JP5173303B2 - Medical image processing apparatus and medical image diagnostic apparatus - Google Patents

Description

  The present invention relates to a medical image processing apparatus that processes medical images and a medical image diagnostic apparatus that includes the medical image processing apparatus.

  The medical image diagnostic apparatus includes a medical image capturing apparatus that captures a medical image, a medical image processing apparatus that processes the medical image, and the like. Examples of the medical imaging apparatus include an X-ray tomography apparatus (X-ray CT apparatus), a nuclear magnetic resonance apparatus (MRI apparatus), and an ultrasonic diagnostic apparatus. An X-ray tomography apparatus is an apparatus that irradiates a subject with X-rays, detects the X-rays that have passed through the subject, and displays the interior (part of interest) of the subject as a CT image. The ultrasonic diagnostic apparatus is an apparatus that transmits an ultrasonic wave to a subject, receives a reflected wave (echo wave) thereof, and displays the inside (target site) of the subject as an ultrasonic image.

  Various image processing techniques have been proposed as image processing techniques for processing the aforementioned medical images. For example, a combined medical image diagnostic apparatus that synthesizes and displays a CT image and an ultrasonic image of the same region of interest (target region) obtained by an X-ray CT apparatus and an ultrasonic diagnostic apparatus, or a specific magnetic resonance image An image diagnosis support system has been proposed in which a corresponding feature portion of an ultrasonic image is aligned with a special feature portion and a magnetic resonance image is generated by superimposing the ultrasonic images (for example, Patent Literature 1 and Patent Literature 1). 2).

On the other hand, a technique for simulating a disease at a site of interest of a subject has also been proposed. For example, by modeling the heart shape and incorporating the mechanical parameters of the myocardium into the model, techniques for simulating heart motion (wall motion) and blood dynamics in the heart chamber, as well as the heart shape A technique for simulating excitation propagation processes and potential changes by modeling and incorporating myocardial electrical parameters into the model has been proposed. From a part model (for example, a heart model) obtained by such a simulation, certain function information of the part of interest can be obtained. In addition, from the medical image (for example, a heart image) obtained by the medical image photographing apparatus, the shape information of the region of interest and other functional information are obtained.
Japanese Patent Laid-Open No. 10-127623 JP 2003-153877 A

  However, since the medical image obtained by the medical imaging apparatus and the part model obtained by the simulation are different images, it is difficult to recognize the relationship between the shape information of the attention part and the function information, and a doctor or other diagnostician However, it is difficult to accurately grasp the state of the site of interest of the subject.

  The present invention has been made in view of the above, and facilitates the recognition of the relationship between the form information of the region of interest of the subject and the function information thereof, and allows the diagnostician to accurately grasp the situation of the region of interest. An image processing apparatus and a medical image diagnostic apparatus are provided.

A first feature according to an embodiment of the present invention is that a medical image processing apparatus simulates a medical image that is an image captured by a medical image capturing apparatus and shows a region of interest of a subject, and a disease of the region of interest. model is a by the site model shows the area of interest by the alignment synthesized for, comprising means for generating and displaying a composite image of the medical image and site model, the site model is stored in a model database cage is Rukoto comprise mechanical spring constant, resting membrane potential and the information of the ion concentration.

  The second feature according to the embodiment of the present invention is that the medical image diagnostic device includes a medical image photographing device for photographing a medical image and the medical image processing device according to the first feature described above.

  According to the present invention, a medical image processing apparatus and a medical image diagnostic apparatus that facilitate the recognition of the relationship between the form information of the region of interest of the subject and the function information, and allow the diagnostician to accurately grasp the state of the region of interest. Can be provided.

  An embodiment of the present invention will be described with reference to the drawings.

  As shown in FIG. 1, a medical image diagnostic apparatus 1 according to an embodiment of the present invention includes a medical image photographing apparatus 2 for photographing a medical image showing a target region (for example, a heart) of a subject, and the medical image taken by the medical image photographing apparatus 2 A medical image database 3 for storing images, a model database 4 for storing a site model (for example, a heart model) for simulating a disease at a site of interest, and a synthesis process for generating a synthesized image of the medical image and the site model are performed. And a medical image processing apparatus 5. These units are connected by a network 6 such as a LAN (Local Area Network).

  The medical image capturing apparatus 2 is an image capturing apparatus that captures a medical image indicating a region of interest (region of interest) of a subject. For example, an X-ray tomography apparatus (X-ray CT apparatus) or an ultrasonic diagnostic apparatus is used as the medical image imaging apparatus 2. When the X-ray tomography apparatus is used, the medical image is a CT image, and when the ultrasonic diagnostic apparatus is used, the medical image is an ultrasonic image (ultrasonic echo image).

  The medical image database 3 is a storage device that stores medical images obtained by the medical image photographing device 2 (for example, volume data or ultrasonic images that are CT images related to each part of the subject). Here, examples of each part of the subject include the heart, lungs, and stomach. CT images (volume data) and ultrasonic images are obtained by the medical image photographing apparatus 2 and stored in the medical image database 3 via the network 6.

  The model database 4 is a model for simulating a disease at a site of interest, and is a storage device that stores a simulation model indicating the site of interest as a site model. When the site of interest is the heart, the shape of the heart is modeled and a heart model is created. Information on the heart model is stored in the model database 4. The information on the heart model includes set value information such as the form, mechanical spring constant, resting membrane potential, and ion concentration.

  Here, as a heart shape model, a cell model (a model in which tens of thousands of cells are arranged in the shape of the heart), a tetrahedron division model (a model expressing the heart by a combination of tetrahedrons of various shapes), etc. Used. For example, a heart region is extracted from a anatomical image of a heart imaged by an X-ray tomography apparatus, and cell division or tetrahedron division is automatically performed to express a person's heart shape. A heart model is used. In addition, a heart model having a standard heart shape instead of an individual heart shape may be used.

  As shown in FIG. 2, the medical image processing apparatus 5 includes a control unit 11 such as a CPU (Central Processing Unit) that centrally controls each unit, and a memory such as a ROM (Read Only Memory) and a RAM (Random Access Memory). 12, a display unit 13 that displays various images such as medical images and part models, an operation unit 14 that receives input operations from an operator, a storage unit 15 that stores various programs, various data, and the like, and an external device A communication unit 16 that performs the above communication, and an image processing unit 17 that processes various images such as medical images and part models. These parts are electrically connected by a bus line 18.

  The control unit 11 controls each unit based on various programs and various data stored in the storage unit 15. In particular, the control unit 11 performs a series of data processing for performing calculation or processing of data based on various programs and data, a synthesis process for generating a composite image of a medical image and a part model, a display process for displaying an image, and the like. Execute.

  The memory 12 is a memory that stores a startup program executed by the control unit 11 and also functions as a work area of the control unit 11. The activation program is read and executed by the control unit 11 when the medical image processing apparatus 5 is activated.

  The display unit 13 is a display device that displays various images such as a two-dimensional image and a three-dimensional image in color. As the display unit 13, for example, a liquid crystal display, a CRT (Cathode Ray Tube) display, or the like is used.

  The operation unit 14 is an input unit that is input by an operator, and is an input unit that receives various input operations such as image display start, image switching, and setting change. For example, an input device such as a mouse or a keyboard is used as the operation unit 14.

  The storage unit 15 is a storage device that stores various programs, data, and the like. In particular, the storage unit 15 is a storage device that stores synthesis data D1 related to the synthesis (positioning) of a medical image and a part model. For example, a magnetic disk device or a semiconductor disk device (flash memory) is used as the storage unit 15. The composition data D1 is information necessary for composition of the medical image and the part model, for example, information such as the amount of expansion / contraction and the amount of deformation. The composition data D1 is obtained by the image processing unit 17 and stored in the storage unit 15 via the bus line 18.

  The communication unit 16 is a device that communicates with an external device via a network 6 such as a LAN or the Internet. As the communication unit 16, a LAN card, a modem, or the like is used. Examples of the external device include a medical image photographing device 2, a medical image database 3, a model database 4, and the like.

  As shown in FIG. 3, the image processing unit 17 includes a time phase confirmation unit 17a, a medical image information acquisition unit 17b, a model information acquisition unit 17c, singular point extraction units 17d and 17e, and contour extraction of inner and outer walls. Means 17f, 17g, singular point fitting means 17h between images and models, contour fitting means 17i between images and models, and image and model alignment means 17j are provided. The image processing unit 17 is configured by software, hardware (circuit), or both. From here, the case where a site of interest is the heart will be described. That is, the medical image is a heart image (heart shape image) G1, and the region model is a heart model M1 (see FIG. 4).

  The time phase confirmation means 17a is a means for confirming the time phases in the electrocardiograms of the heart image G1 and the heart model M1, and adjusting the time phases so that these time phases are the same. By adjusting to the same time phase, the shapes of the heart image G1 and the heart model M1 can be accurately matched. As the time phase, for example, a specific time phase in the diastole, particularly the end diastole is used. When the heart shape model is constructed in the time phase of the end diastole, since the heart image G1 and the heart model M1 are in the same state (substantially stationary state) in the end diastole, the heart image G1 and the heart model M1 in the end diastole When is used, it is possible to match their shapes with higher accuracy.

  The medical image information acquisition unit 17b is a unit that acquires the heart image G1 in a specific time phase (for example, end diastole) from the medical image database 3. Similarly, the model information acquisition unit 17c is a unit that acquires the heart model M1 in a specific time phase (for example, end diastole) from the model database 4. As the information of the heart model M1, for example, set value information such as form, mechanical spring constant, resting membrane potential, and ion concentration is acquired.

  For example, a heart image G1 as shown in FIGS. 4 and 5 is acquired from the medical image database 3 by the medical image information acquisition means 17b. Here, in FIG. 5, the heart image G1 of FIG. 4 is shown two-dimensionally. Further, for example, a heart model M1 as shown in FIGS. 4 and 6 is acquired from the model database 4 by the model information acquisition means 17c. Here, in FIG. 6, the heart model M1 of FIG. 4 is shown two-dimensionally.

  The singular point extraction unit 17d is a unit that selects and extracts a singular point from the heart image G1. Similarly, the singular point extraction unit 17e is a unit that selects and extracts a singular point from the heart model M1. Examples of this singular point include the apex, valve position, aorta, vena cava, coronary artery, ventricular septum, and atrial septum. Note that the singular point is automatically extracted on the heart image G1, and the singular point is set in advance on the heart model M1, and is obtained from the set value information described above.

  As shown in FIG. 5, the singular point extraction means 17d extracts, for example, a plurality of singular points A1 to A4 in the heart image G1. Further, as shown in FIG. 6, for example, a plurality of singular points B1 to B4 are obtained by the singular point extracting means 17e in the heart model M1. Here, each of the singular points A1 to A4 and B1 to B4 is indicated by three-dimensional coordinates (x, y, z). The singular point A2 and the singular point B2 are the origins.

  The inner wall and outer wall contour extracting means 17f is a means for extracting the inner wall and outer wall contours of the heart from the heart image G1. Similarly, the inner wall and outer wall contour extracting means 17g is a means for extracting the inner wall and outer wall contours of the heart from the heart model M1. Note that the contours are automatically extracted on the heart image G1, and the contours are set in advance on the heart model M1, and are obtained from the set value information described above.

  The singular point fitting means 17h between images and models is means for fitting the singular points A1 to A4 and B1 to B4 between the heart image G1 and the heart model M1. At this time, each singular point A1 to A4 of the heart image G1 may be moved, or each singular point B1 to B4 of the heart model M1 may be moved. This is set in advance according to the input operation of the operator to the operation unit 14. By this fitting means, movement information (for example, a conversion coefficient indicating the rotation amount, expansion / contraction amount, etc.) of the singular points A1 to A4 and B1 to B4 is obtained. The movement information of the singular points A1 to A4 and B1 to B4 is stored in the storage unit 15 as synthesis data D1.

  The singular point fitting means 17h between the image and the model, for example, as shown in FIGS. 5 and 6, for example, the separation distances (distance between singular points) m1 to m5 between the singular points A1 to A4 of the heart image G1, The separation distances (distances between singular points) n1 to n5 between the singular points B1 to B4 of the heart model M1 match (m1 = n1, m2 = n2, m3 = n3, m4 = n4, m5 = n5). The singular points A1 to A4 of the heart image G1 or the singular points B1 to B4 of the heart model M1 are moved. Each expansion / contraction amount at this time is linearly distributed to each cell (linear distribution), that is, the expansion / contraction amount of each cell is linearly adjusted, and the movement amount of each cell (movement information of singular points) is obtained. The movement amounts of these cells are stored in the storage unit 15 as synthesis data D1.

  The contour fitting means 17i between the image and the model is a means for fitting the contours of the inner wall and the outer wall between the heart image G1 and the heart model M1. At this time, the contour of the heart image G1 may be moved, or the contour of the heart model M1 may be moved. This is set in advance according to the input operation of the operator to the operation unit 14. By this fitting means, contour movement information (for example, a conversion coefficient indicating a rotation amount, an expansion / contraction amount, etc.) is obtained. The contour movement information is stored in the storage unit 15 as synthesis data D1.

  As shown in FIGS. 5 and 6, the contour fitting means 17i between the image and the model fixes, for example, the distances between singular points m1 to m5 and n1 to n5 (each singular point A1 to A4, B1 to B1). While fixing B4, one midpoint a1 is selected from a plurality of midpoints (marked with x in FIG. 5) on the inner wall of the heart image G1, and a midpoint b1 correlated with the selected midpoint a1 is a heart model. Selected from M1. Next, the middle point a1 of the heart image G1 or the middle point b1 of the heart model M1 so that the shape of the singular point A1-mid point a1-single point A4 and the shape of the singular point B1-mid point b1-single point B4 coincide. Is moved. The cell corresponding to the moved middle point a1 or middle point b1 is also moved together. Each expansion / contraction amount at this time (as much as the cell has moved) is linearly distributed to each cell (linear distribution), that is, the expansion / contraction amount of each cell is linearly adjusted, and the movement amount of each cell (contour movement information) Is required. The movement amounts of these cells are stored in the storage unit 15 as synthesis data D1. Such a process is performed for all the midpoints, and is similarly performed on the outer wall of the heart image G1.

  The image and model alignment unit 17j performs alignment between the heart image G1 and the heart model M1 based on the synthesis data D1 stored in the storage unit 15 and synthesizes them, and the heart image G1 and the heart model This is a means for generating a composite image G2 of M1. Thereby, those synthesized images G2 are obtained. The composite image G2 is displayed on the display unit 13 and, in addition, stored in the storage unit 15 as necessary.

  As shown in FIG. 4, the image and model alignment means 17j uses the synthesis data D1, that is, the amount of movement of each cell, to align the heart image G1 and the heart model M1 (size, shape, etc.). Are combined to synthesize a heart image G1 and a heart model M1. Thereby, the synthesized image G2 of the heart image G1 and the heart model M1 is obtained, and the synthesized image G2 is displayed on the display unit 13. At this time, the wall motion abnormal part R1 and the wall thickness abnormal part R2 are also displayed in different colors on the composite image G2.

  The contour fitting means 17i between the image and the model and the image and model alignment means 17j can be generally configured as follows. Before fitting, the singular points A1 to A4 of the heart image G1 are represented by a coordinate system on the heart image, and the singular points B1 to B4 of the heart model M1 are represented by a coordinate system of the heart model. First, using the coordinate values in the coordinate systems of the singular points A1 to A4 of the heart image G1 and the singular points B1 to B4 of the heart model M1, the relationship between the two coordinate systems is obtained. In general, the relationship is expressed as a = f (b). a is the coordinate value of the heart image, and b is the coordinate value of the heart model. f is a function representing the mapping of the coordinates of both, and a typical example is a linear mapping by a linear function. Other examples include polynomial functions and spline functions. In these latter cases, fitting including deformation can be performed. In either case, the specific shape of the function f is represented by a finite number of parameters. In the fitting process, by solving the simultaneous equations obtained by substituting the coordinate values of the singular points A1 to A4 of the heart image G1 and the singular points B1 to B4 of the heart model M1 into a = f (b). The parameters of the function f are determined. The obtained parameter set specifically represents the correspondence between points in the coordinate system of the heart image G1 and the coordinate system of the heart model M1, and when this is determined, the correspondence between all points is obtained. That's right. Substituting the contour points a1, a2,... Extracted in the heart image G1 into a = f (b), and obtaining b1, b2,. You can also. Conversely, the contour points b1, b2,... Of the heart model M1 are substituted into a = f (b), and the corresponding positions a1, a2,. You can also.

  In such an image processing unit 17, an electrocardiographic synchronization technique and a respiratory motion removal technique between simulation and real-time echocardiography, a technique for registering a heart disease simulation and a CT image, a heart disease simulation model, and real-time ultrasound An alignment technique with an acquired cross section and region of an image, an MPR (Multi Planer Reformation) technique and a VR (Volume Reformation) technique (virtual sonography technique) that extract a corresponding cross section and a corresponding area from the model are used.

  Next, a composite display process of such a medical image diagnostic apparatus 1, in particular, the medical image processing apparatus 5, will be described with reference to FIGS. The control unit 11 of the medical image processing apparatus 5 performs a combining process by the image processing unit 17 and executes a display process for displaying the combined image G2 after the combining process. Here, as an example, a synthesis process for matching the heart image G1 with the heart model M1 is performed.

  As shown in FIG. 7, the control unit 11 selects a heart image G1 and a heart model M1 having the same phase time by using the image processing unit 17 (step S1), and each singular point A1 to A4 ( (See FIG. 5) is extracted (step S2), and the singular points B1 to B4 (see FIG. 6) of the selected heart model M1 are extracted (step S3).

  Next, the control unit 11 calculates the separation distances (distances between singular points) m1 to m5 between the singular points A1 to A4 of the heart image G1 by the image processing unit 17 (step S4), and each singularity of the heart model M1. The distances between the points B1 to B4 (distances between singular points) n1 to n5 are calculated (step S5).

  Next, the control unit 11 causes the image processing unit 17 to use the singular point that is the origin in the heart image G1 so that the distances m1 to m5 and n1 to n5 between the singular points of the heart image G1 and the heart model M1 are the same. One of the singular points A1, A3, A4 other than A2 is moved (step S6), and the expansion / contraction amount is linearly distributed to each cell according to the expansion / contraction direction and expansion / contraction amount at this time, that is, expansion / contraction of each cell The amount is adjusted linearly (step S7). Thereafter, the control unit 11 stores the movement amount and deformation amount of each cell (movement information of the singular points A1 to A4 and B1 to B4) in the storage unit 15 as the synthesis data D1 (step S8).

  Further, the control unit 11 determines whether or not the positions of the singular points A1 to A4 and B1 to B4 are completely matched (Step S9), and repeats Steps S6 to S8 until those positions are completely matched. (NO in step S9). When it is determined that these positions are completely matched within a set accuracy (for example, 1 mm) (YES in step S9), the inner wall of the heart image G1 is displayed as shown in FIG. Select (step S10), extract the outline of the selected inner wall, that is, trace the inner wall (step S11), and set a plurality of midpoints (see FIGS. 5 and 6) in the traced line segment (step S12). . At this time, the midpoints may be set at equal intervals or may be biased. Note that the accuracy setting described above is set in advance in accordance with an input operation performed by the operator on the operation unit 14.

  Next, the control unit 11 selects one midpoint a1 from a plurality of midpoints by using the image processing unit 17 (step S13), and fixes each singular point A1 to A4 with the midpoint a1. Move (step S14). At this time, for example, the control unit 11 has a shape composed of two different singular points and a middle point in the heart image G1 (a singular point A1-a middle point a1-a shape of a singular point A4), and those singular points and middle points. The middle point a1 is moved so that the shape (the shape of the singular point B1-the middle point b1-the singular point B4) consisting of two different singular points and the middle point in the heart model M1 corresponding to the point matches. At this time, the cell or element (element constituting the model) corresponding to the midpoint a1 is also moved together.

  Next, the control unit 11 linearly distributes the expansion / contraction amount at this time to each cell, that is, linearly adjusts the expansion / contraction amount of each cell, and determines the movement amount of each cell (movement information of the contour of the inner wall) as data for synthesis. It is stored in the storage unit 15 as D1 (step S15). It is determined whether or not the distances and directions between the singular points A1 to A4 and the midpoints are within the required accuracy (step S16), and the distances and directions at all the midpoints are within the required accuracy. , Steps S13 to S15 are repeated (NO in Step S16).

  If it is determined that the distance and direction have reached the required accuracy (YES in step S16), the outer wall of the heart image G1 is selected (step S17), and the outline of the selected outer wall is extracted, that is, the outer wall is traced. Then, a plurality of midpoints are set in the traced line segment (step S19). At this time, the midpoints may be set at equal intervals or may be biased.

  Next, the control unit 11 uses the image processing unit 17 to select one midpoint from a plurality of midpoints (step S20), and moves the midpoint while fixing the singular points A1 to A4 ( Step S21). Also at this time, as described above, for example, the control unit 11 has two different singular points and midpoints in the heart image G1 and two different shapes in the heart model M1 corresponding to the singular points and midpoints. The midpoint is moved so that the shape consisting of one singular point and the midpoint matches.

  Next, the control unit 11 linearly distributes the expansion / contraction amount at this time to each cell, that is, linearly adjusts the expansion / contraction amount of each cell, and determines the movement amount of each cell (movement information of the contour of the outer wall) as data for synthesis. It is stored in the storage unit 15 as D1 (step S22). It is determined whether or not the distance and direction between each singular point and the midpoint have reached the required accuracy (step S23), and step S20 is performed until the distance and direction have reached the required accuracy at all the midpoints. To S22 are repeated (NO in step S23).

  When it is determined that the distance and direction have reached the required accuracy (YES in step S23), the composition data D1, which is stored in the storage unit 15, that is, the movement amount of each cell is used. G1 is deformed and matched with the heart model M1 (step S24). Thereby, a composite image G2 of the heart image G1 and the heart model M1 is obtained (see FIG. 4). The control unit 11 displays the composite image G2 on the display unit 13, and further stores the composite image G2 in the storage unit 15 as necessary. At this time, the control unit 11 displays the wall motion abnormal part R1 and the wall thickness abnormal part R2 on the composite image G2 by changing the respective colors.

  With such a composite display process, the composite image G2 is displayed on the display unit 13 and is visually recognized by a diagnostician such as a doctor. At this time, the heart image G1 and the heart model M1 are displayed as one composite image G2, and it becomes easy to recognize the relationship between the heart shape information of the subject and its function information. The situation (state) can be accurately grasped. Furthermore, since information on a diseased part for simulation on the heart model M1 is displayed superimposed on the heart image G1, new qualitative diagnostic information for the disease of the heart, which is the target part, can be given to the diagnostician. it can. In particular, since it becomes possible to accurately grasp the condition (form and function, etc.) of the patient's heart without depending on the experience and skill level of the diagnostician, an accurate diagnosis can be performed.

  Furthermore, by displaying the abnormal part such as the wall motion abnormal part R1 and the wall thickness abnormal part R2 in the composite image G2, the abnormal part is displayed in the composite image G2, and the abnormal part is immediately displayed in addition to the state of the heart. And it can be grasped accurately. That is, Mr. A's (individual) heart model M1 is created from a CT image without any wall motion abnormalities, and abnormalities such as wall motion abnormalities are reproduced on the composite image G2 by a heart disease simulation using the heart model M1. Therefore, new qualitative diagnostic information for heart diseases is given to doctors, etc., and doctors and other diagnosticians can easily recognize the relationship between the heart shape information of the subject and its functional information. It can be carried out. Furthermore, since various comparative examinations and comparative diagnoses between the heart image G1 such as a CT image or an ultrasound image and the heart disease simulation of the heart model M1 can be easily performed, the patient's heart condition (form and Function etc.) can be accurately grasped, and as a result, an accurate diagnosis can be performed.

  As described above, according to the embodiment of the present invention, a medical image (for example, heart image G1) that is an image captured by the medical image capturing apparatus 2 and indicates a target region of a subject, and a disease in the target region. Is combined with a region model (for example, a heart model M1) indicating the region of interest, and a medical image and a combined image G2 of the region model are generated. Since it is displayed as a composite image G2 and it becomes easy to recognize the relationship between the form information of the region of interest of the subject and the function information thereof, a diagnostician such as a doctor can accurately grasp the state (state) of the subject's heart. Can do. In addition, since it becomes possible to superimpose information on a diseased part for simulation on a part model on a medical image (diagnostic image) and display it as a composite image G2, new qualitative diagnostic information for the disease of the attentional part Can be given. As a result, a diagnostician such as a doctor can accurately grasp the status of the site of interest of the subject.

  In particular, when the site of interest is the heart, the combined diagnostic information (image information) of the heart image G1 such as a CT image or an ultrasound image and the heart model M1 of heart disease simulation is displayed in comparison, that is, superimposed. Therefore, it is possible to provide a comprehensive diagnosis environment for heart diseases. That is, it is possible to present qualitative diagnostic information related to ischemic heart disease, angina pectoris, and the like, for example, the activity of ionic current of cardiomyocytes, the mechanical stretching (movement) of cardiomyocytes, and the like. Thereby, the diagnostician can obtain new qualitative diagnostic information for estimating the infarct state or ischemic state of the myocardium. In addition, the cardiac function can be observed in a wide visual field area that cannot be covered only by the ultrasonic image.

  When a medical image (for example, heart image G1) and a part model (for example, heart model M1) are combined, a plurality of singular points A1 to A4 of the medical image and a plurality of singular points B1 to B4 of the part model are obtained. By extracting and aligning the attention site of the medical image and the attention site of the site model based on the plurality of singular points A1 to A4 of the extracted medical image and the plurality of singular points B1 to B4 of the site model, A composite image G2 of a medical image and a part model can be generated well.

  Furthermore, in the case of performing alignment, based on the plurality of singular points A1 to A4 of the extracted medical image (for example, heart image G1) and the plurality of singular points B1 to B4 of the region model (for example, heart model M1), The attention site of the medical image is matched with the size of the attention site of the image and the attention site of the site model, and based on the plurality of singular points A1 to A4 of the extracted medical image and the plurality of singular points B1 to B4 of the site model. By matching the shape of the region model with the target region of the region model, the medical image and the combined image G2 of the region model can be generated with higher accuracy.

  In addition, when the sizes are matched, the distances m1 to m5 between the singular points from the plurality of singular points A1 to A4 of the extracted medical image (for example, the heart image G1) and the extracted part model (for example, the heart) The separation distances n1 to n5 between the singular points are obtained from the plurality of singular points B1 to B4 of the model M1), and the obtained separation distances m1 to m5 of the medical image and the obtained separation distances n1 to n5 of the part model. Since the size of the site of interest in the medical image and the site of interest in the site model are matched so that n5 is the same, it is possible to generate the combined image G2 of the medical image and site model through easy processing. In addition, since the sizes of the medical image and the part model can be made to coincide with each other with high accuracy, it is possible to obtain a highly accurate composite image G2 while preventing an increase in processing time. That.

  In addition, in the case of matching the shapes, the contour of the target region (for example, heart image G1) of the medical image and the contour of the target region of the region model (for example, heart model M1) are extracted, and a plurality of specific points of the extracted medical image are extracted. In addition, based on a plurality of singular points of the extracted part model, the attention part of the medical image and the part model are focused so that the contour of the attention part of the extracted medical image and the contour of the attention part of the extracted part model are the same. By matching the shape with the part, it is possible to generate a composite image G2 of the medical image and the part model with easy processing, and furthermore, it is possible to match the shape of the medical image and the part model with high accuracy. Therefore, it is possible to obtain a synthesized image G2 with high accuracy while preventing an increase in processing time.

  Furthermore, since the abnormal part (for example, the wall motion abnormal part R1 or the wall thickness abnormal part R2) is displayed in the composite image G2 by showing the abnormal part (for example, the wall motion abnormal part R1 or the wall thickness abnormal part R2) in the generated composite image G2. It is possible to provide new qualitative diagnostic information for the diagnosis, so that the diagnostician can immediately and accurately grasp the abnormal part in addition to the heart condition, and further, the heart condition (form and function, etc.) ) Can be easily grasped.

(Other embodiments)
The present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the scope of the invention.

  For example, in the above-described embodiment, when acquiring medical image information (heart image G1) or model information (heart model M1), a specific time phase (end diastole) in the diastole is used as the time phase. However, the present invention is not limited to this, and other time phases may be used. Furthermore, medical image information and model information may be acquired for each time phase to generate the composite image G2. In this case, it is possible to intuitively recognize a time-series change in the state of the heart by arranging a plurality of generated composite images G2 in time series and continuously displaying them on the display unit 13, so that the heart Can easily grasp the situation.

  In the above-described embodiment, the medical imaging apparatus 2 is configured using an X-ray tomography apparatus (X-ray CT apparatus), an ultrasonic diagnostic apparatus, or the like. Other imaging apparatuses may be used, and further, the medical image processing apparatus 5 is incorporated in the medical imaging apparatus 2 such as an X-ray tomography apparatus or an ultrasonic diagnostic apparatus to constitute the medical image diagnostic apparatus 1. It may be.

1 is a block diagram showing a schematic configuration of a medical image diagnostic apparatus according to an embodiment of the present invention. It is a block diagram which shows schematic structure of the medical image processing apparatus with which the medical image diagnostic apparatus shown in FIG. 1 is provided. FIG. 3 is a block diagram illustrating a schematic configuration of an image processing unit included in the medical image processing apparatus illustrated in FIG. 2. It is explanatory drawing for demonstrating the image composition which the image process part shown in FIG. 3 performs. It is a schematic diagram which shows a heart image in order to demonstrate the image synthesis which the image process part shown in FIG. 3 performs. It is a schematic diagram which shows a heart model in order to demonstrate the image synthesis which the image process part shown in FIG. 3 performs. 3 is a flowchart showing a flow of a synthesis process performed by the medical image diagnostic apparatus shown in FIG. 1, particularly, the medical image processing apparatus shown in FIG. 3 is a flowchart showing a flow of a synthesis process performed by the medical image diagnostic apparatus shown in FIG. 1, particularly, the medical image processing apparatus shown in FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Medical image diagnostic apparatus 2 Medical image imaging device 5 Medical image processing apparatus A1-A4 Singular point B1-B4 Singular point G1 Medical image (heart image)
G2 Composite image M1 Site model (heart model)
m1-m5 separation distance (singular point separation distance)
n1-n5 separation distance (singular point separation distance)

Claims (8)

A medical image that is an image captured by a medical imaging apparatus and shows a target region of a subject and a region model that simulates a disease of the target region and indicates the target region are aligned. synthesized Te, comprising means for generating and displaying a composite image of the medical image and the site model,
The site model is stored in the model database, a medical image processing apparatus according to claim Rukoto comprise mechanical spring constant, resting membrane potential and the information of the ion concentration. The means for generating and displaying is
Means for extracting a plurality of singular points of the medical image and a plurality of singular points of the part model;
Means for aligning a site of interest of the medical image and a site of interest of the site model based on the plurality of singular points of the extracted medical image and the plurality of singular points of the site model;
The medical image processing apparatus according to claim 1, further comprising: The means for performing the alignment includes
Means for matching the size of the site of interest of the medical image and the site of interest of the site model based on the plurality of singular points of the extracted medical image and the plurality of singular points of the site model;
Means for matching the shapes of the attention site of the medical image and the attention site of the site model based on the plurality of singular points of the extracted medical image and the plurality of singular points of the site model;
The medical image processing apparatus according to claim 2, further comprising:   The means for matching the sizes obtains a separation distance between each singular point from a plurality of singular points of the extracted medical image and a separation distance between each singular point from the plurality of singular points of the extracted part model. The size of the attention site of the medical image and the attention site of the site model are set such that the obtained separation distance of each of the medical images and the obtained separation distance of each of the site models are the same. The medical image processing apparatus according to claim 3, wherein the medical image processing apparatuses match each other.   The means for matching the shapes extracts the outline of the site of interest of the medical image and the outline of the site of interest of the site model, and based on the extracted singular points of the medical image and the singular points of the site model And the shape of the target site of the medical image and the target site of the site model are matched so that the contour of the target site of the extracted medical image and the profile of the target site of the site model are the same. The medical image processing apparatus according to claim 3 or 4.   The medical image processing apparatus according to any one of claims 1 to 5, further comprising means for indicating an abnormal portion of the attention site in the generated composite image. The medical image processing apparatus according to claim 1, wherein the generating and displaying unit includes a display unit that displays the generated composite image. A medical image photographing device for photographing a medical image;
A medical image processing apparatus according to any one of claims 1 to 7;
A medical image diagnostic apparatus comprising:

Images