JP2020062324A - Medical image processing device, x-ray diagnostic device and medical image processing program - Google Patents

Abstract

To facilitate update of a blood vessel region image in a three-dimensional road map.SOLUTION: A medical image processing device according to one embodiment includes a medical image acquisition part, a storage part, a blood vessel image generation part, an updating part and a composite image generation part. The medical image acquisition part acquires a two-dimensional medical image. The storage part stores three-dimensional medical data including information on a blood vessel region. The blood vessel image generation part generates a two-dimensional blood vessel region image including the information on the blood vessel region from the three-dimensional medical data. The updating part updates the two-dimensional blood vessel region image on the basis of the acquired first two-dimensional medical image. The composite image generation part generates the composite image obtained by combining the updated two-dimensional blood vessel region image, the first two-dimensional medical image and the second two-dimensional medical image acquired subsequently to the first two-dimensional medical image.SELECTED DRAWING: Figure 1

Description

  Embodiments of the present invention relate to a medical image processing apparatus, an X-ray diagnostic apparatus, and a medical image processing program.

  In recent years, various treatment methods have been known in which a device is inserted into a subject and operated, and the device is placed in the subject. For example, in a stent graft insertion operation, an operator such as a doctor prepares a stent graft according to the shape of the subject's aorta, and plans a position for indwelling the stent graft. Then, the operator inserts the stent graft into the subject and places the stent graft according to the preoperative plan.

  Here, in the above-mentioned stent-graft insertion, a three-dimensional roadmap is known as a supporting technique for indwelling the stent-graft as planned before the surgery. In the three-dimensional road map, a blood vessel region image showing a blood vessel in which the stent graft is placed is generated from the three-dimensional image data of the blood vessel, and is superimposed and displayed on the X-ray image observed when the stent graft is placed.

JP, 2008-161643, A

  The problem to be solved by the present invention is to facilitate updating of a blood vessel region image in a three-dimensional road map.

  The medical image processing apparatus according to the embodiment includes a medical image acquisition unit, a storage unit, a blood vessel image generation unit, an update unit, and a composite image generation unit. The medical image acquisition unit acquires a two-dimensional medical image. The storage unit stores three-dimensional medical data including information on the blood vessel region. The blood vessel image generation unit generates a two-dimensional blood vessel region image including information on a blood vessel region from the three-dimensional medical data. The updating unit updates the two-dimensional blood vessel region image based on the acquired first two-dimensional medical image. The composite image generation unit displays the updated two-dimensional blood vessel region image, the first two-dimensional medical image, or the second two-dimensional medical image acquired after the first two-dimensional medical image. Generate a combined composite image.

FIG. 1 is a diagram showing an example of the configuration of a medical image processing system according to the first embodiment. FIG. 2 is a diagram showing an example of the configuration of the X-ray diagnostic apparatus according to the first embodiment. FIG. 3 is a diagram showing an example of the stent graft according to the first embodiment. FIG. 4 is a diagram showing an example of a blood vessel region image according to the first embodiment. FIG. 5A is a diagram showing an example of a marker of the stent graft according to the first embodiment. FIG. 5B is a diagram showing an example of a marker of the stent graft according to the first embodiment. FIG. 6 is a diagram for explaining an example of alignment processing by the update function according to the first embodiment. FIG. 7 is a diagram for explaining an example of alignment processing by the update function according to the first embodiment. FIG. 8 is a diagram for explaining an example of alignment processing by the update function according to the first embodiment. FIG. 9 is a diagram for explaining an example of alignment processing by the update function according to the first embodiment. FIG. 10 is a flowchart showing a processing flow of the medical image processing apparatus according to the first embodiment. FIG. 11 is a diagram showing an example of the configuration of the X-ray diagnostic apparatus according to the second embodiment.

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

(First embodiment)
First, the first embodiment will be described. In the first embodiment, a medical image processing system including a medical image processing apparatus will be described as an example. Further, in the first embodiment, a stent graft will be described as an example of a device.

  FIG. 1 is a diagram showing an example of the configuration of a medical image processing system 1 according to the first embodiment. As shown in FIG. 1, the medical image processing system 1 according to the first embodiment includes an X-ray diagnostic apparatus 10, an image storage apparatus 20, and a medical image processing apparatus 30. Then, in the medical image processing system 1, the X-ray diagnostic apparatus 10, the image storage apparatus 20, and the medical image processing apparatus 30 are communicably connected to each other via a network.

  The X-ray diagnostic apparatus 10 is an apparatus that collects an X-ray image from the subject P. For example, the X-ray diagnostic apparatus 10 collects projection data from the subject P in which the stent graft has been inserted, and generates an X-ray image from the collected projection data. Then, the X-ray diagnostic apparatus 10 transmits the collected projection data and the generated X-ray image to the image storage device 20 and the medical image processing device 30. Further, the X-ray diagnostic apparatus 10 reconstructs three-dimensional image data (volume data) using projection data collected by rotation imaging, and the reconstructed volume data is stored in the image storage device 20 and the medical image processing device 30. You can also send it. The configuration of the X-ray diagnostic apparatus 10 will be described later. Further, in the present embodiment, the projection data, the three-dimensional image data, and the X-ray image may be collectively referred to as X-ray image data.

  The image storage device 20 is a device that stores projection data collected by the X-ray diagnostic apparatus 10 and X-ray images. For example, the image storage device 20 acquires projection data or an X-ray image from the X-ray diagnostic device 10 via a network, and stores the acquired projection data or the X-ray image in a memory provided inside or outside the device. Remember. For example, the image storage device 20 is realized by a computer device such as a server device.

  The medical image processing apparatus 30 acquires X-ray image data via the network and executes various processes using the acquired X-ray image data. For example, the medical image processing apparatus 30 acquires X-ray image data from the image storage device 20. Alternatively, the medical image processing apparatus 30 acquires X-ray image data from the X-ray diagnostic apparatus 10 without going through the image storage apparatus 20. The processing performed by the medical image processing apparatus 30 will be described later in detail. For example, the medical image processing apparatus 30 is realized by computer equipment such as a workstation.

  The location where the X-ray diagnostic apparatus 10, the image storage apparatus 20, and the medical image processing apparatus 30 are installed is arbitrary as long as they can be connected via a network. For example, the medical image processing apparatus 30 may be installed in a hospital different from the X-ray diagnostic apparatus 10. Further, although one X-ray diagnostic apparatus 10 is shown in FIG. 1, the medical image processing system 1 may include a plurality of X-ray diagnostic apparatuses 10.

  As shown in FIG. 1, the medical image processing apparatus 30 includes an input interface 31, a display 32, a memory 33, and a processing circuit 34.

  The input interface 31 receives various input operations from the operator, converts the received input operations into electric signals, and outputs the electric signals to the processing circuit 34. For example, the input interface 31 includes a mouse, a keyboard, a trackball, a switch, a button, a joystick, a touch pad for performing an input operation by touching an operation surface, a touch screen in which a display screen and a touch pad are integrated, and an optical sensor. It is realized by the non-contact input circuit and the voice input circuit used. The input interface 31 may be composed of a tablet terminal or the like that can wirelessly communicate with the main body of the medical image processing apparatus 30. Further, the input interface 31 is not limited to the one including physical operation parts such as a mouse and a keyboard. For example, an electric signal processing circuit that receives an electric signal corresponding to an input operation from an external input device provided separately from the medical image processing apparatus 30 and outputs the electric signal to the processing circuit 34 is also included in the input interface 31. Included in the example.

  The display 32 displays various information. For example, the display 32 displays the X-ray image acquired by the X-ray diagnostic apparatus 10 and the processing result by the processing circuit 34 under the control of the processing circuit 34. The display 32 also displays the blood vessel region image generated by the processing circuit 34 and the composite image. The blood vessel image and the composite image will be described in detail later. The display 32 also displays a GUI (Graphical User Interface) for receiving various instructions and various settings from the operator 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 may be a desktop type, or a tablet terminal or the like capable of wireless communication with the main body of the medical image processing apparatus 30.

  The memory 33 is realized by, for example, a RAM (Random Access Memory), a semiconductor memory device such as a flash memory, a hard disk, an optical disk, or the like. For example, the memory 33 stores the X-ray image data acquired from the X-ray diagnostic apparatus 10 or the image storage apparatus 20. Further, for example, the memory 33 stores the blood vessel region image generated by the processing circuit 34 and the combined image. In addition, for example, the memory 33 stores a program for a circuit included in the medical image processing apparatus 30 to realize its function. The memory 33 may be realized by a server group (cloud) connected to the medical image processing apparatus 30 via a network. Here, the memory 33 is an example of a storage unit.

  The processing circuit 34 controls the overall operation of the medical image processing apparatus 30 by executing the medical image acquisition function 34a, the blood vessel image generation function 34b, the update function 34c, the composite image generation function 34d, and the output function 34e. Here, the medical image acquisition function 34a is an example of a medical image acquisition unit. The blood vessel image generation function 34b is an example of a blood vessel image generation unit. The updating function 34c is an example of an updating unit. The composite image generation function 34d is an example of the composite image generation unit.

  For example, the processing circuit 34 acquires X-ray image data from the X-ray diagnostic apparatus 10 or the image storage apparatus 20 by reading a program corresponding to the medical image acquisition function 34a from the memory 33 and executing the program. Further, for example, the processing circuit 34 reads a program corresponding to the blood vessel image generation function 34b from the memory 33 and executes the program to generate a blood vessel region image from the X-ray image data. Further, for example, the processing circuit 34 updates the blood vessel region image based on the X-ray image data by reading the program corresponding to the updating function 34c from the memory 33 and executing the program. Further, for example, the processing circuit 34 generates a composite image by reading out a program corresponding to the composite image generation function 34d from the memory 33 and executing the program. Further, for example, the processing circuit 34 outputs the combined image by reading the program corresponding to the output function 34e from the memory 33 and executing the program.

  In the medical image processing apparatus 30 shown in FIG. 1, each processing function is stored in the memory 33 in the form of a program executable by a computer. The processing circuit 34 is a processor that realizes a function corresponding to each program by reading the program from the memory 33 and executing the program. In other words, the processing circuit 34 in a state where each program is read has a function corresponding to the read program. Note that, in FIG. 1, the single processing circuit 34 has been described as realizing the medical image acquisition function 34a, the blood vessel image generation function 34b, the update function 34c, the combined image generation function 34d, and the output function 34e. It is also possible to configure the processing circuit 34 by combining the independent processors, and realize the function by executing the program by each processor. Further, each processing function of the processing circuit 34 may be implemented by being appropriately dispersed or integrated into a single or a plurality of processing circuits.

  Next, the X-ray diagnostic apparatus 10 that collects X-ray image data will be described with reference to FIG. FIG. 2 is a diagram showing an example of the configuration of the X-ray diagnostic apparatus 10 according to the first embodiment. As shown in FIG. 2, the X-ray diagnostic apparatus 10 includes an X-ray high voltage apparatus 101, an X-ray tube 102, an X-ray diaphragm 103, a top plate 104, a C arm 105, and an X-ray detector 106. A memory 107, a display 108, an input interface 109, and a processing circuit 110.

  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 has an electric circuit such as a transformer and a rectifier, and the X-ray tube 102 irradiates the high-voltage generator that generates a high voltage to be applied to the X-ray tube 102. And an X-ray control device that controls the output voltage according to the X-rays. The high voltage generator may be of a transformer type or an inverter type.

  The X-ray tube 102 is a vacuum tube having a cathode (filament) that generates thermoelectrons and an anode (target) that generates X-rays upon receiving collision of thermoelectrons. The X-ray tube 102 generates X-rays by irradiating thermoelectrons from the cathode to the anode using the high voltage supplied from the X-ray high voltage device 101.

  The X-ray diaphragm 103 has a collimator that narrows the irradiation range of the X-rays generated by the X-ray tube 102, and a filter that adjusts the X-rays emitted from the X-ray tube 102.

  The collimator in the X-ray diaphragm 103 has, for example, four slidable diaphragm blades. The collimator narrows the X-rays generated by the X-ray tube 102 and irradiates the subject P by sliding the diaphragm blades. Here, the diaphragm blade is a plate-shaped member made of lead or the like, and is provided near the X-ray irradiation port of the X-ray tube 102 for adjusting the X-ray irradiation range.

  The filter in the X-ray squeezer 103 changes the quality of the X-rays that are transmitted depending on the material and the thickness of the X-ray absorber for the purpose of reducing the exposure dose to the subject P and improving the image quality of the X-ray image data. The soft line component that is easily affected is reduced, or the high energy component that causes a reduction in the contrast of X-ray image data is reduced. Further, the filter changes the X-ray dose and irradiation range according to the material, thickness, position, etc., so that the X-rays irradiated from the X-ray tube 102 to the subject P have a predetermined distribution. To attenuate.

  For example, the X-ray diaphragm device 103 has a drive mechanism such as a motor and an actuator, and controls the X-ray irradiation by operating the drive mechanism under the control of the processing circuit 110 described later. For example, the X-ray diaphragm device 103 adjusts the opening of the diaphragm blade of the collimator by applying a driving voltage to the driving mechanism according to the control signal received from the processing circuit 110, and irradiates the subject P with the driving voltage. The irradiation range of X-rays to be controlled is controlled. Further, for example, the X-ray diaphragm device 103 irradiates the subject P by adjusting the position of the filter by applying a drive voltage to the drive mechanism according to the control signal received from the processing circuit 110. Control the distribution of X-ray dose.

  The top board 104 is a bed on which the subject P is placed, and is placed on a bed (not shown). The subject P is not included in the X-ray diagnostic apparatus 10. For example, the bed has a drive mechanism such as a motor and an actuator, and the movement / tilt of the top plate 104 is controlled by operating the drive mechanism under the control of the processing circuit 110 described later. For example, the bed moves or inclines the top plate 104 by applying a drive voltage to the drive mechanism according to the control signal received from the processing circuit 110.

  The C-arm 105 holds the X-ray tube 102, the X-ray diaphragm 103, and the X-ray detector 106 so as to face each other with the subject P interposed therebetween. For example, the C-arm 105 has a drive mechanism such as a motor and an actuator, and is rotated or moved by operating the drive mechanism under the control of the processing circuit 110 described later. For example, the C-arm 105 adds the drive voltage to the drive mechanism in accordance with the control signal received from the processing circuit 110, so that the X-ray tube 102, the X-ray diaphragm device 103, and the X-ray detector 106 are detected. The X-ray irradiation position and irradiation angle are controlled by rotating and moving the P. In FIG. 2, the case where the X-ray diagnostic apparatus 10 is a single plane has been described as an example, but the embodiment is not limited to this and may be a biplane case.

  The X-ray detector 106 is, for example, an X-ray flat panel detector (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 P, 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 an optical sensor array, or a direct conversion type detector having a semiconductor element that converts incident X-rays into electric signals. It may be a detector.

  The memory 107 is realized by, for example, a RAM, a semiconductor memory device such as a flash memory, a hard disk, an optical disk, or the like. For example, the memory 107 receives and stores the X-ray image data collected by the processing circuit 110. The memory 107 also stores programs corresponding to various functions read and executed by the processing circuit 110. The memory 107 may be implemented by a server group (cloud) connected to the X-ray diagnostic apparatus 10 via a network.

  The display 108 displays various information. For example, the display 108 displays a GUI for receiving an operator's instruction and various X-ray images under the control of the processing circuit 110. For example, the display 108 is a liquid crystal display or a CRT display. The display 108 may be a desktop type, or may be a tablet terminal or the like capable of wireless communication with the processing circuit 110.

  The input interface 109 receives various input operations from the operator, converts the received input operations into electric signals, and outputs the electric signals to the processing circuit 110. For example, the input interface 109 includes a mouse, a keyboard, a trackball, a switch, a button, a joystick, a touch pad for performing an input operation by touching an operation surface, a touch screen in which a display screen and a touch pad are integrated, and an optical sensor. It is realized by the non-contact input circuit and the voice input circuit used. The input interface 109 may be composed of a tablet terminal or the like that can wirelessly communicate with the processing circuit 110. Further, the input interface 109 is not limited to the one including physical operation parts such as a mouse and a keyboard. For example, an electric signal processing circuit that receives an electric signal corresponding to an input operation from an external input device provided separately from the X-ray diagnostic apparatus 10 and outputs the electric signal to the processing circuit 110 is also included in the input interface 109. Included in the example.

  The processing circuit 110 controls the overall operation of the X-ray diagnostic apparatus 10 by executing the acquisition function 110a, the output function 110b, and the control function 110c. Here, the collection function 110a is an example of a medical image collection unit.

  For example, the processing circuit 110 collects the X-ray image data by reading the program corresponding to the acquisition function 110a from the memory 107 and executing it. For example, the collection function 110a controls the X-ray high-voltage device 101 and adjusts the voltage supplied to the X-ray tube 102 to control the X-ray dose and ON / OFF of the subject P to be irradiated.

  Further, for example, the collection function 110a controls the operation of the X-ray diaphragm device 103 and adjusts the opening of the diaphragm blade of the collimator to control the irradiation range of the X-rays irradiated to the subject P. To do. Further, the collection function 110a controls the operation of the X-ray diaphragm 103 and adjusts the position of the filter to control the distribution of the X-ray dose. In addition, the collection function 110a controls the operation of the C arm 105 to rotate or move the C arm 105. In addition, for example, the collection function 110a moves or tilts the top 104 by controlling the operation of the bed.

  Further, the collection function 110 a generates projection data based on the detection signal received from the X-ray detector 106, and stores the generated projection data in the memory 107. Further, the collection function 110a performs various image processing on the projection data stored in the memory 107 to generate an X-ray image. Further, the collection function 110a executes noise reduction processing by an image processing filter or scattered radiation correction on the X-ray image, for example. In addition, the collection function 110a reconstructs volume data using projection data collected by rotation imaging, and generates an X-ray image from the reconstructed volume data.

  Further, the processing circuit 110 causes the display 108 to display a GUI or an X-ray image by reading a program corresponding to the output function 110b from the memory 107 and executing the program. The output function 110b also outputs the X-ray image data to the image storage device 20 and the medical image processing device 30. Further, the processing circuit 110 controls various functions of the processing circuit 110 based on an input operation received from an operator via the input interface 109 by reading a program corresponding to the control function 110c from the memory 107 and executing the program. To do.

  In the X-ray diagnostic apparatus 10 shown in FIG. 2, each processing function is stored in the memory 107 in the form of a program executable by a computer. The processing circuit 110 is a processor that realizes a function corresponding to each program by reading the program from the memory 107 and executing the program. In other words, the processing circuit 110 in a state where each program is read has a function corresponding to the read program. Although FIG. 2 shows a case where each processing function of the collection function 110a, the output function 110b, and the control function 110c is realized by the single processing circuit 110, the embodiment is not limited to this. For example, the processing circuit 110 may be configured by combining a plurality of independent processors, and each processor may realize each processing function by executing each program. Further, each processing function of the processing circuit 110 may be realized by being appropriately dispersed or integrated into a single or a plurality of processing circuits.

  The word "processor" used in the above description is, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or an application specific integrated circuit (ASIC), a programmable logic device (for example, It means a circuit such as a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA). The processor realizes the function by reading and executing the program stored in the memory 33 or the memory 107.

  1 and 2, the single memory 33 or the memory 107 has been described as storing a program corresponding to each processing function. However, the plurality of memories 33 may be arranged in a distributed manner, and the processing circuit 34 may be configured to read the corresponding programs from the individual memories 33. Similarly, the plurality of memories 107 may be arranged in a distributed manner, and the processing circuit 110 may be configured to read the corresponding programs from the individual memories 107. Further, instead of storing the program in the memory 33 and the memory 107, the program may be directly incorporated in the circuit of the processor. In this case, the processor realizes the function by reading and executing the program incorporated in the circuit.

  Further, the processing circuit 34 and the processing circuit 110 may implement the functions by utilizing the processor of the external device connected via the network. For example, the processing circuit 34 reads a program corresponding to each function from the memory 33 and executes the program, and uses a server group (cloud) connected to the medical image processing apparatus 30 via a network as a computing resource, Each function shown in FIG. 1 is realized.

  The medical image processing system 1 including the medical image processing apparatus 30 has been described above. With such a configuration, the medical image processing apparatus 30 in the medical image processing system 1 facilitates the update of the blood vessel region image in the three-dimensional road map by the processing by the processing circuit 34. Specifically, the medical image processing apparatus 30 facilitates updating of the three-dimensional road map when a doctor or the like operates the medical device while referring to the three-dimensional road map.

  Here, in the present embodiment, a case where a stent graft is used as an example of the device will be described. For example, the stent graft is produced according to the blood vessel shape of the treatment target site in the subject P. For example, in the stent graft insertion operation for an aortic aneurysm, three-dimensional image data showing the blood vessel shape of the subject P is collected in a preoperative treatment plan, and a stent graft is produced based on the three-dimensional image data.

  For example, the collection function 110a in the X-ray diagnostic apparatus 10 performs rotation imaging to collect projection data at a predetermined frame rate while rotating the C-arm 105, and indicates the blood vessel shape of the subject P from the collected projection data. Reconstruct 3D image data. As an example, the acquisition function 110a performs rotation imaging on the subject P in which the contrast agent is not injected into the blood vessel, and acquires a mask image at a predetermined frame rate. Further, the acquisition function 110a executes rotation imaging of the subject P in which the contrast agent is injected into the blood vessel, and acquires a contrast image at a predetermined frame rate. Next, the collection function 110a reconstructs the three-dimensional image data indicating the blood vessel shape of the subject P by using the difference image data obtained by subtracting the mask image and the contrast image as the projection data. As another example, the collection function 110a reconstructs three-dimensional image data using the mask image as projection data. Further, the collection function 110a reconstructs three-dimensional image data by using the contrast image as projection data. Then, the collection function 110a generates three-dimensional image data indicating the blood vessel shape of the subject P by subtracting the two reconstructed three-dimensional image data.

  The three-dimensional image data showing the blood vessel shape of the subject P may be collected by the X-ray diagnostic apparatus 10, or may be collected by an X-ray diagnostic apparatus other than the X-ray diagnostic apparatus 10. A medical image diagnostic apparatus other than the X-ray diagnostic apparatus (for example, X-ray CT (Computed Tomography)) may be collected.

  For example, the stent graft has a trunk portion (main body) and a plurality of branch portions, as shown in FIG. The trunk shown in FIG. 3 is produced, for example, based on the shape of the aorta of the subject P. Further, for example, the plurality of branch portions shown in FIG. 3 are produced based on the shapes of various arteries (branch blood vessels) branching from the aorta. Note that FIG. 3 is a diagram showing an example of the stent graft according to the first embodiment.

  For example, the stent graft is configured so that the trunk portion and the branch portion can be divided, and the trunk portion is provided with a plurality of holes for fitting the branch portions. In this case, in the stent graft insertion operation, after the trunk portion of the stent graft is placed in the aorta, the branch portion of the stent graft is placed so as to fit into the hole of the trunk portion. This reduces blood flow to the aortic aneurysm and prevents expansion of the aortic aneurysm, while maintaining blood flow to various arteries (branch blood vessels) branching from the aorta.

  After the stent graft is created, the operator performs stent-graft endoscopy according to the preoperative plan. For example, the operator first inserts the main portion of the stent graft into the blood vessel of the subject P in the state of being housed in the catheter, and advances it to the position of the treatment target site (aortic aneurysm). At this time, the trunk of the stent graft is housed in the catheter while being compressed in the radial direction.

  Here, while the stent graft is indwelling, the collection function 110a collects the X-ray image of the treatment target site, and the output function 110b outputs the X-ray image. For example, the collection function 110a collects X-ray images of a treatment target site in time series. Further, the output function 110b causes the display 108 to sequentially display the X-ray images collected in time series. Alternatively, the output function 110b sequentially outputs the X-ray images collected in time series to the medical image processing apparatus 30. In this case, the output function 34e of the medical image processing apparatus 30 causes the display 32 to sequentially display the X-ray images acquired from the X-ray diagnostic apparatus 10. In the following, an X-ray image that is sequentially displayed in parallel with acquisition of X-ray images or an X-ray image that is sequentially displayed in parallel with acquisition of X-ray images from another device is a perspective image. Also described.

  The operator places the trunk portion of the stent graft at the position as planned before the operation while referring to the fluoroscopic image. Specifically, the operator pushes the trunk portion of the stent graft out of the catheter with the tip of the catheter positioned at the treatment target site. Here, as shown in FIG. 3, the stent graft has a spring-shaped wire frame, and is housed in the catheter so as to shrink the wire frame. Therefore, the trunk portion of the stent graft extruded from the catheter is radially expanded by the elastic force of the wire frame and is left in the aorta while being in contact with the inner wall of the blood vessel.

  Here, as described above, the trunk portion of the stent graft is provided with a plurality of holes for fitting the branch portions. If the position of the hole in the trunk of the stent-graft and the position of the entrance of the corresponding branch vessel are deviated, the branch of the stent-graft cannot be placed later, and blood flow to the branch vessel is lost. There is also a risk of inhibiting. Therefore, the operator places the trunk of the stent graft such that the position of each of the plurality of holes in the trunk of the stent graft matches the position of the entrance of the corresponding branch vessel. However, normally, the blood vessel is not clearly drawn on the fluoroscopic image and is a two-dimensional image, so that it is not easy for the operator to accurately grasp the position and orientation of the stent graft to be placed in the subject.

  On the other hand, the medical image processing apparatus 30 according to the first embodiment generates and displays a synthetic image in which a blood vessel region image showing a blood vessel shape (blood vessel running) of a treatment target site is synthesized with a fluoroscopic image and is displayed three-dimensionally. By executing the road map, control is performed so that the operator grasps the blood vessel traveling and easily grasps the position and the direction in which the stent graft is arranged. However, as described above, the stent graft is placed at the site to be treated by a plurality of steps of placing the trunk and then placing the branch. Therefore, after the completion of one step, if the shape of the blood vessel changes due to the placement of the device, a deviation from the shape of the blood vessel region image used for the three-dimensional road map will occur.

  In this case, in order to display the accurate three-dimensional road map again, rotation imaging using a contrast agent is performed again to generate a blood vessel region image showing the current blood vessel shape, which increases the burden on the subject. As a result, the labor of the operator increases. Therefore, the medical image processing apparatus 30 according to the first embodiment updates the blood vessel region image in the three-dimensional road map based on the X-ray image acquired when the stent graft is placed, and thereby the three-dimensional road map. Facilitate updating of the blood vessel region image in. Hereinafter, details of the processing of the medical image processing apparatus 30 according to the first embodiment will be described.

  The medical image acquisition function 34a acquires X-ray image data from the X-ray diagnostic apparatus 10 or the image storage apparatus 20. For example, the medical image acquisition function 34a sequentially acquires X-ray images acquired by the X-ray diagnostic apparatus 10 over time. As an example, the medical image acquisition function 34a sequentially acquires X-ray images acquired over time in the stent graft insertion operation.

  Further, the medical image acquisition function 34a acquires three-dimensional image data indicating a blood vessel shape from the X-ray diagnostic apparatus 10 or the image storage apparatus 20. For example, the medical image acquisition function 34a acquires, from the X-ray diagnostic apparatus 10 or the image storage apparatus 20, the three-dimensional image data of the blood vessel used for manufacturing the stent graft.

  The blood vessel image generation function 34b generates a two-dimensional blood vessel region image including information on the blood vessel region from the three-dimensional image data. Specifically, the blood vessel image generation function 34b uses the volume data including the blood vessel region to generate a two-dimensional blood vessel region image from the direction corresponding to the collection direction of the fluoroscopic image acquired by the medical image acquisition function 34a. . For example, the blood vessel image generation function 34b acquires the information of the imaging system when collecting the fluoroscopic image from the X-ray diagnostic apparatus 10, and determines the projection direction or the rendering direction for the three-dimensional image data based on the acquired information. . Then, the blood vessel image generation function 34b generates a projection image obtained by projecting the three-dimensional image data from the determined projection direction, as a blood vessel region image. Alternatively, the blood vessel image generation function 34b generates a rendering image obtained by rendering three-dimensional image data from the determined rendering direction as a blood vessel region image. The information of the imaging system described above is, for example, information indicating the moving state of the bed, the rotating state of the C arm, and the like.

  As described above, the blood vessel image generation function 34b generates the blood vessel region image in the three-dimensional road map from the three-dimensional image data. Here, the blood vessel image generation function 34b can generate a blood vessel region image to which a landmark corresponding to the characteristic point of the stent graft is added. As described above, the stent graft is produced in accordance with the shape of the blood vessel of the subject, and the branch portion is formed on the trunk. In order to enable a three-dimensional road map that more accurately indicates the indwelling position of such a medical device, the blood vessel image generation function 34b uses the landmarks corresponding to the distal end portion of the trunk of the stent graft and the branching position. The illustrated blood vessel region image can be generated. In the following, a three-dimensional road map using a blood vessel region image with a landmark may be described as a three-dimensional road map with a landmark.

  FIG. 4 is a diagram showing an example of a blood vessel region image according to the first embodiment. For example, the blood vessel image generation function 34b generates the blood vessel region image 50 in which the landmark 52 is added to the blood vessel region 51, as shown in FIG. Here, the blood vessel image generation function 34b attaches a landmark to a position specified on the blood vessel region image by an operation by an operator (for example, a doctor) via the input interface 31, for example.

  In such a case, for example, the blood vessel image generation function 34b first generates the blood vessel region image 50 showing the blood vessel region 51 from the volume data. After that, the output function 34e displays the blood vessel region image 50 on the display 32, and the input interface 31 receives a designation operation for giving the landmark 52 to each position of the blood vessel region image 50. The blood vessel image generation function 34b updates the blood vessel region image 50 displayed on the display 32 to the blood vessel region image 50 in which the landmarks 52 are added to the positions designated via the input interface 31. Then, the blood vessel image generation function 34b stores the generated blood vessel region image in the memory 33.

  The operator specifies the landmarks associated with the characteristic points of the stent graft placed in the blood vessel. For example, the operator refers to the blood vessel region image 50 and designates the position of the distal end portion of the trunk when arranging the produced stent graft and the landmarks indicating the branching position, respectively. Here, the distal end portion of the trunk portion of the stent graft and the branching position are provided with feature points such as markers, and the operator places the feature points at the positions where the feature points are placed when the stent graft is placed at the treatment target site. , Set each landmark. The marker is, for example, a radiopaque metal attached to the stent graft.

  The update function 34c updates the two-dimensional blood vessel region image based on the acquired first two-dimensional medical image. Specifically, the update function 34c updates the blood vessel region image in the three-dimensional road map based on the X-ray image acquired during the procedure using the three-dimensional road map. For example, the update function 34c updates the shape of the blood vessel region image using the feature points of the stent graft based on the X-ray image and the feature points of the blood vessel region image.

  Here, the updating of the blood vessel region image by the updating function 34c described below can be executed at any timing. For example, the update function 34c updates the blood vessel region image according to an operation by the operator via the input interface 31. In such a case, for example, when the operator deviates the shape of the actual blood vessel from the shape of the blood vessel in the blood vessel region image in the three-dimensional road map referred to during the procedure using the three-dimensional road map, An operation for updating the blood vessel region image is executed. As an example, when the shape of the actual blood vessel becomes different from the shape of the blood vessel in the blood vessel region image by placing the stent graft during the procedure, the operator performs an operation for updating the blood vessel region image. To execute.

  Further, for example, the update function 34c updates the blood vessel region image every time the trunk portion and the branch portion of the stent graft are placed. In such a case, for example, the updating function 34c detects the timing when the placement of the trunk or the branching portion is completed, and updates the blood vessel region image at the detected timing. As an example, the update function 34c calculates the amount of change in the shape of the stent graft between the X-ray images collected over time, and when the calculated amount of change is below the threshold value, it is determined that the placement is completed. To do. That is, the update function 34c determines whether or not the placement is completed depending on whether or not the stent graft has been pushed out from the catheter and completely deployed.

  Further, for example, the update function 34c calculates a deviation between the actual shape of the blood vessel and the shape of the blood vessel in the blood vessel area image, and updates the blood vessel area image when the calculated deviation exceeds a threshold value. In such a case, for example, the updating function 34c calculates the deviation between the characteristic point of the stent graft and the corresponding characteristic point in the blood vessel region image every time the placement of the trunk or the branch portion is completed, and the calculated deviation is generated. When the threshold is exceeded, the blood vessel region image is updated.

  As described above, the updating function 34c updates the blood vessel region image in the three-dimensional road map at any timing. Next, details of updating the blood vessel region image by the updating function 34c will be described. Here, the update function 34c can update the blood vessel region image by several methods. Hereinafter, each method will be described in order.

  The update function 34c updates the two-dimensional blood vessel region image by aligning the positions of the feature points included in the two-dimensional blood vessel region image with the positions of the feature points included in the first two-dimensional medical image. . Here, since the stent graft is placed in contact with the inner wall of the blood vessel, the shape of the stent graft after placement is in line with the shape of the blood vessel. Therefore, the update function 34c aligns the position of the feature point in the blood vessel region image with the position of the feature point of the stent graft included in the X-ray image acquired during the procedure using the three-dimensional road map, for example. As a result, the blood vessel region image generated by the blood vessel image generation function 34b is updated. Note that the alignment in this embodiment is, for example, non-rigid alignment. That is, the updating function 34c deforms the blood vessel region image so that the positions of the characteristic points of the blood vessel region image match the positions of the stent graft included in the X-ray image.

  Here, the characteristic point in the stent graft is, for example, the above-mentioned marker. In such a case, the update function 34c first acquires the X-ray image acquired for the subject into which the stent graft has been inserted, and specifies the position of the marker included in the stent graft in the acquired X-ray image.

  For example, the update function 34c acquires an X-ray image to be aligned from among the X-ray images acquired by the X-ray diagnostic apparatus 10 over time, and in the acquired X-ray image, the marker of the stent graft is displayed. Identify the location. The X-ray image to be aligned is, for example, the X-ray image at the time when the update of the blood vessel region image is determined.

  5A and 5B are diagrams showing an example of the marker of the stent graft according to the first embodiment. For example, as shown in FIG. 5A, the stent graft has three markers (marker 61, marker 62, and marker 63) at the tip of the trunk or the branch. Further, for example, as shown in FIG. 5B, the stent graft has three markers (marker 64, marker 65, and marker 66) at the tip of the trunk and the branching portion, and two markers (marker 67 and marker 67) in the middle region. 67). For example, the update function 34c performs pattern matching on the X-ray image using the shape of the marker attached to the stent graft. Thereby, the updating function 34c detects a plurality of markers in the X-ray image.

  Then, the update function 34c updates the blood vessel region image by aligning the position of the landmark in the blood vessel region image with the detected marker. FIG. 6 is a diagram for explaining an example of alignment processing by the update function 34c according to the first embodiment. Here, in FIG. 6, the X-ray image I1 is shown on the left side, and the blood vessel region image 80 is shown on the right side. Further, FIG. 6 shows processing after the update of the blood vessel region image is determined.

  For example, the update function 34c detects the marker 71, the marker 72, and the marker 73 in the X-ray image I1, respectively. Then, the updating function 34c updates the shape of the blood vessel region image 80 by deforming the blood vessel region image 80 by non-rigid body alignment so as to align the position of the corresponding landmark with the detected marker. Here, the marker in the stent graft and the landmark in the blood vessel region image are associated with each other in advance, and the updating function 34c deforms the blood vessel region image so that the position of each landmark matches the position of the corresponding marker.

  For example, the update function 34c deforms the blood vessel region image so that the landmark 81 is aligned with the marker 71 in FIG. For example, the updating function 34c deforms the blood vessel region image so that the ellipse of the landmark 81 passes through the three points of the marker 71. Similarly, the update function 34c deforms the blood vessel region image so that the ellipse of the landmark 82 passes through the three points of the marker 72.

  Here, the updating function 34c deforms the blood vessel region image so as not to exceed the allowable deformation amount in updating the blood vessel region image. For example, the update function 34c deforms the blood vessel region image so that the change in the size of the blood vessel region included in the blood vessel region image does not exceed the threshold value. For example, the update function 34c deforms the blood vessel region image within the range in which the moving distance of the landmark is within the threshold value. Accordingly, the update function 34c does not align the landmark 83 with the marker 73 shown in FIG. 6, but aligns the landmark 81 with the marker 71 and aligns the landmark 82 with the marker 72, for example. Will only do. That is, the update function 34c can prevent the feature points that do not correspond to each other, such as the marker 73 and the landmark 83, from being aligned with each other. When the landmark corresponding to the marker 73 is set in the blood vessel region image, the updating function 34c performs the alignment of the landmark with respect to the marker 73, as described above.

  Further, for example, the update function 34c deforms the blood vessel region image so that the size of the diameter of the landmark after deformation is within the maximum value of the diameter of the stent graft. As an example, the updating function 34c sets the blood vessel region image 80 so that the major axis of the ellipse of the landmark 81 becomes equal to or smaller than the maximum value of the diameter of the stent graft when the landmark 81 is aligned with the marker 71. Transform. As a result, the update function 34c can suppress the unreasonable deformation and perform highly accurate alignment.

  In the example described above, the case has been described in which two-dimensional registration is performed to position the blood vessel region image with respect to the marker detected in the X-ray image. In addition to the above-described alignment, the update function 34c can also perform three-dimensional alignment using, for example, the three-dimensional image data that generated the blood vessel region image. That is, the updating function 34c updates the three-dimensional image data based on the two-dimensional medical image, and generates a new two-dimensional blood vessel region image from the updated three-dimensional image data, thereby updating the blood vessel region image. To do.

  In such a case, for example, the update function 34c converts three-dimensional image data into three-dimensional image data of a medical device generated based on the two-dimensional X-ray image and included in the two-dimensional X-ray image. The three-dimensional image data is updated by aligning the included blood vessel region. Then, the updating function 34c updates the blood vessel region image by newly generating a two-dimensional blood vessel region image from the updated three-dimensional image data.

  FIG. 7 is a diagram for explaining an example of alignment processing by the update function 34c according to the first embodiment. Here, in FIG. 7, the X-ray image I1 is shown on the left side, the three-dimensional model of the stent graft generated based on the X-ray image I1 is shown at the center, and the blood vessel region image 80 is shown on the right side. Further, FIG. 7 shows processing after the update of the blood vessel region image is determined.

  For example, the update function 34c detects the marker 71, the marker 72, and the marker 73 in the X-ray image I1, respectively. Further, the update function 34c acquires a three-dimensional model showing the stent graft. For example, the update function 34c acquires the three-dimensional data (CAD (computer-aided design) data or the like) used when manufacturing the stent graft as a three-dimensional model. In addition, for example, the updating function 34c acquires a three-dimensional model by imaging the manufactured stent graft from multiple directions with an optical camera, an X-ray CT apparatus, the X-ray diagnostic apparatus 10, and the like and modeling it.

  Here, the three-dimensional model acquired by the update function 34c has markers such as the tip portion and the branching position, like the stent graft actually inserted into the subject. The updating function 34c changes the position of the marker in the three-dimensional model based on the position of the marker detected from the X-ray image, thereby generating a three-dimensional model showing the shape of the stent graft after being inserted into the subject. . As an example, the updating function 34c changes the position of the marker in the three-dimensional model based on the positions of the marker 71, the marker 72, and the marker 73 detected from the X-ray image I1, as shown in FIG. A three-dimensional model M71 showing the shape of the stent graft after being inserted into the subject is generated. That is, the updating function 34c adjusts the positions of the acquired marker 71 ′, marker 72 ′, and marker 73 ′ of the three-dimensional model to the positions of the marker 71, the marker 72, and the marker 73 detected in the X-ray image I1, respectively. , A three-dimensional model M71 showing the shape of the stent graft after being inserted into the subject.

  Here, the correspondence of each marker can be identified by the relative position of each marker. For example, the markers attached to the stent graft have different intervals between the three markers, as shown by the marker 71 in FIG. 7. That is, the update function 34c identifies the correspondence between the three markers 71 in the X-ray image and the three markers 71 'in the three-dimensional model based on the difference in the intervals between the three markers. Similarly, the update function 34c also specifies the correspondence relationship between the marker 72 and the marker 73 between the marker 72 'and the marker 73'. Then, the update function 34c aligns the corresponding marker in the three-dimensional model with the marker detected in the X-ray image in a non-rigid position, thereby indicating the three-dimensional shape of the stent graft after being inserted into the subject. A model M71 is generated.

  In addition, when generating the above-mentioned three-dimensional model M71, the updating function 34c acquires the above-mentioned three-dimensional model before the start of the stent graft insertion operation and stores it in the memory 33. Then, after the stent graft insertion operation is started, the updating function 34c reads the three-dimensional model from the memory 33 and executes the deformation of the three-dimensional model based on the position of the marker detected from the X-ray image.

  The method of uniquely identifying the correspondence between each of the markers specified in the X-ray image and each of the markers in the three-dimensional model is not limited to the above example. For example, when the shape and size of the markers attached to the stent graft are different, the updating function 34c compares the shape and size of each marker detected in the X-ray image with the shape and size of the marker in the three-dimensional model. Thus, the correspondence can be uniquely specified.

  Then, the update function 34c updates the shape of the blood vessel region in the three-dimensional image data by aligning the three-dimensional image data that has generated the blood vessel region image with the generated three-dimensional model. For example, the updating function 34c updates the shape of the blood vessel region in the three-dimensional image data by aligning the three-dimensional image data used to generate the blood vessel region image 80 with the three-dimensional model M71 in a non-rigid body position.

  As an example, the update function 34c is configured such that the ellipse plane passing through the three points in the marker 71 ′ and the ellipse plane indicating the landmark 81 are parallel to each other, and the ellipse indicating the landmark 81 is the marker 71 ′. The three-dimensional image data used to generate the blood vessel region image 80 is updated so as to pass through the three points in. Similarly, in the update function 34c, the elliptical plane passing through the three points in the marker 72 ′ and the elliptical plane indicating the landmark 82 are parallel to each other, and the ellipse indicating the landmark 82 is 3 in the marker 72 ′. The three-dimensional image data used to generate the blood vessel region image 80 is updated so as to pass through the points.

  Note that the updating function 34c deforms the three-dimensional image data so that the allowable deformation amount is not exceeded even when the three-dimensional image data is updated, as in the case of updating the blood vessel region image described above. That is, similar to the above-described two-dimensional registration, the update function 34c prevents the change in the size of the blood vessel region included in the three-dimensional image data from exceeding the threshold even in the three-dimensional registration. Transform. Further, the update function 34c deforms the three-dimensional image data so that the size of the diameter of the transformed landmark is within the maximum value of the diameter of the stent graft.

  As described above, when the 3D image data is updated, the update function 34c stores the updated 3D image data in the memory 33. Then, the updating function 34c updates the blood vessel region image by controlling the blood vessel image generating function 34b so as to regenerate the blood vessel region image using the newly stored three-dimensional image data.

  In the above example, the case where the blood vessel region image or the three-dimensional image data is aligned with the marker of the stent graft has been described. The update function 34c can also perform, for example, alignment using the shape of the blood vessel, in addition to the alignment described above. That is, the updating function 34c extracts the blood vessel region included in the two-dimensional X-ray image, and aligns the shape of the blood vessel region included in the two-dimensional blood vessel region image with the shape of the extracted blood vessel region. Then, the blood vessel region image is updated.

  That is, the updating function 34c updates the blood vessel region image by extracting the blood vessel region from the X-ray image after the stent graft has been placed and aligning the blood vessel region of the blood vessel region image with the extracted blood vessel region. . Here, for example, the update function 34c extracts a blood vessel region from a two-dimensional X-ray image acquired by injecting a contrast agent.

  For example, the update function 34c acquires an X-ray image collected in a state where a contrast agent is injected into a blood vessel including the treatment target site after the stent graft is inserted to the treatment target site (such as an aortic aneurysm). Then, the updating function 34c acquires the blood vessel region from the acquired X-ray image. As an example, the update function 34c extracts a region having a pixel value larger than a threshold value as a blood vessel region from an X-ray image collected in a state where a positive contrast medium (iodine-based contrast medium or the like) is injected, The contour of the extracted blood vessel region is acquired as a blood vessel shape.

  Then, the updating function 34c updates the blood vessel region image by aligning the blood vessel region included in the blood vessel region image with the extracted blood vessel region. For example, the updating function 34c updates the blood vessel region image by deforming the blood vessel region image so that the contour of the blood vessel in the blood vessel region image matches the contour of the extracted blood vessel region. FIG. 8 is a diagram for explaining an example of the alignment processing by the update function 34c according to the first embodiment. Here, in FIG. 8, an X-ray image I2 collected while injecting a contrast agent into the blood vessel after the stent graft has been placed is shown on the left side, and a blood vessel outline 80 'in the blood vessel region image is shown on the right side. Further, FIG. 7 shows processing after the update of the blood vessel region image is determined.

  For example, as shown in FIG. 8, the updating function 34c extracts the blood vessel V1 from the X-ray image I2 collected with the contrast agent injected, and acquires the contour (boundary line) 74 of the extracted blood vessel V1. To do. The updating function 34c acquires the contour 80 'of the blood vessel in the blood vessel region image by projecting, for example, the three-dimensional image data used to generate the blood vessel region image from the direction in which the blood vessel region image is generated.

  Then, the updating function 34c deforms the contour (boundary line) 74 of the blood vessel V1 so that the boundary line 84 of the blood vessel contour 80 'in the blood vessel region image matches. For example, the update function 34c compresses or expands the boundary line 84 of the blood vessel contour 80 ′ in the blood vessel region image in the radial direction or bends the boundary line 84 along the core line to thereby form the contour (boundary line) 74 of the blood vessel V1. To match.

  Similarly, the update function 34c transforms another boundary line in the blood vessel contour 80 'in the blood vessel region image so as to match the corresponding boundary line in the blood vessel V1. As a result, the updating function 34c calculates the deformation amount at each position for matching the boundary line of the blood vessel outline 80 'in the blood vessel region image with the boundary line of the blood vessel V1. Then, the update function 34c updates the blood vessel region image by deforming the blood vessel region image with the calculated deformation amount.

  Note that the updating function 34c can execute the above-described alignment using the shape of the blood vessel in combination with the process of aligning the blood vessel region image or the three-dimensional image data with the marker of the stent graft. For example, the update function 34c may be executed by combining the process of aligning the landmark of the blood vessel region image with the marker of the stent graft detected from the X-ray image and the above-described alignment using the shape of the blood vessel. it can. As a result, the update function 34c can further improve the alignment accuracy.

  In addition, in the above-described embodiment, when the three-dimensional image data is aligned with the marker of the stent graft, the three-dimensional model is updated according to the position of the marker of the stent graft, and the updated three-dimensional model and the blood vessel region image are combined. The case of aligning the three-dimensional image data used for generation has been described. However, the embodiment is not limited to this. For example, when the X-ray diagnostic apparatus 10 is a biplane apparatus, when the three-dimensional image data is aligned using X-ray images acquired from different directions. But it is okay.

  In such a case, the update function 34c identifies the three-dimensional position of the feature point included in the two-dimensional X-ray image based on the two-dimensional X-ray image acquired from a plurality of directions, and identifies the identified feature point. The three-dimensional image data is updated by aligning the feature points included in the three-dimensional image data with the three-dimensional position.

  FIG. 9 is a diagram for explaining an example of the alignment processing by the update function 34c according to the first embodiment. Here, in FIG. 9, the upper row shows the alignment in one direction, and the lower row shows the alignment in the other direction. Further, on the left side of FIG. 8, the X-ray images I1 acquired simultaneously in the upper direction and the lower direction are respectively shown, and on the right side, the blood vessel region images 80 are shown from the upper direction and the lower direction, respectively. Further, FIG. 8 shows processing after the update of the blood vessel region image is determined.

  For example, as shown in FIG. 9, the update function 34c estimates the three-dimensional positions of the marker 71, the marker 72, and the marker 73 using two X-ray images acquired from different directions. It should be noted that the estimation of the three-dimensional position using the two X-ray images collected from different directions is executed by arbitrarily using the existing method. Then, the updating function 34c updates the blood vessel region image by aligning the landmarks of the three-dimensional image data that generated the blood vessel region image with the estimated three-dimensional position of each marker. The alignment process is executed in the same manner as when the above-described three-dimensional model is used.

  The composite image generation function 34d generates a composite image by combining the blood vessel region image generated by the blood vessel image generation function 34b and the X-ray image acquired by the medical image acquisition function 34a. Further, the composite image generation function 34d composites the two-dimensional blood vessel region image updated by the update function 34c, the X-ray image used for the update, or the X-ray image acquired after the X-ray image. Generate a composite image.

  That is, the composite image generation function 34d converts the blood vessel region image generated by the blood vessel image generation function 34b into each X-ray image sequentially acquired by the medical image acquisition function 34a with the start of the landmark-added three-dimensional road map. The superimposed composite images are sequentially generated. Further, the composite image generation function 34d sequentially generates a composite image in which the blood vessel region image updated by the update function 34c is superimposed on each X-ray image sequentially acquired by the medical image acquisition function 34a. The synthetic image generation function 34d generates a synthetic image by synthesizing the latest blood vessel region image with the X-ray image every time the blood vessel region image is updated by the updating function 34c. Here, the composite image combined by the composite image generation function 34d is, for example, a superimposed image in which the blood vessel region image is superimposed on the X-ray image.

  The output function 34e outputs the composite image generated by the composite image generation function 34d. For example, the output function 34e causes the display 32 to sequentially display the combined images that are sequentially combined. Further, for example, the output function 34e outputs the composite image to the X-ray diagnostic apparatus 10. In such a case, the output function 110b of the X-ray diagnostic apparatus 10 causes the display 108 to display the composite image acquired from the medical image processing apparatus 30.

  As described above, the medical image acquisition function 34a sequentially acquires the two-dimensional X-ray images acquired over time. The update function 34c updates the two-dimensional blood vessel region image based on the first X-ray image included in the plurality of two-dimensional X-ray images sequentially acquired. The synthetic image generation function 34d synthesizes the updated two-dimensional blood vessel region image with the second X-ray image acquired after the first X-ray image in the plurality of sequentially acquired X-ray images. Generate an image. That is, the medical image processing apparatus 30 displays the three-dimensional road map 32 or the display while acquiring an X-ray image in real time during the procedure in, for example, a stent graft insertion operation performed using the X-ray diagnostic apparatus 10. It is displayed on 108. Then, when the medical image processing apparatus 30 determines to update the blood vessel region image in the three-dimensional road map, it updates the blood vessel region image based on the acquired X-ray image, and uses the updated blood vessel region image 3 The dimensional road map is displayed on the display 32 or the display 108.

  Next, an example of a processing procedure by the medical image processing apparatus 30 will be described with reference to FIG. FIG. 10 is a flowchart showing a processing flow of the medical image processing apparatus 30 according to the first embodiment. Step S101 is a step corresponding to the blood vessel image generation function 34b. Step S102 is a step corresponding to the composite image generation function 34d and the output function 34e. Steps S103 and S104 are steps corresponding to the update function 34c. Step S110 is a step corresponding to the medical image acquisition function 34a.

  In the medical image processing apparatus 30 according to the first embodiment, the processing circuit 34 generates a blood vessel region image used for a landmark-added three-dimensional road map using the three-dimensional image data including the treatment target site (step S101). ). Then, the processing circuit 34 starts the landmark-added three-dimensional road map by superimposing the generated blood vessel region image on the perspective image and displaying the image (step S102).

  Then, the processing circuit 34 determines whether or not to update the blood vessel region image (step S103). Here, when updating (step S103 update), the processing circuit 34 updates the landmark-added three-dimensional road map by updating the blood vessel region image based on the fluoroscopic image. On the other hand, when not updating (No at step S103), the processing circuit 34 sequentially superimposes the first generated blood vessel region image on the sequentially acquired fluoroscopic images and sequentially displays the images.

  After that, the processing circuit 34 determines whether to end the processing (step S105). Here, when the process is not finished (No at Step S105), the processing circuit 34 continues the process. On the other hand, when the processing is to be ended (Yes at Step S105), the processing circuit 34 ends the processing.

  As described above, according to the first embodiment, the medical image acquisition function 34a acquires a two-dimensional X-ray image. The memory 33 stores three-dimensional image data including information on the blood vessel region. The blood vessel image generation function 34b generates a two-dimensional blood vessel region image including information on the blood vessel region from the three-dimensional image data. The update function 34c updates the two-dimensional blood vessel region image based on the acquired first two-dimensional X-ray image. The synthetic image generation function 34d is configured to update the two-dimensional blood vessel region image and the first two-dimensional X-ray image, or the second two-dimensional X-ray image acquired after the first two-dimensional X-ray image. A combined image is generated by combining and. Therefore, the medical image processing apparatus 30 according to the first embodiment can update the blood vessel region image without performing rotation imaging using the contrast agent, and can easily update the blood vessel region image in the three-dimensional road map. To be able to.

  Further, according to the first embodiment, the updating function 34c positions the position of the feature point included in the two-dimensional blood vessel region image with respect to the position of the feature point included in the first two-dimensional X-ray image. By matching, the two-dimensional blood vessel region image is updated. Therefore, the medical image processing apparatus 30 according to the first embodiment can update the blood vessel region image using the fluoroscopic image used in the three-dimensional road map, and the blood vessel region image can be updated more easily. to enable.

  In addition, according to the first embodiment, the updating function 34c updates the three-dimensional image data based on the first two-dimensional X-ray image, and newly updates the two-dimensional blood vessel region from the updated three-dimensional image data. The two-dimensional blood vessel region image is updated by generating the image. Therefore, the medical image processing apparatus 30 according to the first embodiment can update the blood vessel region image by using the three-dimensional information, and enables more accurate updating.

  Further, according to the first embodiment, the update function 34c is applied to the three-dimensional model of the stent graft included in the first two-dimensional X-ray image generated based on the first two-dimensional X-ray image. Then, the three-dimensional image data is updated by aligning the blood vessel region included in the three-dimensional image data. Therefore, the medical image processing apparatus 30 according to the first embodiment enables the three-dimensional image data to be updated more easily.

  Further, according to the first embodiment, the updating function 34c uses the first two-dimensional X-ray images acquired from a plurality of directions to generate the three-dimensional feature points included in the first two-dimensional X-ray image. Is specified, and the feature points included in the three-dimensional medical data are aligned with the identified three-dimensional positions of the feature points to update the three-dimensional image data. Therefore, the medical image processing apparatus 30 according to the first embodiment can more easily update the three-dimensional image data when it is a biplane apparatus.

  Further, according to the first embodiment, the updating function 34c extracts the blood vessel region included in the first two-dimensional X-ray image, and converts the shape of the extracted blood vessel region into a two-dimensional blood vessel region image. The two-dimensional blood vessel region image is updated by aligning the shape of the included blood vessel region. Therefore, the medical image processing apparatus 30 according to the first embodiment makes it possible to further improve the alignment accuracy.

  Further, according to the first embodiment, the updating function 34c extracts the blood vessel region from the first two-dimensional X-ray image acquired by injecting the contrast agent. Therefore, the medical image processing apparatus 30 according to the first embodiment makes it possible to easily extract a blood vessel region.

  Further, according to the first embodiment, the updating function 34c modifies the two-dimensional blood vessel region image or the three-dimensional image data so as not to exceed the allowable deformation amount in updating the two-dimensional blood vessel region image. Let Therefore, the medical image processing apparatus 30 according to the first embodiment makes it possible to improve the alignment accuracy.

(Second embodiment)
Now, the first embodiment has been described so far, but it may be implemented in various different forms other than the first embodiment described above.

  In the above-described embodiment, the marker attached to the stent graft has been described as the characteristic point of the stent graft. However, the embodiment is not limited to this, and for example, information corresponding to the shape of the stent graft may be used as the characteristic point. Here, the information corresponding to the shape of the stent graft is, for example, information indicating a characteristic portion in the contour or core line of the stent graft. In such a case, the landmark specified in the blood vessel region image is arranged at the position corresponding to the above-mentioned feature point.

  Further, in the above-described embodiment, the case where the shape of the blood vessel included in the X-ray image is acquired by using the X-ray image collected in the state where the contrast agent is injected has been described. However, the embodiment is not limited to this, and for example, the shape of the blood vessel may be acquired using the wire frame of the stent graft.

  For example, a stent graft has a corrugated metal wire frame as shown in FIG. Therefore, the outer contour of the stent graft is not drawn on the X-ray image, but this wire frame is drawn on the X-ray image. Therefore, the update function 34c identifies the wire frame included in the X-ray image by using pattern matching or the like, and forms the line segment that passes through the end of the identified wire frame, thereby obtaining the obtained line segment. It is acquired as the contour (boundary line) of the blood vessel region in the X-ray image.

  Further, in the above-described embodiment, the stent graft having three markers at the distal end and the branch position has been described as an example. However, the embodiment is not limited to this, and for example, a stent graft having two or less markers or four or more markers may be used.

  Further, in the above-described embodiment, the case where the medical image processing apparatus 30 includes the processing circuit 34 having the blood vessel image generation function 34b, the update function 34c, and the combined image generation function 34d has been described. However, the embodiment is not limited to this. For example, the processing circuit 110 in the X-ray diagnostic apparatus 10 may have a function corresponding to the blood vessel image generation function 34b, the update function 34c, and the composite image generation function 34d.

  FIG. 11 is a diagram showing an example of the configuration of the X-ray diagnostic apparatus 10 according to the second embodiment. For example, as shown in FIG. 11, the processing circuit 110 in the X-ray diagnostic apparatus 10 includes a blood vessel image generation function 110d, an update function 110e, and a synthetic image generation function 110f in addition to the acquisition function 110a, the output function 110b, and the control function 110c. Have. Here, the blood vessel image generation function 110d is a function corresponding to the blood vessel image generation function 34b. The update function 110e is a function corresponding to the update function 34c. The composite image generation function 110f is a function corresponding to the composite image generation function 34d.

  Each component of each device according to the above-described embodiment is functionally conceptual, and does not necessarily have to be physically configured as illustrated. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or part of the device may be functionally or physically distributed / arranged in arbitrary units according to various loads and usage conditions. It can be integrated and configured. Furthermore, all or arbitrary parts of the processing functions performed by each device can be realized by a CPU and a program that is analyzed and executed by the CPU, or can be realized as hardware by a wired logic.

  Further, the image processing method described in the above-described embodiment can be realized by executing a medical image processing program prepared in advance on a computer such as a personal computer or a workstation. This program can be distributed via a network such as the Internet. The program is recorded in a computer-readable non-transitory recording medium such as a hard disk, a flexible disk (FD), a CD-ROM, an MO, or a DVD, and executed by being read from the recording medium by the computer. You can also

  According to at least one embodiment described above, it is possible to easily update the blood vessel region image in the three-dimensional road map.

  Although some embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the invention described in the claims and the equivalents thereof as well as included in the scope and the gist of the invention.

1 Medical Image Processing System 10 X-Ray Diagnostic Device 30 Medical Image Processing Device 34, 110 Processing Circuit 34a Medical Image Acquisition Function 34b, 110d Blood Vessel Image Generation Function 34c, 110e Update Function 34d, 110f Synthetic Image Generation Function 34e, 110b Output Function 110a Collection function

Claims (11)

A medical image acquisition unit for acquiring a two-dimensional medical image,
A storage unit for storing three-dimensional medical data including information on a blood vessel region;
A blood vessel image generation unit that generates a two-dimensional blood vessel region image including information on a blood vessel region from the three-dimensional medical data;
An updating unit for updating the two-dimensional blood vessel region image based on the acquired first two-dimensional medical image,
Generating a composite image that combines the updated two-dimensional blood vessel region image and the first two-dimensional medical image or the second two-dimensional medical image acquired after the first two-dimensional medical image A composite image generation unit for
A medical image processing apparatus comprising:   The updating unit aligns the positions of the feature points included in the two-dimensional blood vessel region image with the positions of the feature points included in the first two-dimensional medical image to obtain the two-dimensional blood vessel region image. The medical image processing apparatus according to claim 1, which updates the.   The updating unit updates the three-dimensional medical data based on the first two-dimensional medical image, and newly generates a two-dimensional blood vessel region image from the updated three-dimensional medical data, thereby generating the two-dimensional blood vessel. The medical image processing apparatus according to claim 1, wherein the area image is updated.   The updating unit includes the three-dimensional medical data included in the three-dimensional medical data with respect to the three-dimensional model of the medical device included in the first two-dimensional medical image generated based on the first two-dimensional medical image. The medical image processing apparatus according to claim 3, wherein the three-dimensional medical data is updated by aligning a blood vessel region.   The updating unit identifies a three-dimensional position of a feature point included in the first two-dimensional medical image based on the first two-dimensional medical image collected from a plurality of directions, and determines three of the identified feature points. The medical image processing apparatus according to claim 3, wherein the three-dimensional medical data is updated by aligning feature points included in the three-dimensional medical data with a three-dimensional position.   The updating unit extracts a blood vessel region included in the first two-dimensional medical image, and aligns the shape of the blood vessel region included in the two-dimensional blood vessel region image with the shape of the extracted blood vessel region. 6. The medical image processing apparatus according to claim 1, wherein the two-dimensional blood vessel region image is updated.   The medical image processing apparatus according to claim 6, wherein the updating unit extracts the blood vessel region from the first two-dimensional medical image injected and collected with a contrast agent.   The updating unit deforms the two-dimensional blood vessel region image or the three-dimensional medical data so as not to exceed an allowable deformation amount in updating the two-dimensional blood vessel region image. The medical image processing apparatus according to one. The medical image acquisition unit sequentially acquires the two-dimensional medical images collected over time,
The update unit updates the two-dimensional blood vessel region image based on the first two-dimensional medical image included in a plurality of two-dimensional medical images sequentially acquired,
The composite image generation unit includes the updated two-dimensional blood vessel region image and the second two-dimensional medical image acquired after the first two-dimensional medical image in the plurality of sequentially acquired two-dimensional medical images. Generate a composite image by combining with the image,
The medical image processing apparatus according to claim 1. A medical image collection unit for collecting two-dimensional medical images,
A storage unit for storing three-dimensional medical data including information on a blood vessel region;
A blood vessel image generation unit that generates a two-dimensional blood vessel region image including information on a blood vessel region from the three-dimensional medical data;
An updating unit for updating the two-dimensional blood vessel region image based on the acquired first two-dimensional medical image,
Generating a composite image that combines the updated two-dimensional blood vessel region image and the first two-dimensional medical image or the second two-dimensional medical image acquired after the first two-dimensional medical image A composite image generation unit for
An X-ray diagnostic apparatus comprising: Acquire a two-dimensional medical image,
A two-dimensional blood vessel region image including blood vessel region information is generated from three-dimensional medical data including blood vessel region information,
Updating the two-dimensional blood vessel region image based on the acquired first two-dimensional medical image,
Generating a composite image that combines the updated two-dimensional blood vessel region image and the first two-dimensional medical image or the second two-dimensional medical image acquired after the first two-dimensional medical image To do
A medical image processing program that causes a computer to execute each process.

Images