JP2019153180A - Image processing apparatus, 3d modeling apparatus and data structure - Google Patents

Abstract

To accurately reproduce the softness of organs in a smaller unit than that for anatomical parts.SOLUTION: The image processing apparatus according to an embodiment includes a memory, a creation unit, and an output unit. The memory stores one or more medical 3D images having a plurality of voxels indicating an organ of a subject. The creation unit individually creates design drawing data indicating two or more of a shape, hardness, density, and effective atomic number of the organ for substantially each voxel based on the medical 3D images. The output unit outputs the design drawing data.SELECTED DRAWING: Figure 1

Description

  Embodiments described herein relate generally to an image processing apparatus, a 3D modeling apparatus, and a data structure.

  In recent years, the application of 3D printers has been dramatically advanced in the medical field. For example, according to the American Heart Association Academic Meeting in 2016 (AHA2016) and the 102nd North American Radiological Society (RSNA2016), a jig and a surgical device are modeled by a 3D printer, and a surgical device is operated by surgery using the jig. Research on indwelling tests has been underway. Not limited to this, it is widely known that an organ formed by a 3D printer is used for explanation and practice before surgery, medical education, and the like.

  Here, the latest 3D printer can create a soft model by changing the mixing ratio of materials. The relationship between the mixing ratio of materials and softness is held by 3D printer manufacturers. Technology for measuring the softness of the organ that is the object of modeling is owned by image processing manufacturers. In addition, a technique is known in which a softness table is held in a 3D printer for each organ or for each part in the organ to change the softness of the modeled object. Here, “part in the organ” means an anatomical part such as fat or blood vessel constituting the organ.

  However, this type of technology is in a situation where the softness cannot be correctly reproduced in units smaller than “every organ or every part in the organ”. Accordingly, for example, for a patient having an organ including a malformed part that cannot be classified as “for each organ or for each part in the organ”, the softness cannot be accurately reproduced for each part for each patient.

Japanese Patent No. 5239037 JP 2014-74938 A

  The problem to be solved by the invention is to accurately reproduce the softness of organs in smaller units than anatomical parts.

  The image processing apparatus according to the embodiment includes a memory, a creation unit, and an output unit. The memory stores one or more medical 3D images having a plurality of voxels indicating the organ of the subject. The creation unit creates design drawing data indicating two or more of the shape, hardness, density, and effective atomic number of the organ individually for each approximately voxel based on the medical 3D image. The output unit outputs the design drawing data.

FIG. 1 is a block diagram illustrating a configuration example of a modeling system including an image processing apparatus and a 3D modeling apparatus according to the first embodiment. FIG. 2 is a schematic diagram for explaining a medical 3D image according to the first embodiment. FIG. 3 is a schematic diagram for explaining the first image indicating the hardness in the first embodiment. FIG. 4 is a schematic diagram for explaining the second image indicating the density in the first embodiment. FIG. 5 is a schematic diagram for explaining a third image showing an effective atomic number in the first embodiment. FIG. 6 is a schematic diagram for explaining a fourth image showing a shape in the first embodiment. FIG. 7 is a schematic diagram for explaining information indicating a shape in a modified example of the first embodiment. FIG. 8 is a schematic diagram for explaining a configuration example of the design drawing data in the first embodiment. FIG. 9 is a block diagram illustrating a configuration example of the 3D modeling apparatus according to the first embodiment. FIG. 10 is a flowchart for explaining the operation in the first embodiment. FIG. 11 is a block diagram illustrating a configuration example of the 3D modeling apparatus according to the second embodiment. FIG. 12 is a schematic diagram illustrating a configuration example of a first table related to hardness in the second embodiment. FIG. 13 is a schematic diagram illustrating a configuration example of a second table relating to the density in the second embodiment. FIG. 14 is a schematic diagram illustrating a configuration example of a third table related to effective atomic numbers in the second embodiment. FIG. 15 is a schematic diagram for explaining a configuration example of design drawing data in the second embodiment. FIG. 16 is a flowchart for explaining the operation in the second embodiment. FIG. 17 is a flowchart for explaining the operation in the second embodiment. FIG. 18 is a schematic diagram for explaining data for 3D modeling in the second embodiment. FIG. 19 is a schematic diagram for explaining data for 3D modeling according to the second embodiment. FIG. 20 is a block diagram illustrating a configuration example of a modeling system including an image processing device and a 3D modeling device according to the third embodiment. FIG. 21 is a block diagram illustrating a configuration example of an image processing device according to the third embodiment. FIG. 22 is a flowchart for explaining the operation in the third embodiment. FIG. 23 is a flowchart for explaining a modified example of the operation in the third embodiment. FIG. 24 is a block diagram illustrating another modification of the third embodiment.

  Hereinafter, embodiments of an image processing apparatus, a data structure, and a 3D modeling apparatus will be described in detail with reference to the drawings. The following image processing apparatus and 3D modeling apparatus can each be implemented with either a hardware configuration or a combination configuration of hardware resources and software. As the software of the combined configuration, a program that is installed in the computer from a network or a non-transitory computer-readable storage medium in advance and causes the computer to realize each function of the image processing apparatus or the 3D modeling apparatus is used.

  The following image processing apparatus is a computer apparatus for creating design drawing data from a medical 3D image generated by a modality (medical image diagnostic apparatus). The image processing apparatus may be incorporated in the modality, or may be a computer apparatus such as a workstation separate from the modality. Hereinafter, for the sake of brevity, the image processing apparatus will be described by exemplifying either the form incorporated in the modality or the form provided separately from the modality. However, the image processing apparatus can be implemented in a form not illustrated.

  Modality can be applied to any medical diagnostic imaging device that can scan a subject and generate a medical 3D image, such as a computed tomography (CT) device, a magnetic resonance imaging (MRI) device, or an ultrasound diagnostic device. It is. As such a CT apparatus, spectrum CT, dynamic CT, and traditional CT can be used as appropriate. As the MRI apparatus, a traditional MR can be used as appropriate. In the following description, the CT apparatus will be mainly described as an example of a modality.

<First Embodiment>
FIG. 1 is a block diagram illustrating a configuration example of a modeling system including an image processing apparatus and a 3D modeling apparatus according to the first embodiment. In this modeling system, the CT apparatus 1 and the 3D modeling apparatus 40 are connected to each other via a network Nw.

  The CT apparatus 1 includes a CT gantry 10, a bed 20, and a console apparatus 30.

  The CT gantry 10 includes an X-ray tube 11, an X-ray detector 12, a rotating frame 13, an X-ray high voltage device 14, a CT control device 15, a wedge 16, a collimator 17, and a DAS 18.

  The X-ray tube 11 generates X-rays. Specifically, the X-ray tube 11 includes a vacuum tube that holds a cathode that generates thermoelectrons and an anode that generates X-rays by receiving thermoelectrons flying from the cathode. The X-ray tube 11 is connected to an X-ray high voltage device 14 via a high voltage cable. A tube voltage is applied between the cathode and the anode by the X-ray high voltage device 14. Thermionic electrons fly from the cathode toward the anode by applying the tube voltage. Tube current flows by thermionic electrons flying from the cathode toward the anode. By applying a high voltage from the X-ray high voltage device 14 and supplying a filament current, thermoelectrons fly from the cathode toward the anode, and X-rays are generated when the thermoelectrons collide with the anode. The X-rays generated in the X-ray tube 11 are formed into, for example, a cone beam shape via the collimator 17 and are irradiated to the subject P.

  The X-ray detector 12 detects X-rays generated from the X-ray tube 11 and passing through the subject P, and outputs an electrical signal corresponding to the detected X-ray dose to the DAS 18. The X-ray detector 12 has a structure in which a plurality of X-ray detection element arrays in which a plurality of X-ray detection elements are arrayed in the channel direction are arrayed in the slice direction (column direction, row direction). The X-ray detector 12 is, for example, an indirect conversion type detector having a grid, a scintillator array, and an optical sensor array. The scintillator array has a plurality of scintillators. The scintillator outputs light having a light amount corresponding to the incident X-ray dose. The grid is disposed on the X-ray incident surface side of the scintillator array and has an X-ray shielding plate that absorbs scattered X-rays. The optical sensor array converts an electrical signal corresponding to the amount of light from the scintillator. For example, a photomultiplier tube is used as the optical sensor. The X-ray detector 12 may be a direct conversion type detector (semiconductor detector) having a semiconductor element that converts incident X-rays into an electrical signal.

  The rotating frame 13 is an annular frame that supports the X-ray tube 11 and the X-ray detector 12 so as to be rotatable about the rotation axis Z. Specifically, the rotating frame 13 supports the X-ray tube 11 and the X-ray detector 12 so as to face each other. The rotating frame 13 is supported by a fixed frame (not shown) so as to be rotatable around the rotation axis Z. The X-ray tube 11 and the X-ray detector 12 are rotated about the rotation axis Z by rotating the rotation frame 13 about the rotation axis Z by the CT control device 15. The rotating frame 13 receives power from the drive mechanism of the CT control device 15 and rotates around the rotation axis Z at a constant angular velocity. An image field of view (FOV) is set at the opening of the rotating frame 13.

  In the present embodiment, the longitudinal direction of the rotation axis of the rotary frame 13 or the top plate of the bed 20 in the non-tilt state is orthogonal to the Z-axis direction and the Z-axis direction, and the axial direction that is horizontal to the floor surface is X An axial direction perpendicular to the axial direction and the Z-axis direction and perpendicular to the floor surface is defined as a Y-axis direction.

  The X-ray high voltage device 14 includes an electric circuit such as a transformer and a rectifier, and generates a high voltage to be applied to the X-ray tube 11 and a filament current to be supplied to the X-ray tube 11. And an X-ray control device that controls the output voltage in accordance with the X-rays irradiated by the X-ray tube 11. The high voltage generator may be a transformer system or an inverter system. The X-ray high voltage apparatus 14 may be provided on the rotating frame 13 in the CT gantry 10 or may be provided on a fixed frame (not shown) in the CT gantry 10.

  The wedge 16 adjusts the X-ray dose irradiated to the subject P. Specifically, the wedge 16 attenuates X-rays so that the dose of X-rays irradiated from the X-ray tube 11 to the subject P has a predetermined distribution. For example, a metal plate such as aluminum such as a wedge filter or a bow-tie filter is used as the wedge 16.

  The collimator 17 limits the irradiation range of X-rays that have passed through the wedge 16. The collimator 17 slidably supports a plurality of lead plates that shield X-rays, and adjusts the shape of the slit formed by the plurality of lead plates. The collimator 17 shapes the X-rays into, for example, a cone beam shape by limiting the X-ray irradiation range.

  The DAS 18 (Data Acquisition System) reads out an electrical signal corresponding to the X-ray dose detected by the X-ray detector 12 from the X-ray detector 12, amplifies the read-out electrical signal with a variable amplification factor, and a view period. CT raw data having a digital value corresponding to the X-ray dose over the view period is collected by integrating the electrical signal over a period of time. The DAS 18 is realized by, for example, an ASIC (Application Specific Integrated Circuit) equipped with a circuit element capable of generating CT raw data. The CT raw data is transmitted to the console device 30 via a non-contact data transmission device or the like.

  The CT control device 15 controls the X-ray high voltage device 14 and the DAS 18 in order to execute X-ray CT imaging in accordance with the control from the system control circuit 36. The CT control device 15 includes a processing circuit having a CPU (Central Processing Unit) and the like, and a driving mechanism such as a motor and an actuator. The processing circuit includes, as hardware resources, a processor such as a CPU or MPU (Micro Processing Unit) and a memory such as a ROM (Read Only Memory) or a RAM (Random Access Memory). The CT control device 15 may be realized by an ASIC, an FPGA (Field Programmable Gate Array), a CPLD (Complex Programmable Logic Device), or an SPLD (Simple Programmable Logic Device).

  The CT gantry 10 has a Rotate / Rotate-Type (third generation CT) in which an X-ray generation unit and an X-ray detection unit are integrally rotated around a subject, and a large number of X-ray detections arrayed in a ring shape. There are various types such as Stationary / Rotate-Type (fourth generation CT) in which the element is fixed and only the X-ray generation unit rotates around the subject, and any type is applicable to the present embodiment.

  The console device 30 includes a memory 31, a CT data memory 32, a display 33, an input interface 34, an image generation circuit 35, a system control circuit 36, a network interface 37, and a processing circuit 38. The memory 31, the display 33, the input interface 34, the network interface 37, and the processing circuit 38 constitute an image processing device 39. However, when the image processing apparatus is incorporated into the modality as in this embodiment, the memory 31, the display 33, the input interface 34, and the network interface 37 are used for both the processing of the console apparatus 30 and the processing of the image processing apparatus 39. Used. Data communication among the memory 31, CT data memory 32, display 33, input interface 34, image generation circuit 35, system control circuit 36, network interface 37, and processing circuit 38 is performed via a bus. Further, when the image processing apparatus is incorporated into the modality as in the present embodiment, the system control circuit 36 may be included in the processing circuit 38. However, in the present embodiment, a configuration example in which the system control circuit 36 and the processing circuit 38 are separately provided from the viewpoint of matching with the above description that the image processing apparatus may be provided separately from the modality. Says.

  The memory 31 is a storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or an integrated circuit storage device that stores various information. The memory 31 may be a drive device that reads / writes various information from / to a portable storage medium such as a CD-ROM drive, a DVD (Digital Versatile Disc) drive, or a flash memory. The storage area of the memory 31 may be in the X-ray CT apparatus 1 or in an external storage device connected by a network.

  The memory 31 stores, for example, one or more medical 3D images having a plurality of voxels indicating the organ of the subject P. For example, as shown in FIG. 2, the medical 3D image g0 includes supplementary information and medical 3D image data. The 3D image data may be called volume data. The value of each voxel constituting the medical 3D image data is obtained from the scan result of the subject. The one or more medical 3D images may include, for example, a series of images along a time series. As the medical 3D image g0, a CT image is used in the first embodiment. However, the medical 3D image g0 is not limited thereto, and a medical image corresponding to the modality in which the image processing apparatus is provided can be used as appropriate.

  Further, for example, the memory 31 stores design drawing data, CT raw data, data in the middle of processing, a display image, a control program according to the present embodiment, a table, a program for the processing circuit 38, and the like.

  The design drawing data is data created based on a medical 3D image and individually indicating two or more of the shape, hardness, density, and effective atomic number of an organ for each voxel. The “substantially every voxel” may be “a unit of about 1 to several hundreds of voxels” or a unit distance such as “a unit of 1 to several mm”. For example, when eight voxels are collected in the XYZ directions, “substantially every voxel” is a unit of 512 voxels. That is, when i, j, and k voxels are collected in the XYZ directions, “substantially every voxel” is a unit of i × j × k voxels. The “substantially voxel” may be called a voxel set. In addition, the values may be collected for each voxel by classifying and segmenting (segmenting) values in a close range instead of the number and distance of voxels. In any case, when there are a plurality of voxels included in “approximately every voxel”, it is necessary to obtain a value (representative value) for each approximately voxel. As a method for obtaining a value for each approximate voxel, for example, an extraction method for extracting a median value, a maximum value, or a minimum value from a plurality of voxel values included in “approximately each voxel”, or a value for the plurality of voxels A calculation method for calculating an average value from the above can be used as appropriate. Note that the extraction method may extract the value of a voxel having a preset relative position without being based on the value of the voxel. In this case, for example, a value may be extracted from a voxel positioned relatively at the center among a plurality of voxels included in “approximately every voxel”. On the other hand, when there is one voxel included in “substantially for each voxel”, it is not necessary to execute the extraction method and the calculation method described above. The design drawing data may be created so as to include, for example, one or more of three images individually indicating hardness, density, and effective atomic number for each voxel. For example, as shown in FIG. 3, the first image g <b> 1 indicating the hardness includes incidental information and 3D image data. The value for each approximately voxel constituting the 3D image data of the first image g1 indicates the hardness. Here, “hardness” is an index corresponding to a deformation rate with respect to pressure, and may be read as “softness”. As such an index of “hardness”, for example, elastic modulus, flexibility, strength, hardness (hardness), toughness, and the like can be used as appropriate. The elastic modulus is, for example, Young's modulus or Poisson's ratio. The strength indicates, for example, rigidity, tensile strength, compressive strength, shear strength, and the like. The hardness as hardness indicates, for example, Vickers hardness, Brinell hardness, Rockwell hardness, Shore hardness, Knoop hardness, Mohs hardness, and the like. Toughness refers to the work load, tenacity, brittleness (brittleness), etc. for material destruction. Such design drawing data is obtained by calculating the value of each voxel (representative value) from a medical 3D image and then obtaining the value of an index (hardness, density, effective atomic number) from the value for each approximate voxel. , May be created. Alternatively, the design drawing data obtains a value (representative value) for each voxel from the value of each voxel index after obtaining the value of each voxel (hardness, density, effective atomic number) of the medical 3D image. It may be created.

  Similarly, as shown in an example in FIG. 4, the second image g <b> 2 indicating the density includes incidental information and 3D image data. The value for each approximately voxel constituting the 3D image data of the second image g2 indicates the density.

  Similarly, as shown in FIG. 5, the third image g <b> 3 showing the effective atomic number includes incidental information and 3D image data. The value for each approximately voxel constituting the 3D image data of the third image g3 indicates an effective atomic number (Zeff).

  Further, as illustrated in FIG. 6, the above-described medical 3D image may be used as the fourth image g4 indicating the shape. Alternatively, as shown in FIG. 7, an STL file corresponding to one of the aforementioned medical 3D images may be used as the information g4i indicating the shape. Supplementally, the design drawing data may be created so as to include the fourth image g4 or the information g4i. As shown in FIG. 8, the design drawing data of the first embodiment is created so as to include the first image g1 and the fourth image.

  For example, the memory 31 may store the specification of the 3D modeling apparatus 40 that is the output destination of the design drawing data. The specifications of the 3D modeling apparatus 40 are received from the 3D modeling apparatus 40 via the network interface 37 and written into the memory 31 from the processing circuit 38. The specification of 3D modeling apparatus 40 here means the index applicable to modeling of 3D modeling thing among hardness, density, and effective atomic number.

  The CT data memory 32 is a storage device that stores the CT raw data transmitted from the CT gantry 10. The CT data memory 32 is a storage device such as an HDD, SSD, or integrated circuit storage device.

  The display 33 displays various information under the control of the system control circuit 36 and the processing circuit 38. For example, the display 33 outputs display data of a medical 3D image in the memory 31, GUI (Graphical User Interface) for receiving various operations from the user, and the like. As the display 33, for example, a CRT display, a liquid crystal display, an organic EL display, an LED display, a plasma display, or any other display known in the art can be used as appropriate.

  The input interface 34 receives various input operations from the user, converts the received input operations into electric signals, and outputs them to the system control circuit 36 and the processing circuit 38. For example, the input interface 34 is a collection condition for collecting CT raw data, a reconstruction condition for reconstructing a medical 3D image, a condition for generating design drawing data from a medical 3D image, and the 3D modeling apparatus 40. A design drawing data output command or the like is received from the user. As the input interface 34, for example, a mouse, a keyboard, a trackball, a switch, a button, a joystick, a touch pad, a touch panel display, and the like can be used as appropriate. In the present embodiment, the input interface 34 is not limited to a physical operation component such as a mouse, keyboard, trackball, switch, button, joystick, touch pad, and touch panel display. For example, an example of the input interface 34 includes an electric signal processing circuit that receives an electric signal corresponding to an input operation from an external input device provided separately from the apparatus and outputs the electric signal to the processing circuit 38. .

  The image generation circuit 35 performs a reconstruction process based on the protocol at the time of the main scan and the CT raw data transmitted from the CT gantry 10, and a medical 3D image (CT that represents the spatial distribution of CT values related to the subject P. Image). The protocol at the time of the main scan indicates, for example, a single energy CT scan or a dual energy CT scan. As the image reconstruction algorithm, an existing image reconstruction algorithm such as an FBP (filtered back projection) method or a successive approximation reconstruction method may be used. The image generation circuit 35 performs various image processes on the generated medical 3D image. For example, the image generation circuit 35 performs 3D image processing such as volume rendering, surface volume rendering, pixel value projection processing, MPR (Multi-Planer Reconstruction) processing, and CPR (Curved MPR) processing on a medical 3D image for display. Generate an image. The generated medical 3D image and display image are stored in the memory 31.

  The system control circuit 36 reads out the control program in the memory 41 based on the input operation received from the user via the input interface 34 and develops it on the memory in the processing circuit 38, and X-rays according to the developed control program. Each part of the CT apparatus 1 is controlled. For example, the system control circuit 36 controls the CT gantry 10 and the bed 20 synchronously in order to perform CT imaging during a main scan such as a single energy CT scan or a dual energy CT scan. The system control circuit 36 can execute a positioning scan by the CT gantry 10. The system control circuit 36 controls the CT gantry 10 and the bed 20 synchronously for positioning scanning. Further, the system control circuit 36 displays a display image or the like on the display 33 in accordance with the processing of the image generation circuit 35.

  The network interface 37 is a circuit for connecting the image processing device 39 in the console device 30 to the network Nw and communicating with the 3D modeling device 40. As the network interface 37, for example, a network interface card (NIC) can be used. In the following description, description that the network interface 37 is interposed in the communication between the image processing device 39 and the 3D modeling device 40 is omitted.

  The processing circuit 38 controls the operation of the image processing device 39 according to the electric signal of the input operation output from the input interface 34. For example, the processing circuit 38 includes, as hardware resources, a processor such as a CPU, MPU, or GPU (Graphics Processing Unit) and an (internal) memory such as a ROM or RAM. The processing circuit 38 reads out a program from the memory 31, for example, and executes an acquisition function 381, a creation function 382, and an output function 383 by a processor that executes the program loaded in the (internal) memory. Each function may include a display control function for displaying data related to processing on the display 33. Moreover, each function is an example, and it is sufficient if the functions are the same as a whole. Therefore, all the functions may be combined into one function, or may be distributed and implemented in smaller functions.

  Here, the acquisition function 381 is a function for acquiring a medical 3D image. For example, the acquisition function 381 acquires a medical 3D image from another modality (not shown) or an image server via the network Nw and stores it in the memory 31. In the present embodiment, the acquisition function 381 is not used.

  As shown in FIG. 2, the creation function (creation unit) 382 generates two or more of the organ shape, hardness, density, and effective atomic number individually for each voxel based on the medical 3D image g0. This is a function for creating the design drawing data shown.

  For example, the creation function 382 may create design drawing data so as to include one or more of three images g1 to g3 that individually indicate the hardness, density, and effective atomic number for each voxel.

  In addition, for example, when one or more medical 3D images include a series of images along a time series, the creation function 382 calculates a deformation amount associated with a periodic motion of the organ based on the series of images. By measuring, the first image g1 indicating the hardness may be obtained, and the design drawing data may be created so as to include the first image g1. When the organ is a blood vessel, for example, the creation function 382 corrects the motion by extracting the blood vessel from the time-series CT image, measures the deformation amount in the time direction of the cross-sectional area of the blood vessel, and uses structural analysis to analyze the blood vessel. The first image g1 may be generated by estimating the hardness and including the estimated value in the voxel. As the amount of deformation, for example, the amount of deformation of an organ placed in an organ or a human body accompanying an exercise such as a heartbeat can be used. Specifically, for example, as the deformation amount, a deformation amount, a motion amount (variation amount), a cross-sectional area variation amount, hardness, stiffness, and the like can be used as appropriate.

  Specifically, the creation function 382 builds a dynamic model based on time-series CT images, performs structural fluid analysis on the blood vessels of the heart using the dynamic model, and accurately determines mechanical indices in the blood vessels. The first image g1 may be generated by calculating and including the calculated value in the voxel. A known method may be used to calculate the mechanical index based on such time-series CT images. The mechanical index means a mechanical index related to the blood vessel wall. Examples of the mechanical index related to the blood vessel wall include an index related to the displacement of the blood vessel wall, an index related to the stress and strain generated in the blood vessel wall, an index related to the distribution of internal pressure applied to the blood vessel lumen, and a material property representing the hardness of the blood vessel. Classified into indicators. Examples of the index relating to the material characteristics representing the hardness of the blood vessel include an average slope of a curve indicating the relationship between the stress and strain of the blood vessel tissue. The dynamic model is a numerical model for expressing the behavior of blood vessels and blood. The mechanical model has different types depending on the method of structural fluid analysis. For example, the dynamic model is classified into a continuum dynamic model and a simple dynamic model. The continuum mechanical model is used, for example, in a finite element method (FEM) or a boundary element method. The simple dynamic model is classified into, for example, a material dynamic model based on material dynamics and a hydrodynamic model based on rheology. Note that the type of the dynamic model is not particularly limited unless otherwise specified in the following description.

  In addition, when the medical 3D image g0 includes a CT image, the creation function 382 obtains a second image g2 indicating the density based on the CT image, and the design drawing data so as to include the second image g2. You may create it. In order to calculate the density from the CT image, a known technique using spectrum CT capable of energy discrimination may be used.

  Similarly, when the medical 3D image g0 includes a CT image, the creation function 382 obtains a third image g3 indicating an effective atomic number based on the CT image, and is designed to include the third image g3. You may create figure data. In order to calculate the effective atomic number from the CT image, a known method using spectrum CT capable of energy discrimination may be used.

  The creation function 382 may create design drawing data so as to include one of the medical 3D images g0 as the fourth image g4 indicating the shape. Alternatively, the creation function 382 may create design drawing data so as to include an STL file corresponding to one of the medical 3D images as the information g4i indicating the shape. An STL (Standard Triangulated Language) file is widely used in the field of 3D printers, and has a data structure in which a shape is approximately expressed by a set of minute triangles called facets. The STL file includes normal vector data and coordinates of vertices of triangles for each facet. Since the shape can be understood from other images g1 to g3, the fourth image g4 and the information g4i indicating the shape may be omitted.

  In addition, when the memory 31 further stores the specification of the 3D modeling apparatus that is the output destination of the design drawing data, the creation function 382 may create the design drawing data so as to conform to the specification. This specification is received from the 3D modeling apparatus 40 by the creation function (communication unit) 382 communicating with the 3D modeling apparatus 40 via the network interface 37 before creating the design drawing data. The specification may be written in the memory 31.

  Such a creation function 382 may create design drawing data triggered by the input of a request including the output destination of the design drawing data. As an output destination of design drawing data, for example, the 3D modeling apparatus 40 or a simulation apparatus (not shown) can be used as appropriate. As the output destination 3D modeling apparatus 40, an arbitrary 3D printer such as a metal printer, an organic printer, or an inorganic printer is applicable.

  The output function (output unit) 383 is a function for outputting the created design drawing data. For example, the output function 383 outputs the design drawing data toward the output destination. As described above, the output destination is, for example, the 3D modeling apparatus 40 or the simulation apparatus (not shown) designated by the request input through the input interface.

  The acquisition function 381, the creation function 382, and the output function 383 may be implemented by the processing circuit 38 for a single substrate, or may be implemented by being distributed by the processing circuits 38 for a plurality of substrates. Similarly, although the console device 30 has been described as performing a plurality of functions with a single console, a plurality of functions may be performed by separate consoles.

  On the other hand, as illustrated in FIG. 9, the 3D modeling apparatus 40 includes a memory 41, a processing circuit 42, a modeling unit 43, and a network interface 44. The 3D modeling apparatus 40 may be referred to as a “3D printer”.

  The memory 41 is a storage device such as an HDD, an SSD, or an integrated circuit storage device that stores various information. The memory 41 stores, for example, design drawing data, data being processed, programs and tables according to the present embodiment.

  The processing circuit 42 controls the operation of the modeling unit 43 according to the command or data received via the network Nw. For example, the processing circuit 38 includes, as hardware resources, a processor such as a CPU, MPU, or GPU (Graphics Processing Unit) and a memory such as a ROM or RAM. The processing circuit 42 can execute the communication function 421 and the control function 422 by a processor that executes a program loaded in the memory.

  The communication function 421 is a function for executing communication between the image processing apparatuses 39 via the network interface 44. The communication function 421 receives design drawing data from the image processing apparatus 39 and writes it in the memory 41. Further, the communication function may transmit the specification of the 3D modeling apparatus 40 to the image processing apparatus 39 based on a request from the image processing apparatus 39.

  The control function 422 controls the modeling unit 43 based on the design drawing data received by the communication function 421. For example, the control function 422 divides the 3D image included in the design drawing data into a plurality of cross-sectional images corresponding to the thickness of each layer when 3D modeling is performed, and sequentially obtains each of the obtained cross-sectional images. The operation of the modeling unit 43 is controlled by sending it to 43. The control function 422 may be provided in the modeling unit 43.

  The modeling unit 43 is a known device for manufacturing a 3D modeled object. The modeling unit 43 only needs to be able to model a 3D model. For example, a hot melt lamination method (FDM), an ink jet method (material jetting method), a powder fixing method (SLS / SLM), and an optical modeling method (SLA). Any of these may be used. The modeling unit 43 models a 3D model according to control from the processing circuit 42. The modeling unit 43 may be read as another name such as “modeling mechanism unit” or “3D printing unit”.

  The network interface 44 is a circuit for connecting the 3D modeling apparatus 40 to the network Nw and communicating with the image processing apparatus 39. As the network interface 44, for example, a network interface card (NIC) can be used. In the following description, a description that the network interface 44 is interposed in communication between the 3D modeling apparatus 40 and the image processing apparatus 39 is omitted.

  Next, operation | movement of the modeling system comprised as mentioned above is demonstrated using the flowchart of FIG.

  First, the CT apparatus 1 executes CT imaging after positioning imaging of the subject P according to the scan plan, and generates a 3D medical image of the subject along a time series. The 3D medical image is stored in the memory 31.

  Next, in step ST1, in the image processing apparatus 39 in the CT apparatus 1, the input interface 34 is operated by the user, and a request including the output destination of the design drawing data is input.

  After step ST1, in step ST2, the creation function 382 of the processing circuit 38 creates design drawing data triggered by the input of the request. However, before that, the creation function 382 performs an inquiry request for requesting the specification of the 3D modeling apparatus 40 by executing communication with the 3D modeling apparatus 40 via the network interface 37. 40.

  After step ST2, in step ST3, the creation function 382 receives the specification from the 3D modeling apparatus 40 and writes the specification in the memory 31.

  After step ST3, the creation function 382 reads a medical 3D image from the memory 31 in steps ST4 to ST5. The creation function 382 creates design drawing data based on the medical 3D image so as to conform to the specification stored in the memory 31. For example, when the medical 3D image includes a series of images along a time series, the creation function 382 calculates the deformation amount associated with the periodic movement of the organ based on the series of images. By measuring, the 1st image g1 which shows hardness is obtained. In addition, the creation function 382 sets one of the series of medical 3D images g0 as the fourth image g4 indicating the shape. Thereafter, the creation function 382 creates design drawing data including a first image g1 indicating hardness and a fourth image g4 indicating shape. Note that the STL file indicating the shape may be included in the design drawing data without including the fourth image g4 indicating the shape.

  After step ST5, in step ST6, the output function 383 outputs the created design drawing data to the 3D modeling apparatus 40 that is the output destination in the request input in step ST1.

  After step ST6, in step ST7, the communication function 421 of the 3D modeling apparatus 40 receives the design drawing data from the image processing apparatus 39 and writes it in the memory 41.

  After step ST7, in step ST8, the control function 422 controls the modeling unit 43 based on the design drawing data. The modeling unit 43 models a 3D modeled object based on the design drawing data under the control of the control function 422.

  As described above, according to the present embodiment, one or more medical 3D images having a plurality of voxels indicating the organ of the subject are stored. Based on the medical 3D image, design drawing data indicating two or more of the shape, hardness, density, and effective atomic number of the organ is shown for each approximately voxel individually. Output blueprint data. Thereby, the softness of the organ can be accurately reproduced in a unit (substantially voxel unit) smaller than the anatomical portion.

  Here, according to the present embodiment, for example, the design drawing data can be created so as to include two images individually showing the shape and hardness of the organ for each substantially voxel. Thereby, the softness of the organ can be accurately reproduced in a small unit corresponding to the shape and hardness of the organ.

  In addition, according to the present embodiment, for example, based on a series of images along a time series, by measuring the amount of deformation accompanying the periodic movement of the organ, a first image showing hardness is obtained, Blueprint data can be created to include the first image. Further, according to the present embodiment, for example, the design drawing data can be created so as to include one of the medical 3D images as the fourth image indicating the shape. However, this embodiment is not limited to the two indices (hardness and shape) used in the description, and as described above, a design diagram showing any two or more of the shape, hardness, density, and effective atomic number It is possible to obtain the same effect by implementing the method so as to create data. The same applies to the following embodiments and modifications.

  Further, according to the present embodiment, when the memory further stores the specification of the 3D modeling apparatus that is the output destination of the design drawing data, the design drawing data can be created so as to conform to the specification. Thereby, creation of design drawing data that does not conform to the specifications of the 3D modeling apparatus can be prevented.

  Further, according to the present embodiment, it is possible to create design drawing data triggered by the input of a request including the output destination of the design drawing data, and output the drawing drawing data to the output 3D modeling apparatus. Thereby, design drawing data can be output to a desired 3D modeling apparatus.

<Second Embodiment>
Next, a modeling system including the image processing apparatus and the 3D modeling apparatus according to the second embodiment will be described. The overall configuration of the modeling system is as shown in FIG.

  Compared to the first embodiment, the second embodiment has a data creation function 423 for creating 3D modeling data from the design drawing data in the processing circuit 42 of the 3D modeling apparatus 40, as shown in FIG. It has been added. Along with this, other configurations in the 3D modeling apparatus 40 are also slightly changed.

  For example, for each index value of the organ (modeling object) of the subject, the memory 41 has a mixing ratio of the material that approximately represents the index, and a value of the index of the 3D modeling object obtained from the mixing ratio. And the difference between the index value of the organ and the organ. Specifically, the organ of the subject is a real organ, the indices are hardness, density, and effective atomic number, and the material is resin. At this time, the memory 41 stores a first table T1 related to hardness, a second table T2 related to density, and a third table T3 related to effective atomic number, as shown in FIG. 12 to FIG. Note that the memory 41 does not need to store the three tables T1 to T3, and may store two or more tables.

  The first table T1 stores the hardness, the resin mixing ratio, and the difference from the actual hardness in association with each other. Here, the “hardness” in the left column corresponds to the “hardness” shown in the design drawing data. The “resin mixing ratio” in the center column indicates the resin mixing ratio that approximately represents the “hardness” in the left column. The “difference from actual hardness” in the right column indicates “the difference between the hardness of the 3D object obtained from the mixing ratio and the hardness of the organ (hardness of the actual object)”. Here, the hardness of the real object can be estimated from the medical image in advance by, for example, a method of estimating the hardness of the organ from the elastography image. The hardness of the 3D structure can be calculated from the mixing ratio, for example, as shown in the following (i) to (ii).

  (I) The hardness when each of the plurality of resins is individually printed is experimentally acquired. There are as many hardnesses as there are resins.

  (Ii) The hardness when printing is performed by mixing a plurality of resins is weighted and added using the mixing ratio for the hardness of each resin obtained in (i) above.

  Here, by subtracting the calculated hardness of the 3D object from the estimated actual hardness, the “difference from the actual hardness” in the right column can be calculated.

  The second table T2 stores the density, the resin mixing ratio, and the difference from the actual density in association with each other. Here, “density” in the left column corresponds to “density” shown in the design drawing data. The “resin mixing ratio” in the center column indicates the resin mixing ratio that approximately represents the “density” in the left column. “Difference with actual density” in the right column indicates “difference between density of 3D object and organ density (real density) obtained from the mixing ratio”.

  The third table T3 stores the effective atomic number, the mixing ratio of the resin, and the difference from the actual effective atomic number in association with each other. Here, the “effective atomic number” in the left column corresponds to the “effective atomic number” indicated in the design drawing data. The “resin mixing ratio” in the center column indicates the resin mixing ratio that approximately represents the “effective atomic number” in the left column. The “difference from the effective atomic number of the actual object” in the right column indicates “the difference between the effective atomic number of the 3D object obtained from the mixture ratio and the effective atomic number of the organ (effective effective atomic number of the actual object)” Yes.

  Supplementally, for example, when the resin mixing ratio is determined so that the density of the 3D object is close to the density of the actual organ, the resin mixing ratio is determined to be “the density is actually close”. In that case, other parameters such as the effective atomic number and hardness of the 3D object are separated from the actual organ. In this case, the “difference from the actual density” decreases, while the “difference from the actual hardness” and the “difference from the actual effective atomic number” increase. Similarly, when the mixing ratio of the resin is determined so that the effective atomic number of the 3D object is close to the actual effective atomic number of the actual organ, the “difference from the effective atomic number of the actual object” becomes smaller, “Difference with actual hardness” and “Difference with actual density” increase. Depending on the application of the 3D object, the resin mixing ratio may be set so that the difference between the two parameters is reduced.

  For example, when a user wants to model a 3D model with a small “difference from actual hardness” for surgical practice, etc., the resin mixing ratio is determined so that the “hardness” is close to the actual model. The difference between the effective atomic number and the actual density is allowed to increase. On the other hand, when the user wants to model a “3D model that can capture an X-ray image close to the actual object”, a resin that has a small “difference from the effective atomic number of the actual object” and “difference from the actual density”. It is also possible to accept that the “difference from the actual hardness” becomes large.

  Alternatively, the processing circuit 42 compares the difference in the memory for each voxel with respect to each of the hardness, density, and effective atomic number individually indicated by one or more images, and based on the comparison result, the minimum The value of hardness, density, or effective atomic number corresponding to the difference of may be selected for each voxel.

  As described above, the hardness, density, or effective atomic number may be selected by the user according to the use such as surgical practice, or may be selected by the processing circuit 42 according to the comparison result between the differences. When the user selects, the hardness, density, or effective atomic number is used as an index common to all voxels in the 3D modeling data created from the design drawing data. When the processing circuit 42 selects, three types of hardness, density, and effective atomic number are used for the 3D modeling data created from the design drawing data. For each voxel, the hardness, density, or effective atomic number is used. The value of is assigned. In the present embodiment, a case where the processing circuit 42 selects is described as an example.

  As described above, the communication function (reception unit) 421 of the processing circuit 42 uses the organ hardness, density, and effective atomic number as the three indicators of the organ, and shows the value of the indicator for each voxel for each voxel. Blueprint data including two or more of the three medical 3D images is received from the image processing device 39.

  Here, the design drawing data is data used to create 3D modeling data for outputting a desired 3D modeling object from the 3D modeling apparatus 40. As shown in FIG. 15, the design drawing data is configured by combining a plurality of medical 3D images. The medical 3D image is expressed as a set of cubic voxels, and an index value at the position in the 3D space is assigned to each voxel. For example, the second image g2 is an image representing the spatial distribution of the density of the 3D object, and a density value is assigned as an index value for each voxel. Similarly, the third image g3 is an image representing the distribution of effective atomic numbers of the 3D structure, and a value of “Zeff” is assigned as an index value for each voxel. Which type of index value is assigned to which image is defined by the accompanying information attached to each image. In the present embodiment, an example in which different types of index values are assigned to each image has been shown. However, the design drawing data is not limited to this example. For example, the design drawing data may be configured as one medical 3D image, and a plurality of types of index values such as density and effective atomic number may be individually assigned to substantially each voxel of one medical 3D image. The data structure of the design drawing data includes a plurality of incidental information and a plurality of medical 3D images, and is used for comparison processing, selection processing, and creation processing by the data creation function 423 of the 3D modeling apparatus 40. The plurality of incidental information individually defines the index when the organ index of the subject is two or more of the hardness, density, and effective atomic number of the organ. In the plurality of medical 3D images, the accompanying information is individually attached, and the value of the index is indicated for each voxel. In the comparison process, the data creation function (comparison unit) 423 of the 3D modeling apparatus 40 calculates the difference between the index value of the 3D model and the index value of the actual organ for each voxel for each medical 3D image. This is a process of obtaining and comparing differences at the same position of each medical 3D image. The selection process is based on the result of the data creation function (selection unit) 423 of the 3D modeling apparatus 40 comparing the differences by the comparison process, and the smallest of the index values at the same position of each medical 3D image is selected. This is a process of selecting an index value corresponding to the difference. In the creation process, the data creation function (creating unit) 323 of the 3D modeling apparatus 40 creates a new 3D image using the value of the index selected by the selection process as the value of the approximate voxel at the same position. It is a process which has a 3D image and creates 3D modeling data for modeling a 3D modeled object.

  In this way, the 3D modeling data selects the index value corresponding to the smallest difference from the index values at the same position of each medical 3D image in the design drawing data, and the selected index value is set. It is created by creating a new 3D image with the value of the approximate voxel at the same position. When 3D modeling data is formed in order from the bottom layer, 3D modeling data uses cross-sectional images from the bottom layer to the top layer that can be extracted from the 3D image. It is done.

  For example, as shown in FIGS. 16 and 17, the 3D modeling data dp has a value of an index (density or Zeff) of a smaller difference among a plurality of indices (density and Zeff) in the design drawing data approximately voxel. Includes every. Here, FIG. 16 shows a relationship between 3D image data of the 3D modeling data dp and cross-sectional images from the lowest layer L_1 to the highest layer L_n that can be extracted from the 3D image data. FIG. 16 shows the value of the selected index for each of approximately voxels at a plurality of positions (five places in the drawing) of the 3D image data. FIG. 17 shows the value of the selected index for each of approximately voxels at a plurality of positions (nine in the drawing) regarding the cross-sectional image of the i-th layer L_i from the lowest layer of the 3D modeling data dp. As shown in FIGS. 16 and 17, the 3D modeling data dp includes an index value of a smaller difference for each approximately voxel of each layer. Note that the 3D image in the 3D modeling data is not limited to the case where the index value corresponding to the minimum difference is included for each voxel, but may include the resin mixing ratio corresponding to the minimum difference for each approximately voxel. .

  The control function 422 is the same as that of the first embodiment.

  The data creation function 423 is a function for executing the comparison process, the selection process, and the creation process. Note that the data creation function 423 may be implemented in a distributed manner, for example, a comparison function that executes comparison processing, a selection function that executes selection processing, and a creation function that executes creation processing.

  Other configurations are the same as those of the first embodiment.

  Next, the operation of the modeling system configured as described above will be described using the flowcharts of FIGS.

  First, the CT apparatus 1 executes CT imaging after positioning imaging of the subject P, for example, according to a scan plan showing a dual energy CT scan, and generates a 3D medical image (CT image) of the subject. The 3D medical image is stored in the memory 31.

  Next, in step ST11, in the image processing apparatus 39 in the CT apparatus 1, the input interface 34 is operated by the user, and a request including the output destination of the design drawing data is input.

  After step ST11, in step ST12, the creation function 382 of the processing circuit 38 starts creation of design drawing data triggered by the input of the request. The creation function 382 reads a CT image that is a medical 3D image from the memory 31.

  After step ST12, in step ST13, the creation function 382 obtains a second image g2 indicating the density for each voxel based on the CT image. In addition, the creation function 382 obtains a third image g3 indicating the effective atomic number for each voxel based on the CT image. Thereafter, the creation function 382 creates design drawing data so as to include the second image g2 and the third image g3.

  After step ST13, in step ST14, the output function 383 outputs the created design drawing data to the 3D modeling apparatus 40 that is the output destination in the request input in step ST1.

  After step ST14, in step ST21, the communication function 421 of the 3D modeling apparatus 40 receives the design drawing data from the image processing apparatus 39 and writes it in the memory 41.

  After step ST21, in step ST22, the data creation function 423 calculates the index value of the 3D object and the index value of the organ for each voxel for each identification information included in the incidental information of the design drawing data. Compare the differences. Specifically, the data creation function 423 performs the “difference from the actual density” corresponding to the “density” value of the second table T2 and the “effective” of the third table T3 for each of the substantially same voxels. The value of “difference from effective atomic number of actual object” corresponding to the value of “atomic number” is compared.

  After step ST22, in step ST23, the data creation function 423 selects an index value corresponding to the minimum difference based on the comparison result.

  After step ST23, in step ST24, based on the selected result, the data creation function 423 performs 3D modeling for modeling a 3D model so as to include a mixture of index values corresponding to different identification information. Create data.

  After step ST24, in step ST25, the data creation function 423 determines whether the creation of 3D modeling data has been completed based on whether or not the comparison has been completed for each of the substantially voxels. If the result of determination is no, the process returns to step ST22 and continues processing. As a result of the determination, if the creation of the 3D modeling data is completed, the process proceeds to step ST26.

  After step ST25, in step ST26, the control function 422 controls the modeling unit 43 based on the design drawing data. The modeling unit 43 models a 3D modeled object based on the design drawing data under the control of the control function 422.

  As described above, according to the present embodiment, in the 3D modeling apparatus, design drawing data of three images each indicating the hardness, density, and effective atomic number for each voxel are received from the image processing apparatus. For each of the hardness, density, and effective atomic number individually indicated by one or more images, the difference in the memory is compared for each voxel. Based on the comparison result, the hardness, density or effective atomic number corresponding to the smallest difference is selected. Based on the selected result, 3D modeling data for modeling an organ 3D modeling object for each voxel is created.

  As described above, since the 3D modeling data that selectively includes the index value corresponding to the smallest difference among the plurality of index values is created, in addition to the effects of the first embodiment, more accurately the organ Softness can be reproduced.

<Third Embodiment>
FIG. 20 is a block diagram illustrating a configuration example of a modeling system including an image processing device and a 3D modeling device according to the third embodiment.

  The third embodiment is a modification of the first or second embodiment, and the image processing apparatus 50 is provided separately from the modality. Accordingly, in the CT apparatus 1a, the functions 381 to 383 of the processing circuit 38 are omitted as compared with the configuration shown in FIG.

  In the modeling system shown in FIG. 20, the 3D modeling apparatus 40, the image processing apparatus 50, the CT apparatus 1a, the MRI apparatus 60, the ultrasonic diagnostic apparatus 70, and the X-ray angio apparatus 75 described above are connected to each other via a network Nw. . As a modeling system, if the image processing apparatus 50 can acquire a medical 3D image offline or the like, modalities such as the CT apparatus 1a, the MRI apparatus 60, the ultrasonic diagnostic apparatus 70, and the X-ray angio apparatus 75 (medical image diagnosis). (Apparatus) may be omitted.

  Here, the image processing apparatus 50 includes a memory 51, a display 52, an input interface 53, a network interface 54, and a processing circuit 55, as shown in FIG. The processing circuit 55 executes an acquisition function 551, a creation function 552, and an output function 553 by a processor that executes a program loaded in the memory.

  The configurations of the memory 51, the display 52, the input interface 53, the network interface 54, and the processing circuit 55 are the same as those of the memory 31, the display 33, the input interface 34, the network interface 37, and the processing circuit 38 described above. The acquisition function 551, the creation function 552, and the output function 553 are the same functions as the acquisition function 381, the creation function 382, and the output function 383 described above.

  The CT apparatus 1a irradiates the subject with X-rays from the X-ray tube, detects the irradiated X-rays with an X-ray detector, and relates to the subject based on the output from the X-ray detector A medical 3D image (CT image) is generated. The CT apparatus 1a stores the generated medical 3D image in a memory (not shown) and transmits it to the image processing apparatus 50 in response to a transmission request or the like. As such a CT apparatus 1a, spectrum CT, dynamic CT, and traditional CT can be used as appropriate.

  The MRI apparatus 60 excites a nuclear spin of a subject placed in a static magnetic field with a radio frequency (RF) signal having a Larmor frequency, and reconstructs a magnetic resonance signal generated from the subject upon excitation. A medical 3D image (MR image) is generated. The MRI apparatus 60 stores the generated medical 3D image in a memory (not shown) and transmits it to the image processing apparatus 50 in response to a transmission request or the like. As such an MRI apparatus 60, a conventional MR can be used as appropriate.

  The ultrasonic diagnostic apparatus 70 radiates an ultrasonic pulse from the vibration element in the ultrasonic probe into the subject, converts a reflected wave from the subject into an electric signal by the vibration element, and based on the electric signal. A medical 3D image (UL elastography image) is generated. The ultrasonic diagnostic apparatus 70 stores the generated medical 3D image in a memory (not shown) and transmits it to the image processing apparatus 50 in response to a transmission request or the like.

  The X-ray angio device 75 collects projection data of the subject from multiple directions while revolving the X-ray tube and the X-ray detector arranged opposite to the arm around the subject, and reconstructs the projection data. Similarly to the CT apparatus 1a, a medical 3D image can be generated. The medical 3D image may be called a CBCT (Cone Beam CT) image. The X-ray angio device 75 stores the generated medical 3D image in a memory (not shown) and transmits it to the image processing device 50 in response to a transmission request or the like.

  Next, operation | movement of the modeling system comprised as mentioned above is demonstrated using the flowchart of FIG.

  First, it is assumed that each modality such as the CT apparatus 1a, the MRI apparatus 60, the ultrasonic diagnostic apparatus 70, and the X-ray angio apparatus 75 stores a medical 3D image generated by scanning a subject.

  Next, in step ST31, in the image processing apparatus 50, the user operates the input interface 53, and a request including an output destination of the design drawing data is input.

  After step ST31, in step ST32, the acquisition function 551 of the processing circuit 55 transmits a request for acquiring a medical 3D image to a plurality of modalities via the network interface 54 when the request is input. This acquisition request is transmitted to the CT apparatus 1a and the MRI apparatus 60, for example.

  After step ST32, in step ST33, the acquisition function 551 receives medical 3D images from the CT apparatus 1a and the MRI apparatus 60, and writes the medical 3D images in the memory 51.

  After step ST33, in step ST34, the acquisition function 551 executes alignment processing between the written medical 3D images as preprocessing for creating design drawing data. The registration process is also called a registration process, and the positions of the images are set so that the anatomical positional relationship between the images obtained in the same imaging target and in different imaging situations is the same. This is a process for aligning (and a coordinate system assigned to an image). “Different imaging situations” here means imaging situations under different conditions using the same modality, or imaging situations using different modalities. Note that, in the case of images obtained in the same imaging situation as in the first embodiment, alignment processing is not necessary. As registration processing, rigid registration and non-rigid registration can be used as appropriate. Rigid registration is, for example, a process of comparing the shapes of two images and performing rotation, translation, and enlargement / reduction of one image so that the shapes of the two images match. Non-rigid registration is, for example, a process of comparing the shapes of two images and distorting one image so that the shapes of the two images match. When the alignment process is completed, the acquisition function 551 writes the medical 3D image after the alignment process in the memory 51.

  After step ST34, in step ST35, the creation function 552 creates design drawing data based on the medical 3D image after the alignment processing in the memory 51. For example, when the medical 3D image acquired from the MRI apparatus 60 includes a series of images along a time series, the creation function 552 generates a deformation amount due to the periodic motion of the organ based on the series of images. Is measured to obtain a first image g1 indicating the hardness. Alternatively, the creation function 552 obtains a first image g1 indicating hardness based on a medical 3D image (elastography image) acquired from the ultrasound diagnostic apparatus 70. Further, the creation function 552 obtains a second image g2 indicating density (or a third image g3 indicating effective atomic number) from the medical 3D image (CT image) acquired from the CT apparatus 1a. Alternatively, the creation function 552 obtains the third image g3 indicating the effective atomic number from the medical 3D image (MR image) acquired from the MRI apparatus 60. Further, the creation function 552 obtains a fourth image g4 indicating the shape from the medical 3D image acquired from the X-ray angio apparatus 75.

  That is, when creating the design drawing data, the creation function 552 extracts parameters of a type that is good at measurement from the medical 3D image of each modality. For example, shape data is acquired from a medical 3D image of the X-ray angio device 75, hardness information is acquired from a CT image or an elastography image, and an effective atomic number is acquired from an MR image. Thereby, the creation function 552 creates design drawing data including a plurality of arbitrary images among the first image g1 to the fourth image g4.

  In the example of this embodiment, the creation function 552 creates design drawing data including a first image g1 indicating hardness and a second image g2 indicating density.

  After step ST35, in step ST36, the output function 553 outputs the created design drawing data to the 3D modeling apparatus 40 that is the output destination in the request input in step ST31.

  After step ST36, the 3D modeling apparatus 40 performs processing in the same manner as steps ST7 to ST8 described above.

  As described above, according to the present embodiment, even if the image processing apparatus is provided separately from the modality, as in the first embodiment, one or more having a plurality of voxels indicating the organ of the subject. 3D medical images are stored. Based on the medical 3D image, design drawing data indicating two or more of the shape, hardness, density, and effective atomic number of the organ is shown for each approximately voxel individually. Output blueprint data. Thereby, the softness of the organ can be accurately reproduced in a unit (substantially voxel unit) smaller than the anatomical portion.

  Supplementally, in the first embodiment, processing from storage of a medical 3D image to creation of design drawing data is executed in the modality. In contrast, in the third embodiment, processing from storage of medical 3D images to creation of design drawing data is executed in the image processing apparatus by acquiring medical 3D images from separate modalities. .

  Note that the third embodiment may be modified as shown in FIG. That is, instead of step ST32, as in steps ST2 to ST3, specifications are acquired from the 3D modeling apparatus 40 (steps ST32-1 to ST32-2), and a medical 3D image is displayed on a plurality of modalities according to the specifications. An acquisition request may be transmitted (step ST32-3). The other steps ST31 and ST33 to ST36 are the same as described above. According to such a modification, in addition to the effects of the third embodiment, creation of design drawing data that does not conform to the specifications of the 3D modeling apparatus can be prevented.

  Further, the third embodiment may be modified as shown in FIG. That is, instead of the 3D modeling apparatus 40, the design drawing data output destination may be the simulation apparatus 80 connected to the network Nw. As the simulation apparatus 80, for example, an apparatus that performs fluid analysis using CFD (computed flow dynamics) is preferable from the viewpoint of reproducing the softness of an organ. In this case, the image processing device 50 creates design drawing data from the medical 3D image acquired from each modality, and outputs the design drawing data to the simulation device 80. The simulation device 80 displays the first image g1, the second image g2, or the third image g3 included in the design drawing data, and appropriately executes a simulation process. According to such a modified example, in addition to the effects of the third embodiment, an index image that accurately reproduces the softness of the organ is displayed in units smaller than the anatomical part (substantially voxel units). be able to. In addition, improvement in simulation accuracy can be expected.

  In addition, the third embodiment and the respective modifications thereof are not limited to the first embodiment, and the effects of both the second and third embodiments can be obtained by applying the second embodiment to the second embodiment. it can.

  According to at least one embodiment described above, one or more medical 3D images having a plurality of voxels indicating the organ of the subject are stored. Based on the medical 3D image, design drawing data indicating two or more of the shape, hardness, density, and effective atomic number of the organ is shown for each approximately voxel individually. Output blueprint data. Thereby, the softness of the organ can be accurately reproduced in a unit (substantially voxel unit) smaller than the anatomical portion.

  The term “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 implements the function by reading and executing the program stored in the memory. Instead of storing the program in the memory, the program may be directly incorporated into the processor circuit. In this case, the processor realizes the function by reading and executing the program incorporated in the circuit. Each processor in each embodiment is not limited to being configured as a single circuit for each processor, but may be configured as a single processor by combining a plurality of independent circuits to realize the function. Good. Furthermore, a plurality of components shown in FIGS. 1, 9 and 21 may be integrated into one processor to realize the function.

  In addition, although some embodiment of this invention was described, these embodiment is shown as an example and is not intending limiting the range of 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 modifications thereof are included in the invention described in the claims and equivalents thereof in the same manner as included in the scope and gist of the invention.

31, 41, 51 Memory 33, 52 Display 34, 53 Input interface 37, 44, 54 Network interface 38, 42, 55 Processing circuit 381, 551 Acquisition function 382, 552 Creation function 383, 553 Output function 39, 50 Image processing device 40 3D modeling apparatus 421 Communication function 422 Control function 423 Data creation function 43 Modeling unit 80 Simulation apparatus P Subject

Claims (12)

A memory for storing one or more medical 3D images having a plurality of voxels indicative of the organ of the subject;
Based on the medical 3D image, a creation unit that creates design drawing data that individually shows two or more of the shape, hardness, density, and effective atomic number of the organ for each approximately voxel;
An image processing apparatus comprising: an output unit that outputs the design drawing data.   The said creation part creates the said blueprint data so that one or more of the three images which show the said hardness, the said density, and the said effective atomic number for every voxel separately may be included. Image processing apparatus. The one or more medical 3D images include a series of images in time series;
The creation unit obtains a first image indicating the hardness by measuring a deformation amount associated with a periodic motion of the organ based on the series of images, and includes the first image. The image processing apparatus according to claim 2, wherein the design drawing data is created. The medical 3D image includes a CT image,
The image processing apparatus according to claim 2, wherein the creation unit obtains a second image indicating the density based on the CT image and creates the design drawing data so as to include the second image. The medical 3D image includes a CT image,
The creation unit obtains a third image indicating the effective atomic number based on the CT image, and creates the design drawing data so as to include the third image. An image processing apparatus according to 1.   The image processing device according to claim 2, wherein the creation unit creates the design drawing data so as to include one of the medical 3D images as a fourth image indicating the shape.   The image processing according to claim 2, wherein the creation unit creates the design drawing data so as to include an STL file corresponding to one of the medical 3D images as information indicating the shape. apparatus. The memory further stores the specification of the 3D modeling apparatus that is the output destination of the design drawing data,
The image processing apparatus according to claim 1, wherein the creation unit creates the design drawing data so as to conform to the specification.   The image processing apparatus according to claim 8, further comprising: a communication unit that writes the specifications received from the 3D modeling apparatus into the memory by executing communication with the 3D modeling apparatus. The creation unit creates the design drawing data triggered by an input of a request including an output destination of the design drawing data,
The output unit outputs the design drawing data toward the output destination,
The output destination is a 3D modeling apparatus or a simulation apparatus.
The image processing apparatus according to claim 1. For each index value of the organ of the subject, the mixing ratio of the material that approximately represents the index, and the difference between the index value of the 3D object and the index value of the organ obtained from the mixing ratio, A memory for storing
A design drawing including two or more of three medical 3D images in which the hardness, density, and effective atomic number of the organ are used as three indicators of the organ, and the value of the indicator is indicated for each voxel for each indicator. A receiving unit for receiving data from the image processing apparatus;
For each of the medical 3D images in the design drawing data, a comparison unit that obtains a difference in the memory for each of the approximately voxels and compares the differences at the same position of each of the medical 3D images;
Based on the result of the comparison, a selection unit that selects the value of the index corresponding to the smallest difference among the values of the respective indexes at the same position;
By creating a new 3D image in which the value of the selected index is set to the value of the approximate voxel at the same position, the 3D model for modeling the 3D model of the organ having the new 3D image A creation section for creating data;
3D modeling apparatus. A data structure of design drawing data used in a 3D modeling apparatus that models a 3D model,
When the index of the organ of the subject is two or more of the hardness, density and effective atomic number of the organ, a plurality of incidental information defining the index individually,
A plurality of medical 3D images in which the accompanying information is individually attached, and the value of the index is shown for each voxel;
Including
The comparison unit of the 3D modeling apparatus obtains a difference between the index value of the 3D model and the index value of the organ for each of the approximately 3 voxels for each of the medical 3D images, and each of the medical 3D images. A comparison process for comparing differences at the same position of
A selection process in which the selection unit of the 3D modeling apparatus selects the index value corresponding to the smallest difference among the index values at the same position based on the comparison result;
The creation unit of the 3D modeling apparatus creates the new 3D image using the selected index value as the value of the approximate voxel at the same position, thereby having the new 3D image and the 3D modeling of the organ. A creation process for creating 3D modeling data for modeling an object;
Data structure of blueprint data used for.