JP6729994B2 - Image processing apparatus, image processing method, and program - Google Patents

Description

The present invention relates to an image processing device, an image processing method, and a program for performing image processing on a dynamic image in which a body part is captured.

Diagnosis of chronic obstructive disease (COPD) is often performed by examination of respiratory function using a spirometer (also referred to as spirometry examination). This spiro test examines vital capacity and the ease with which air can pass when exhaling. However, in the spiro test, since the patient is forced to breathe hard, the burden on the patient is large, and the test result changes depending on the patient's will, and thus the reproducibility and reliability of the test result are low.

By the way, in recent years, by applying digital technology, an image (also referred to as an X-ray dynamic image) in which the movement of the affected part is captured by X-ray imaging can be obtained relatively easily. For example, an X-ray dynamic image capturing a structure including a site (also referred to as a target site) to be inspected and diagnosed is acquired by imaging using a semiconductor image sensor such as an FPD (flat panel detector) (for example, , Patent Document 1). As a result, an X-ray dynamic image can be acquired with a relatively simple configuration without using a contrast agent. Further, it becomes possible to make a diagnosis by analyzing the movement of the target portion, which cannot be performed by the conventional diagnosis using a still image obtained by X-ray photography.

JP, 2009-136573, A

However, the diagnosis using the X-ray dynamic image obtained by FPD or the like largely depends on the visual judgment of the doctor, and the diagnosis result tends to vary depending on the skill level of the doctor.

Such a problem is not limited to an X-ray dynamic image obtained by X-ray photography, but a dynamic image capturing a movement of a part in a living body obtained by other methods such as ultrasonic waves and nuclear magnetic resonance. Generally common.

The present invention has been made in view of the above problems, and an object of the present invention is to provide a technique capable of realizing highly accurate diagnosis using a dynamic image in which the movement of a target site in a living body is captured.

In order to solve the above problems, the image processing apparatus according to the first aspect is a dynamic state in which a moving deformed portion of the outer edge of the diaphragm, which is a target site in a living body, is deformed while moving according to the passage of time. For each frame image of the acquisition unit that acquires an image and two or more frame images that form the dynamic image, it corresponds to two or more locations included in the moving and deformed portion of the outer edge of the diaphragm of the frame image. A recognition unit for recognizing shape-related information regarding the shape of the moving and deformed portion of the outer edge of the diaphragm, including a position information report indicating at least one of an absolute position and a relative positional relationship of two or more points; A shape index value corresponding to the shape of the outer edge of the diaphragm is calculated for each frame image of the two or more frame images based on the shape-related information recognized by the recognition unit for each frame image, A calculator that calculates an evaluation value related to the degree of change in the shape index value between two or more frame images as a deformation evaluation value related to the degree of deformation of the moving deformed portion of the outer edge of the diaphragm over time. And
An image processing apparatus according to a second aspect, an acquisition unit that acquires a dynamic image in which a moving and deformed portion of the outer edge of the diaphragm, which is a target site in a living body, that is deformed while moving according to the passage of time is captured, Targeting each frame image of two or more frame images forming the dynamic image, absolute values of two or more points corresponding to two or more points included in the moving and deformed portion of the outer edge of the diaphragm in the frame image are absolute. A recognition unit for recognizing shape-related information regarding the shape of the moving and deformed portion of the outer edge of the diaphragm, which includes position information indicating at least one of a position and a relative positional relationship, and a target for each frame image by the recognition unit. Based on the shape-related information recognized as, a calculation unit that calculates a deformation evaluation value related to the degree of deformation of the moving deformed portion of the outer edge of the diaphragm according to the passage of time, and the shape-related information, The calculating unit includes position information indicating absolute positions of one or more points corresponding to one or more points included in the movement-deformed portion, and the calculating unit includes the recognizing unit for each frame image of the two or more frame images. Based on the shape-related information recognized by the index calculation unit that calculates displacement index values corresponding to the displacement between the two or more frame images, and the two or more points. And an evaluation value calculation unit that calculates the deformation evaluation value that indicates the degree of variation of the displacement index value between.
An image processing apparatus according to a third aspect is the image processing apparatus according to the second aspect, wherein the degree of variation includes a difference value, a ratio, and a difference value of the displacement index value between the two or more points. At least one value of the statistical value is included.

An image processing apparatus according to a fourth aspect is the image processing apparatus according to any one of the first to third aspects, wherein the recognizing unit generates two or more frame images that form the dynamic image. The shape-related information is recognized for each frame image in the two or more sets of frame images respectively included, and the calculation unit targets each frame image of each of the two or more sets of frame images, The deformation evaluation value is calculated based on the shape-related information recognized by the recognition unit.

An image processing apparatus according to a fifth aspect is the image processing apparatus according to the fourth aspect, wherein in the dynamic image, the intervals between the frame images in two or more frame images forming the frame images of each set are constant. Is.

An image processing apparatus according to a sixth aspect is the image processing apparatus according to the fourth or fifth aspect, wherein the calculation unit calculates a plurality of the deformation evaluations for the two or more sets of frame images. Calculate the statistical value of the value.

An image processing apparatus according to a seventh aspect is the image processing apparatus according to the sixth aspect, wherein the statistical value includes at least a maximum value, a minimum value, a median value, and an average value of the plurality of deformation evaluation values. Contains one value.

A program according to an eighth aspect is a program that causes the image processing apparatus to function as the image processing apparatus according to any one of the first to seventh aspects, by being executed by a control unit included in the image processing apparatus. Is.

The image processing method according to the ninth aspect is (a) an acquisition that acquires a dynamic image in which a moving deformed portion of the outer edge of the diaphragm, which is a target site in the living body, that is deformed while moving according to the passage of time is captured. And (b) targeting each frame image of the two or more frame images constituting the dynamic image acquired in the acquisition step, the frame image included in the moving and deformed portion of the outer edge of the diaphragm in the frame image 2 Recognition for recognizing shape-related information regarding the shape of the moving deformed portion of the outer edge of the diaphragm, including position information indicating at least one of an absolute position and a relative positional relationship of two or more points corresponding to at least one place. And (c) a shape corresponding to the shape of the outer edge of the diaphragm for each frame image of the two or more frame images based on the shape-related information recognized for each frame image in the recognition step. An index value is calculated, and an evaluation value related to the degree of change of the shape index value between the two or more frame images is transformed to a degree of deformation of the moving and deformed portion of the outer edge of the diaphragm over time. A calculation step of calculating the evaluation value.
The image processing method according to the tenth aspect is (a) acquisition to acquire a dynamic image in which a moving deformed portion of the outer edge of the diaphragm, which is a target site in a living body, is deformed while moving according to the passage of time. And (b) targeting each frame image of the two or more frame images constituting the dynamic image acquired in the acquisition step, the frame image included in the moving and deformed portion of the outer edge of the diaphragm in the frame image 2 Recognition for recognizing shape-related information regarding the shape of the moving deformed portion of the outer edge of the diaphragm, including position information indicating at least one of an absolute position and a relative positional relationship of two or more points corresponding to at least one place. And (c) a deformation evaluation value relating to the degree of deformation of the moving deformed portion of the outer edge of the diaphragm according to the passage of time, based on the shape-related information recognized for each of the frame images in the recognition step. And a calculation step for calculating, wherein the shape-related information includes position information indicating an absolute position of one or more points corresponding to one or more points included in the movement-deformed portion, and the calculation step includes Based on the shape-related information recognized in the recognition step for each frame image of the two or more frame images, the displacement corresponding to the displacement between the two or more frame images, targeting the two or more points. There is an index calculation step of calculating each index value, and an evaluation value calculation step of calculating the deformation evaluation value indicating the degree of variation of the displacement index value between the two or more points.

The image processing device according to any of the first to seventh aspects can realize highly accurate diagnosis using a dynamic image in which the movement of the target site in the living body is captured.

The image processing device according to any one of the fourth to seventh aspects can obtain an evaluation value related to the deformation of the target site that changes with the passage of time, and thus highly accurate diagnosis can be easily realized.

With the image processing apparatus according to the fifth aspect, information regarding the deformation of the target site over time can be easily acquired.

The image processing device according to any of the sixth and seventh aspects can easily realize highly accurate diagnosis using the dynamic image in which the movement of the target portion is captured.

The image processing device according to the second or third aspect can also easily calculate the evaluation value related to the deformation of the target portion.

According to the program of the eighth aspect, it is possible to obtain the same effect as that of the image processing apparatus of each of the first to seventh aspects.

According to the image processing method of the ninth aspect, the same effect as that of the image processing device of the first aspect can be obtained.

It is a block diagram which illustrates the composition of the image processing device concerning one embodiment. It is a block diagram which illustrates the functional composition concerning deformation analysis processing. It is a figure which illustrates the some frame image which comprises a dynamic image. It is a figure which shows an example in which the outer edge of the diaphragm is linearly recognized from each frame image. It is a figure which shows an example in which the outer edge of the diaphragm is linearly recognized from each frame image. It is a figure which shows an example in which the outer edge of the diaphragm is recognized as dots from each frame image. It is a figure which illustrates one mode which the approximate straight line which concerns on the outer edge of a diaphragm is calculated|required. It is a figure which illustrates one mode which the approximate straight line which concerns on the outer edge of a diaphragm is calculated|required. It is a figure which illustrates one mode which the approximate circle which concerns on the outer edge of a diaphragm is calculated|required. It is a figure which illustrates one mode which the approximate function which concerns on the outer edge of a diaphragm is calculated|required. It is a figure for demonstrating the calculation method of the displacement index value which concerns on the outer edge of a diaphragm. It is a graph which illustrates the relationship between the order of a frame and a displacement index value. It is a graph which illustrates the relationship between the order of a frame and a displacement index value. It is a flow chart which illustrates the operation flow of deformation analysis processing.

Hereinafter, an embodiment and a modification of the present invention will be described with reference to the drawings. In the drawings, parts having similar configurations and functions are designated by the same reference numerals, and redundant description will be omitted in the following description. Further, the drawings are schematically shown, and the mutual relationship between the size and the position of the images respectively shown in the different drawings is not necessarily exactly described and may be appropriately changed. 3 to 6, an XY coordinate system in which the upper left of the image is the origin, the right direction is the X direction, and the lower direction is the Y direction is attached. Further, FIGS. 7 to 11 are provided with an XY coordinate system in which the right direction is the X direction and the downward direction is the Y direction. Further, in FIGS. 3 and 4, a time axis corresponding to the shooting time of each frame image Fx is attached.

<(1) Overview of image processing device>
FIG. 1 is a block diagram illustrating the configuration of an image processing device 1 according to an embodiment. As shown in FIG. 1, the image processing apparatus 1 includes a general computer in which a control unit 2, a storage unit 3, an interface (I/F) unit 4, a display unit 5, and an operation unit 6 are connected to a bus line 7. It has the same configuration as.

The control unit 2 has, for example, a processor 2a such as a CPU and a memory 2b such as a volatile RAM. The processor 2a reads the program P1 stored in the storage unit 3 and executes various processes according to the program P1. As a result, a process (also referred to as a deformation analysis process) of analyzing the movement of a site (also referred to as a target site) to be diagnosed in the living body captured by the dynamic image is realized. That is, the function of the image processing apparatus 1 that executes the deformation analysis process is realized by the program P1 being executed by the processor 2a.

The storage unit 3 includes, for example, a nonvolatile semiconductor memory or a hard disk, and stores the program P1 and various data. The various data may include data indicating parameters and the like necessary for executing the process according to the program P1, and data at least temporarily generated as a result of the arithmetic process.

The I/F unit 4 is connected to various devices arranged outside the image processing apparatus 1 via various communication lines so that data can be transmitted and received. For example, the I/F unit 4 acquires the dynamic image D1 from the external device 100 that is connected to the I/F unit 4 so that data can be transmitted and received. Here, the external device 100 may include various devices such as a modality, a server, and another personal computer (also referred to as a personal computer). The modality may include, for example, a medical imaging device such as an FPD (flat panel detector) capable of imaging a dynamic image using X-rays.

Further, the dynamic image D1 is an image in which a portion of the outer edge of the target portion in the living body that is deformed while moving according to the passage of time (also referred to as a moving and deformed portion) is captured. The living body may include various animals including humans. The target part may include, for example, a part such as a diaphragm and a heart whose outer edge is deformed while moving in the body according to the passage of time. The outer edge of the target site may be formed by, for example, a boundary portion between the target site and another site. In the present embodiment, the living body is a human being as a subject, and the target site is the left and right diaphragms.

The display unit 5 visually outputs various image data. The display unit 5 has various display devices such as a liquid crystal display (LCD).

The operation unit 6 has, for example, a keyboard and a pointing device such as a mouse. The operation unit 6 outputs to the control unit 2 a signal (also referred to as an instruction signal) generated in response to an operation on a keyboard, a mouse, or the like. The operation unit 6 may have a configuration such as a touch panel.

<(2) Functional configuration related to deformation analysis processing>
In the deformation analysis process, a dynamic image D1 (FIG. 3) is acquired, and each frame image F _X (X is a natural number of 1 to N) that constitutes the dynamic image D1 is targeted and relates to the shape of the moving deformed portion. Information (also called shape-related information) is recognized. Then, based on the recognized shape-related information, an evaluation value (also referred to as a deformation evaluation value) relating to the degree of deformation of the moving deformed portion according to the passage of time is calculated. Thereby, the diagnosis using the deformation evaluation value can realize a highly accurate diagnosis using the dynamic image D1 in which the movement of the target site in the living body is captured.

FIG. 2 is a block diagram illustrating a functional configuration related to the deformation analysis process realized by the control unit 2. As shown in FIG. 2, the control unit 2 has an acquisition unit 21, a recognition unit 22, a calculation unit 23, and an output control unit 24 as a functional configuration realized by the control unit 2.

In the present embodiment, when the data of the dynamic image D1 is input to the acquisition unit 21, for example, the recognition unit 22 and the calculation unit 23 sequentially perform the arithmetic processing, and the output control unit 24 provides information regarding the result of the arithmetic processing. Is output. FIG. 3 is a diagram illustrating a plurality of frame images F _{1 to} F _N (N is a natural number) that form the dynamic image D1.

<(2-1) Acquisition unit>
The acquisition unit 21 acquires the dynamic image D1. The dynamic image D1 acquired here may be, for example, one immediately after being obtained by the modality, or one obtained in advance by the modality and stored in various devices such as a server or a personal computer. good.

It should be noted that at the time of capturing the dynamic image D1, it is sufficient that at least the target site to be diagnosed is captured in the dynamic image D1. At this time, by preventing other parts other than the target part from being captured in the dynamic image D1 as much as possible, the amount of exposure to other parts can be reduced and the burden on the subject can be reduced. On the other hand, if other parts other than the target part are captured in the dynamic image D1, comprehensive analysis and diagnosis including not only the target part but also other parts can be realized. In addition, the frame rate of the dynamic image D1 can be set to a value within a range suitable for the deformation analysis processing according to the speed and the cycle of movement and deformation of the target site.

<(2-2) Recognition unit>
Recognition unit 22 as a target each frame image F _X of two or more frame images constituting dynamic image D1 obtained by the obtaining unit 21 recognizes the shape-related information about the shape of the transfer-deformation portion. The shape-related information may include at least one of position information and shape information.

The position information is information indicating at least one of an absolute position and a relative positional relationship of two or more points corresponding to two or more points included in the moving and deformed portion of the frame image F _X. Note that the absolute position of the point can be indicated by, for example, the coordinates of the pixel in the frame image F _X. As for the relative position, for example, one of two or more points may be used as a reference, and the positions of other points may be indicated by a coordinate difference or the like. The shape information is information indicating the shape of a region (also referred to as an edge region) L _X corresponding to the moving and deformed portion of the frame image F _X. In the present embodiment, the edge region L _X has a linear shape.

Here, the recognition of the position information by the recognition unit 22 includes, for example, the recognition of the positions of two or more pixels arranged linearly corresponding to the moving and deforming portion (also referred to as linear recognition), and the moving and deforming portion. The recognition of the positions of two or more discrete pixels included in the above (also referred to as dot recognition) and the like are included. It should be noted that two or more pixels arranged linearly corresponding to the moving and deformed portion form an edge region L _X. The recognition of the shape information by the recognition unit 22 includes, for example, recognition of a function indicating the shape of a linear edge area (also referred to as a linear edge area) L _X.

Further, in the present embodiment, the recognition unit 22 targets each frame image F _X in the two or more sets of frame images F _X that respectively include the two or more frame images F _X forming the dynamic image D1. Shape-related information is recognized. As a result, the evaluation value related to the deformation of the target site that changes with the passage of time is calculated by the calculation unit 23, and high-precision diagnosis can be easily realized. Here, the dynamic image D1, if the interval of the frame image F _X in 2 or more frame images F _X constituting each set of frame image F _X is constant, according to a modification of sites with the elapse of time Information can be easily obtained.

<(2-2-1) Linear recognition of position information>
FIG. 4 is a diagram illustrating a state in which a linear edge region L _X (X is a natural number of 1 to N) corresponding to a moving deformed portion of the outer edge of the diaphragm is recognized from each frame image F _X of the dynamic image D1. is there. In FIG. 4, a linear edge region L _X corresponding to the outer edge of a general diaphragm of a healthy person is illustrated. On the other hand, FIG. 5 illustrates a linear edge region L _X corresponding to the outer edge of the diaphragm in a patient with severe chronic obstructive disease (COPD).

The linear recognition of position information can be realized by adopting various processes for extracting an edge from an image, for example. For example, known image processing technology (for example, “Image feature analysis and computer-aided diagnosis: Accurate determination of ribcage boundary in chest radiographs”, Xin-Wei Xu and Kunio Doi, Medical Physics, Volume 22(5), May 1995, pp. 617-626.) is adopted, the boundary line between the target site and other sites can be automatically recognized from the image.

Further, as another process for extracting the linear edge region L _X related to the diaphragm from each frame image F _X , for example, a known process for extracting the edge (contour) of the subject captured in the image (edge extraction process) (Also called) etc. are also possible. Specifically, for example, for each frame image F _X , the edge of the lung field including the diaphragm as the target site is extracted by the edge extraction processing targeting the frame image F _X. Then, a portion of the edge that extends along the X-axis direction that is substantially perpendicular to the moving direction of the diaphragm to some extent is searched from the +Y side to the −Y side for each X coordinate. Thereby, the linear edge region L _X related to the outer edge of the diaphragm can be extracted from the frame image F _X.

At this time, as shown in FIG. 4, in the healthy person, the linear edge regions L _X corresponding to the outer edges of the left and right diaphragms can be detected as one continuous curve. FIG. 4 illustrates the linear edge region L _XL related to the left diaphragm and the linear edge region L _XR related to the right diaphragm. On the other hand, as shown in FIG. 5, in patients with severe COPD, the linear edge regions L _X corresponding to the outer edges of the left and right diaphragms were connected with a plurality of continuous curves discontinuous. Can be detected in a manner. FIG. 5 illustrates the linear edge region L _{XR of the} right diaphragm in which two continuous curves are connected in a discontinuous manner.

Note that, for example, each frame image F _X is visually output to the display unit 5 in sequence, and in response to the operation of the operation unit 6 by the user, the linear edge regions L _X are manually designated on each frame image F _X. By doing so, a mode in which each linear edge region L _X is recognized may be adopted.

<(2-2-2) Point information recognition of position information>
FIG. 6 shows two or more points P _X (X is a natural number of 1 to N) corresponding to two or more outer edges of the left and right diaphragms, which are moving and deformed portions, from each frame image F _X of the dynamic image D1. It is a figure which illustrates a mode that position information is recognized. In FIG. 6, two or more points P _XR (specifically, three points P _{XR1 to} P _XR3 ) related to the right diaphragm and two or more points P _XL (specifically, three points) related to the left diaphragm. P _{XL1 to} P _XL3 ) are illustrated.

Here, for example, two or more desired points P _X can be recognized on the linear edge region L _X after the linear recognition of the position information described above is performed. Further, when the linear recognition of the position information is not performed, for example, points corresponding to two or more desired points P _X designated on one frame image F _X are the other frame images. A mode recognized on F _X may be adopted. Here, designation of two or more desired point P _X on one frame image F _X, for example, in a state in which the one frame image F _X is visually output on the display unit 5, an operation by the user unit It can be realized by the operation of 6. In this case, the corresponding point to two or more desired point P _X on each of the other frame image F _X, for example, known for searching corresponding points of said template matching or phase only correlation (POC), etc. It can be recognized by various processes. Note that, for example, each frame image F _X is sequentially visually output to the display unit 5, and in response to an operation of the operation unit 6 by the user, two or more desired points P _X are manually input on each frame image F _X. It is also possible to adopt a mode in which each desired point P _X is recognized by being designated by.

The desired point P _X can be set to, for example, a point according to the type of deformation evaluation value calculated by the calculation unit 23. Specifically, for example, when the deformation of the diaphragm is evaluated based on the change in the inclination of the linear edge region L _X related to the diaphragm during breathing, the linear edge region L _X A mode may be adopted in which at least two points in the vicinity of at least both ends are recognized as the desired point P _X. By the way, in the frame image F _X in which the diaphragm is captured, the vicinity of the rib angle is likely to be unclear, so the point closer to the center than both ends of the linear edge region L _X is the desired point P _X. If recognized, the reliability of the deformation evaluation value calculated by the calculation unit 23 can be improved. Note that FIG. 6 illustrates points P _XR1 and P _XR3 near both ends of the right diaphragm and points P _XL1 and P _XL3 near both ends of the left diaphragm.

Further, when the linear edge region L _X is a curved line that is convex upward and has a vertex in a portion other than the vicinity of both ends, the vertex is one of the two or more desired points P _X. It may be set. Incidentally, in FIG. 6, the point P _XL2 vertex portion of the point P _XR2 and left diaphragm apex of the right diaphragm is illustrated. It should be noted that the two or more desired points P _X are, for example, two points which are either one of two points in the vicinity of both ends of the linear edge region L _X and a point at the apex. Alternatively, it may be three points including two points near both ends of the linear edge region L _X and a vertex point. Further, the two or more desired points P _X are not limited to 2 points and 3 points, and may be 4 points or more.

<(2-2-3) Recognition of shape information>
As processing shape information of the linear edge area L _X in the recognition unit 22 is recognized, for example, after the linear edge area L _X recognized by the line-recognition of the above-described position information, the linear edge area L _X A process that requires a function indicating the shape of Here, as the function indicating the shape of the linear edge region L _X , for example, a quadratic or higher function indicating the relationship between the X coordinate and the Y coordinate on the frame image can be adopted. At this time, function representing the shape of the linear edge area L _X as the shape information of the linear edge area L _X is absolute position and relative for all points on the linear edge area L _X It may indicate a positional relationship.

<(2-3) Calculation unit>
The calculation unit 23 calculates an evaluation value (deformation evaluation value) relating to the degree of deformation of the moving deformed portion according to the passage of time, based on the shape-related information recognized by the recognition unit 22 for each frame image F _X. To do. The deformation evaluation value is a value for evaluating the deformation of the diaphragm as the target site, and can be calculated from the shape-related information regarding two or more frame images F _X. In the present embodiment, the calculation unit 23, the each set of frame image F _X of two or more sets of frame image F _X is a target, based on recognized by the recognition unit 22 shapes related information, deformation evaluation The value is calculated. As a result, information on the deformation evaluation value relating to the degree of deformation of the diaphragm as the target site, which changes with the passage of time, is obtained. As a result, highly accurate diagnosis can be easily realized.

Further, the calculation unit 23 calculates a statistical value (also referred to as a deformation evaluation statistical value) for a plurality of deformation evaluation values calculated for two or more sets of frame images F _X as described above. Here, the deformation evaluation statistical value is a value obtained by analyzing the deformation of the diaphragm as the target site, and can be calculated from a plurality of deformation evaluation values, for example. Then, by calculating the statistical value (deformation evaluation statistical value) relating to the plurality of deformation evaluation values, highly accurate diagnosis using the dynamic image D1 in which the movement of the target site is captured can be easily realized.

As shown in FIG. 2, the calculation unit 23 has an index calculation unit 231, an evaluation value calculation unit 232, and a statistical value calculation unit 233.

<(2-3-1) Index calculation unit>
The index calculation unit 231 represents the shape corresponding to the shape of the linear edge region L _X , based on the shape-related information recognized by the recognition unit, for each frame image F _X of the two or more frame images F _X. A value serving as an index (also called a shape index value) is calculated. The shape index value includes, for example, the inclination of the approximate straight line related to the moving and deforming portion, the curvature of the approximate circle and the coefficient of the approximate function, and the deviation between the approximate straight line and a plurality of points corresponding to a plurality of points on the moving and deforming portion. One or more numerical values among the values indicating the degree (also referred to as the degree of deviation from the approximate straight line) are included. In this embodiment, one type of numerical value is calculated as the shape index value.

Here, for example, the inclination of the approximate straight line with respect to two or more points or the linear edge regions L _X corresponding to two or more locations included in the moving and deforming portion of the frame image F _X is the approximate straight line relating to the moving and deforming portion. It can be calculated as the slope. The inclination of the approximate straight line as such a shape index value may change according to the deformation in the moving deformed portion of the outer edge of the diaphragm.

Further, for example, the curvature of the approximate circle with respect to two or more points or linear edge regions L _X corresponding to two or more locations included in the moving and deforming portion of the frame image F _X is calculated as the curvature of the approximate circle relating to the moving and deforming portion. Can be done. The curvature of the approximate circle as such a shape index value may also change according to the deformation in the moving deformed portion of the outer edge of the diaphragm.

Further, for example, the coefficient of the approximation function for two or more points or the linear edge regions L _X corresponding to two or more locations included in the movement-deformed portion of the frame image F _X is calculated as the coefficient of the approximation function for the movement-deformed portion. Can be done. The coefficient of the approximation function as such a shape index value may also change according to the deformation in the moving deformed portion of the outer edge of the diaphragm.

In addition, a value indicating the degree of deviation between the approximate straight line and two or more points corresponding to two or more points included in the moving and deformed portion of the frame image F _X or a plurality of points in the linear edge region L _X is approximate. It can be calculated as a value indicating the degree of deviation from the straight line. The value indicating the degree of deviation from the approximate straight line as the shape index value corresponds to the flatness in the moving and deforming portion of the outer edge of the diaphragm, and may change according to the deformation in the moving and deforming portion of the outer edge of the diaphragm. ..

Also, the index calculation unit 231, a target frame images F _X of two or more frame images F _X, based on recognized by the recognition unit 22 shapes related information, a plurality of points between two or more frame images F _X A value (also referred to as a displacement index value) according to the displacement may be calculated. Here, as the plurality of points, for example, two or more points corresponding to two or more locations included in the moving and deformed portion of the frame image F _X, a plurality of points in the linear edge region L _X , or the like can be adopted. .. That is, each displacement index value is, for example, two or more points corresponding to two or more points included in the moving and deformed portion of the frame image F _X or a plurality of points in the linear edge region L _X , and is 2 or more. Can be calculated as a value according to the displacement between the frame images F _X. Here, the displacement index value can be calculated by including the position information indicating the absolute position of one or more points corresponding to one or more places included in the moving and deformed portion in the shape-related information.

Hereinafter, as the shape index value, the slope of the approximate straight line, the curvature of the approximate circle, the coefficient of the approximate function, and the calculation method of the value indicating the degree of deviation from the approximate straight line will be described in order, and then the calculation method of the displacement index value explain.

<(2-3-1-1) Calculation method of slope of approximate straight line>
The approximate straight line can be calculated based on the shape-related information recognized by the recognition unit 22.

Here, for example, if one or more of information recognition unit 22 position information and shape information of the linear edge area L _X for each frame image F _X is recognized as the shape-related information, the linear edge area L _X , A set of pixels and can be regarded as a set of points. Therefore, for example, with respect to a set of a plurality of points forming the linear edge region L _X , an approximate straight line can be calculated by using the least square method or the like.

FIG. 7 and FIG. 8 are diagrams showing how approximate straight lines relating to the moving and deformed portion of the outer edge of the diaphragm are respectively obtained. 7 and 8, the approximate straight line L1 _XR with respect to the linear edge region L _XR indicated by the broken line is indicated by a thick line.

Further, for example, if the recognition unit 22 recognizes the position information relating to two or more points of the frame image F _X corresponding to two or more positions of the moving and deformed portion of each frame image F _X as the shape-related information, the 2 With respect to the above points, the approximate straight line L1 _X can be calculated by using the least square method or the like.

<(2-3-1-2) Calculation method of curvature of approximate circle>
The approximate circle can be calculated based on the shape-related information recognized by the recognition unit 22.

Here, for example, if one or more pieces of information of the position information and the shape information of the linear edge region L _X is recognized as the shape-related information for each frame image F _X by the recognition unit 22, the linear edge region L _X is determined as the shape-related information. An approximate circle can be calculated for a set of a plurality of constituent points by using the least square method or the like. Further, for example, if the recognition unit 22 recognizes the position information regarding two or more points of the frame image F _X corresponding to two or more positions of the moving and deformed portion of each frame image F _X as the shape-related information, the 2 With respect to the above points, the approximate circle can be calculated by using the least square method or the like. Then, for example, the reciprocal of the radius of the approximate circle can be calculated as the curvature of the approximate circle.

FIG. 9 is a diagram showing how an approximate circle relating to a moving and deformed portion of the outer edge of the diaphragm is obtained. In FIG. 9, the approximate circle C1 _XR for the linear edge region L _XR indicated by the broken line is indicated by the thick line.

<(2-3-1-3) Calculation method of coefficient of approximate function>
The approximate function can be calculated based on the shape-related information recognized by the recognition unit 22. Here, the approximate function is another function different from the above-described linear function as the approximate straight line. As the approximate function, for example, a quadratic function and a function higher than the quadratic function can be adopted. Here, a function of order that can approximately express the shape of the moving and deformed portion may be adopted. For example, the moving deformed portion of the outer edge of the diaphragm can be approximately represented by a quadratic function.

Here, for example, if one or more pieces of information of the position information and the shape information of the linear edge region L _X is recognized as the shape-related information for each frame image F _X by the recognition unit 22, the linear edge region L _X is determined as the shape-related information. An approximate function can be calculated for a set of a plurality of constituent points by using the least square method or the like. Further, for example, if the recognition unit 22 recognizes the position information relating to three or more points of the frame image F _X corresponding to three or more positions of the moving and deformed portion of each frame image F _X as the shape-related information, the 3 With respect to the above points, the approximate function can be calculated by using the least square method or the like.

FIG. 10 is a diagram showing how an approximate function relating to the moving and deformed portion of the outer edge of the diaphragm is obtained. In FIG. 10, the approximation function F1 _XR for the linear edge region L _XR indicated by the broken line is indicated by the thick line.

<(2-3-1-4) Calculation method of value indicating degree of deviation from approximate straight line>
The value indicating the degree of deviation from the approximate straight line can be calculated based on the shape-related information recognized by the recognition unit 22. Here, first, the approximate straight line can be calculated by the same method as the above-described approximate straight line calculating method. Then, the degree of deviation between the approximate straight line and two or more points corresponding to two or more points included in the moving and deformed portion of the frame image F _X or a plurality of points in the linear edge region L _X (deviation from the approximate straight line A value indicating the degree can be calculated.

Here, for example, if one or more pieces of information of the position information and the shape information of the linear edge region L _X is recognized as the shape-related information for each frame image F _X by the recognition unit 22, the linear edge region L _X is determined as the shape-related information. For a plurality of constituent points, a value indicating the degree of deviation between the plurality of points and the approximate straight line can be calculated. Further, for example, if the recognition unit 22 recognizes the position information relating to two or more points of the frame image F _X corresponding to two or more positions of the moving and deformed portion of each frame image F _X as the shape-related information, the 2 A value indicating the degree of deviation between the above points and the approximate straight line can be calculated.

At this time, for example, a statistical value related to the distance between two or more points or a plurality of points and the approximate straight line can be calculated as a value indicating the degree of deviation from the approximate straight line. Here, if, for example, an average value, a maximum value, or a value indicating a variation such as a variance or a standard deviation of the distance between two or more points or a plurality of points and the approximate straight line is adopted as the statistical value, the deviation degree The value that indicates can well represent the flatness of the outer edge of the moving and deformed portion of the diaphragm.

<(2-3-1-5) Calculation method of displacement index value>
The displacement index value can be calculated based on the shape-related information recognized by the recognition unit 22.

Here, for example, if one or more pieces of information of the position information and the shape information of the linear edge area L _X is recognized as the shape-related information for each frame image F _X by the recognition unit 22, the linear edge area L _X is recognized on the linear edge area L _X. At, multiple points P _X can be recognized. Further, for example, if the recognition unit 22 recognizes the position information relating to two or more points of the frame image F _X corresponding to two or more positions of the moving and deformed portion of each frame image F _X as the shape-related information, the 2 The above points can be treated as a plurality of points P _X.

Then, for example, the displacement index values according to the displacements of the plurality of points P _X between the two or more frame images F _X can be calculated. If the two or more frame images F _X are the two frame images F _X , for example, the displacement indexes of the plurality of points P _X between the two frame images F _X are displacement indexes corresponding to the displacements of the plurality of points P _X , respectively. It can be calculated as a value.

FIG. 11 is a diagram for explaining a method of calculating a displacement index value related to a moving and deformed portion of the outer edge of the diaphragm.

11, among the plurality of frame images F _X constituting the dynamic image D1, the line of the right diaphragm in the frame image F _{m (m} is a natural number) and the frame image F _{m + a} after a second than the frame image F _m The edge regions L _mR and L _(m+a)R are indicated by broken lines. Here, a may be a preset natural number. Further, FIG. 11 shows two points P _XR1 and P _XR3 near both ends as a plurality of points P _X on each linear edge region L _XR . Specifically, two points P _mR1 and P _mR3 near both ends on the linear edge region L _mR and two points P _{(m+a) R1} and P _(m+a) near both ends on the linear edge region L _(m+a)R. Each _R3 is shown. The point P _{(m+a) R1} and the point P _mR1 correspond to each other, and the same point on the diaphragm is captured. Further, the point P _(m+a)R3 and the point P _mR3 correspond to each other, and the same point on the diaphragm is captured.

In the example shown in FIG. 11, for example, between two frame images F _m and F _(m+a) , displacement amounts Tr1 and Tr3 of two points P _XR1 and P _XR3 as a plurality of points P _X are respectively displacement index values. It is calculated. For example, the distance between the point P _mR1 and the point P _(m+a)R1 can be calculated as the displacement amount Tr1, for example. Further, the distance between the point P _mR3 and the point P _(m+a)R3 can be calculated as the displacement amount Tr3, for example. The distance can be calculated based on, for example, coordinate values.

Incidentally, for example, 2 or more frame images F _X as calculation target of each displacement index value corresponding to the displacement of the plurality of points P _X is, if three frame images F _X, between the three frame images F _X A mode is also conceivable in which the acceleration of the change in displacement in is calculated as the displacement evaluation value. At this time, the acceleration of the change in displacement, for example, a first frame image of the three frame images F _X and the displacement between the second frame image, the second of the three frame images F _X The difference in displacement between the frame image and the third frame image may be adopted.

<(2-3-2) Evaluation value calculation unit>
The evaluation value calculation unit 232 determines the degree of change in the shape index value between two or more frame images F _X if the index calculation unit 231 has calculated the shape index value for each frame image F _X. The evaluation value is calculated as the deformation evaluation value. Thereby, the evaluation value related to the deformation of the target site between the two or more frame images F _X can be easily calculated. In the present embodiment, the evaluation value calculation section 232, evaluation value according plurality of sets of frame images F _X to the degree of change in the shape index values between two or more frame images F _X respectively constituting the dynamic image D1 Is calculated as the deformation evaluation value. Thereby, a plurality of change evaluation values that change in the time direction can be acquired.

Here, for example, 2 or more frame images F _X constituting each set of frame image F _X is, if two frame images F _X, the change in the shape index values between the two frame images F _X A value indicating the degree can be calculated as the deformation evaluation value. At this time, as the value indicating the degree of the shape index value, for example, the difference between the shape index values obtained by subtracting the other shape index value from the one shape index value, and one shape index value is the other shape index value. The ratio of the shape index value obtained by dividing by the index value or the like can be adopted.

Further, for example, 2 or more frame images F _X constituting each set of frame image F _X is, if three frame images F _X, the degree of change in the shape index values between the three frame images F _X Can be calculated as the deformation evaluation value. At this time, as the value indicating the degree of change of the shape index value, for example, the acceleration of the change of the shape index value or the like can be adopted. The acceleration of the change in shape index values, for example, a difference between the shape index values between the first frame image and the second frame image of the three frame images F _X, among the three frame images F _X The difference between the shape index value difference between the second frame image and the third frame image may be used.

In addition, the evaluation value calculation unit 232, if the index calculation unit 231 has calculated the displacement index value according to the displacement of a plurality of points between the two or more frame images F _X , the displacement index value between the plurality of points. The evaluation value indicating the degree of variation of is calculated as the deformation evaluation value. Then, in the present embodiment, the evaluation value calculation unit 232 causes the degree of variation between the plurality of points of the displacement index values related to the two or more frame images F _X forming the plurality of sets of frame images F _X in the dynamic image D1. Is calculated as a deformation evaluation value.

Here, if the different distance between the two or more frame images F _X constituting each set of frame image F _X is appropriate, correction processing of the multiplication or the like of the correction coefficients that are applied as appropriate, a plurality of comparable A deformation evaluation value can be calculated. However, if the distance between the two or more frame images F _X constituting each set of frame image F _X is constant, special correction processing multiple variations evaluation value easily comparable without being subjected accurately Can be calculated.

The distance between the two or more frame images F _X, for example, may be a gap of the frame image F _X adjacent constituting the dynamic image D1, the frame image F _X some distance constituting the dynamic image D1 May be at intervals. The distance between the two or more frame images F _X constituting each set of frame image F _X, for example, fast and periodic variation of the diaphragm as a transfer-deformation region, and as appropriate in accordance with the frame rate of dynamic images D1 It should be set. Here, if the interval between the two or more frame images F _X is clearly shorter than one cycle of the movement of the diaphragm, it is possible to appropriately evaluate the movement of the diaphragm. Specifically, for example, if one cycle of the movement of the diaphragm is about 3 seconds and the frame rate in the dynamic image D1 is 15 frames/sec, the interval between the two or more frame images F _X is 1/3 sec. It is possible to adopt a mode in which the interval is set to 5 frames or the like corresponding to.

If each frame image F _X of the dynamic image D1 is used as a reference and each set of frame images F _X is set, information relating to a detailed change in the deformation evaluation value is obtained. For example, each set of frame images F _X may be set for each predetermined number of frame images F _{X of} the dynamic image D1. In this case, for example, constituting the dynamic image D1, one or more frame images F _X is other pair of frame images F _X sandwiched a pair of frame images F _X of the plurality of sets of frame image F _X Aspects may be employed.

It should be noted that if all the sets of frame images F _X for which the evaluation value calculation unit 232 calculates the deformation evaluation value correspond to a period shorter than the period (half cycle) in which the moving and deforming portion moves in one direction. However, the adverse effect due to the switching of the deformation direction is unlikely to occur.

Here, the slope of the approximate straight line as the shape index value, the curvature of the approximate circle, the coefficient of the approximate function, the calculation of the deformation evaluation value related to the value indicating the degree of deviation from the approximate straight line, and the deformation evaluation value related to the displacement index value The calculation of will be described.

<(2--3-2-1) Calculation of deformation evaluation value related to inclination of approximate straight line>
When the slope of the approximate straight line related to the moving and deformed portion of the outer edge of the diaphragm changes rapidly, it is assumed that the angle of the diaphragm changes rapidly with breathing. Therefore, if the change in the inclination of the approximate straight line according to the passage of time is evaluated, the movement abnormality in the movement-deformed portion of the outer edge of the diaphragm can be easily recognized.

Therefore, when the slope of the approximate straight line is calculated as the shape index value by the index calculation unit 231, the evaluation value calculation unit 232 calculates the deformation evaluation value related to the degree of change in the slope of the approximate straight line. For example, in the present embodiment, the evaluation value calculation unit 232, the change in slope of the approximate line of the dynamic image D1 a plurality of sets of frame images F _X as the shape index values between two or more frame images F _X constituting respectively A deformation evaluation value related to the degree of is calculated. Thereby, a plurality of change evaluation values that change in the time direction can be acquired.

<(2-3-2-2) Calculation of deformation evaluation value related to curvature of approximate circle>
When the curvature of the approximate circle related to the moving and deformed portion of the outer edge of the diaphragm changes abruptly, it is assumed that the degree of curvature (ie, the shape) of the diaphragm changes abruptly with breathing. Therefore, if the change in the curvature of the approximate circle with the passage of time is evaluated, it is possible to easily recognize the abnormal movement in the movement-deformed portion of the outer edge of the diaphragm.

Therefore, when the index calculation unit 231 calculates the curvature of the approximate circle as the shape index value, the evaluation value calculation unit 232 calculates the deformation evaluation value related to the degree of change in the curvature of the approximate circle. For example, in the present embodiment, the evaluation value calculation unit 232, the change in curvature of the approximate circle of the dynamic image D1 a plurality of sets of frame images F _X as the shape index values between two or more frame images F _X constituting respectively A deformation evaluation value related to the degree of is calculated. Thereby, a plurality of change evaluation values that change in the time direction can be acquired.

<(2-3-2-3) Calculation of deformation evaluation value related to coefficient of approximate function>
When the coefficient of the approximate function related to the moving and deformed portion of the outer edge of the diaphragm changes abruptly, it is assumed that the degree of bending (ie, the shape) of the diaphragm changes abruptly with breathing. For example, if the approximation function is a quadratic function, if the coefficient of the quadratic term of the quadratic function changes abruptly, it is assumed that the degree of bending of the diaphragm changes rapidly with breathing. Therefore, if the change in the coefficient of the quadratic term of the quadratic function as an approximate function according to the passage of time is evaluated, it is possible to easily recognize the movement abnormality in the movement-deformed portion of the outer edge of the diaphragm.

Therefore, for example, when the index calculation unit 231 calculates the coefficient of the quadratic term of the quadratic function that is an approximate function as the shape index value, the evaluation value calculation unit 232 causes the coefficient of the quadratic term of the quadratic function that is the approximate function. A deformation evaluation value related to the degree of change of is calculated. For example, in the present embodiment, the evaluation value calculation unit 232, the change of the coefficients of the approximation function of a plurality of sets of frame images F _X as shape index values between two or more frame images F _X respectively constituting the dynamic image D1 A deformation evaluation value related to the degree of is calculated. Thereby, a plurality of change evaluation values that change in the time direction can be acquired.

<(2-3-2-4) Calculation of deformation evaluation value related to degree of deviation from approximate straight line>
The flatness of the diaphragm can be evaluated by the degree of deviation between the approximate straight line related to the moving and deformed portion of the outer edge of the diaphragm and a plurality of points corresponding to a plurality of points on the moving and deforming portion (deviation degree from the approximate straight line). If the degree of deviation from the approximate straight line changes abruptly, it is assumed that the flatness (ie, shape) of the diaphragm changes abruptly with breathing. For example, it is presumed that the flatness of the diaphragm is large when the deviation degree from the approximate straight line is small, and the flatness of the diaphragm is small when the deviation degree from the approximate straight line is large. Therefore, if the change in the degree of deviation from the approximate straight line with the passage of time is evaluated, it can be evaluated how the flatness of the moving and deformed portion of the outer edge of the diaphragm has changed. As a result, the movement abnormality in the movement-deformed portion of the outer edge of the diaphragm can be easily recognized.

Therefore, when the index calculation unit 231 calculates the value related to the deviation degree from the approximate straight line as the shape index value, the evaluation value calculation unit 232 evaluates the deformation related to the degree of change in the value related to the deviation degree from the approximate straight line. The value is calculated. For example, in this embodiment, degree of deviation in the evaluation value calculation section 232, and the approximate line as the shape index values between two or more frame images F _X respectively constituting a plurality of sets of frame images F _X in dynamic image D1 A deformation evaluation value related to the degree of change in the value related to is calculated. Thereby, a plurality of change evaluation values that change in the time direction can be acquired.

<(2-3-2-5) Calculation method of deformation evaluation value from displacement index value>
If two or more frame images F _X have similar displacements at a plurality of points P _X corresponding to the moving and deformed portions of the outer edge of the diaphragm, the shape of the diaphragm changes too much despite the execution of breathing. It is presumed that not. On the contrary, if the displacements at the plurality of points P _X corresponding to the moving and deformed portions of the outer edge of the diaphragm are significantly different between the two or more frame images F _X , the shape of the diaphragm changes rapidly with breathing. It is presumed that it is doing. Therefore, if the degree of variation in displacement regarding the plurality of points P _X is evaluated, the abnormal motion in the moving and deformed portion of the outer edge of the diaphragm can be easily recognized.

Therefore, when the index calculation unit 231 calculates the displacement index values related to the plurality of points, the evaluation value calculation unit 232 calculates the evaluation value related to the degree of variation of the displacement index values related to the plurality of points. For example, in the present embodiment, in the evaluation value calculation unit 232, the degree of variation between the plurality of deformation index values of the two or more frame images F _X forming the plurality of frame images F _X in the dynamic image D1 between the plurality of points. A deformation evaluation value indicating is calculated. Thereby, a plurality of change evaluation values that change in the time direction can be acquired.

Here, the degree of variation may include, for example, at least one of a difference value, a ratio, and a statistical value of displacement index values between a plurality of points. Further, the statistical value may include, for example, the variance, the standard deviation, the difference between the maximum value and the minimum value, the ratio between the maximum value and the minimum value, and the like. In the example shown in FIG. 11, the difference value regarding the displacement index value between the plurality of points P _XR1 and P _XR3 is a value obtained by subtracting the displacement amount Tr3 from the displacement amount Tr1. As the ratio of the displacement index value between the plurality of points P _XR1 and P _XR3 , for example, a value obtained by dividing the displacement amount Tr1 by the displacement amount Tr3 or a value obtained by dividing the displacement amount Tr3 by the displacement amount Tr1 is adopted. Can be done.

Here, if the degree of variation is small, it is presumed that the moving and deforming portion of the outer edge of the diaphragm hardly deforms, and the plurality of points P _X corresponding to the moving and deforming portion of the outer edge of the diaphragm move substantially in parallel. It On the other hand, if the degree of variation is large, it is inferred that the moving and deformed portion of the outer edge of the diaphragm is moving while being deformed.

<(2-3-3) Statistics calculation part>
The statistical value calculation unit 233 calculates a statistical value (deformation evaluation statistical value) relating to the plurality of deformation evaluation values calculated by the evaluation value calculation unit 232 for two or more sets of frame images F _X in the dynamic image D1. .. By appropriately referring to this deformation evaluation statistical value, it is possible to easily realize a highly accurate diagnosis using the dynamic image D1 in which the movement of the diaphragm as the target site is captured. The deformation evaluation statistical value calculated here may include at least one of the maximum value, the minimum value, the median value, and the average value of the plurality of deformation evaluation values. Thereby, the statistical value concerning a plurality of deformation evaluation values can be easily calculated.

Here, for example, when the maximum value of the plurality of deformation evaluation values is calculated as the deformation evaluation statistical value, it is possible to capture a motion accompanied by a remarkable deformation in the diaphragm as the target site. Further, for example, when the minimum value of the plurality of deformation evaluation values is calculated as the deformation evaluation statistical value, an abnormality in which the minimum value of the deformation evaluation value is too small can be captured during a period in which the diaphragm as the target site is largely deformed.

12 and 13 are diagrams showing an example of changes in the deformation evaluation value with the passage of time. FIGS. 12 and 13 show changes over time in the displacement index values at two points, and the difference between the displacement index values indicating the degree of variation in the displacement index values at the two points at each timing is the deformation evaluation value. Equivalent to. Then, FIG. 12 shows an example of the change of the deformation evaluation value with respect to time for a healthy person, and FIG. 13 shows the deformation evaluation value of the COPD patient with time. An example of the change is shown.

Specifically, FIG. 12 and FIG. 13 show the displacement index values at two points corresponding to two locations near both ends in the moving deformed portion of the outer edge of the diaphragm, with respect to the time during exhalation during tidal breathing. Changes are illustrated. 12 and 13, the horizontal axis indicates the front order (also referred to as the reference frame order) of the frame images F _X of each set for which the displacement index value is calculated, and the vertical axis indicates the frames of each set. The displacement index value for each of the two points of the image F _X is shown. Here, the displacement index values for points P _XR1 and P _XR3 near both ends of the moving and deformed portion of the outer edge of the right diaphragm shown in FIG. 11 are illustrated. Specifically, the displacement index value related to the point P _XR1 on the lateral rib angle side is shown by a black square mark, and the change of the displacement index value according to the reference frame order is drawn by a solid line. _Further , the displacement index value related to the point P _XR3 on the heart side is indicated by a black triangle, and the change of the displacement index value according to the reference frame order is indicated by a thick broken line. The maximum value of the difference between the deformation index values related to the two points as the deformation evaluation statistical value is shown by the length of the double-headed arrow in FIGS. 12 and 13.

As shown in FIGS. 12 and 13, the maximum value of the difference between the deformation index values related to the two points as the deformation evaluation statistical value is significantly different between the healthy person and the COPD patient. Therefore, by appropriately referring to such deformation evaluation statistical values, it is possible to easily realize a highly accurate diagnosis using the dynamic image D1 in which the movement of the diaphragm as the target portion is captured.

<(2-4) Output control unit>
The output control unit 24 controls the visible output of information on the display unit 5 and the output of information to the external device 100 by the I/F unit 4. Here, the information visually output on the display unit 5 and the information output to the external device 100 by the I/F unit 4 include, for example, information related to the result of the arithmetic processing in the calculation unit 23. The information related to the result of the arithmetic processing may include, for example, the statistical value calculated by the statistical value calculation unit 233, the deformation evaluation value calculated by the evaluation value calculation unit 232. At this time, the statistical value is compared with a preset range or threshold value, and information such as the fact that an abnormality has occurred in the target site and the type of abnormality that may have occurred in the target site, etc. It may be output.

<(3) Operation flow of deformation analysis processing>
FIG. 14 is a flowchart showing an example of the operation flow of the deformation analysis processing executed in the image processing apparatus 1. This operation flow can be realized by, for example, the control unit 2 that executes the program P1. Here, the deformation analysis process is started according to the operation of the operation unit 6 by the user, and the processes of steps S1 to S4 are sequentially performed.

In step S1, the acquisition unit 21 acquires the dynamic image D1.

In step S2, the recognition unit 22 targets each frame image F _{X of} the two or more frame images F _X forming the dynamic image D1 acquired in step S1 to obtain shape-related information regarding the shape of the moving and deformed portion. Be recognized.

In step S3, the calculating unit 23, based on the recognized shape-related information as a target of each frame image F _X in step S2, deformation evaluation value according to a modification of the transfer-deformation portion with the elapse of time is calculated. Further, in step S3 according to the present embodiment, the calculation unit 23, the statistics of the plurality of deformation evaluation value calculated as a target frame image F _X of two or more sets of dynamic images D1 is calculated.

In step S4, the output control unit 24 outputs information related to the result of the arithmetic processing calculated in step S3.

<(4) Summary>
As described above, in the image processing device 1 according to the embodiment, the shape-related information regarding the shape of the moving and deformed portion is targeted for each frame image F _{X of} the two or more frame images F _X forming the dynamic image D1. Is recognized. Then, based on the recognized plurality of shape-related information, the deformation evaluation value related to the deformation of the moving deformed portion according to the passage of time is calculated. In addition, a statistical value (deformation evaluation statistical value) of a plurality of deformation evaluation values calculated for two or more sets of frame images F _X in the dynamic image D1 is calculated. As a result, by obtaining the objective indices that contribute to the diagnosis, such as the deformation evaluation value and the deformation evaluation statistical value, the dynamic image D1 in which the movement of the diaphragm as the target site in the human body as the living body is captured is obtained. The highly accurate diagnosis used can be realized.

<(5) Modification>
The present invention is not limited to the above-described embodiment, and various modifications and improvements can be made without departing from the gist of the present invention.

For example, in the above-described embodiment, the statistical values of the plurality of deformation evaluation values calculated for two or more sets of frame images F _X in the dynamic image D1 are calculated, but the present invention is not limited to this. For example, the deformation evaluation value may be calculated by targeting only one set of frame images F _X in the dynamic image D1. As a specific example, a set of frame image F _X is a frame image F _X corresponding to the maximum expiration, if the set of the frame image F _X corresponding to the time of maximum inspiration, the deformation evaluation value calculated diagnostic It can be an objective index that contributes. As a result, it is possible to realize a highly accurate diagnosis using the dynamic image D1 in which the movement of the diaphragm as the target site in the human body as a living body is captured.

Further, in the above-described embodiment, the statistical values of the plurality of deformation evaluation values calculated for the two or more sets of frame images F _X in the dynamic image D1 are calculated, but the present invention is not limited to this. For example, a mode may be adopted in which the plurality of deformation evaluation values are calculated without calculating the statistical values of the plurality of deformation evaluation values. In such a case, for example, if changes in a plurality of deformation evaluation values over time are visually output in the form of a graph or the like, it can be an objective index that contributes to diagnosis. Further, as shown in FIG. 12 and FIG. 13, the change of the displacement index value with respect to each point can be visually confirmed without calculating the deformation evaluation value from the displacement index value with respect to a plurality of points. Even if it is output, it can be an objective index that contributes to diagnosis. Therefore, highly accurate diagnosis can be realized.

In addition, in the above-described embodiment, each frame image F _X forming the dynamic image D1 is a two-dimensional image, but the present invention is not limited to this. For example, each frame image F _X may be a three-dimensional image. The three-dimensional image can be acquired by, for example, computer tomography (CT). If each frame image F _X is a three-dimensional image, the edge region corresponding to the moving and deformed portion of the frame image F _X may be recognized as, for example, a planar region, or one edge image may be recognized. It may be recognized as a linear region. That is, the edge region corresponding to the moving and deformed portion may include, for example, at least one of a linear region and a planar region.

Further, in the above-described embodiment, the recognition of the position information by the recognition unit 22 includes linear recognition and dot recognition, but the recognition is not limited to this. For example, if each frame image F _X is a three-dimensional image, the recognition unit 22 recognizes the position information by recognizing the positions of two or more pixels arranged in a plane corresponding to the moving and deformed portion (the plane (plane)). (Also called state recognition) may be adopted. Further, recognition of the positions of two or more discrete pixels included in the planar movement-deformed portion (dot recognition) may be adopted.

Further, in the above-mentioned one embodiment, the shape expression information is recognized for all the frame images F _X in the dynamic image D1, but the present invention is not limited to this. For example, if the shape expression information is recognized for a plurality of sets of frame images F _{X to be} evaluated of the plurality of frame images F _X forming the dynamic image D1, the calculation speed is improved by omitting unnecessary calculation. Can be achieved.

Further, in the above-described embodiment, the numerical value of any one of the shape index value and the displacement index value is calculated, and one kind of numerical value is calculated as the shape index value, but the present invention is not limited to this. .. For example, the numerical value of at least one of the shape index value and the displacement index value may be calculated, or two or more numerical values may be calculated as the shape index value. Then, for example, when both the shape index value and the displacement index value are calculated, both the deformation evaluation value based on the shape index value and the displacement evaluation value based on the displacement index value may be calculated. Further, when two or more types of numerical values are calculated as the shape index value, for example, a deformation evaluation value may be calculated for each type of shape index value.

In the above embodiment, the value indicating the degree of deviation from the approximate straight line is a value indicating the degree of deviation between the approximate straight line and a plurality of points corresponding to a plurality of points on the moving and deforming portion, but the present invention is not limited to this. Absent. For example, it may be a value indicating the degree of deviation between the approximate straight line and one point corresponding to one location included in the moving and deformed portion. That is, the value indicating the degree of deviation from the approximate straight line may be the degree of deviation between the approximate straight line and one or more points corresponding to one or more locations included in the moving and deformed portion. As the one or more points, for example, two or more points used when calculating the approximate straight line and points included in the edge region (for example, a vertex portion) and the like can be adopted. As the value indicating the degree of deviation between the approximate straight line and one point corresponding to one place included in the moving and deformed portion, for example, the distance between the approximate straight line and the one point or the like can be adopted.

Further, in the above-described one embodiment, the target site is the diaphragm, but the target site is not limited to this. For example, the target part may be another part of the living body, such as the heart, whose outer edge deforms while moving over time. That is, a mode can be adopted in which the target site includes, for example, at least one site of the diaphragm and the heart. This makes it possible to realize highly accurate diagnosis using dynamic images in which movements of the diaphragm, the heart, and the like are captured.

Further, in the above-described embodiment, the curvature of the approximate circle has been described as an example of the shape index value, but the present invention is not limited to this, and the radius of curvature of the approximate circle may be adopted as the shape index value, for example.

In addition, in the above-described embodiment, the dynamic image D1 is obtained by imaging using X-rays, but the present invention is not limited to this. For example, the dynamic image D1 may be acquired by another modality such as a magnetic resonance imaging (MRI) apparatus and an ultrasonic diagnostic apparatus (echo).

It is needless to say that all or part of each of the above-described one embodiment and various modified examples can be appropriately combined in a consistent range.

1 image processing device 2 control unit 2a processor 2b memory 3 storage unit 5 display unit 6 operation unit 21 acquisition unit 22 recognition unit 23 calculation unit 24 output control unit 100 external device 231 index calculation unit 232 evaluation value calculation unit 233 statistical value calculation unit D1 dynamic image P1 program

Claims (10)

An acquisition unit that acquires a dynamic image in which a moving and deformed portion of the outer edge of the diaphragm, which is the target site in the living body, is deformed while moving according to the passage of time,
Targeting each frame image of two or more frame images forming the dynamic image, absolute values of two or more points corresponding to two or more points included in the moving and deformed portion of the outer edge of the diaphragm in the frame image are absolute. A recognition unit that recognizes shape-related information regarding the shape of the moving deformed portion of the outer edge of the diaphragm, including position information indicating at least one of a position and a relative positional relationship,
Based on the shape-related information recognized by the recognition unit for each frame image, a shape index value corresponding to the shape of the outer edge of the diaphragm is calculated for each frame image of the two or more frame images, Calculation to calculate an evaluation value related to the degree of change in the shape index value between the two or more frame images as a deformation evaluation value related to the degree of deformation of the moving deformed portion of the outer edge of the diaphragm over time. Department,
An image processing apparatus comprising: An acquisition unit that acquires a dynamic image in which a moving and deformed portion of the outer edge of the diaphragm, which is the target site in the living body, is deformed while moving according to the passage of time,
Targeting each frame image of two or more frame images forming the dynamic image, absolute values of two or more points corresponding to two or more points included in the moving and deformed portion of the outer edge of the diaphragm in the frame image are absolute. A recognition unit that recognizes shape-related information regarding the shape of the moving deformed portion of the outer edge of the diaphragm, including position information indicating at least one of a position and a relative positional relationship,
Based on the shape-related information recognized by the recognition unit for each frame image, a calculation unit that calculates a deformation evaluation value related to the degree of deformation of the moving deformed portion of the outer edge of the diaphragm according to the passage of time. ,
Equipped with
The shape related information is
Including position information indicating an absolute position of one or more points corresponding to one or more places included in the movement-deformed part,
The calculation unit,
Based on the shape-related information recognized by the recognition unit for each frame image of the two or more frame images, a displacement corresponding to a displacement between the two or more frame images for the two or more points. An index calculation unit that calculates each index value,
An evaluation value calculation unit that calculates the deformation evaluation value indicating the degree of variation of the displacement index value between the two or more points,
The image processing apparatus according to claim Rukoto to have a. The image processing apparatus according to claim 2 , wherein
The degree of variation includes
An image processing apparatus comprising at least one of a difference value, a ratio, and a statistical value of the displacement index value between the two or more points. An image processing apparatus according to any one of claims 1 to 3 , wherein:
The recognition unit,
Recognizing the shape-related information for each frame image in two or more sets of frame images that respectively include two or more frame images forming the dynamic image,
The calculation unit,
An image processing apparatus, wherein the deformation evaluation value is calculated based on the shape-related information recognized by the recognition unit, for each set of frame images of the two or more sets of frame images. The image processing apparatus according to claim 4 , wherein
In the dynamic image, the image processing device is characterized in that the intervals of the frame images in two or more frame images forming each of the sets of frame images are constant. The image processing apparatus according to claim 4 or 5 , wherein
The calculation unit,
An image processing apparatus, comprising: calculating a statistical value related to the plurality of deformation evaluation values calculated for the two or more sets of frame images. The image processing apparatus according to claim 6 ,
The statistical values include
An image processing apparatus comprising at least one of a maximum value, a minimum value, a median value, and an average value of the plurality of deformation evaluation values. A program that causes the image processing device to function as the image processing device according to any one of claims 1 to 7, when being executed by a control unit included in the image processing device. (A) An acquisition step of acquiring a dynamic image in which a moving and deformed portion of the outer edge of the diaphragm, which is the target site in the living body, is deformed while moving according to the passage of time,
(B) Targeting each frame image of the two or more frame images constituting the dynamic image acquired in the acquisition step, at two or more positions included in the moving and deformed portion of the outer edge of the diaphragm of the frame images. A recognition step of recognizing shape-related information relating to the shape of the moving deformed portion of the outer edge of the diaphragm, which includes position information indicating at least one of an absolute position and a relative positional relationship of two or more corresponding points;
(C) A shape index value corresponding to the shape of the outer edge of the diaphragm for each frame image of the two or more frame images based on the shape-related information recognized for each frame image in the recognition step. The calculated evaluation value relating to the degree of change of the shape index value between the two or more frame images is used as the deformation evaluation value relating to the degree of deformation of the moving deformed portion of the outer edge of the diaphragm according to the passage of time. A calculation step for calculating,
An image processing method comprising: (A) An acquisition step of acquiring a dynamic image in which a moving and deformed portion of the outer edge of the diaphragm, which is the target site in the living body, is deformed while moving according to the passage of time,
(B) Targeting each frame image of the two or more frame images constituting the dynamic image acquired in the acquisition step, at two or more positions included in the moving and deformed portion of the outer edge of the diaphragm of the frame images. A recognition step of recognizing shape-related information relating to the shape of the moving deformed portion of the outer edge of the diaphragm, which includes position information indicating at least one of an absolute position and a relative positional relationship of two or more corresponding points;
(C) A deformation evaluation value relating to the degree of deformation of the moving deformed portion of the outer edge of the diaphragm over time is calculated based on the shape-related information recognized for each of the frame images in the recognition step. A calculation step,
Equipped with
The shape related information is
Including position information indicating an absolute position of one or more points corresponding to one or more places included in the movement-deformed part,
The calculation step is
Based on the shape-related information recognized in the recognition step for each frame image of the two or more frame images, the displacement corresponding to the displacement between the two or more frame images for the two or more points An index calculation step for calculating each index value,
An evaluation value calculation step of calculating the deformation evaluation value indicating the degree of variation of the displacement index value between the two or more points,
Image processing method according to claim Rukoto to have a.