
The cross-section detection unit 33 performs processing for detecting a blood vessel cross-section in a direction (almost) perpendicular to the blood flow direction of the coronary artery. More specifically, the cross-section detection unit 33 acquires the blood flow direction at a certain pixel position from the blood flow direction specifying data, and obtains an expression of a plane orthogonal to the blood flow direction. Then, the cross-section detection unit 33 obtains an intersection area between this plane formula and the blood vessel wall of the coronary artery. Thereby, the coordinate value (and pixel value) of the pixel of the blood vessel cross section at the position of the pixel is acquired. The cross section detector 33 corresponds to an example of the “cross section detector” of the present invention.

  The cross-section detector 33 detects a blood vessel cross-section at a predetermined interval (predetermined pixel interval) as the coronary artery image region Ci is tracked by the blood vessel tracking unit 32. FIG. 4 shows an outline of the process executed by the cross-section detection unit 33. As shown in the figure, the cross-section detection unit 33 detects a blood vessel cross-section sj in a direction orthogonal to the blood flow direction dj at the pixel gj (j = 1 to M) at a predetermined pixel interval.

(Cross-section judgment part)
The cross section determination unit 34 determines the number of blood vessel cross sections detected by the cross section detection unit 33, and based on the number, whether or not a feature point exists in the vicinity of the blood vessel cross section, and if it exists, Processing to determine the type of the feature point is performed.

  First, the number of blood vessel cross sections will be described. FIG. 5 shows an aspect of the blood vessel cross section around the branch position of the coronary artery. The cross-section detector 33 detects the blood vessel cross-section sj in the pixel gj upstream of the coronary artery branch position. Next, the cross-section detector 33 detects a blood vessel cross-section at a pixel located at a position displaced from the pixel gj in the blood flow direction dj by a predetermined pixel interval.

  At this time, the cross-section detection unit 33 is configured so as to detect only pixels in a region separated by a predetermined distance in a direction orthogonal to the blood flow direction dj, and pixels of blood vessels other than the blood vessel after the branch are detected. It is desirable to prevent this situation. The predetermined distance can be determined according to, for example, the blood vessel diameter of the blood vessel (for example, “predetermined distance = three times the blood vessel diameter of the blood vessel”).

  When the position displaced by a predetermined pixel distance from the pixel gj is on the downstream side of the branch position, there are two or more pixels to be subjected to cross-section detection next. In FIG. 5, since the branch is bifurcated, the cross section is detected at the two pixels g (j + 1) and g (j + 1) ′ at the next stage of the pixel gj, and the blood vessel cross section s (j + 1) is obtained. ), S (j + 1) ′.

  The cross section determination unit 34 determines the number of cross sections detected at each stage by the cross section detection unit 33. This determination process can be determined by referring to, for example, the number of pixels on which cross-section detection is performed, or can be determined based on the connection state of pixels forming a blood vessel cross-section.

  The connected state has the following meaning. That is, one blood vessel cross section is formed by a closed curve composed of adjacent pixels. Mathematically speaking, this indicates that the detected blood vessel cross section contains only one connected component. On the other hand, when there are a plurality of blood vessel cross sections, a plurality of closed curves composed of adjacent pixels are obtained and include a plurality of connected components. As described above, by obtaining the number of connected components by referring to the coordinates of all the pixels forming the blood vessel cross section detected by the cross section detecting unit 33, the number of blood vessel cross sections can be obtained.

  Next, determination of the presence of a feature point in the vicinity of a blood vessel cross section and determination of the type of feature point will be described. First, when the number of blood vessel cross sections detected by the cross section detector 33 changes from one to two or more, the cross section determination unit 34 determines that a feature point exists in the vicinity of the position, and the feature point is Judged to be a branch position.

  Also, as shown in FIG. 6, when the number of blood vessel cross sections detected by the cross section detector 33 changes from 1 to 0, it is determined that a feature point exists in the vicinity of the position, and the feature point is a coronary artery. It is determined that the tip position is.

(Branch position extraction unit)
The branch position extraction unit 35 performs a process of extracting the branch position of the blood vessel in the coronary artery image region Ci. The branch position extraction unit 35 corresponds to an example of the “branch position extraction unit” of the present invention.

  The processing of the branch position extraction unit 35 will be described more specifically. The branch position extraction unit 35 operates when the number of blood vessel cross sections detected by the cross section detection unit 33 changes from 1 to 2 or more. For example, as illustrated in FIG. , The equation of a circle or sphere inscribed in the blood vessel wall is obtained based on the image data of the image area Ci of the coronary artery, and the coordinates of the center of the circle or sphere are obtained. The branch position extraction unit 35 defines the coordinates of the center as the coordinates of the target branch position.

  As a method of generating a circle or a sphere inscribed in the blood vessel wall, for example, a crushing process similar to the extraction of the tip position is performed to identify the crotch position f ′ at the branch, and a circle (or sphere) inscribed in the crotch position By enlarging the diameter, a circle (or sphere) inscribed in the blood vessel wall can be obtained.

  The figure inscribed in the blood vessel wall is not limited to a circle or a sphere, and may be inscribed in an arbitrary shape such as an ellipse, an ellipsoid, a polygon or a polyhedron, depending on the shape of the blood vessel wall of the coronary artery. Figures can be used. In this case, a position uniquely obtained from the inscribed figure such as the center of gravity, inner center, and outer center of the generated inscribed figure can be used as the branch position.

  Such various positions used as branch positions are collectively referred to as “center positions”. The center position is preferably defined on the image area Ci of the coronary artery, and more preferably defined on the inscribed graphic (if the branch position is defined on the inscribed graphic, the branch position is automatically set. Because it is defined on the image area Ci.)

(Tip position extraction unit)
The tip position extraction unit 36 performs a process of extracting the tip position of the blood vessel in the image area Ci of the coronary artery. The tip position extraction unit 36 corresponds to an example of “tip position extraction means” of the present invention.

  The processing of the tip position extraction unit 36 will be described more specifically. The presence of the tip position of the blood vessel is detected by the method shown in FIG. 6, and the tip position extraction unit 36 determines the coordinates of the tip position by using the method shown in FIG. 8, for example. Can do.

  A position aj shown in FIG. 8 indicates the position of the blood vessel cross section sj in FIG. 6, and a position a (j + 1) indicates a position moved from the blood vessel cross section sj by a predetermined pixel interval in the blood flow direction. The blood vessel cross section sj is detected at the position aj, and the blood vessel cross section is not detected at the next position a (j + 1) (arrow (1) in FIG. 8). Thereby, it is detected that the tip position exists between the position aj and the position a (j + 1) (described above). Here, a distance (pixel interval) between the position aj and the position a (j + 1) is represented by Δa.

  The tip position extraction unit 36 tries to detect a blood vessel cross section at a position a (j + 2) returned from the position a (j + 1) by a distance Δa / 2 in the direction opposite to the blood flow direction (arrow (2)). In the example of FIG. 8, a blood vessel cross section is detected at a position a (j + 2). Next, the tip position extraction unit 36 detects a blood vessel cross section at a position a (j + 3) moved by a distance Δa / 4 from the position a (j + 1) in the blood flow direction (arrow (3)). In the example of FIG. 8, the blood vessel cross section is not detected at the position a (j + 3). Further, the tip position extraction unit 36 tries to detect a blood vessel cross section at a position a (j + 4) that is returned from the position a (j + 3) by a distance Δa / 8 in the direction opposite to the blood flow direction (arrow (4)). In the example of FIG. 8, a blood vessel cross section is detected at a position a (j + 4).

  In this manner, the distal end position extraction unit 36 determines whether the position al where the blood vessel cross section is detected and the position a (l + 1) where the blood vessel cross section is not detected (or the position al where the blood vessel cross section is not detected and the position a (l + 1) where it is detected). The driving is continued until the distance reaches a predetermined δ = Δa / (2 ^ k). Then, the coordinates of an arbitrary position (for example, the middle point) between the position al and the position a (l + 1) at that time are defined as the coordinates of the tip position.

(Feature point specification part)
The feature point designating unit 37 designates each branch position extracted by the branch position extracting unit 35 and each tip position extracted by the tip position extracting unit 36 as feature points. That is, the coordinates of each branch position acquired by the branch position extracting unit 35 and the coordinates of each tip position acquired by the tip position extracting unit 36 are respectively designated as the coordinates of the feature points.

  The feature point designating unit 37 performs the above-described designating process, for example, by adding identification information (such as a flag) to pixel data of a pixel located at these coordinates, or associating these pixel data. The feature point designation unit 37 also designates the root position ci of the coronary artery extracted by the root position extraction unit 31 as the feature point.

[Wire Model Creation Department]
The wire model creation unit 38 creates a wire model image of the coronary artery image region Ci based on the feature points (root position ci, branch position, tip position) designated by the feature point designation unit 37. The wire model creation unit 38 corresponds to an example of the “wire model creation unit” of the present invention. The wire model creation unit 38 is configured to include a microprocessor or the like that executes processing described later in accordance with the computer program.

  A specific example of the wire model creation process will be described. First, the wire model creation unit 38 sequentially connects the root position ci designated by the feature point designation unit 37 and the branch position with a line. Then, for each tip position, the last branch position until the tip position is reached and the tip position are connected by a line. Thereby, a wire model image of the image area Ci of the coronary artery is obtained.

  At this time, the line (connection line) connecting the two feature points may be a straight line, or a curve or a polygonal line reflecting the form of the image area Ci of the coronary artery. When the latter is adopted, the wire model creation unit 38 creates a connection line based on arbitrary information indicating the form of the coronary artery image region Ci, such as a thinned image of the coronary artery image region Ci or blood flow direction specifying data. .

  FIG. 9 shows an example of a wire model image of the coronary artery image region Ci created by the wire model creation unit 38. The wire model image Wi (i = 1 to n) shown in the figure is created based on the coronary artery image area Ci in FIG. 3, and each root position ci of each coronary artery, each branch position f, It is an image formed by connecting the tip position h with a connecting line in the order corresponding to the blood flow direction.

[Identification information addition processing unit]
The identification information provision processing unit 4 performs a process of imparting identification information to the feature points designated in each heart image Gi in a predetermined order. The identification information addition processing unit 4 together with the root position extraction unit 31 and the branch position extraction unit 35 constitutes an example of the “identification information addition unit” of the present invention.

  The identification information addition processing unit 4 includes a cross-sectional size detection unit 41, a blood vessel tracking unit 42, and an identification information addition unit 43. Each of these units is configured to include a microprocessor or the like that executes processing to be described later according to the above computer program. Hereinafter, an example of the configuration of each of these units will be specifically described.

(Cross section size detector)
The cross-sectional size detection unit 41 performs a process of detecting the cross-sectional size of each blood vessel after branching (each blood vessel downstream from the branch position) at the blood vessel branch position extracted by the branch position extraction unit 35.

  Here, the “size” of the blood vessel cross section refers to the length of the diameter of the blood vessel cross section (in the case of a circular cross section, the diameter and radius, in the case of an elliptic cross section, the major axis diameter and the minor axis diameter, etc.) In the case of a cross-section of a shape, it means an arbitrary amount that reflects the size of the blood vessel cross section, such as the diameter in any direction), the cross-sectional area of the blood vessel cross-section, and the circumference of the blood vessel wall in the blood vessel cross-section To do.

  For example, the cross-sectional size detection unit 41 includes information on the coordinates of each branch position input from the branch position extraction unit 35, image data of the coronary artery image region Ci input from the coronary artery extraction processing unit 2, and blood flow direction specifying data. Based on the above, the cross-sectional size of each blood vessel located downstream of each branch position is detected.

  First, the cross-sectional size detection unit 41 specifies the branch position in the image area Ci of the coronary artery using the coordinate information of each branch position. Next, the cross-sectional size detection unit 41 determines a position (cross-sectional size detection position) advanced from the branch position by a predetermined distance (pixel interval) in the blood flow direction for each blood vessel downstream of the specified branch position. To do.

  Subsequently, the cross-section size detection unit 41 performs the same processing as that of the cross-section detection unit 33 described above, and acquires a blood vessel cross-section at the cross-section size detection position. Then, the cross-sectional size detection unit 41 calculates the size of the blood vessel cross-section, for example, by counting the number of pixels or calculating the distance between the pixels.

  The cross-sectional size detection unit 41 performs the above-described processing on each branch position input from the branch position extraction unit 35, and acquires the cross-sectional sizes of all blood vessels on the downstream side of each branch position.

(Blood vessel tracking part)
The blood vessel tracking unit 42 tracks the wire model image Wi created by the wire model creating unit 38 from the root position ci of the coronary artery along the blood flow direction. The tracking process by the blood vessel tracking unit 42 is executed in the same manner as the blood vessel tracking unit 42 described above.

(Identification information giving unit 43)
The identification information assigning unit 43 assigns identification information to the feature point designated in the wire model image in accordance with the tracking of the wire model image by the blood vessel tracking unit 42. This identification information is information including a character string or the like for identifying each feature point. Hereinafter, the identification information provision process by the identification information provision process part 4 is demonstrated, referring FIG. FIG. 10 shows an example of a manner of giving identification information to the wire model image Wi (only the right coronary artery) shown in FIG.

  The tracking by the blood vessel tracking unit 42 is started from the root position ci of the coronary artery as described above. The identification information giving unit 43 gives the identification information “0 (i)” to the root position ci. The cross-sectional size detector 41 detects the cross-sectional sizes of the two blood vessels that are branched at the root position ci.

  The blood vessel tracking unit 42 defines a blood vessel having a larger cross-sectional size (a blood vessel on the left side in FIG. 10) as a main blood vessel (main stream MS), and a blood vessel having a smaller cross-sectional size (a blood vessel on the right side in the paper also). It is defined as a blood vessel tributary (substream SS).

  The blood vessel tracking unit 42 tracks the substream SS to the next branch position along the blood flow direction. The identification information giving unit 43 gives the identification information “0-1 (i)” to this branch position. The cross-sectional size detection unit 41 detects the cross-sectional sizes of the two blood vessels after branching at this branching position. The blood vessel tracking unit 42 tracks the blood vessel on the side having a larger cross-sectional size (main stream in the substream SS) to the tip position along the blood flow direction. The identification information giving unit 43 gives the identification information “0-2 (i)” to the tip position. In addition, the blood vessel tracking unit 42 tracks the blood vessel on the side having a smaller cross-sectional size (substream in the substream SS) to the tip position along the blood flow direction. The identification information giving unit 43 gives the identification information “0-0-1 (i)” to the tip position.

  In addition, the blood vessel tracking unit 42 tracks the main stream MS to the next branch position along the blood flow direction. The identification information adding unit 43 adds identification information “1 (i)” to this branch position. The cross-sectional size detection unit 41 detects the cross-sectional sizes of the two blood vessels after branching at this branching position. The blood vessel tracking unit 42 defines a blood vessel having a larger cross-sectional size as a continuation of the main stream MS, and defines a blood vessel having a smaller cross-sectional size as a new substream. The identification information addition processing unit 4 adds identification information to the feature points on the new substream in the same manner as the substream SS.

  The blood vessel tracking unit 42 further tracks the main stream MS along the blood flow direction to the next branch position. The identification information giving unit 43 gives the identification information “2 (i)” to this branch position. The cross-sectional size detection unit 41 detects the cross-sectional sizes of the two blood vessels after branching at this branching position. The blood vessel tracking unit 42 defines a blood vessel having a larger cross-sectional size as a continuation of the main stream MS, and defines a blood vessel having a smaller cross-sectional size as a new substream. The identification information addition processing unit 4 adds identification information to the feature points on the new substream in the same manner as the substream SS.

  In this way, the identification information “0 (i)”, “1 (i)”, “2 (i)”, “3 (i) is added to the feature points on the main stream MS of the wire model image Wi (right coronary artery). ) ”,“ 4 (i) ”,“ 5 (i) ”,“ 6 (i) ”, respectively, and identification information“ 0 (i) ”to“ 5 (i) ”. Identification information is sequentially given to the feature points on each substream branched at the branch position.

  The character string “(i)” attached to the end of each identification information indicates that the identification information is attached to the feature point of the i-th heart image Gi. This character string “(i)” will be referred to as an image identification unit, and the other character string will be referred to as a feature point identification unit. For example, in the identification information “1-1 (i)”, “1-1” is a feature point identification unit, and “(i)” is an image identification unit.

  Note that the identification information given to the feature points is not limited to the above-described ones, and any form of identification information that enables identification of each feature point can be applied. However, as in this embodiment, it is desirable to use identification information that hierarchically represents the branching mode of feature points.

[Feature Point Matching Section]
The feature point matching unit 51 performs processing for matching a feature point of the heart image Gi and a feature point of the heart image G (i + 1) corresponding to the next time phase for the heart image Gi of a certain time phase. . That is, the feature point matching unit 51 associates the feature points specified in the heart image Gi and the feature points specified in the heart image G (i + 1) with respect to the heart images Gi and G (i + 1) of successive frames.

  It should be noted that instead of collating feature points between two successive time phase (two consecutive frames) heart images in this way, the feature points specified in the heart image Gi and any other heart image Gi ′ You may make it perform the process which collates with the feature point designated by (i '≠ i).

  The feature point matching unit 51 corresponds to an example of the “feature point matching unit” of the present invention. Further, the feature point matching unit 51 is configured to include a microprocessor or the like that executes processing described later in accordance with the computer program.

  The feature point matching unit 51 matches feature points by referring to the identification information given to the feature points of the wire model images Wi and W (i + 1) of the heart images Gi and G (i + 1).

  FIG. 11 shows the wire model image W (i + 1) of the heart image G (i + 1) and the identification information given to the feature points. This wire model image W (i + 1) has the feature points to which the identification information 2 (i) and 2-1 (i) are assigned among the feature points of the wire model image Wi in FIG. 10 and a connection line connecting them. Not done. The cause is that the blood vessel corresponding to the connection line has not been photographed due to the orientation of the heart when the heart image G (i + 1) is photographed, and the feature point (branch position) by the feature point designation processing unit 3. It is conceivable that was not extracted effectively. Therefore, the feature points after the feature point 3 (i) of the wire model image Wi are those in which the first number is lowered by one in the wire model image W (i + 1) (for example, the wire model image Wi). The feature point 3 (i) is the feature point 2 (i + 1) in the wire model image W (i + 1).

  For example, the feature point matching unit 51 first compares the hierarchical structure (branch form) of feature points based on the identification information assigned to the feature points of the wire model images Wi and W (i + 1). If the mutual hierarchical structure is the same, it is determined that all feature points on both wire model images Wi, W (i + 1) are the same. Then, each feature point of the wire model image Wi is associated with a feature point of W (i + 1) to which identification information having the same feature point identification unit as that of the identification information is attached. This association is performed, for example, by associating pixel data of each feature point.

  When the hierarchical structure of feature points is different as shown in FIGS. 10 and 11, the feature point matching unit 51 extracts feature points from one wire model image (here, the wire model image W (i + 1)). It is determined that there is a leak, and feature points that are not extracted are specified. As the specifying method, for example, first, the hierarchical structures of both pieces of identification information are compared, and the number of feature points on the main stream is compared.

  In the above example, the identification information “0 (i)”, “1 (i)”, “2 (i)”, “3 (i)”, “4 (i) is displayed on the main stream of the wire model image Wi. ) ”,“ 5 (i) ”,“ 6 (i) ”are set, and seven feature points are set on the main stream of the wire model image W (i + 1). ) ”,“ 1 (i + 1) ”,“ 2 (i + 1) ”,“ 3 (i + 1) ”,“ 4 (i + 1) ”,“ 5 (i + 1) ”are set. ing. The feature point matching unit 51 recognizes that one feature point on the main stream of the wire model image W (i + 1) has not been extracted.

  Next, the feature point matching unit 51 compares the hierarchical structures of the substreams branched from each branch position (feature point), and identifies which feature point has not been extracted.

  In the above example, first, the substream hierarchical structure “0-1 (i) → 0-2 (i), 0-1 (i) → 0-1 from the feature point 0 (i) of the wire model image Wi. −1 (i) ”and the substream hierarchical structure“ 0-1 (i + 1) → 0-2 (i + 1), 0-1 (i + 1) from the feature point 0 (i + 1) of the wire model image W (i + 1) ” → 0-1-1 (i + 1) ". Since both hierarchical structures are the same, a comparison is made in substreams from the next branch position.

  The hierarchical structure of the substream from the next branch position 1 (i) of the wire model image Wi is the same as the hierarchical structure of the substream from the next branch position 1 (i + 1) of the wire model image W (i + 1). Therefore, the feature point matching unit 51 recognizes that the feature point corresponding to the branch position 1 (i) of the wire model image Wi is effectively extracted from the wire model image W (i + 1), and starts from the next branch position. Transition to comparison in the sub-stream.

  The hierarchical structure of the substream from the next branch position 2 (i) of the wire model image Wi is “2-1 (i)”. On the other hand, the hierarchical structure of the substream from the next branch position 2 (i + 1) of the wire model image W (i + 1) is “2-1 (i + 1) → 2-2 (i + 1), 2-1 (i + 1) → 2 -1-1 (i + 1) → 2-1-2 (i + 1), 2-1-1 (i + 1) → 2-1-1-1 (i + 1) ”. These hierarchical structures are different from each other. Thereby, the feature point matching unit 51 determines that the feature point corresponding to the branch position 2 (i) (and the tip position 2-1 (i)) of the wire model image W (i) is from the wire model image W (i + 1). Identify that it was not extracted.

  Furthermore, the feature point matching unit 51 determines the hierarchical structure of the substream from the branch position 2 (i + 1) of the wire model image W (i + 1) and the substream from the next branch position 3 (i) of the wire model image Wi. Compared with the hierarchical structure, it is confirmed that the feature point corresponding to the branch position 2 (i) is not extracted, and the feature point corresponding to the branch position 2 (i + 1) is the branch position 3 (i). Make sure that there is. Further, the feature point matching process may be performed with reference to information such as the coordinates of the feature points and the distance between the feature points.

  By executing the above processing for each substream, the feature points of the wire model image Wi and the feature points of the wire model image W (i + 1) are collated, and the collated feature points are associated with each other. A feature point that does not have an associated feature point is called a single feature point, and a feature point that has not been extracted is called a lost feature point.

[Disappearance feature point processing section]
The erasure feature point processing unit 52 performs processing related to the erasure feature point (and the single feature point). The erasure feature point processing unit 52, for example, instructs to ignore the single feature point corresponding to each erasure feature point and perform the subsequent processing, or estimates the position of the erasure feature point to complement the erasure feature point. Or perform processing. The position of the disappearing feature point can be estimated from the positional relationship between the single feature point and the surrounding feature points, for example. In addition, for example, it is possible to instruct that the disappearance feature point of the thick blood vessel such as the main stream is complemented and the single feature point of the thin blood vessel is ignored.

  In the following, processing is performed ignoring single feature points. The erasure feature point processing unit 52 is configured to include a microprocessor or the like that executes processing described later in accordance with the computer program.

(Displacement calculation unit)
For the feature points collated by the feature point collating unit 51, the displacement calculating unit 53 displaces the position of the feature point specified in one heart image Gi and the position of the feature point specified in the other heart image Gi ′. The process which calculates is performed. The displacement calculation unit 53 includes a microprocessor or the like that executes processing described later in accordance with the computer program. The displacement calculator 53 corresponds to an example of the “displacement calculator” of the present invention.

  Here, “displacement” means “displacement amount” indicating the displaced distance, or both “displacement amount” and “displacement direction”. That is, the “displacement” may indicate only the “displacement amount” that is a scalar amount, or may indicate the “displacement amount” and the “displacement direction” that are vector amounts.

  In the example of FIGS. 10 and 11, the feature point matching unit 51 associates the feature points of the wire model image Wi and the feature points of the wire model image W (i + 1) as follows (the association is “˜”). 0 (i) to 0 (i + 1); 1 (i) to 1 (i + 1); 3 (i) to 2 (i + 1); 4 (i) to 3 (i + 1); 5 (i) to 4 ( i + 1); 6 (i) to 5 (i + 1); 0-1 (i) to 0-1 (i + 1); 0-2 (i) to 0-2 (i + 1); 0-1-1 (i) to 0-1-1 (i + 1); 1-1 (i) to 1-1 (i + 1); 1-2 (i) to 1-2 (i + 1); 1-3 (i) to 1-3 (i + 1) 1-1-1 (i) to 1-1-1 (i + 1); 1-2-1 (i) to 1-2-1 (i + 1); 3-1 (i) to 2-1 (i + 1) 3-2 (i) to 2-2 (i + 1); 3-1. 1 (i) to 2-1-1 (i + 1); 3-1-2 (i) to 2-1-2 (i + 1); 3-1-1-1 (i) to 2-1-1-1 (I + 1); 4-1 (i) to 3-1 (i + 1); 5-1 (i) to 4-1.

  For each pair of associated feature points, the displacement calculation unit 53 calculates the displacement amount of the positions of the feature points based on the coordinate values of both feature points. For example, the coordinate value of the feature point 1 (i) of the wire model image Wi is (xi, yi, zi), and the coordinate value of the feature point 1 (i + 1) of the wire model image W (i + 1) is (x (i + 1)). , Y (i + 1), z (i + 1)), the displacement amount of these feature points is Δ1 (i) = {(x (i + 1) −xi) ^ 2 + (y (i + 1) −yi) ^ 2 + Calculated by (z (i + 1) −zi) ^ 2} ^ (1/2) (Euclidean distance). Further, the displacement direction of the feature point can be easily obtained by calculating a (unit) vector from (xi, yi, zi) to (x (i + 1), y (i + 1), z (i + 1)).

  An example of a calculation result by the displacement calculation unit 53 is shown in FIG. The feature point displacement information D shown in the figure is information in which displacements in heart images Gi and G (i + 1) of successive frames are recorded for each feature point.

  In the “frame” column, frame numbers of consecutive frames are recorded. For example, “1, 2” in the “frame” column represents the first frame and the second frame.

  In the “displacement” column, the displacement of the feature point between the frames shown in the “frame” column is recorded. When the displacement calculation unit 53 calculates only the displacement amount, the scalar amount is recorded in the “displacement” column, and when the displacement amount and the displacement direction are calculated, the vector amount is recorded.

  As for the feature point 2 (i), since the single feature point is ignored as described above, no displacement is recorded in the feature point displacement information D. In addition, you may make it complement by calculating the displacement of a single feature point using the displacement of another feature point. For example, an average value of the displacement of the feature point 1 (i) and the displacement of the feature point 3 (i) can be set as the displacement of the feature point 2 (i). Further, weighting is performed by the ratio of the distance between the feature point 1 (i) and the feature point 2 (i) and the distance between the feature point 3 (i) and the feature point 2 (i), so that the feature point 2 (i) The displacement may be calculated.

[Feature point mapping part]
The feature point mapping unit 54 performs a process of mapping the feature point designated by the feature point designating unit 37 to a predetermined heart image (display heart image). The specified feature point is given a coordinate value indicating its position. Further, the same coordinate system as that of the heart image Gi is set for the display heart image. The feature point mapping unit 54 maps the feature points to the display heart image based on the coordinate system set for the display heart image and the coordinate values of each feature point.

  Further, the feature point mapping unit 54 acquires the feature point displacement information D from the displacement calculation unit 53 and associates the displacement information with each feature point mapped to the display heart image. The feature point mapping unit 54 is configured to include a microprocessor or the like that executes processing described later in accordance with the computer program.

[Interpolation processing section]
The interpolation processing unit 55 performs processing for interpolating displacements at positions other than the feature points of the display heart image. More specifically, the interpolation processing unit 55 selects, for example, a feature point around the interpolation position P for an arbitrary interpolation position P of the display heart image, and based on the displacement of the selected feature point. The displacement of the interpolation position P is calculated.

  For selection of feature points around the interpolation position P, for example, feature points mapped to an area that is a predetermined distance or less from the interpolation position P may be selected, or feature points that are close to the interpolation position P are sequentially selected. You may choose. At this time, feature points in a predetermined direction from the interpolation position P may be preferentially selected.

  The displacement ΔP of the interpolation position P can be calculated using, for example, the following equation: The selected feature points are Q1, Q2, and Q3, and the displacements of the feature points Q1, Q2, and Q3 are respectively ΔQ1, ΔQ2, Assuming ΔQ3 and the distances between the feature points Q1, Q2, and Q3 and the interpolation position P are d (Q1), d (Q2), and d (Q3), respectively, ΔP = (d (Q1) × ΔQ1 + d (Q2) × ΔQ2 + d (Q3) × ΔQ3) / (d (Q1) + d (Q2) + d (Q3)). Here, ΔQ1, ΔQ2, and ΔQ3 may be scalar quantities or vector quantities.

  In this way, the interpolation processing unit 55 determines the displacement of one or more interpolation positions. At this time, as shown in the feature point displacement information D, displacement is calculated for each pair of two consecutive frames for each interpolation position. That is, for the interpolation position P, the displacement in frames 1 and 2, the displacement in frames 2 and 3,..., The displacement in frames n−1 and n are calculated. The calculated displacement information is associated with the interpolation position P (its coordinate value). Here, the displacement of the feature point and the interpolation position in the continuous frames k and k + 1 is referred to as “inter-frame displacement”.

  Note that the interpolation processing unit 55 does not operate when it is not necessary to perform displacement interpolation due to a user request or the like. Alternatively, the user may manually set the interpolation position P, or the user may designate a partial region of the display heart image and automatically set the interpolation position P within this designated region. As a result, the displacement state of the region (region of interest (ROI) or the like) in which the user pays attention can be expressed in more detail. The interpolation processing unit 55 is configured to include a microprocessor or the like that executes processing to be described later according to the above computer program.

[Display color specification part]
The display color designating unit 56 designates the display color of each feature point and the interpolation position and the density of the display based on the displacement of the feature point and the interpolation position set in the display heart image. More specifically, the display color designation unit 56 stores in advance information (display color information) for dividing the range of interframe displacement into a plurality of stages and designating the display color at each stage.

  For example, the display color information is obtained by dividing the range of inter-frame displacement into five stages of stage 1 (small displacement) to stage 5 (large displacement). This is information specifying “white”, “yellow”, “orange”, “pink”, “red”.

  In addition, you may make it designate the shade of each display color. For example, with respect to “red” in stage 5, the shade can be designated according to the magnitude of the displacement. Further, when the displacement information is a vector quantity, it is possible to specify different display colors and shades depending on the displacement direction. Thereby, for example, it is possible to display so that the displacement when the heart is contracting and the displacement when the heart is expanding can be identified. In addition, instead of the display color, only shading may be designated. In any case, it is sufficient that the display color information is set so that the feature point and the displacement state of the interpolation position can be identified.

  For each feature point and interpolation position set in the display heart image, the display color designating unit 56 selects a stage corresponding to the displacement from the display color information, and displays the display color and shading (simply “display”) of the selected stage. Is designated as the display color of the feature points. The display color designation unit 56 designates a display color corresponding to each inter-frame displacement for each feature point and interpolation position. The display color designating unit 56 includes a microprocessor, a hard disk drive, and the like that execute processing to be described later according to the above computer program.

[Display section]
The display unit 57 performs processing for displaying a display heart image based on the display color designated by the display color designation unit 56.

  More specifically, the display unit 57 first displays a display heart with a display color corresponding to the first interframe displacement (interframe displacement of frames 1 and 2) of each feature point and interpolation position. Display an image. After a predetermined time has elapsed, the display color is changed to correspond to the second inter-frame displacement. Further, after a predetermined time has elapsed, the display color is changed to correspond to the third inter-frame displacement. In this manner, the display color corresponding to the first inter-frame displacement to the display color corresponding to the (n-1) th inter-frame displacement are sequentially switched and displayed every predetermined time. At this time, for example, if the display color is switched at the same time interval as the frame rate of the moving image of the heart, the displacement of the feature point or the like can be displayed as if it were a moving image.

  If only display information is specified by the display color specifying unit 56, a heart image expressing the displacement of the feature points or the like by the display is displayed.

  The display color designation unit 56 includes a microprocessor, a hard disk drive, a display, and the like that execute processing described later in accordance with the computer program. A display heart image whose display color is switched and displayed at a predetermined time interval corresponds to an example of “wall motion information” of the present invention indicating a change state of a feature point (and an interpolation position).

[Operation]
The operation of the wall motion measuring apparatus 1 having the above configuration will be described with reference to FIG. The flowchart shown in FIG. 13 represents an example of the operation of the wall motion measuring apparatus 1.

  First, a plurality of heart images Gi forming a moving image of the heart are input from the medical image diagnostic apparatus 1000 or the database 2000 to the wall motion measuring apparatus 1 (S1). The coronary artery extraction processing unit 2 of the wall motion measuring apparatus 1 extracts the coronary artery image region Ci from each heart image Gi (S2).

  Next, the feature point designation processing unit 3 designates the feature points of the image area Ci of each coronary artery (S3). The wow model creation unit 38 creates the wire model image Wi of the image area Ci of each coronary artery based on the designated feature point (S4).

  Subsequently, the identification information addition processing unit 4 adds identification information to the feature points of each wire model image Wi (S5). The feature point matching unit 51, for the heart images Gi and G (i + 1) of two consecutive frames, the feature point specified in the heart image Gi (the wire model image Wi) and the wire of the heart image G (i + 1) ( The feature point designated in the model image W (i + 1)) is collated (S6). The displacement calculation unit 53 calculates the interframe displacement between the position of the feature point specified in the heart image Gi and the position of the feature point specified in the heart image G (i + 1) for the matched feature points (S7). .

  Further, the feature point mapping unit 54 maps the feature point designated by the feature point designating unit 37 to the display heart image (S8). The interpolation processing unit 55 calculates the interframe displacement at each interpolation position of the display heart image (S9).

  Next, the display color designating unit 56 designates a display color corresponding to the inter-frame displacement for each feature point and interpolation position based on the feature point and interpolation position displacement set in the display heart image (S10). ). The display unit 57 displays the heart image for display and switches the display color of each feature point and interpolation position at predetermined time intervals (S11).

[Action / Effect]
The operation and effect of the wall motion measuring apparatus 1 operating as described above will be described. First, the wall motion measuring apparatus 1 designates feature points in the coronary artery image region Ci for each of a plurality of heart images Gi forming a moving image of the heart, and two heart images Gi of successive frames, It acts to display a display heart image that expresses the change state of the position of the feature point designated for G (i + 1) (that is, the state of wall motion at the feature point) by the difference in display color. This heart image for display expresses the displacement of each feature point according to the time phase by display color and / or shading.

  The heart image Gi used for the processing by the wall motion measuring apparatus 1 is an image taken by any medical image diagnostic apparatus 1000 as described above. Therefore, it is possible to evaluate heart wall motion based on heart images acquired by various types of medical image diagnostic apparatuses.

  Moreover, since the displacement state of the feature point designated on the coronary artery distributed over a wide range of the heart surface can be grasped, it is possible to evaluate the wall motion over the wide range of the heart image. Furthermore, since the displacement state of the part other than the feature point is interpolated and displayed based on the displacement state of the feature point, it is possible to evaluate the wall motion over a wider range and with higher accuracy. Wall motion evaluation becomes possible.

[Modification]
A modification of the wall motion measuring apparatus 1 of this embodiment will be described.

  In the above-described embodiment, feature points are specified only on the coronary artery image region Ci of the heart image Gi. However, it is possible to additionally specify feature points in other regions. For example, the contour region of the heart image Gi, the heart septum, the atrium, the ventricle, the aortic valve, the pulmonary valve, the tricuspid valve, the image region corresponding to a relatively large blood vessel, etc. Can be considered. Thereby, it is possible to evaluate wall motion over a wider range of the heart image.

  Further, the wall motion information presented by the wall motion measuring device 1 is not limited to a display heart image that expresses a displacement state of a feature point or the like with a difference in display color. For example, numerical data such as the feature point displacement information D in FIG. 12 can be displayed.

  Also, the manner of presenting the wall motion information is not limited to the configuration in which the wall motion information is displayed on the display, and any presenting manner such as printing out an image or the like can be employed.

  In the above-described embodiment, a display heart image different from the plurality of heart images Gi acquired by the medical image diagnostic apparatus 1000 is prepared in advance, and the feature points and interpolation positions specified for the display heart image are prepared. The change state of the position of the feature point or the like is expressed by changing the display color of the image. The display color is designated for the feature point or the like on each heart image Gi, and the heart images G1 to Gn are used. Then, by displaying a moving image, a change state of a position such as a feature point may be expressed.

  Further, the feature points and interpolation positions designated in the heart image Gi are connected by a straight line, and the display is set on each surface of the polyhedron image formed thereby to display the wall motion state. You can also Note that the connection line that connects the feature points and the like is not limited to a straight line, and a curved line may be used as appropriate.

<Second Embodiment>
A medical image diagnostic apparatus according to the present invention will be described. In the first embodiment described above, the wall motion measuring device that receives and processes the heart image from the medical image diagnostic device 1000 or the like has been described. However, the function of this wall motion measuring device is mounted on the medical image diagnostic device. What is the medical image diagnostic apparatus of the present invention.

  FIG. 14 shows an example of the configuration of the medical image diagnostic apparatus according to the present invention. In addition, the same code | symbol is attached | subjected to the component similar to 1st Embodiment. The medical image diagnostic apparatus 10 shown in the figure is provided with an image acquisition unit 11 (image acquisition means) that acquires a plurality of heart images Gi forming a moving image of the heart.

  When the medical image diagnostic apparatus 10 is an X-ray CT apparatus, the image acquisition unit 11 irradiates X-rays to the subject from various directions and detects and collects transmitted X-rays. It includes a gantry, a preprocessing device that performs processing (preprocessing) for converting collected data into projection data, an image reconstruction device that reconstructs an image based on projection data, and the like.

  When the medical image diagnostic apparatus 10 is an MRI apparatus, the image acquisition unit 11 includes a superconducting magnet device that applies a static magnetic field or a gradient magnetic field to the subject, and a high-frequency magnetic field to the subject to which the static magnetic field and the gradient magnetic field are added. And an RF coil that detects and collects a resonance signal generated in response thereto, an image reconstruction device that reconstructs an image based on data collected by the RF coil, and the like.

  In other medical image diagnostic apparatuses, a part that collects data representing the internal form of the subject and reconstructs an image based on the collected data functions as the image acquisition unit 11.

  The medical image diagnostic apparatus 10 extracts a coronary artery image region Ci from the heart image Gi acquired by the image acquisition unit 11 (coronary artery extraction processing unit 2), and performs the first implementation on the extracted coronary artery image region Ci. By performing the same processing as that of the form, it operates to present wall motion information.

  According to such a medical image diagnostic apparatus 10, wall motion can be evaluated over a wide range of heart images.

  The configuration specifically described above is merely an example for implementing the wall motion measuring apparatus and medical image diagnostic apparatus of the present invention. Therefore, arbitrary modifications within the scope of the present invention can be made as appropriate.

It is a schematic block diagram showing an example of the whole structure of suitable embodiment of the wall motion measuring apparatus which concerns on this invention. It is a figure showing an example of the heart image input into suitable embodiment of the wall motion measuring apparatus which concerns on this invention. It is a figure showing an example of the image area | region of the coronary artery which suitable embodiment of the wall motion measuring apparatus based on this invention extracts from a heart image. It is a schematic explanatory drawing for demonstrating the process which detects the blood vessel cross section of the image area | region of the coronary artery by suitable embodiment of the wall motion measuring apparatus which concerns on this invention. It is a schematic explanatory drawing for demonstrating the process which judges the number of the blood vessel cross sections of the image area | region of the coronary artery by preferable embodiment of the wall motion measuring apparatus which concerns on this invention. It is a schematic explanatory drawing for demonstrating the process which judges the number of the blood vessel cross sections of the image area | region of the coronary artery by preferable embodiment of the wall motion measuring apparatus which concerns on this invention. It is a schematic explanatory drawing for demonstrating the process which extracts the branch position of the blood vessel of the image area | region of a coronary artery by suitable embodiment of the wall motion measuring apparatus which concerns on this invention. It is a schematic explanatory drawing for demonstrating the process which extracts the front-end | tip position of the blood vessel of the image area | region of a coronary artery by suitable embodiment of the wall motion measuring apparatus which concerns on this invention. It is the schematic showing an example of the wire model image of the image area | region of the coronary artery created by suitable embodiment of the wall motion measuring apparatus based on this invention. It is the schematic showing an example of the provision aspect of the identification information with respect to the wire model image of the image area | region of the coronary artery by suitable embodiment of the wall motion measuring apparatus which concerns on this invention. FIG. 5 is a schematic diagram showing an example of a mode of giving identification information to a wire model image in an image area of a coronary artery according to a preferred embodiment of a wall motion measuring apparatus according to the present invention. It is a figure showing an example of the feature point displacement information produced by suitable embodiment of the wall motion measuring apparatus which concerns on this invention. It is a flowchart showing an example of operation | movement of suitable embodiment of the wall motion measuring apparatus which concerns on this invention. 1 is a schematic block diagram showing an example of the overall configuration of a preferred embodiment of a medical image diagnostic apparatus according to the present invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Wall motion measuring apparatus 2 Coronary artery extraction process part 3 Feature point designation | designated process part 31 Root position extraction part 32 Blood vessel tracking part 33 Section detection part 34 Section determination part 35 Branch position extraction part 36 Tip position extraction part 37 Feature point designation part 38 Wire Model creation unit 4 Identification information addition processing unit 41 Section size detection unit 42 Blood vessel tracking unit 43 Identification information addition unit 51 Feature point matching unit 52 Disappearance feature point processing unit 53 Displacement calculation unit 54 Feature point mapping unit 55 Interpolation processing unit 56 Display color Designation unit 57 Display unit 10, 1000 Medical image diagnostic device 11 Image acquisition unit 2000 Database Gi Heart image Ci Coronary artery image area ci Root position Wi, W (i + 1) Wire model image D Feature point displacement information

Claims (16)

A wall motion measuring device for measuring a state of wall motion of a heart based on a plurality of heart images forming a motion image of the heart,
For each of the plurality of heart images, a feature point designating unit for designating at least a feature point in the image area of the coronary artery;
Information presenting means for presenting wall motion information indicating a change state of the position of the designated feature point based on two or more heart images of the plurality of heart images;
Comprising
A wall motion measuring device. The feature point specifying means includes:
A branch position extracting means for extracting a branch position of a blood vessel in the image area of the coronary artery,
Designating the branch position of the extracted blood vessel as the feature point;
The wall motion measuring apparatus according to claim 1. The feature point specifying means includes:
Root position extraction means for extracting the root position of the coronary artery in the image area of the coronary artery;
Blood vessel tracking means for tracking the image area of the coronary artery from the root position extracted by the root position extraction means in the direction of blood flow;
When the blood vessel tracking means tracks the image area of the coronary artery, a cross-section detection means for detecting a blood vessel cross section in a direction substantially perpendicular to the blood flow direction at a predetermined interval;
Further comprising
The branch position extracting means extracts the branch position of the blood vessel when the number of the detected blood vessel cross sections changes from 1 to 2 or more;
The wall motion measuring apparatus according to claim 2. The branch position extraction means generates a figure inscribed in the blood vessel wall at the changed position when the number of the blood vessel cross sections detected by the cross section detection means changes from 1 to 2 or more. Extracting the center position of the figure as the branch position of the blood vessel,
The wall motion measuring device according to claim 3. The feature point specifying means includes:
A tip position extracting means for extracting the tip position of the blood vessel in the image area of the coronary artery,
Designating the extracted blood vessel tip position as the feature point;
The wall motion measuring apparatus according to claim 1. The feature point specifying means includes:
Root position extraction means for extracting the root position of the coronary artery in the image area of the coronary artery;
Blood vessel tracking means for tracking the image area of the coronary artery from the root position extracted by the root position extraction means in the direction of blood flow;
When the blood vessel tracking means tracks the image area of the coronary artery, a cross-section detection means for detecting a blood vessel cross section in a direction substantially perpendicular to the blood flow direction at a predetermined interval;
Further comprising
The tip position extracting means extracts the tip position of the blood vessel when the number of the detected blood vessel cross sections changes from 1 to 0.
The wall motion measuring apparatus according to claim 4. Wire model creation means for creating a wire model image of the image area of the coronary artery based on the feature points designated by the feature point designation means;
The wall motion measuring apparatus according to any one of claims 1 to 6, wherein A feature point matching means for matching the designated feature point to one of the two heart images of the plurality of heart images and the designated feature point to the other;
Displacement calculating means for calculating a displacement between the position of the feature point specified in the one heart image and the position of the feature point specified in the other heart image for the matched feature points;
Further comprising
The information presenting means presents the wall motion information based on the calculated displacement of the feature point.
The wall motion measuring apparatus according to claim 1. Each of the plurality of heart images is a heart image corresponding to one of the preset time phases of the heart,
The second heart image is a second heart image in which the time phases are continuous.
The wall motion measuring apparatus according to claim 8. The feature point collating unit collates, for each of the plurality of heart images, a feature point of the heart image with a feature point of the heart image corresponding to the next time phase of the heart image.
The wall motion measuring apparatus according to claim 9. For each of the plurality of heart images, further comprising identification information providing means for giving identification information to the designated feature points in the heart image in a predetermined order,
The feature point matching means performs matching of the feature points by matching the given identification information to the feature points of each of the two heart images.
The wall motion measuring device according to any one of claims 8 to 10, wherein The identification information giving means is
Root position extraction means for extracting the root position of the coronary artery in the image area of the coronary artery;
Blood vessel tracking means for tracking the image area of the coronary artery from the root position extracted by the root position extraction means in the direction of blood flow;
With
Sequentially assigning identification information to the feature points according to the tracking by the blood vessel tracking means;
The wall motion measuring apparatus according to claim 11. The identification information giving means is
A branch position extracting means for extracting a branch position of a blood vessel in the image area of the coronary artery;
Cross-sectional size detection means for detecting the size of each cross-section of the plurality of blood vessels after branching at the extracted blood vessel branching position;
Further comprising
Based on the detected cross-sectional size, the blood vessel tracking means tracks the main blood flow having the largest cross-sectional size among the plurality of blood vessels after the branching in the blood flow direction, and includes blood vessel tributaries other than the main blood flow. Follow each in the direction of blood flow,
The identification information giving means sequentially gives the hierarchical identification information to the designated feature points in each of the blood vessel main flow and the blood vessel tributary,
The wall motion measuring device according to claim 12. The information presenting means includes display means for displaying a heart image expressing the difference in displacement of the feature points calculated by the displacement calculating means with display colors and / or shades as the wall motion information.
The wall motion measuring device according to any one of claims 8 to 10, wherein Based on the displacement of the feature points in each of the plurality of heart images calculated by the displacement calculation unit, the information presenting unit represents the displacement of the feature points according to the time phase in display color and / or shade. Including display means for displaying a heart image as the wall motion information,
The wall motion measuring apparatus according to claim 10. Image acquisition means for acquiring a plurality of heart images forming a moving image of the heart;
Coronary artery image extracting means for extracting a coronary artery image region from each of the acquired plurality of heart images;
For each of the plurality of heart images, feature point designating means for designating at least feature points in the extracted coronary artery image area;
Information presenting means for presenting wall motion information indicating a change state of the position of the designated feature point based on two or more heart images of the plurality of heart images;
Comprising
A medical image diagnostic apparatus characterized by that.

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