Medical image processing device, X-ray diagnostic device, and medical image processing method

Abstract

Embodiments relate to a medical image processing device, an X-ray diagnostic device, and a medical image processing method. The purpose is to improve the visual recognizability of X-ray images. The medical image processing device of the embodiment includes an acquisition unit, a processing unit, and an output unit. The acquisition unit acquires multiple X-ray images including a device inserted into a subject's body. The processing unit suppresses the movement of a characteristic portion between the X-ray images, the characteristic portion being located at a position separated from the front end of the device and having a characteristic shape. The output unit outputs the multiple X-ray images in which the movement of the characteristic portion is suppressed.

Description

[0001] Reference to related applications

[0002] This application enjoys the benefit of priority of Japanese Patent Application No. 2020-129283 filed on July 30, 2020, Japanese Patent Application No. 2020-131435 filed on August 3, 2020, and Japanese Patent Application No. 2021-124826 filed on July 29, 2021, and the entire contents of these Japanese patent applications are cited in this application. Technical Field

[0003] The embodiments relate to a medical image processing apparatus, an X-ray diagnostic apparatus, and a medical image processing method. Background Art

[0004] Various endovascular treatments are known, performed by inserting devices such as catheters and guidewires into a subject's blood vessels. Furthermore, during endovascular treatment, X-ray images are collected and displayed to assist the operator in operating the device. However, depending on the treatment area, the device may move on the X-ray image, making it difficult to observe.

[0005] Furthermore, while blood vessel shapes typically do not appear on X-ray images, previously acquired blood vessel images are sometimes displayed to assist with device manipulation within blood vessels. However, depending on the treatment area, image motion due to factors such as heartbeat and respiration can sometimes make observation difficult. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to improve the visual recognizability of X-ray images.

[0007] A medical image processing apparatus according to an embodiment includes an acquisition unit, a processing unit, and an output unit. The acquisition unit acquires a plurality of X-ray images including a device inserted into a subject's body. The processing unit suppresses movement of a characteristic portion, which is separate from the distal end of the device and has a characteristic shape, between the X-ray images. The output unit outputs the plurality of X-ray images in which the movement of the characteristic portion is suppressed.

[0008] Effect

[0009] According to the medical image processing apparatus of the embodiment, the visibility of X-ray images can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 This is a block diagram showing an example of the configuration of the medical image processing system according to the first embodiment.

[0011] Figure 2 This is a block diagram showing an example of the configuration of the X-ray diagnostic apparatus according to the first embodiment.

[0012] Figure 3 This is a diagram showing an example of processing of the processing function of the first embodiment.

[0013] Figure 4 This is a diagram showing an example of processing of the processing function of the first embodiment.

[0014] Figure 5 This is a diagram showing an example of matching processing according to the first embodiment.

[0015] Figure 6 This is a flowchart for explaining a series of processes performed by the medical image processing apparatus according to the first embodiment.

[0016] Figure 7 This is a diagram showing an example of matching processing according to the second embodiment.

[0017] Figure 8 It is a diagram showing a display example of the second embodiment.

[0018] Figure 9 This is a diagram showing an example of equipment according to the second embodiment.

[0019] Figure 10 This is a block diagram showing an example of the configuration of an X-ray diagnostic apparatus according to the second embodiment.

[0020] Figure 11A It is a diagram showing a display example of the first embodiment.

[0021] Figure 11B It is a diagram showing a display example of the third embodiment.

[0022] Figure 12A These are diagrams for explaining the first process and the second process of the third embodiment.

[0023] Figure 12B These are diagrams for explaining the first process and the second process of the third embodiment.

[0024] Figure 12C These are diagrams for explaining the first process and the second process of the third embodiment.

[0025] Figure 13 It is a diagram for explaining the fixing position of the third embodiment.

[0026] Figure 14 This is a flowchart for explaining a series of processes performed by the medical image processing apparatus according to the third embodiment. DETAILED DESCRIPTION

[0027] Hereinafter, embodiments of a medical image processing apparatus, an X-ray diagnostic apparatus, and a program will be described in detail with reference to the accompanying drawings.

[0028] (First embodiment)

[0029] In the first embodiment, Figure 1 The medical image processing system 1 shown in FIG. 1 is described as an example. For example, the medical image processing system 1 includes an X-ray diagnostic apparatus 10 and a medical image processing apparatus 30. The X-ray diagnostic apparatus 10 and the medical image processing apparatus 30 are connected to each other via a network NW. Figure 1 This is a block diagram showing an example of the configuration of the medical image processing system 1 according to the first embodiment.

[0030] The X-ray diagnostic apparatus 10 collects X-ray images from the subject P1. For example, while subject P1 is undergoing intravascular treatment, the X-ray diagnostic apparatus 10 collects two-dimensional X-ray images from the subject P1 over time and sequentially transmits the collected X-ray images to the medical image processing apparatus 30. The structure of the X-ray diagnostic apparatus 10 will be described later.

[0031] The medical image processing device 30 acquires the X-ray images collected by the X-ray diagnostic device 10 and performs various processes using the X-ray images. For example, the medical image processing device 30 performs processes to improve the visibility of the device and presents the processed X-ray images to the user. Figure 1 As shown, it has an input interface 31 , a display 32 , a memory 33 and a processing circuit 34 .

[0032] The input interface 31 accepts various input operations from the user, converts the accepted input operations into electrical signals, and outputs them to the processing circuit 34. For example, the input interface 31 can be implemented using a mouse, keyboard, trackball, switch, button, joystick, touchpad for input operations by touching the operating surface, touchscreen integrating a display screen and touchpad, non-contact input circuit using optical sensors, or audio input circuit. Furthermore, the input interface 31 can also be implemented using a tablet terminal capable of wirelessly communicating with the processing circuit 34. Furthermore, the input interface 31 can also be a circuit that accepts input operations from the user through motion capture. For example, the input interface 31 processes signals obtained via a tracker and images collected by the user, thereby accepting the user's body movements, line of sight, and other input operations. Furthermore, the input interface 31 is not limited to interfaces with physical operating components such as a mouse and keyboard. For example, a signal processing circuit that receives electrical signals corresponding to input operations from an external input device separate from the main body of the medical image processing device 30 and outputs these electrical signals to the main body of the medical image processing device 30 is also included in the example of the input interface 31.

[0033] The display 32 displays various information. For example, the display 32 displays X-ray images processed by the processing circuit 34 (described later). Furthermore, for example, the display 32 displays a GUI (Graphical User Interface) for accepting various instructions and settings from the user via the input interface 31. For example, the display 32 is a liquid crystal display or a CRT (Cathode Ray Tube) display. The display 32 can be a desktop device or a tablet terminal capable of wireless communication with the main body of the medical image processing device 30.

[0034] In addition, Figure 1 In the description, the medical image processing apparatus 30 is assumed to include a display 32. However, the medical image processing apparatus 30 may also include a projector in place of or in addition to the display 32. The projector can project images onto a screen, a wall, a floor, or the body surface of the subject P1 under the control of the processing circuit 34. For example, the projector can also project images onto any plane, object, or space using projection mapping.

[0035] The memory 33 stores various data. For example, the memory 33 stores X-ray images before and after processing by the processing circuit 34 (described later). Furthermore, the memory 33 stores programs used by the circuits included in the medical image processing device 30 to implement their functions. For example, the memory 33 can be implemented by semiconductor memory devices such as RAM (Random Access Memory), flash memory, a hard disk, or an optical disk. Alternatively, the memory 33 can be implemented by a server cluster (cloud) connected to the medical image processing device 30 via a network.

[0036] The processing circuit 34 controls the overall operation of the medical image processing apparatus 30 by executing a control function 34a, an acquisition function 34b, a processing function 34c, and an output function 34d. Here, the acquisition function 34b is an example of an acquisition unit. Furthermore, the processing function 34c is an example of a processing unit. Furthermore, the output function 34d is an example of an output unit.

[0037] For example, the processing circuit 34 reads and executes a program corresponding to the control function 34 a from the memory 33 , thereby controlling various functions such as the acquisition function 34 b , the processing function 34 c , and the output function 34 d based on input operations received from the user via the input interface 31 .

[0038] Furthermore, for example, the processing circuit 34 reads and executes a program corresponding to the acquisition function 34b from the memory 33, thereby acquiring an X-ray image of the subject P1. Furthermore, for example, the processing circuit 34 reads and executes a program corresponding to the processing function 34c from the memory 33, thereby processing the X-ray image. Furthermore, for example, the processing circuit 34 reads and executes a program corresponding to the output function 34d from the memory 33, thereby outputting an X-ray image processed by the processing function 34c. Details of the processing by the acquisition function 34b, the processing function 34c, and the output function 34d will be described later.

[0039] exist Figure 1 In the illustrated medical image processing device 30, each processing function is stored in a memory 33 in the form of a computer-executable program. The processing circuit 34 is a processor that implements the functions corresponding to each program by reading and executing the program from the memory 33. In other words, the processing circuit 34, having read the program, has the function corresponding to the read program.

[0040] In addition, Figure 1In the description, the control function 34a, the acquisition function 34b, the processing function 34c, and the output function 34d are implemented by a single processing circuit 34. However, the processing circuit 34 may be composed of a plurality of independent processors, and each processor may execute a program to implement these functions. Furthermore, the processing functions of the processing circuit 34 may be appropriately distributed or integrated into a single or multiple processing circuits.

[0041] Alternatively, the processing circuit 34 may utilize a processor of an external device connected via the network NW to implement functions. For example, the processing circuit 34 reads and executes programs corresponding to various functions from the memory 33 and utilizes a server group (cloud) connected to the medical image processing apparatus 30 via the network NW as computing resources, thereby implementing Figure 1 The functions shown.

[0042] Next, use Figure 2 The X-ray diagnostic apparatus 10 will be described. Figure 2 1 is a block diagram showing an example of the configuration of the X-ray diagnostic apparatus 10 according to the first embodiment. Figure 2 As shown, the X-ray diagnostic apparatus 10 includes an X-ray high voltage device 101 , an X-ray tube 102 , an X-ray collimator 103 , a top plate 104 , a C-arm 105 , an X-ray detector 106 , an input interface 107 , a display 108 , a memory 109 , and a processing circuit 110 .

[0043] The X-ray high-voltage device 101 supplies a high voltage to the X-ray tube 102 under the control of the processing circuit 110. For example, the X-ray high-voltage device 101 includes a high-voltage generator, which includes circuits such as a transformer and a rectifier to generate the high voltage applied to the X-ray tube 102, and an X-ray control device that controls the output voltage according to the X-rays emitted by the X-ray tube 102. The high-voltage generator can be a transformer or inverter type.

[0044] The X-ray tube 102 is a vacuum tube having a cathode (filament) that generates thermal electrons and an anode (target) that generates X-rays upon collision with the thermal electrons. The X-ray tube 102 generates X-rays by irradiating the anode with thermal electrons from the cathode using a high voltage supplied from the X-ray high voltage device 101.

[0045] The X-ray collimator 103 includes a collimator that narrows the irradiation range of X-rays generated by the X-ray tube 102 and a filter that adjusts the X-rays irradiated from the X-ray tube 102 .

[0046] The collimator in the X-ray aperture device 103 has, for example, four slidable aperture blades. By sliding the aperture blades, the collimator narrows the X-rays generated by the X-ray tube 102 and irradiates the subject P1. The aperture blades are plate-shaped members made of lead or other materials and are located near the X-ray irradiation port of the X-ray tube 102 to adjust the X-ray irradiation range.

[0047] The filter in the X-ray aperture 103 aims to reduce the radiation dose to the subject P1 and improve the quality of X-ray images. The filter changes the quality of the transmitted X-rays according to its material and thickness, reducing soft-ray components that are easily absorbed by the subject P1 and high-energy components that reduce the contrast of the X-ray image. Furthermore, the filter varies the X-ray dose and irradiation range according to its material, thickness, and position, attenuating the X-rays so that the X-rays emitted from the X-ray tube 102 to the subject P1 have a predetermined distribution.

[0048] For example, the X-ray collimator 103 includes a drive mechanism, such as a motor and an actuator. This drive mechanism operates under the control of the processing circuit 110 (described later), thereby controlling X-ray irradiation. For example, the X-ray collimator 103 applies a drive voltage to the drive mechanism based on a control signal received from the processing circuit 110, thereby adjusting the aperture of the collimator blades and controlling the range of X-ray irradiation directed at the subject P1. Furthermore, for example, the X-ray collimator 103 applies a drive voltage to the drive mechanism based on a control signal received from the processing circuit 110, thereby adjusting the position of the filter and controlling the distribution of the X-ray dose directed at the subject P1.

[0049] The top plate 104 is a bed on which the subject P1 is placed and is positioned above a diagnostic couch (not shown). The subject P1 is not included in the X-ray diagnostic apparatus 10. The diagnostic couch includes a drive mechanism, such as a motor and an actuator. Under the control of the processing circuit 110 (described later), the movement and tilting of the top plate 104 are controlled by operating the drive mechanism. For example, the diagnostic couch applies a drive voltage to the drive mechanism based on a control signal received from the processing circuit 110, thereby moving or tilting the top plate 104.

[0050] The C-arm 105 holds the X-ray tube 102, the X-ray collimator 103, and the X-ray detector 106 in a manner that they are opposite to each other across the subject P1. For example, the C-arm 105 has a driving mechanism such as a motor and an actuator, and rotates or moves by operating the driving mechanism under the control of the processing circuit 110 described later. For example, the C-arm 105 applies a driving voltage to the driving mechanism based on a control signal received from the processing circuit 110, thereby rotating or moving the X-ray tube 102, the X-ray collimator 103, and the X-ray detector 106 relative to the subject P1, thereby controlling the irradiation position and irradiation angle of the X-rays. In addition, Figure 2 In the description, the case where the X-ray diagnostic apparatus 10 is a single-plane system is taken as an example, but the embodiment is not limited thereto, and a dual-plane system may also be employed.

[0051] The X-ray detector 106 is, for example, an X-ray flat panel detector (FPD) having detection elements arranged in a matrix. The X-ray detector 106 detects X-rays emitted from the X-ray tube 102 and transmitted through the subject P1, and outputs a detection signal corresponding to the detected X-ray dose to the processing circuit 110. The X-ray detector 106 may be an indirect conversion type detector having a grid, a scintillator array, and a photosensor array, or a direct conversion type detector having semiconductor elements that convert incident X-rays into electrical signals.

[0052] The input interface 107 can be configured similarly to the above-described input interface 31 . For example, the input interface 107 receives various input operations from a user, converts the received input operations into electrical signals, and outputs the electrical signals to the processing circuit 110 .

[0053] The display 108 can be configured similarly to the display 32. For example, the display 108 displays X-ray images collected from the subject P1 under the control of the processing circuit 110. The X-ray diagnostic apparatus 10 may also include a projector in place of or in addition to the display 108.

[0054] The memory 109 can be configured similarly to the aforementioned memory 33. For example, the memory 109 stores X-ray images collected from the subject P1 or stores programs used by circuits included in the X-ray diagnostic apparatus 10 to implement their functions.

[0055] The processing circuit 110 executes a control function 110a, a collection function 110b, and an output function 110c, thereby controlling the overall operation of the X-ray diagnostic apparatus 10. The collection function 110b is an example of a collection unit, and the output function 110c is an example of an output unit.

[0056] For example, the processing circuit 110 reads and executes a program corresponding to the control function 110 a from the memory 109 , thereby controlling various functions such as the collection function 110 b and the output function 110 c based on input operations received from the user via the input interface 107 .

[0057] Furthermore, for example, the processing circuit 110 reads and executes a program corresponding to the collection function 110b from the memory 109, thereby collecting X-ray images from the subject P1. Furthermore, for example, the processing circuit 110 reads and executes a program corresponding to the output function 110c from the memory 109, thereby outputting the X-ray images collected from the subject P1. Details of the processing performed by the collection function 110b and the output function 110c will be described later.

[0058] exist Figure 2 In the illustrated X-ray diagnostic apparatus 10, each processing function is stored in the form of a computer-executable program in the memory 109. The processing circuit 110 is a processor that implements the functions corresponding to each program by reading and executing the program from the memory 109. In other words, the processing circuit 110, having read the program, has the function corresponding to the read program.

[0059] In addition, Figure 2 In the description, the control function 110a, the collection function 110b, and the output function 110c are implemented by a single processing circuit 110. However, the processing circuit 110 may be composed of a plurality of independent processors, and each processor may execute a program to implement the functions. Furthermore, the processing functions of the processing circuit 110 may be appropriately distributed or integrated into a single or multiple processing circuits.

[0060] Alternatively, the processing circuit 110 may utilize a processor of an external device connected via the network NW to implement functions. For example, the processing circuit 110 reads and executes a program corresponding to each function from the memory 109 and utilizes a server group connected to the X-ray diagnostic apparatus 10 via the network NW as a computing resource, thereby implementing Figure 2 The functions shown.

[0061] The above describes a configuration example of the medical image processing system 1. With this configuration, the medical image processing device 30 in the medical image processing system 1 improves the visibility of a device inserted into the body of the subject P1 through processing by the processing circuit 34.

[0062] First, the collection of X-ray images from subject P1 will be described. For example, while a device is inserted into subject P1 and endovascular treatment is being performed, the collection function 110b collects X-ray images of the device within the imaging range over time. The imaging range can be set by a user, such as a physician performing the endovascular treatment, or it can be automatically set based on patient information.

[0063] Specifically, the collection function 110b controls the operation of the X-ray collimator 103, adjusting the aperture of the collimator's aperture blades to control the range of X-ray exposure to the subject P1. Furthermore, the collection function 110b controls the operation of the X-ray collimator 103 to adjust the position of the filter, thereby controlling the X-ray dose distribution. Furthermore, the collection function 110b controls the operation of the C-arm 105 to rotate or move it. Furthermore, for example, the collection function 110b controls the operation of the diagnostic bed to move or tilt the top plate 104. In other words, the collection function 110b controls the operation of the mechanical system, including the X-ray collimator 103, C-arm 105, and top plate 104, to control the imaging range and angle of the collected X-ray images.

[0064] The collection function 110b also controls the X-ray high-voltage device 101, adjusting the voltage supplied to the X-ray tube 102 to control the X-ray dosage and on / off control of the X-ray irradiation to the subject P1. Furthermore, the collection function 110b generates X-ray images based on the detection signals received from the X-ray detector 106. The collection function 110b can also perform various image processing on the generated X-ray images. For example, the collection function 110b can perform noise reduction processing and scattered radiation correction using image processing filters on the generated X-ray images.

[0065] In addition, the device inserted into the body of the subject P1 is generally linear. Examples of such linear devices include catheters and guidewires used in intravascular treatment. For example, in cardiac PCI (Percutaneous Coronary Intervention), a user such as a physician operates the guidewire inserted into the body of the subject P1 to advance it to the lesion. Here, the lesion is, for example, a stenotic portion of a blood vessel such as a chronic total occlusion (CTO). In this case, the collection function 110b collects X-ray images including the tip of the guidewire within the imaging range over time. In addition, the collection function 110b can also continue to collect X-ray images while appropriately adjusting the imaging range to follow the tip position of the guidewire when the tip position of the guidewire moves.

[0066] Next, the acquisition function 34b acquires the X-ray images collected by the X-ray diagnostic apparatus 10 via the network NW. For example, first, the output function 110c transmits the X-ray images collected by the collection function 110b to an image storage device via the network NW. In this case, the acquisition function 34b can acquire the X-ray images from the image storage device via the network NW. An example of such an image storage device is a PACS (Picture Archiving Communication System) server. Alternatively, the acquisition function 34b can acquire the X-ray images directly from the X-ray diagnostic apparatus 10 without intervening through other devices.

[0067] Next, processing function 34c performs processing to suppress device motion on the X-ray image. Specifically, depending on the treatment target site, device motion may occur due to, for example, the heartbeat or respiration of subject P1. Furthermore, if the collected X-ray image is displayed as is, device motion may appear on the X-ray image, making it difficult for the user to visually identify the device. Therefore, processing function 34c performs processing to suppress device motion on the X-ray image before display.

[0068] Here, use Figure 3 An example of processing performed by the processing function 34c will be described. Figure 3 This is a diagram showing an example of processing by the processing function 34c according to the first embodiment. Figure 3 The X-ray image I111 and the X-ray image I112 are X-ray images that include the device D1 inserted into the body of the subject P1 within the imaging range. For example, the X-ray image I112 is an X-ray image in the next frame of the X-ray image I111.

[0069] exist Figure 3 In the case shown, the processing function 34c performs processing to suppress the movement of the front end position of the device D1 on the image. Specifically, the processing function 34c first determines the front end position of the device D1 in each of the X-ray image I111 and the X-ray image I112. Next, the processing function 34c processes the X-ray image I112 in such a way that the front end position of the device D1 on the image is consistent between the X-ray image I111 and the X-ray image I112. For example, the processing function 34c moves the X-ray image I112 parallel to the front end position of the device D1 determined in the X-ray image I111. In addition, the output function 34d causes the display 32 to display the X-ray image I111 and the processed X-ray image I112 in sequence. In this case, the front end position of the device D1 is fixed on the image, so the user can observe the device D1 more easily.

[0070] However, in Figure 3 In the case shown, even if the user moves the device D1 forward or backward, the front end position of the device D1 does not move on the image. Figure 3 The fixed display shown is useful for observing the front and surrounding areas of the device D1, but it is sometimes difficult to recognize its movement when operating the device D1.

[0071] Therefore, processing function 34c is as follows Figure 4 As shown, by performing a process of suppressing the movement of a characteristic portion that is separate from the front end of the device D1 and has a characteristic shape, the visibility of the device D1 is further improved. Figure 4 : is a diagram showing an example of the processing of the processing function 34c of the first embodiment. Figure 4 The X-ray image I121 and the X-ray image I122 are X-ray images that include the device D1 inserted into the body of the subject P1 within the imaging range. For example, the X-ray image I122 is an X-ray image in the next frame of the X-ray image I121.

[0072] Here, the device D1 is inserted into the blood vessel of the subject P1 and deforms along the shape of the blood vessel. That is, the device D1 has a portion that is deformed by insertion into the blood vessel and has a characteristic shape. Hereinafter, the portion of the device D1 that is generated by insertion into the blood vessel and has a characteristic shape of the device D1 is also recorded as a characteristic portion. For example, the characteristic portion is a portion with a large curvature in the linear device D1. That is, in Figure 4 In the illustrated case, the processing function 34 c performs processing to suppress the movement of characteristic portions between the X-ray image I 121 and the X-ray image I 122 .

[0073] For example, the processing function 34c can suppress the motion of the feature part by performing matching processing between images. Figure 5 An example of matching processing between images will be described. Figure 5 This is a diagram showing an example of matching processing according to the first embodiment.

[0074] In addition, Figure 5 In the example of the matching process between images, the endpoint-free DP (Dynamic Programming) matching is described. Figure 5 In the following, the case where the X-ray image I131 in frame 1 is used as a reference frame and the motion of the characteristic portion is suppressed in the X-ray image I13t in frame t after frame 1 is described. Figure 5In the illustrated case, the processing function 34 c suppresses the motion of the characteristic portion by performing matching processing between the X-ray image I131 and the X-ray image I13 t.

[0075] Specifically, the processing function 34c first extracts the contour of the device D1 from the X-ray image I131. Next, the processing function 34c generates a contour model C1 by creating multiple vertices on the extracted contour. Similarly, the processing function 34c extracts the contour of the device D1 from the X-ray image I13t and generates a contour model Ct.

[0076] Next, the processing function 34c finds corresponding points between the X-ray image I131 and the X-ray image I13t. For example, the processing function 34c defines a cost corresponding to the correspondence between multiple vertices in the contour model C1 and multiple vertices in the contour model Ct, and finds the corresponding points by minimizing this cost. The cost can be defined, for example, based on the difference in feature values between the corresponding vertices.

[0077] For example, processing function 34c adds the curvature of device D1 at each vertex in contour models C1 and Ct and the surrounding pixel values as features. The surrounding pixel values are, for example, the average of the pixel values within a predetermined range from the vertex. Furthermore, processing function 34c defines a cost based on the difference in feature values and solves a minimization problem to minimize the cost. This allows corresponding points to be found so that vertices with the same degree of feature values correspond to each other.

[0078] Furthermore, the processing function 34c aligns the X-ray image I13t with respect to the X-ray image I131 based on the vertex correspondence. For example, the processing function 34c calculates a rotation and translation matrix W based on the vertex correspondence using singular value decomposition or the like. The processing function 34c then applies the rotation and translation matrix W to translate and rotate the X-ray image I13t parallely, thereby aligning the X-ray image I13t with respect to the X-ray image I131.

[0079] Here, in the calculation of the rotation-translation matrix W, the curvature of each vertex is used as a feature quantity. In addition, the curvature of the straight portion of the device D1 is approximately zero, and the characteristic portion of the device D1 where the curvature changes contributes more to the calculation of the rotation-translation matrix W. Therefore, when the X-ray image I13t and the X-ray image I131 are aligned using the rotation-translation matrix W, as shown in FIG. Figure 5 As shown, the characteristic portion is preferentially aligned and its motion is suppressed. Furthermore, the output function 34d displays the X-ray image I131 and the X-ray image I13t to which the rotation and translation matrix W is applied on the display 32 in sequence.

[0080] Furthermore, the processing function 34c can generate the contour model C1 for the entire device D1 appearing in the X-ray image I131, or for a portion of the device D1. For example, the processing function 34c can generate the contour model C1 for a portion of a predetermined length from the front end of the device D1. Alternatively, for example, the processing function 34c can generate vertices at regular intervals from the front end of the device D1, and terminate the generation of vertices when the number of vertices reaches a predetermined number, thereby generating the contour model C1. Alternatively, for example, the processing function 34c can generate vertices at regular intervals from the front end of the device D1, and terminate the generation of vertices when the distribution of feature quantities at the generated vertices exceeds a predetermined variance, thereby generating the contour model C1. The same applies to the contour model Ct.

[0081] In addition, Figure 5 , the vertices in the contour model are generated at substantially regular intervals, but the intervals between vertices can be changed as appropriate. For example, the processing function 34c can arrange the vertices densely in the portion with large curvature of the contour model and sparsely in the portion with small curvature.

[0082] In addition, Figure 5 While the description assumes that corresponding points are found, the embodiment is not limited to this. For example, the processing function 34c creates a graph showing changes in characteristic quantities such as curvature along the contour model for each X-ray image. Furthermore, by optimizing the positional relationship between the graphs, the processing function 34c can align the X-ray images to suppress movement of characteristic portions.

[0083] In addition, Figure 5 While the example in FIG. 3 illustrates a case where a single characteristic portion appears in each image, the embodiment is not limited thereto and can be applied similarly to a case where multiple characteristic portions appear in each image. Furthermore, processing function 34c can generate contour models C1 and Ct based on the number of characteristic portions. For example, processing function 34c can generate vertices at regular intervals from the front end of device D1 and terminate vertex generation when it determines that a predetermined number of characteristic portions are included, thereby generating contour models C1 and Ct.

[0084] Specifically, the processing function 34c controls the number of feature segments used. When performing motion suppression for feature segments, considering more feature segments improves accuracy, but also increases the computational complexity. The processing function 34c can accept user adjustments to the number of feature segments used, or it can automatically adjust the number of feature segments based on the processing capabilities of the medical image processing device 30, the frame rate of the collected X-ray images, and other factors.

[0085] Next, use Figure 6 An example of a processing procedure of the medical image processing apparatus 30 will be described. Figure 6 This is a flowchart illustrating a series of processing steps performed by the medical image processing apparatus 30 according to the first embodiment. Steps S101, S102, and S104 correspond to the acquisition function 34b. Steps S103, S105, S106, and S107 correspond to the processing function 34c. Steps S108 and S109 correspond to the output function 34d.

[0086] First, the processing circuit 34 determines whether to start the process of suppressing the movement of the device D1 (step S101). For example, even after the device D1 is inserted into the body of the subject P1, depending on the position of the device D1, sometimes the process of suppressing the movement of the device D1 is not necessary. For example, in cardiac PCI, the device D1 is inserted from the femoral artery of the subject P1 and moves in the blood vessel toward the heart. Here, the process of suppressing the movement of the device D1 is not necessary when the device D1 is located in the lower limb of the subject P1, but is necessary when the device D1 is close to the heart and is affected by the heartbeat. Therefore, the processing circuit 34 can determine that the process of suppressing the movement of the device D1 has started when the device D1 reaches the vicinity of the heart.

[0087] The determination in step S101 may be made by receiving an input operation from a user such as a physician, or may be made automatically by analyzing the position of the device D1 by the processing circuit 34. If the processing is not started (no in step S101), the processing circuit 34 enters a standby state. If the processing is started (yes in step S101), the process proceeds to step S102.

[0088] Next, the processing circuit 34 acquires X-ray image I131 (step S102) and generates contour model C1 (step S103). Furthermore, the processing circuit 34 acquires X-ray image I13t (step S104) and generates contour model Ct (step S105). X-ray image I13t is an X-ray image of the frame following X-ray image I131. X-ray image I13t may be an X-ray image of the frame immediately following X-ray image I131 or an X-ray image several frames later.

[0089] Next, the processing circuit 34 calculates the rotation-translation matrix W (step S106). For example, the processing circuit 34 performs endpoint-free DP matching between the contour model C1 and the contour model Ct to find corresponding points, thereby calculating the rotation-translation matrix W. Furthermore, the processing circuit 34 applies the calculated rotation-translation matrix W to the X-ray image I13t (step S107). This aligns the X-ray image I13t with respect to the X-ray image I131, and the motion of the characteristic portions of the device D1 in both the X-ray image I131 and the X-ray image I13t is suppressed.

[0090] Furthermore, the processing circuit 34 displays the X-ray image I13t to which the rotation and translation matrix W is applied on the display 32 (step S108 ). That is, in step S108 , the processing circuit 34 displays the X-ray image in which the motion of the characteristic portion is suppressed on the display 32 .

[0091] Next, the processing circuit 34 determines whether to continue the process of suppressing the motion of device D1 (step S109). If it continues (step S109 returns yes), the process proceeds to step S104 again. For example, if the X-ray image I13t of frame t is acquired and the process of suppressing the motion of device D1 is performed, and the process proceeds from step S109 to step S104 again, the processing circuit 34 can acquire the X-ray image of frame (t+1) and again perform the process of suppressing the motion of device D1. On the other hand, if the process of suppressing the motion of device D1 is not to be continued (step S109 returns no), the processing circuit 34 terminates the process.

[0092] In addition, Figure 6 In the processing flow shown, the X-ray image I131 obtained in step S102 becomes the reference frame. Figure 6 In the illustrated processing flow, the motion of device D1 is suppressed using the characteristic features of its shape at the time X-ray image I131 is acquired. However, it is also assumed that X-ray image I131 is not optimal as a reference frame. For example, it is assumed that at the time X-ray image I131 is acquired, most of device D1 is located within the straight portion of a blood vessel, and no characteristic features are present in device D1. Furthermore, it is assumed that subject P1 is moving at the time X-ray image I131 is acquired, causing noise in X-ray image I131.

[0093] Therefore, the processing circuit 34 can also change the reference frame as appropriate. For example, the processing circuit 34 causes the display 32 to display a plurality of frames of X-ray images that have just been collected, and accepts a selection operation from the user to select a certain X-ray image as the reference frame, thereby resetting the reference frame. In addition, for example, the processing circuit 34 accepts an input operation from the user to change the reference frame, and re-sets the X-ray image that has just been collected as the reference frame. In addition, the processing circuit 34 can use the X-ray image of the reset reference frame as the X-ray image I131, and perform Figure 6 Processing after step S103 in .

[0094] In addition, when executing Figure 6 During the processing, for example, the user may operate the C-arm 105, thereby changing the working angle. In other words, the imaging angle may change between the X-ray image I131 and the X-ray image I13t. In such cases, the shape of the device D1 may change in the image, making it impossible to perform the process of suppressing the movement of the characteristic portion.

[0095] Therefore, the processing circuit 34 may automatically terminate the process of suppressing motion of the characteristic portion when the camera angle changes. Alternatively, the processing circuit 34 may automatically restart the process of suppressing motion of the characteristic portion when the camera angle returns to its original state. Alternatively, the processing circuit 34 may reset the reference frame when the camera angle changes.

[0096] In addition, when executing Figure 6 During the processing, the device D1 not only advances within the blood vessel but may also retreat (withdraw). Furthermore, if the device D1 retreats after, for example, passing a bend in the blood vessel, a characteristic portion may not appear in the X-ray image I13t. Therefore, the processing circuit 34 may automatically terminate the process of suppressing the movement of the characteristic portion if the device D1 retreats and the characteristic portion no longer appears in the X-ray image I13t.

[0097] Alternatively, even if the device D1 retreats and the characteristic portion no longer appears in the X-ray image I13t, the processing circuit 34 can continue to suppress motion of the characteristic portion based on past processing results. For example, the influence of motion caused by heartbeat or respiration is roughly uniform across the entire imaging range and occurs periodically. Therefore, even after the device D1 retreats and the characteristic portion no longer appears in the X-ray image I13t, motion of the portion of the X-ray image I13t where the characteristic portion resides can be substantially suppressed by applying a past rotation-translation matrix W that aligns with the phase of the heartbeat or respiration. For example, each time the processing circuit 34 calculates the rotation-translation matrix W, it associates it with the phase information of the subject P1's heartbeat or respiration and stores it in the memory 33. Furthermore, when the device D1 retreats and the characteristic portion no longer appears in the X-ray image I13t, the processing circuit 34 reads the rotation-translation matrix W of the same phase from the memory 33 and applies it to the X-ray image I13t.

[0098] Furthermore, it is assumed that corresponding points cannot be found between the contour model C1 and the contour model Ct due to various reasons. For example, there may be a situation where the shape of the contour models changes significantly due to the device D1 moving forward or backward significantly, making it difficult to find corresponding points. For example, when the contour model C1 and the contour model Ct are generated for a portion of the device D1 that is a specified length away from the front end, if the device D1 moves beyond the specified length, the contour model C1 and the contour model Ct represent other portions of the device D1, making it impossible to find corresponding points between the contour models. In addition, when the X-ray image I13t is collected, there is body movement of the subject P1, which generates noise in the X-ray image I13t, making it difficult to find corresponding points.

[0099] Therefore, if the processing circuit 34 cannot find corresponding points between the contour models C1 and Ct, it can automatically terminate the feature motion suppression process. For example, the processing circuit 34 can continuously calculate the sum of the distances between corresponding points as a positional error, and automatically terminate the feature motion suppression process when the positional error exceeds a threshold. Alternatively, the processing circuit 34 can calculate the similarity between the contour models and automatically terminate the feature motion suppression process when the similarity falls below a threshold.

[0100] Alternatively, if no corresponding points can be found between the contour models C1 and Ct, the processing circuit 34 may continue to suppress the motion of the feature portion based on past processing results. For example, if no corresponding points can be found between the X-ray image I131 and the X-ray image I13t, the processing circuit 34 reads a previously calculated rotation and translation matrix W stored in the memory 33 that is consistent with the phase of the heartbeat or respiration, and applies it to the X-ray image I13t.

[0101] Furthermore, for example, the processing circuit 34 may use the rotation and translation matrix W calculated just before when no corresponding points can be found between the contour models C1 and Ct. The following describes a case where an X-ray image I13(t-1) was collected in the frame immediately preceding the X-ray image I13t. In most cases, the time between the collection of X-ray image I13(t-1) and the collection of X-ray image I13t is short, and the motion between the images is small. Therefore, by applying the rotation and translation matrix W calculated to suppress the motion of the characteristic portion in X-ray image I13(t-1) unchanged to X-ray image I13t, the motion of the characteristic portion in X-ray image I13t can also be substantially suppressed. Thus, even if no corresponding points can be found between the contour models C1 and Ct due to only one frame of noise, the process of suppressing the motion of the characteristic portion can continue.

[0102] Alternatively, the processing circuit 34 may also periodically update the reference frame. Figure 6 When the process from steps S104 to S109 in the image processing section is repeated a predetermined number of times, the most recently acquired X-ray image is reset as the reference frame. Furthermore, the processing circuit 34 uses the X-ray image of the reset reference frame as X-ray image I131 and re-executes the process from step S103 onward. This allows the processing circuit 34 to continue suppressing the motion of the feature, even in situations such as when the shape of the contour model significantly changes due to movement of the device D1, or when the shape of the feature on the image changes due to a change in the operating angle.

[0103] As described above, according to the first embodiment, the acquisition function 34b acquires a plurality of X-ray images including the device D1 inserted into the body of the subject P1. Furthermore, the processing function 34c suppresses the movement of a characteristic portion between X-ray images, the characteristic portion being located at a position separated from the front end of the device D1 and having a characteristic shape. Furthermore, the output function 34d causes the display 32 to display the plurality of X-ray images in which the movement of the characteristic portion has been suppressed. Therefore, the medical image processing apparatus 30 of the first embodiment can improve the visibility of the device D1 inserted into the body of the subject P1. That is, the medical image processing apparatus 30 of the first embodiment can improve the visibility of X-ray images. Furthermore, the medical image processing apparatus 30 can reduce the burden on the user's eyes and mental stress, making it easier to perform intravascular treatment.

[0104] In particular, the medical image processing apparatus 30 of the first embodiment allows the user to easily determine whether the device D1 is moving in the intended direction when the user operates the device D1. Specifically, when processing is performed to suppress the motion of a characteristic portion, the tip of the device D1 moves on the image in response to the user's operation of the device D1. This allows the user to understand the progress of the device D1 and more easily perform intravascular treatment.

[0105] Furthermore, when a marker is attached to the device D1, the marker can be detected from multiple X-ray images and aligned, allowing the device D1 to be fixed and displayed. Here, the marker is, for example, a metal piece having a predetermined shape and size. However, from the perspective of invasiveness to the subject P1 and operability of the device D1, it is preferable not to attach a marker to the device D1. Furthermore, when thin blood vessels are the subject, there are cases where it is not possible to attach a marker to the device D1. In contrast, the medical image processing apparatus 30 of the first embodiment can suppress the movement of characteristic portions of the shape of the device D1 and display the device D1, regardless of whether the device D1 is attached with a marker or not.

[0106] Furthermore, it is assumed that, for example, when operation of device D1 is complete and only the vicinity of the tip of device D1 is to be observed, it is preferable to suppress the motion of the tip of device D1. Therefore, the medical image processing apparatus 30 may switch between suppressing the motion of the feature portion and suppressing the motion of the tip in response to user input.

[0107] (Second embodiment)

[0108] Furthermore, although the first embodiment has been described above, the present invention can be implemented in various different forms other than the above-described embodiment.

[0109] For example, in the above embodiment, Figure 5 As shown in FIG, the description assumes that the motion of the characteristic portion is suppressed by finding corresponding points using endpoint-free DP matching. However, the embodiment is not limited to this.

[0110] For example, the processing function 34c can also extract feature parts from a plurality of X-ray images and perform matching processing on the feature parts between the X-ray images, thereby suppressing the movement of the feature parts. Figure 7 The case of performing matching processing of characteristic parts will be described. Figure 7 This is a diagram showing an example of matching processing according to the second embodiment.

[0111] Specifically, processing function 34c first extracts the outline of device D1 from X-ray image I131 of frame 1. Next, processing function 34c generates a contour model C1 by creating multiple vertices on the extracted contour. Furthermore, processing function 34c cuts out portions of contour model C1 corresponding to characteristic features as pattern A1. For example, processing function 34c compares the curvature at each vertex of contour model C1 with a threshold value and cuts out portions corresponding to vertices whose curvature exceeds the threshold value as pattern A1.

[0112] Next, processing function 34c performs pattern matching on X-ray image I13t of frame t using pattern A1. This allows processing function 34c to determine the position and orientation of the characteristic portion in X-ray image I13t. Furthermore, processing function 34c calculates a rotation-translation matrix W based on the position and orientation of the characteristic portion in X-ray image I131 and the position and orientation of the characteristic portion in X-ray image I13t. Furthermore, processing function 34c applies rotation-translation matrix W to X-ray image I13t, thereby causing X-ray image I13t to translate and rotate, thereby suppressing the motion of the characteristic portion.

[0113] Furthermore, in the above-described embodiment, the processing for suppressing motion of characteristic portions of the X-ray image I13t is performed, and the processed X-ray image I13t is displayed on the display 32. However, the embodiment is not limited to this. For example, the processing circuit 34 may also perform processing for suppressing motion of characteristic portions of the X-ray image I13t, generate a composite image using the processed X-ray image I13t, and display the generated composite image on the display 32.

[0114] Below, use Figure 8 The case of displaying a synthesized image will be described. Figure 8 : is a diagram showing a display example of the second embodiment. Figure 8 In the following, a case where a composite image of the X-ray image I13t and the blood vessel image is displayed will be described.

[0115] For example, the acquisition function 34b pre-acquires a vascular image collected from the subject P1 and stores it in the memory 33. For example, the vascular image can be acquired by imaging the subject P1 with a contrast agent injected into the blood vessels using the X-ray diagnostic apparatus 10. The type of contrast agent is not particularly limited and can be a positive contrast agent primarily composed of iodine, barium sulfate, or a gaseous contrast agent such as carbon dioxide. Furthermore, the injection of the contrast agent can be performed manually by a user, such as a physician, or automatically by an injector installed in the X-ray diagnostic apparatus 10.

[0116] For example, the collection function 110b repeatedly irradiates X-rays before injecting a contrast agent into the blood vessels of the subject P1, thereby collecting a plurality of mask images. Alternatively, the collection function 110b repeatedly irradiates X-rays after injecting a contrast agent into the blood vessels of the subject P1, thereby collecting a plurality of contrast images. Furthermore, the collection function 110b generates a plurality of mask images and a plurality of contrast images by performing a difference process between the plurality of mask images and the plurality of contrast images. Figure 8 Alternatively, the collection function 110b may omit the collection of the mask image and perform threshold processing on the contrast image to generate the blood vessel images I141 to I14n.

[0117] For example, when collecting vascular images of the coronary arteries of subject P1, the acquisition function 110b performs electrocardiographic synchronization during the generation of vascular images I141 to I14n. For example, the acquisition function 110b collects mask images while measuring subject P1's heartbeat, attaching phase information to each mask image. Furthermore, the acquisition function 110b collects contrast images while measuring subject P1's heartbeat, attaching phase information to each contrast image. Furthermore, the acquisition function 110b generates vascular images I141 to I14n by performing a difference process between the mask image and the contrast image at the corresponding phase. In this case, the acquisition function 110b can attach phase information to each of vascular images I141 to I14n.

[0118] The vascular images I141-I14n collected by the collection function 110b are transmitted to the medical image processing apparatus 30 via the network NW. For example, the output function 110c transmits the vascular images I141-I14n to an image storage device such as a PACS server. In this case, the acquisition function 34b can obtain the vascular images I141-I14n from the image storage device. Alternatively, the acquisition function 34b can directly obtain the vascular images I141-I14n from the X-ray diagnostic apparatus 10 without going through the image storage device. Furthermore, the acquisition function 34b stores the obtained vascular images I141-I14n in the memory 33.

[0119] Next, the medical image processing device 30 obtains a plurality of X-ray images including the device inserted into the body of the subject P1 within the imaging range, and performs processing to suppress the motion of a characteristic portion of the device D1 that is located at a position separated from the front end thereof and has a characteristic shape. For example, the processing function 34c performs Figure 5 The method such as endpoint free DP matching shown in the figure performs image matching processing between the X-ray image I131 and the X-ray image I13t, thereby calculating the rotation and translation matrix W. In addition, for example, the processing function 34c is Figure 7 By using a method such as pattern matching shown in FIG. 1 , a feature portion matching process is performed between the X-ray image I131 and the X-ray image I13t, thereby calculating a rotation-translation matrix W. The processing function 34c then applies the calculated rotation-translation matrix W to the X-ray image I13t, thereby suppressing the motion of the feature portion in the X-ray image I13t.

[0120] Furthermore, processing function 34c synthesizes vascular image I14t with X-ray image I13t. For example, if X-ray image I13t is acquired at phase Et, processing function 34c identifies vascular image I14t at phase Et from among vascular images I141 to I14n and synthesizes it with X-ray image I13t. Processing function 34c can also perform correction processing on vascular image I14t to improve synthesis accuracy.

[0121] For example, processing function 34c performs correction processing T1 on vascular image I14t based on the results of matching X-ray image I131 with X-ray image I13t. Specifically, X-ray image I13t and vascular image I14t are both acquired at phase Et, but the position and orientation of X-ray image I13t are changed by applying rotation and translation matrix W to the image. Therefore, processing function 34c also applies rotation and translation matrix W to vascular image I14t, changing its position and orientation in the same manner as X-ray image I13t. This improves the accuracy of the synthesis of X-ray image I13t and vascular image I14t.

[0122] Furthermore, for example, processing function 34c performs correction processing T2 on vascular image I14t based on the characteristic portion extracted from X-ray image I13t. Specifically, since the characteristic portion is part of device D1 inserted into the blood vessel, in order to properly synthesize X-ray image I13t and vascular image I14t, at least the position and shape of the characteristic portion in X-ray image I13t must match the vascular region shown in vascular image I14t. Therefore, processing function 34c corrects vascular image I14t so that the position and shape of the vascular region shown in vascular image I14t match those of the characteristic portion extracted from X-ray image I13t. Processing function 34c may perform both correction processing T1 and correction processing T2, or only one of them.

[0123] The processing function 34c then generates a composite image I15t of the corrected vascular image I14t and the X-ray image I13t, and the output function 34d displays the composite image I15t on the display 32. As a result, the vascular image I14t and the X-ray image I13t are composited with high precision, and the motion of the portion of the vascular image I141 corresponding to the characteristic portion is suppressed, allowing the user to more easily understand the positional relationship between the blood vessels and the device D1.

[0124] In addition, in the above embodiment, as an example of a characteristic part, a portion with a large curvature in the device is described. However, the embodiment is not limited to this. For example, the processing function 34c is as follows Figure 9 As shown, the branch B1 in the device D2 can also be used as a characteristic part, and the movement of the characteristic part can be suppressed. Figure 9 This is a diagram showing an example of a device D2 according to the second embodiment.

[0125] For example, the processing function 34c first extracts the outline of the device D2. Then, the processing function 34c identifies the branch B1 in the outline of the device D2, and for the portion closer to the user's hand than the branch B1 (at Figure 9 The contour model is created by using the solid line in the image (shown in the figure). The processing function 34c then suppresses the movement of the branch portion B1 by finding corresponding points on the contour model between the multiple X-ray images. Furthermore, when finding the corresponding points, the processing function 34c may also set constraints so that the branch portions B1 in each image correspond to each other.

[0126] In the above-mentioned embodiment, the description of the process of suppressing the motion of the characteristic portion is as follows. Figure 5The description above illustrates how the characteristic portion is aligned between X-ray images as shown. Specifically, in the above embodiment, the process of fixing the characteristic portion is described as a process for suppressing the motion of the characteristic portion. However, the embodiment is not limited to this. For example, as a process for suppressing the motion of the characteristic portion, the processing function 34c may also perform a process for reducing the difference between the positions and orientations of the characteristic portion between images. In other words, the process of suppressing the motion of the characteristic portion may be a process of fixing the characteristic portion or a process of reducing the degree of motion of the characteristic portion.

[0127] Furthermore, in the above-described embodiment, multiple X-ray images with suppressed motion of characteristic portions are displayed on the display 32. However, the embodiment is not limited to this. For example, the output function 34d may transmit multiple X-ray images with suppressed motion of characteristic portions to another device, such as the X-ray diagnostic apparatus 10. In this case, the device receiving the images displays the images, thereby providing the user with multiple X-ray images with suppressed motion of characteristic portions.

[0128] In the above embodiment, the medical image processing device 30 is described as performing the process of suppressing the motion of the feature portion. However, the embodiment is not limited to this. For example, the processing circuit 110 of the X-ray diagnostic device 10 may also perform a function equivalent to the above-mentioned processing function 34c. Figure 10 Provide explanation. Figure 10 1 is a block diagram showing an example of the configuration of the X-ray diagnostic apparatus 10 according to the second embodiment. Figure 10 As shown, the processing circuit 110 executes a control function 110a, a collection function 110b, an output function 110c, and a processing function 110d. The processing function 110d is an example of a processing unit.

[0129] For example, the collection function 110b irradiates a subject P1 with a device D1 inserted into it with X-rays, detects the X-rays that have passed through subject P1, and collects multiple X-ray images. Furthermore, the processing function 110d suppresses the motion of a characteristic feature located at a position separated from the tip of the device D1 and having a distinctive shape between the multiple collected X-ray images. For example, the processing function 110d uses X-ray image I131 as a reference frame and performs matching processing with X-ray image I13t collected after X-ray image I131, thereby calculating a rotation and translation matrix W. Furthermore, the processing function 110d applies the calculated rotation and translation matrix W to X-ray image I13t, thereby suppressing the motion of the characteristic feature between X-ray image I131 and X-ray image I13t. Furthermore, the output function 110c displays the multiple X-ray images, in which the motion of the characteristic features has been suppressed by the processing function 110d, on the display 108.

[0130] In the first and second embodiments described above, for example, Figure 4 As shown in the above description, the case where the motion of a characteristic portion located at a position separated from the distal end of the device and having a characteristic shape is suppressed is described. However, it is also possible to assume that the portion located at a position separated from the distal end of the device does not have a characteristic shape. For example, it is possible to assume that the blood vessel into which the device is inserted has a nearly straight shape, and the device is also straight, so that the portion with a large curvature cannot be identified.

[0131] Therefore, in the third embodiment, instead of suppressing the motion of the device's characteristic portion, processing is performed to suppress the motion of the characteristic portion contained in the vascular image in the corresponding time phase, thereby improving the visibility of the X-ray image. For example, if conditions related to the positional relationship between the tip and the characteristic portion are satisfied, the processing circuit 34 identifies the vascular image in the corresponding time phase from among the vascular images in the multiple time phases for each of the multiple X-ray images. Furthermore, the processing circuit 34 determines the processing to suppress the motion of the characteristic portion contained in the vascular image in the corresponding time phase. Furthermore, instead of suppressing the motion of the device's characteristic portion, the processing circuit 34 performs processing to suppress the motion of the characteristic portion contained in the vascular image in the corresponding time phase on the X-ray image.

[0132] In the third embodiment, Figure 1The medical image processing system 1 shown in FIG. 1 is used as an example for description. For example, before starting intravascular treatment on subject P1, the X-ray diagnostic apparatus 10 collects vascular images from subject P1 and transmits the collected vascular images to the medical image processing apparatus 30. Alternatively, for example, while the intravascular treatment is being performed on subject P1, the X-ray diagnostic apparatus 10 collects two-dimensional X-ray images from subject P1 over time and transmits the collected X-ray images sequentially to the medical image processing apparatus 30.

[0133] The medical image processing device 30 acquires the vascular image and X-ray images collected by the X-ray diagnostic apparatus 10 and performs various processing operations using the vascular image and X-ray image. For example, the medical image processing device 30 performs a first processing operation on the vascular image and, based on the results of the first processing operation, performs a second processing operation on the X-ray image. Furthermore, the medical image processing device 30 displays the X-ray image after the second processing operation.

[0134] The processing circuit 34, for example, reads and executes a program corresponding to the acquisition function 34b from the memory 33 to acquire a vascular image and an X-ray image of the subject P1. Alternatively, for example, the processing circuit 34 reads and executes a program corresponding to the processing function 34c from the memory 33 to perform a first process on the vascular image and, based on the results of the first process, performs a second process on the X-ray image. Alternatively, for example, the processing circuit 34 reads and executes a program corresponding to the output function 34d from the memory 33 to output an X-ray image processed by the processing function 34c.

[0135] For example, the collection function 110b collects X-ray images over time while subject P1 is undergoing intravascular treatment. For example, during cardiac PCI, the collection function 110b collects X-ray images of the coronary arteries within the imaging range over time. The imaging range can be set by a user, such as a physician performing the intravascular treatment, or automatically by the collection function 110b based on patient information.

[0136] Specifically, the collection function 110b controls the operation of the X-ray collimator 103, adjusting the aperture of the collimator's aperture blades to control the range of X-ray exposure to the subject P1. Furthermore, the collection function 110b controls the operation of the X-ray collimator 103 to adjust the position of the filter, thereby controlling the X-ray dose distribution. Furthermore, the collection function 110b controls the operation of the C-arm 105 to rotate or move it. Furthermore, for example, the collection function 110b controls the operation of the diagnostic bed to move or tilt the top 104. In other words, the collection function 110b controls the range and angle of the collected X-ray images by controlling the operation of the mechanical system, including the X-ray collimator 103, the C-arm 105, and the top 104.

[0137] The collection function 110b also controls the X-ray high-voltage device 101, adjusting the voltage supplied to the X-ray tube 102, thereby controlling the X-ray dosage and on / off switching of the X-rays irradiated to the subject P1. Furthermore, the collection function 110b generates X-ray images based on the detection signals received from the X-ray detector 106. The collection function 110b can also perform various image processing on the generated X-ray images. For example, the collection function 110b can perform noise reduction and scattered radiation correction using image processing filters on the generated X-ray images. Furthermore, the output function 110c sequentially transmits the collected X-ray images to the medical image processing device 30.

[0138] Furthermore, the collection function 110b collects vascular images from the subject P1 before the start of intravascular treatment. Here, the collection function 110b collects vascular images based on the imaging range of the X-ray images collected during the treatment. For example, in the case of cardiac PCI, X-ray images that include the coronary arteries within the imaging range are scheduled to be collected. Therefore, the collection function 110b collects vascular images that include the coronary arteries within the imaging range.

[0139] Specifically, the collection function 110b captures a plurality of X-ray images of the subject P1 while a contrast agent is injected into the blood vessels. X-ray images collected while a contrast agent is injected into the blood vessels are also referred to as contrast images. The type of contrast agent is not particularly limited and can include positive contrast agents primarily composed of iodine, barium sulfate, or other agents, as well as gaseous contrast agents such as carbon dioxide. Furthermore, injection of the contrast agent can be performed manually by a user, such as a physician, or automatically by an injector installed in the X-ray diagnostic apparatus 10.

[0140] For example, after injecting a contrast agent into the blood vessels of subject P1, the collection function 110b repeatedly irradiates X-rays to collect multiple contrast images. Alternatively, the collection function 110b repeatedly irradiates X-rays before injecting a contrast agent into the blood vessels of subject P1 to collect multiple mask images. Furthermore, the collection function 110b generates multiple vascular images by performing differential processing between the multiple mask images and the multiple contrast images. Alternatively, the collection function 110b may omit the collection of mask images and perform threshold processing on the pixel values of the contrast image, or perform semantic segmentation on the contrast image, thereby extracting pixels representing contrast-enhanced blood vessels from the contrast image to generate vascular images. Furthermore, the output function 110c transmits the collected vascular images to the medical image processing device 30.

[0141] Below, use Figure 11A and Figure 11BAn example of display of X-ray images by the medical image processing apparatus 30 will be described. Figure 11A and Figure 11B : is a diagram showing a display example of the third embodiment. Figure 11A and Figure 11B In the following, the case of displaying an X-ray image collected for the coronary artery of the subject P1 is described. Figure 11A and Figure 11B In the following, a case where an X-ray image and a blood vessel image are synthesized and displayed is described.

[0142] First, before starting intravascular treatment, blood vessel images are collected. For example, the collection function 110b captures an image of the subject P1 in which a contrast agent has been injected into the blood vessel, and collects the image. Figure 11A The X-ray images I211 to I21n are shown. Figure 11A The X-ray images I211 to I21n shown are contrast images. In addition, the collection function 110b collects blood vessels by extracting blood vessels from the X-ray images I211 to I21n. Figure 11A The vascular images I221 to I22n are shown. For example, the acquisition function 110b performs threshold processing on the pixel values of X-ray images I211 to I21n to extract pixels corresponding to blood vessels and generate vascular images I221 to I22n. Alternatively, for example, the acquisition function 110b may acquire multiple mask images by imaging subject P1 before a contrast agent is injected into the blood vessels, and perform subtraction processing on these images from the X-ray images I211 to I21n to generate vascular images I221 to I22n.

[0143] Next, the acquisition function 34b acquires the vascular images I221-I22n. For example, the output function 110c transmits the vascular images I221-I22n to an image storage device via the network NW. In this case, the acquisition function 34b can acquire the vascular images I221-I22n from the image storage device via the network NW. An example of such an image storage device is a PACS (Picture Archiving Communication System) server. Alternatively, the acquisition function 34b can acquire the vascular images I221-I22n directly from the X-ray diagnostic apparatus 10 without intervening through other devices.

[0144] After the intravascular treatment starts, the collection function 110b captures an image of the subject P1 with the device inserted into the blood vessel, and collects Figure 11AThe X-ray image I231 shown is shown. Furthermore, the acquisition function 34b acquires the X-ray image I231. For example, the output function 110c transmits the X-ray image I231 to the image storage device via the network NW. In this case, the acquisition function 34b can acquire the X-ray image I231 from the image storage device via the network NW. Alternatively, the acquisition function 34b can acquire the X-ray image I231 directly from the X-ray diagnostic apparatus 10 without intervening through other devices.

[0145] In addition, the device inserted into the body of the subject P1 is generally linear. Examples of such linear devices include catheters and guidewires used in intravascular treatment. For example, in cardiac PCI, a user such as a physician operates the guidewire inserted into the body of the subject P1 and moves it until it reaches the lesion. Here, the lesion is, for example, a stenotic portion of a blood vessel such as a chronic total occlusion (CTO). In this case, the collection function 110b collects the X-ray image I231 in such a way that the front end of the guidewire is included in the imaging range. In addition, the collection function 110b can also appropriately adjust the imaging range in such a way as to follow the front end position of the guidewire when the front end position of the guidewire moves.

[0146] Next, the output function 34d combines the vascular image with the X-ray image I231. Here, the vascular images I221 to I22n and the X-ray image I231 were acquired for the coronary arteries of subject P1 and exhibit motion due to heartbeats. Therefore, the output function 34d selects an image from the vascular images I221 to I22n whose heartbeat phase corresponds to the X-ray image I231 and combines it with the X-ray image I231.

[0147] For example, the output function 34d can select a vascular image corresponding to the phase of X-ray image I231 based on phase information. Phase information here refers to information indicating at which point in the cardiac cycle the image was acquired. For example, the acquisition function 110b measures the heartbeat of subject P1 and acquires X-ray images I211 to I21n, attaching phase information to each of these images. This phase information is also inherited by vascular images I221 to I22n generated based on X-ray images I211 to I21n. Furthermore, the acquisition function 110b measures the heartbeat of subject P1 and acquires X-ray image I231, attaching phase information to X-ray image I231. The output function 34d then compares the phase information attached to each of vascular images I221 to I22n with the phase information attached to X-ray image I231 and selects the vascular image corresponding to the phase of X-ray image I231 from among vascular images I221 to I22n. Furthermore, the output function 34 d combines the selected blood vessel image with the X-ray image I 231 to generate a composite image I 241 , and displays the composite image on the display 32 .

[0148] In the composite image I241, for example Figure 11B As shown, the blood vessel B2 in the blood vessel image is displayed superimposed on the device D3 in the X-ray image 1231. This allows the user performing the intravascular treatment to operate the device D3 while understanding the positional relationship between the device D3 and the blood vessel B2.

[0149] Similarly to X-ray image I231, collection function 110b collects multiple X-ray images over time. Furthermore, output function 34d selects the corresponding phase of each of the multiple X-ray images from among vascular images I221 to I22n to generate a composite image. Each time a composite image is generated, output function 34d causes display 32 to sequentially display the newly generated composite image. In other words, output function 34d displays the composite image in real time. This allows the user performing intravascular treatment to understand the current position of device D3 relative to blood vessel B2 and to advance device D3 to a lesion such as a CTO.

[0150] Here, in the multiple composite images displayed sequentially, the device D3 and the blood vessel B2 move dynamically in accordance with the heartbeat. Furthermore, it may be burdensome for the user to follow the device D3 and the blood vessel B2 whose positions change with each frame.

[0151] Furthermore, there are known technologies for displaying X-ray images collected for a moving part while suppressing that motion. For example, when device D3 is labeled, the labeled portion of device D3 can be fixed and displayed by detecting the labeled portion from multiple X-ray images and performing alignment. The labeled portion can be, for example, a metal piece of a predetermined shape and size.

[0152] However, while this fixed display improves visibility near the device D3 marker, it doesn't necessarily improve visibility of blood vessel B2. For example, blood vessel B2 not only shifts in position due to heartbeats but also deforms. Therefore, even if the device D3 marker is fixed, blood vessel B2 often remains unfixed.

[0153] Furthermore, the user may focus on device D3 or blood vessel B2. For example, the user may focus on the vascular region where device D3 is scheduled to move, observe the composite image, and then operate device D3. However, if the marker of device D3 is detected and displayed fixedly, the fixed position cannot be changed based on the marker. Furthermore, if the vascular region where device D3 is scheduled to move moves, for example, visibility may be insufficient when operating device D3.

[0154] Therefore, the processing circuit 34 in the medical image processing apparatus 30 can suppress the motion of any position on the image and improve the visual recognition by executing the first processing and the second processing described in detail below. Figure 12A 、 Figure 12B and Figure 12C The processing performed by the processing circuit 34 will be described. Figure 12A 、 Figure 12B and Figure 12C These are diagrams for explaining the first process and the second process of the third embodiment.

[0155] First, the processing function 34c selects a blood vessel region to be processed for motion suppression in the blood vessel image. For example, the processing function 34c selects the blood vessel region based on an input operation from the user.

[0156] For example, the output function 34d causes one or more of the vascular images I221 to I22n to be displayed on the display 32. For example, the output function 34d causes the vascular image I221 to be displayed on the display 32. In addition, the user configures a rectangular ROI on the vascular image I221 based on the predetermined vascular region to be reached by the device D3. For example, the user configures the ROI on the vascular image I221 based on the target vascular region to be reached by the device D3. For example, the user configures the ROI in the vascular region that becomes the path to reach the target vascular region. Alternatively, the user may configure the ROI in the vascular region itself that reaches the target. Thus, the processing function 34c can select the vascular region within the ROI as the vascular region to suppress movement. In addition, in Figure 12A The ROI is a rectangular one, but the shape and size of the ROI can be changed arbitrarily.

[0157] Next, the processing function 34c determines a first process for suppressing the motion of the selected blood vessel region between the plurality of blood vessel images. Figure 12A In the following, a case where a rotational translation process is selected as the first process will be described. In this rotational translation process, the vascular image is moved and rotated so that the position and orientation of the vascular region are substantially consistent across multiple vascular images. For example, the processing function 34c first obtains the vascular pattern VP of the vascular region selected from the vascular image I221. Next, the processing function 34c searches for a pattern VP' similar to the vascular pattern VP in other vascular images, such as the vascular images I222 and I223.

[0158] For example, processing function 34c manages the vascular patterns contained in each vascular image, such as vascular image I222 and vascular image I223, in a tree structure. Blood vessels typically have branches, with the number of branches increasing toward the upstream or downstream direction of the blood flow. Therefore, processing function 34c can assign nodes to each branch and manage the shape of each branch in a tree structure. Furthermore, processing function 34c can quickly search for pattern VP' by sequentially comparing the shape of each branch with the vascular pattern VP, proceeding from the root node toward the leaf nodes.

[0159] Next, the processing function 34c calculates a rotation-translation matrix W based on the position and orientation of the vascular pattern VP in the vascular image I221 and the position and orientation of the pattern VP' in other vascular images. For example, the processing function 34c calculates a rotation-translation matrix W1 based on the vascular pattern VP in the vascular image I221 and the pattern VP' in the vascular image I222. Furthermore, the processing function 34c calculates a rotation-translation matrix W2 based on the vascular pattern VP' in the vascular image I222 and the pattern VP' in the vascular image I223. In other words, by calculating the rotation-translation matrix W1 and the rotation-translation matrix W2, the processing function 34c determines the rotation-translation process as the first process.

[0160] Then, the processing function 34c applies the calculated rotation and translation matrix W to each blood vessel image to perform a first process of suppressing the motion of the selected blood vessel region. Figure 12A As shown, by applying the rotation and translation matrix W1 to the blood vessel image I222, the blood vessel image I222 is aligned with the blood vessel image I221. In addition, the processing function 34c applies the rotation and translation matrix W1 and the rotation and translation matrix W2 to the blood vessel image I223, thereby aligning the blood vessel image I223 with the blood vessel image I221. Figure 12A As shown in the lower part of FIG, the selected blood vessel region is aligned in the plurality of blood vessel images. Figure 12A In the case shown, the processing function 34c performs a rotation-translation process as the first process, which moves and rotates each blood vessel image so that the position and orientation of the blood vessel region in the blood vessel image I221 as the reference frame are substantially consistent with those of the blood vessel region in the blood vessel image of a frame different from the reference frame.

[0161] Next, processing function 34c is based on Figure 12A Specifically, the processing function 34c applies the second processing to the plurality of X-ray images. Figure 12A The first processing determined in the embodiment of the present invention is performed, thereby performing a second processing of suppressing motion between multiple X-ray images. For example, the processing function 34c performs the second processing, such as Figure 12B As shown, multiple X-ray images are aligned.

[0162] exist Figure 12BIn this description, it is assumed that the phases of X-ray image I231 and vascular image I221 are associated, the phases of X-ray image I232 and vascular image I222 are associated, and the phases of X-ray image I233 and vascular image I223 are associated. In this case, processing function 34c applies rotation and translation matrix W1 to X-ray image I232, thereby aligning X-ray image I232 with X-ray image I231. Furthermore, processing function 34c applies rotation and translation matrix W1 and rotation and translation matrix W2 to X-ray image I233, thereby aligning X-ray image I233 with X-ray image I231. This allows multiple X-ray images to be aligned, similar to the vascular images.

[0163] Specifically, as a second process for suppressing motion between X-ray images, processing function 34c applies the rotation and translation processing performed on the vascular image to the X-ray image of the corresponding phase, maintaining the same rotation and translation processing. This allows the regions corresponding to the vascular pattern VP in the X-ray image to be aligned with each other, even if no blood vessels appear on the X-ray image.

[0164] And, the output function 34d is as follows Figure 12C As shown, the output function 34d generates a composite image of the aligned vascular image and the aligned X-ray image, and sequentially displays the composite images on the display 32. For example, the output function 34d generates a composite image 1241 of the aligned vascular image 1221 and the aligned X-ray image 1231, and displays the composite image 1241 on the display 32. Furthermore, the output function 34d generates a composite image 1242 of the aligned vascular image 1222 and the aligned X-ray image 1232, and displays the composite image 1242 on the display 32. Furthermore, the output function 34d generates a composite image 1243 of the aligned vascular image 1223 and the aligned X-ray image 1233, and displays the composite image 1243 on the display 32. Specifically, the output function 34d outputs a composite image of the vascular image whose motion has been suppressed by the first processing and the X-ray image whose motion has been suppressed by the second processing.

[0165] like Figure 12A 、 Figure 12B and Figure 12C As shown, the processing function 34c can suppress the movement of an arbitrarily selected blood vessel region by executing the first processing and the second processing. Figure 13In the case shown, the processing function 34c selects the blood vessel area shown by the rectangle as a fixed position and suppresses the movement within the rectangular area. As a result, in the X-ray image, the movement of the device D3 within the rectangular area is suppressed. In addition, in the blood vessel image, the movement of the blood vessel B2 within the rectangular area is suppressed. In addition, in the state where the movement within the rectangular area is suppressed, the device D3 and the blood vessel B2 are displayed synthetically. Therefore, in the operation of the device D3 within the rectangular area, the user can obtain high visual recognition, for example, can easily perform the operation of moving the device D3 to reach the target. In addition, Figure 13 It is a diagram for explaining the fixing position of the third embodiment.

[0166] in addition, Figure 12A The vascular images I221, I222, and I223 shown may be a series of vascular images acquired in a single imaging session or a combination of vascular images acquired in other imaging sessions. Specifically, the processing function 34c may use a single cut vascular image to perform the first and second processing described above, or, if another cut vascular image exists whose phase and imaging range in the cardiac cycle roughly match those of the X-ray image, further utilize the other cut vascular image.

[0167] For example, consider a scenario where a vascular image is acquired at a frame rate of 10 f / s (frame / seat) and an X-ray image is acquired at a frame rate of 20 f / s, making it impossible to determine the phase of the vascular image corresponding to a portion of the X-ray image. Here, if a vascular image of the same portion is acquired at a frame rate of 10 f / s and the phase shifts by 0.05 seconds over the cardiac cycle, processing function 34c can combine these two clipped vascular images and determine a vascular image whose phase corresponds to each X-ray image. This allows processing function 34c to avoid frame rate degradation even when the frame rates of the vascular image and X-ray image differ, or when there is a phase shift over the cardiac cycle.

[0168] Next, use Figure 14 An example of a processing procedure of the medical image processing apparatus 30 will be described. Figure 14 This is a flowchart for explaining a series of processes performed by the medical image processing apparatus 30 according to the third embodiment. Steps S201, S202, S203, S204, S205, S206, and S208 correspond to the processing function 34c. Step S207 corresponds to the output function 34d.

[0169] First, the processing circuit 34 determines whether to start the process of suppressing the motion of the X-ray image (step S201). For example, in the case where the imaging range is controlled in a manner that follows the position of the front end of the device D3, sometimes the process of suppressing the motion of the X-ray image is not necessary depending on the position of the device D3. For example, with respect to cardiac PCI, the device D3 is inserted from the femoral artery of the subject P1 and moves in the blood vessel toward the heart. Here, the process of suppressing the motion of the X-ray image is not necessary when the device D3 is located in the lower limb of the subject P1, but is necessary when the device D3 is close to the heart and is affected by the heartbeat. Therefore, the processing circuit 34 can determine that the process of suppressing the motion of the X-ray image has started when the device D3 reaches the vicinity of the heart.

[0170] The determination in step S201 may be made by receiving an input operation from a user such as a physician, or may be made automatically by the processing circuit 34 by analyzing the position of the device D3. If the processing circuit 34 does not start processing (no in step S201), it enters a standby state. If the processing is started (yes in step S201), the process proceeds to step S202.

[0171] Next, the processing circuit 34 selects a blood vessel region (step S202). For example, the processing circuit 34 displays the blood vessel image I221 on the display 32 and accepts an input operation from the user, thereby selecting a blood vessel region. Next, the processing circuit 34 searches for a pattern VP' similar to the blood vessel pattern VP of the selected blood vessel region in each blood vessel image other than the blood vessel image I221 (step S203). If the pattern VP' is not found (step S204 negative), the processing circuit 34 terminates the process. On the other hand, if the pattern VP' is found (step S204 positive), the processing circuit 34 calculates a rotation and translation matrix W based on the position and orientation of the blood vessel pattern VP in the blood vessel image I221 and the position and orientation of the pattern VP' in the other blood vessel images (step S205).

[0172] Next, the processing circuit 34 applies the rotation-translation matrix W to each image (step S206). Specifically, the processing circuit 34 applies the rotation-translation matrix W to the vascular images to suppress the motion of the vascular region between the multiple vascular images. That is, the processing circuit 34 performs a first process to suppress the motion of the vascular region between the vascular images. Furthermore, the processing circuit 34 applies the rotation-translation matrix W to the X-ray images to suppress the motion of the region corresponding to the vascular region between the X-ray images. That is, based on the results of the first process, the processing circuit 34 performs a second process to suppress the motion between the X-ray images. The processing circuit 34 then displays a composite image of the vascular image whose motion was suppressed by the first process and the X-ray image whose motion was suppressed by the second process on the display 32 (step S207).

[0173] Next, the processing circuit 34 determines whether to continue the process of suppressing the motion of the selected vascular region (step S208). If so (step S208 affirmative), the process proceeds again to step S203. On the other hand, if not (step S208 negative), the processing circuit 34 terminates the process. For example, when treating a CTO, until device D3 reaches the CTO, the processing circuit 34 continues to suppress the motion of the vascular region that forms the path of the CTO to facilitate the movement of device D3. On the other hand, when device D3 reaches the CTO, the processing circuit 34 switches to suppressing the motion of device D3 to facilitate operations such as dilating the CTO using device D3. That is, when device D3 reaches the CTO, the processing circuit 34 determines in step S208 that the process of suppressing the motion of the selected vascular region is not to be continued. For example, when device D3 reaches the CTO, the processing circuit 34 begins a process of determining the position of a marker attached to device D3 in each of the multiple X-ray images and fixing the marker in the display.

[0174] In addition, in the implementation Figure 14 During the processing, the working angle may change, for example, due to user operation of the C-arm 105. In other words, the imaging angle may change between the vascular image and the X-ray image. In such cases, the results of the first processing of the vascular image may not be used to suppress motion in the X-ray image.

[0175] Therefore, the processing circuit 34 may be configured to automatically terminate the motion suppression process for the X-ray image when the imaging angle changes. Alternatively, the processing circuit 34 may automatically resume the motion suppression process for the X-ray image when the imaging angle returns to its original state. Alternatively, the processing circuit 34 may acquire a vascular image corresponding to the changed imaging angle when the imaging angle changes and continue the motion suppression process for the X-ray image.

[0176] As described above, according to the third embodiment, the acquisition function 34b acquires multiple vascular images and multiple X-ray images collected for a region with periodic motion. Furthermore, the processing function 34c selects a vascular region from the vascular images and determines a first process for suppressing motion of the vascular region between the multiple vascular images. Furthermore, the processing function 34c applies the first process to the multiple X-ray images, thereby performing a second process for suppressing motion between the multiple X-ray images. Furthermore, the output function 34d outputs the X-ray images in which motion has been suppressed by the second process. Therefore, the medical image processing apparatus 30 of the third embodiment can improve the visibility of X-ray images collected for a region with motion.

[0177] For example, even in X-ray images collected for areas with motion, it is possible to determine the marker attached to device D3 and display it fixedly. However, this fixed display offers limited options for fixed positions and cannot display blood vessels that device D3 does not reach. In contrast, the medical image processing apparatus 30 of the third embodiment offers increased flexibility regarding fixed positions. For example, the medical image processing apparatus 30 can also display blood vessels that device D3 does not reach.

[0178] Furthermore, X-ray images collected for areas experiencing motion do not always include device D3. For example, during the treatment planning phase, X-ray images may be collected without inserting device D3 into subject P1. Furthermore, even when device D3 is included in an X-ray image, it is not limited to being marked. In other words, there are cases where the X-ray image does not contain features that can be used for alignment. Even in such cases, the medical image processing device 30 can suppress motion in the X-ray image by using the vascular image.

[0179] (Fourth embodiment)

[0180] Furthermore, although the third embodiment has been described above, the present invention can be implemented in various different forms other than the above-described embodiment.

[0181] For example, in the third embodiment, instead of suppressing the motion of the characteristic portion of the device, the motion of the characteristic portion contained in the vascular image of the corresponding time phase is suppressed. However, the embodiment is not limited to this. For example, the motion of the characteristic portion contained in the vascular image of the corresponding time phase may be suppressed regardless of whether the motion of the characteristic portion of the device is suppressed. For example, the processing circuit 34 may suppress the motion of the characteristic portion contained in the vascular image of the corresponding time phase without determining whether the condition related to the positional relationship between the tip and the characteristic portion is satisfied, and may instead suppress the motion of the characteristic portion contained in the vascular image of the corresponding time phase.

[0182] Alternatively, the processing circuit 34 may perform a process of suppressing the motion of the characteristic portion of the device instead of suppressing the motion of the characteristic portion included in the vascular image of the corresponding time phase. Figure 11BAs shown, when device D3 is moved within a blood vessel, the vessel in which device D3 is located may gradually become finer. Furthermore, for example, assume that it becomes impossible to identify the vascular region in a vascular image such as vascular image I221. In this case, processing circuit 34 can suppress the motion of the device's characteristic portion instead of suppressing the motion of the characteristic portion contained in the vascular image in the corresponding time phase. For example, processing circuit 34 can determine whether the vascular region can be identified in a vascular image such as vascular image I221, and if it is determined that the vascular region cannot be identified, suppress the motion of the device's characteristic portion.

[0183] In the above embodiment, a case is described where a vascular image such as the vascular image I221 is displayed on the display 32 and a user input operation referring to the illuminated vascular image is received to select a vascular region where motion is suppressed. However, the embodiment is not limited to this.

[0184] For example, the processing function 34c can also accept user input via an image other than the vascular image and select a vascular region. For example, the output function 34d displays a vascular model collected from the subject P1 on the display 32. Such a vascular model can be collected, for example, by scanning the subject P1 with a contrast agent using an X-ray CT (CT) device. Here, the user configures an ROI on the vascular model, or specifies any vessel on the vascular model, based on the target vascular region to be reached by the device D3. Furthermore, the processing function 34c identifies a vascular region in the vascular image that corresponds to the vessel within the ROI configured on the vascular model or the specified vessel. In this way, the processing function 34c can select a vascular region whose motion is suppressed based on the user input accepted via the vascular model.

[0185] Alternatively, the processing function 34c can be configured to accept user input, not through an image, to select a vascular region. For example, the processing function 34c analyzes the vascular image and assigns an anatomical label representing the vessel name to each vascular region included in the vascular image. The processing function 34c then accepts the user's designation of the vessel name to select a vascular region for which motion is suppressed.

[0186] For example, the output function 34d displays a list of blood vessel names included in the blood vessel image on the display 108. Furthermore, the processing function 34c can accept an operation from the user to select any blood vessel name in the list. Furthermore, the processing function 34c can also accept an operation from the user to enter a blood vessel name using a keyboard or other means, or to enter a blood vessel name by voice.

[0187] Alternatively, the processing function 34c may automatically select a blood vessel region. For example, the processing function 34c may select a region of a predetermined size and shape at the center of the blood vessel image as the blood vessel region for which motion is suppressed.

[0188] Furthermore, for example, processing function 34c may automatically select a vascular region for motion suppression based on the position of device D3. For example, if the user moves device D3 toward a lesion, processing function 34c may identify the nearest branch of a blood vessel in the direction of device D3's movement in the vascular image and select it as the vascular region for motion suppression.

[0189] Furthermore, in the above-described embodiment, a composite image of a vascular image whose motion has been suppressed by the first processing and an X-ray image whose motion has been suppressed by the second processing is displayed. However, the embodiment is not limited to this. The output function 34d may also display the X-ray image whose motion has been suppressed by the second processing on the display 32 without being synthesized with the vascular image. In other words, the medical image processing apparatus 30 may use the vascular image only for suppressing motion in the X-ray image and omit display of the vascular image.

[0190] Furthermore, in the above embodiment, the rotation and translation matrix W is calculated by searching for the pattern VP' in the vascular image, and the movement of the vascular region between multiple vascular images is suppressed. In other words, the above embodiment describes the case where the first processing is performed through pattern matching. However, the embodiment is not limited to this.

[0191] For example, the processing function 34c can execute the first process by performing matching between images without searching for a specific pattern. For example, the processing function 34c can execute the first process by endpoint-free DP (Dynamic Programming) matching.

[0192] For example, processing function 34c is Figure 12A The contour of the vascular region is extracted from the vascular image I221 shown. Next, processing function 34c generates a contour model C1 based on the extracted contour. For example, processing function 34c extracts the core line of the vascular region as the contour and generates multiple vertices along the core line to generate contour model C1. Similarly, processing function 34c generates contour model C2 based on vascular image I222 and contour model C3 based on vascular image I223.

[0193] Next, processing function 34c finds corresponding points between the contour models. For example, processing function 34c defines a cost associated with establishing correspondences between multiple vertices in contour model C1 and multiple vertices in contour model C2, and finds corresponding points by minimizing this cost. The cost can be defined, for example, based on the difference in feature values between the corresponding vertices. For example, processing function 34c adds the curvature of the blood vessel at each vertex in contour models C1 and C2 as a feature value. Furthermore, processing function 34c defines a cost based on the difference in feature values and solves a minimization problem to minimize this cost. This allows corresponding points to be found so that vertices with the same degree of feature values are in correspondence with each other.

[0194] Furthermore, processing function 34c aligns vascular image I222 with vascular image I221 based on the vertex correspondence. For example, processing function 34c calculates a rotation-translation matrix W1 for aligning vascular image I222 with vascular image I221 based on the vertex correspondence, using singular value decomposition or the like. Similarly, processing function 34c calculates a rotation-translation matrix W2 for aligning vascular image I223 with vascular image I222. Processing function 34c then applies rotation-translation matrix W1 to vascular image I222, thereby aligning vascular image I222 with vascular image I221. Furthermore, processing function 34c applies rotation-translation matrix W1 and rotation-translation matrix W2 to vascular image I223, thereby aligning vascular image I223 with vascular image I221.

[0195] That is, the processing function 34c can calculate the rotation translation matrix W1 and the rotation translation matrix W2 by endpoint free DP matching and perform the first processing. Figure 12B Similarly to the case shown, the processing function 34c can perform the alignment of each X-ray image using the rotation and translation matrices W1 and W2. That is, the processing function 34c can perform the second process of suppressing motion between X-ray images based on the processing results of the endpoint-free DP matching.

[0196] Furthermore, in the above embodiment, the case of suppressing motion in the multiple vascular images by executing the first processing on the multiple vascular images has been described. However, execution of the first processing on the multiple vascular images may be omitted. Specifically, the processing function 34c may determine the first processing for suppressing motion of vascular regions between the multiple vascular images, not execute the first processing on the multiple vascular images, and apply the first processing to the multiple X-ray images, thereby performing the second processing for suppressing motion between the multiple X-ray images.

[0197] In the above embodiment, the coronary arteries are described as an example of a site with periodic motion. However, the embodiment is not limited to this and can be similarly applied to various sites affected by the heartbeat. Furthermore, it can be similarly applied to various sites affected by respiration. In this case, processing function 34c performs rotational translation processing on the vascular image based on the phase in the respiratory cycle, for the X-ray image of the corresponding phase, thereby performing a second process to suppress motion between X-ray images.

[0198] In the above-mentioned embodiment, it is assumed that, in the description of the process of suppressing the movement of the blood vessel region, for example, Figure 12A The description has been made of the process of making the vascular regions in each vascular image consistent with each other as shown. That is, in the above-mentioned embodiment, the process of fixing the vascular region is described as the process of suppressing the movement of the vascular region. However, the embodiment is not limited to this. For example, as the process of suppressing the movement of the vascular region, the processing function 34c may also perform a process of reducing the difference between the images of the position and orientation of the vascular region. That is, the process of suppressing the movement of the vascular region may be a process of fixing the vascular region or a process of reducing the degree of movement of the vascular region. Similarly, the process of suppressing the movement of the X-ray image may be a process of fixing the region corresponding to the vascular region selected in the X-ray image or a process of reducing the degree of movement of the region.

[0199] Furthermore, the above embodiment describes a case where rotation and translation processing is determined as the first processing. Specifically, the above embodiment describes a case where the position and orientation of a vascular region are corrected during the process of suppressing the movement of the vascular region. However, the embodiment is not limited to this, and the processing function 34c may correct only one of the position and orientation of the vascular region.

[0200] When correcting the position of a vascular region, the processing function 34c, for example, determines as a first process a process for aligning the vascular images so that the positions of the vascular regions in the vascular image I221 serving as the reference frame and those in vascular images of frames different from the reference frame are substantially aligned. For example, the processing function 34c determines as a first process a translation matrix for translating each vascular image. Furthermore, the processing function 34c performs as a second process the alignment process determined as the first process on the X-ray images whose phases correspond to the respective vascular images. This allows the processing function 34c to suppress motion between multiple X-ray images.

[0201] Furthermore, when correcting the position of a vascular region, the processing function 34c specifies, as a first process, a process of rotating each vascular image so that the orientation of the vascular region in the vascular image I221 serving as the reference frame and the vascular region in a frame different from the reference frame are substantially aligned. For example, the processing function 34c specifies, as the first process, a rotation matrix for rotating each vascular image. Furthermore, the processing function 34c performs, as a second process, the rotation process specified as the first process on the X-ray image corresponding to the phase of each vascular image. This allows the processing function 34c to suppress motion between multiple X-ray images.

[0202] Furthermore, in the above-described embodiment, the X-ray image whose motion has been suppressed by the second processing is displayed on the display 32. However, the embodiment is not limited to this. For example, the output function 34d may transmit the X-ray image whose motion has been suppressed to another device, such as the X-ray diagnostic apparatus 10. In this case, the device receiving the image can display the X-ray image, thereby providing the user with the X-ray image whose motion has been suppressed.

[0203] In the above embodiment, the X-ray diagnostic apparatus 10 is described as collecting blood vessel images from the subject P1, but the embodiment is not limited thereto. That is, blood vessel images may be collected by an X-ray diagnostic apparatus other than the X-ray diagnostic apparatus 10.

[0204] In addition, in the above embodiment, the medical image processing device 30 is described as performing the process of suppressing the motion of the X-ray image. However, the embodiment is not limited to this. For example, the processing circuit 110 of the X-ray diagnosis device 10 may also perform a function equivalent to the above-mentioned processing function 34c. Figure 10 This point is explained. Figure 10 As shown, the processing circuit 110 executes a control function 110a, a collection function 110b, an output function 110c, and a processing function 110d. The processing function 110d is an example of a processing unit.

[0205] For example, the collection function 110b collects multiple X-ray images of a region of subject P1 that exhibits periodic motion. Furthermore, the processing function 110d selects a vascular region from the vascular images collected for the region of subject P1 that exhibits periodic motion. The vascular images may be collected from subject P1 by the collection function 110b or acquired from another device via the network NW. The processing function 110d then performs a first process to suppress motion of the selected vascular region across the multiple vascular images. Based on the results of the first process, the processing function 110d then performs a second process to suppress motion across the multiple X-ray images. The output function 110c then outputs the X-ray images in which motion has been suppressed by the second process. For example, the output function 110c displays a composite image on the display 108 of the vascular images in which motion has been suppressed by the first process and the X-ray images in which motion has been suppressed by the second process.

[0206] The term "processor" used in the above description refers to circuits such as a CPU, a GPU (Graphics Processing Unit), or an Application Specific Integrated Circuit (ASIC), a programmable logic device (for example, a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), and a Field Programmable Gate Array (FPGA)). When the processor is, for example, a CPU, the processor implements the function by reading and executing a program stored in a storage circuit. On the other hand, when the processor is, for example, an ASIC, instead of storing the program in the storage circuit, the function is directly loaded into the circuit of the processor as a logic circuit. In addition, the processors of this embodiment are not limited to being configured as a single circuit for each processor, but multiple independent circuits can be combined to form one processor to implement its function. Furthermore, multiple components in each figure can be integrated into one processor to implement the function.

[0207] In addition, Figure 1 In the description, it is assumed that a single memory 33 stores programs corresponding to the respective processing functions of the processing circuit 34. Figure 2 and Figure 710 is described as storing a single memory 109 for each processing function of the processing circuit 110. However, the embodiment is not limited to this. For example, a plurality of memories 33 may be distributed, and the processing circuit 34 may read the corresponding program from each memory 33. Similarly, a plurality of memories 109 may be distributed, and the processing circuit 110 may read the corresponding program from each memory 109. Alternatively, instead of storing the program in memory, the program may be directly embedded in the circuit of the processor. In this case, the processor realizes its functions by reading and executing the program embedded in the circuit.

[0208] The components of the devices in the above-described embodiments are conceptual and functional, and do not necessarily need to be physically configured as shown. That is, the specific manner in which the devices are distributed or integrated is not limited to that shown; all or part of them can be functionally or physically distributed or integrated in arbitrary units, depending on various loads, usage conditions, and the like. Furthermore, all or any part of the processing functions performed in each device can be implemented by a CPU and programs parsed and executed by the CPU, or as hardware based on wired logic.

[0209] Furthermore, the medical information processing methods described in the above embodiments can be implemented by executing a pre-prepared medical information processing program on a computer such as a personal computer or workstation. This program can be distributed via a network such as the Internet. Alternatively, this program can be recorded on a computer-readable, non-transitory recording medium such as a hard disk, floppy disk (FD), CD-ROM, MO, or DVD, and read from the recording medium by a computer for execution.

[0210] According to at least one embodiment described above, the visibility of an X-ray image collected for a region with movement can be improved.

[0211] Several embodiments have been described, but these embodiments are provided as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other ways, and various omissions, substitutions, modifications, and combinations of the embodiments can be made without departing from the scope of the invention. These embodiments and their variations are included within the scope and spirit of the invention and are also included in the invention described in the claims and their equivalents.

Claims

1. A medical image processing device comprising: an acquiring unit that acquires a plurality of X-ray images including a device inserted into a body of a subject; a processing unit that performs image matching processing between the X-ray images to suppress movement of a characteristic portion, the characteristic portion being a portion located at a position separated from the front end of the device and having a characteristic shape; and an output unit that outputs the plurality of X-ray images in which the motion of the characteristic portion is suppressed, The matching processing is either (a) endpoint free DP matching, i.e., endpoint free dynamic programming matching, and (b) pattern matching of the part corresponding to the feature part in the contour model of the device obtained from the X-ray image respectively, and the endpoint free DP matching refers to obtaining the correspondence between the points on the contour model based on the feature quantity attached to the vertices on the contour model.

2. The medical image processing apparatus according to claim 1, wherein: The processing unit extracts the characteristic portion from each of the plurality of X-ray images and performs matching processing on the characteristic portion between the X-ray images, thereby suppressing movement of the characteristic portion.

3. The medical image processing apparatus according to claim 1, wherein: The processing unit performs the matching process between the X-ray image of a reference frame and the X-ray image of a frame other than the reference frame, thereby suppressing the movement of the characteristic portion.

4. The medical image processing apparatus according to claim 3, wherein: The processing unit periodically updates the reference frame.

5. The medical image processing apparatus according to claim 1, wherein: A storage unit is provided for storing blood vessel images collected from the subject. The processing unit performs correction processing on the blood vessel image based on a result of the matching processing. The output unit outputs a composite image of the X-ray image in which the motion of the characteristic portion is suppressed and the blood vessel image after the correction process. The medical image processing apparatus according to claim 1 , wherein: A storage unit is provided for storing blood vessel images collected from the subject. The processing unit performs correction processing on the blood vessel image based on the characteristic portion. The output unit outputs a composite image of the X-ray image in which the motion of the characteristic portion is suppressed and the blood vessel image after the correction process.

7. The medical image processing apparatus according to any one of claims 1 to 6, wherein: The device is linear, The characteristic portion is a portion of the device having a large curvature.

8. The medical image processing apparatus according to claim 1, wherein: A storage unit is provided for storing vascular images of the subject collected at a plurality of time phases. When the processing unit satisfies a condition related to the positional relationship between the front end and the characteristic portion, For each of the plurality of X-ray images, determining a corresponding blood vessel image in the time phase from the blood vessel images in the plurality of time phases, determining a process for suppressing the motion of a characteristic portion included in the vascular image of the corresponding time phase; Instead of suppressing the motion of the characteristic portion of the device, the X-ray image is subjected to a process of suppressing the motion of the characteristic portion included in the blood vessel image of the corresponding time phase.

9. The medical image processing apparatus according to claim 1, wherein: The processing unit adds curvature as the feature value to each vertex in the contour model produced based on the plurality of X-ray images, and obtains corresponding points between different images in such a way that vertices having the same degree of the feature value become in correspondence with each other, thereby performing the endpoint-free DP matching.

10. The medical image processing apparatus according to claim 1, wherein: The processing unit cuts out a portion corresponding to the characteristic portion from the contour model created based on an image included in the plurality of X-ray images as a pattern, and performs the pattern matching on other images included in the plurality of X-ray images using the pattern.

11. An X-ray diagnostic device comprising: a collecting unit that collects a plurality of X-ray images including a device inserted into a body of a subject; a processing unit that performs image matching processing between the X-ray images to suppress movement of a characteristic portion, the characteristic portion being a portion located at a position separated from the front end of the device and having a characteristic shape; and an output unit that outputs the plurality of X-ray images in which the motion of the characteristic portion is suppressed, The matching processing is either (a) endpoint free DP matching, i.e., endpoint free dynamic programming matching, and (b) pattern matching between the contour model of the device obtained from the X-ray image and the feature part, wherein the endpoint free DP matching refers to obtaining the correspondence between the points on the contour model based on the feature quantities attached to the vertices on the contour model.

12. A medical image processing method comprising the following steps: acquiring a plurality of X-ray images including the device inserted into the body of the subject; performing inter-image matching processing between the X-ray images, thereby suppressing movement of a characteristic portion, the characteristic portion being a characteristic portion located at a position separated from a front end of the device; and outputting the plurality of X-ray images in which the motion of the characteristic portion is suppressed, The matching processing is either (a) endpoint free DP matching, i.e., endpoint free dynamic programming matching, and (b) pattern matching between the contour model of the device obtained from the X-ray image and the feature part, wherein the endpoint free DP matching refers to obtaining the correspondence between the points on the contour model based on the feature quantities attached to the vertices on the contour model.

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