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

Abstract

Medical image processing device (30, 300) with a processing circuit (37, 350), configured for Capturing image data that includes a patient's blood vessel, Capturing an index value regarding blood flow at each position of the blood vessel by performing a fluid analysis of a structure of the blood vessel included in the captured image data, Capturing switching information to determine a display mode of a color image, in which a value of an index relating to blood flow or a quantity dependent thereon is indicated by color information, based on the switching information, setting at least one reference value at which the color changes as an edge, Generating a result image using the set reference value for an image indicating a blood vessel of the patient, and Initiate a notification to display the result image.

Description

Cross-reference to related registrations

[0001] This application is based on and claims the priority benefit of Japanese patent application number 2016-230530, filed on November 28, 2016, and Japanese patent application number 2017-223826, filed on November 21, 2017. Area

[0002] The embodiments described herein relate to a medical image processing device, an X-ray computed tomography (CT) device and a medical image processing method. background

[0003] It is known that the causes of ischemic diseases of organs, broadly classified, include disturbances in blood circulation and functional impairment of the organ itself. For example, stenosis, which is an example of impaired blood circulation in a coronary artery, is a serious injury that leads to ischemic heart disease, and in this type of ischemic heart disease, it is necessary to determine whether to treat it with medication, a vascular prosthesis, or something similar. In recent years, a method for measuring fractional flow reversal (FOR) using a pressure line in coronary angiography (CAG) via catheter has been recommended as a diagnostic tool for assessing hematogenous ischemia in coronary arteries.

[0004] On the other hand, a method for non-invasively performing hematogenous ischemia assessment of coronary arteries using medical images of the heart acquired by a medical diagnostic imaging device, such as an X-ray CT scanner, a magnetic resonance imaging (MRI) scanner, or an ultrasound device, was also known. As described above, hematogenous ischemia assessment was performed using various methods, and treatment was implemented according to the development of these methods. In recent years, there has been a desire to determine the practical effect of the treatment before actually administering it.

[0005] WO 2014 / 084286A1 describes a medical information processing device comprising a generation unit and a display control unit. The generation unit produces display information representing the state of a first region and the state of a second region, corresponding to the coronary flow reserve of the first region in the tissue of a subject and the fractional flow reserve of the second region in a feeding vessel of the first region. The display control unit performs a control operation such that the display information produced by the generation unit is shown in a display unit in the form of a diagram.

[0006] US 2015 / 0 119 705 A1 discloses devices, systems, and methods for visually displaying a vessel and assessing the risk associated with a vessel condition. In one embodiment, a method for assessing a patient's vessel comprises obtaining physiological measurements from a first instrument and a second instrument positioned within the patient's vessel while the second instrument is moved longitudinally through the vessel from a first position to a second position and the first instrument remains stationary within the vessel; outputting the physiological measurements and an image of the vessel to a display, wherein the output image includes visualizations based on the obtained physiological measurements; and assessing whether surgical intervention should be performed based on the physiological measurements and the image of the vessel.

[0007] According to the invention, a medical image processing device, an X-ray computed tomography (CT) device and a medical image processing method as specified in the accompanying patent claims are provided. Brief description of the characters Fig. Figure 1 shows an example of a configuration of a medical image processing system according to a first embodiment; Fig. Figure 2 shows an example of a configuration of a medical image processing device according to the first embodiment; Fig. Figure 3 is a diagram illustrating an example of processing performed by an analysis function according to the first embodiment; Fig. Figure 4 is a diagram to illustrate temporal phases in a fluid analysis according to the first embodiment; Fig. Figure 5A is a diagram illustrating a calculation example of ΔFFR by the analysis function according to the first embodiment; Fig. Figure 5B is a diagram illustrating a calculation example of ΔFFR by the analysis function according to the first embodiment; Fig. Figure 5C is a diagram illustrating a calculation example of ΔFFR using the analysis functions according to the first embodiment; Fig. Figure 6A shows an example of a color image generated by a generation function according to the first embodiment; Fig. Figure 6B shows an example of a color image generated by the generation function according to the first embodiment; Fig. Figure 6C shows an example of a color image generated by the generation function according to the first embodiment; Fig. Figure 6D shows an example of a color image generated by the generation function according to the first embodiment; Fig. Figure 6E shows an example of a color image generated by the generation function according to the first embodiment; Fig. Figure 6F shows an example of a color image generated by the generation function according to the first embodiment; Fig. Figure 7A shows an example of a color image generated by the generation function according to the first embodiment; Fig. Figure 7B shows an example of a color image generated by the generation function according to the first embodiment; Fig. Figure 8A shows an example of a color image generated by the generation function according to the first embodiment; Fig. Figure 8B shows an example of a color image generated by the generation function according to the first embodiment; Fig. Figure 9A shows an example of a color image generated by the generation function according to the first embodiment; Fig. Figure 9B shows an example of a color image generated by the generation function according to the first embodiment; Fig. 10 is a flowchart showing a process of processing carried out by the medical image processing device according to the first embodiment; Fig. Figure 11 shows an example of a color image generated by a generation function according to a second embodiment; Fig. Figure 12A shows an example of the generation of a color image, which is generated by the generation function, according to the second embodiment; Fig. Figure 12B shows an example of the generation of a color image, which is generated by the generation function, according to the second embodiment; Fig. Figure 12C shows an example of the generation of a color image produced by the generation function according to the second embodiment; and Fig. Figure 13 shows an example of a configuration of an X-ray CT device according to a third embodiment. Detailed description

[0008] According to one embodiment, a medical image processing device comprises a processing circuit. The processing circuit is configured to acquire image data encompassing a patient's blood vessel. The processing circuit is configured to acquire an index value relating to blood flow at each position of the blood vessel by performing a fluid analysis of the blood vessel's structure as captured in the image data. The processing circuit is configured to acquire information specifying a display condition for the index value, as switching information for switching a display mode when the index value is displayed. The processing circuit is configured to generate a result image in which pixel values ​​reflecting the index value are assigned in a display mode according to the switching information, for an image depicting a patient's blood vessel.The processing circuit is designed to cause a display to show the resulting image.

[0009] Embodiments of a medical image processing device, an X-ray CT device, and a medical image processing method according to the present application are explained in detail below with reference to the accompanying figures. The embodiments described below are not intended to limit the medical image processing device, the X-ray CT device, and the medical image processing method according to the present application. First embodiment

[0010] First, a first embodiment is described. In the first embodiment, an application of a technique according to the present application to a medical image processing device is described.

[0011] An explanation is given below using a medical image processing system, which includes the medical image processing device, as an example. Furthermore, a case is explained below as an example, where a blood vessel of the heart is the target of analysis.

[0012] Fig. Figure 1 shows an example of a configuration of the medical image processing system according to the first embodiment. As shown in Fig. Figure 1 shows that the medical image processing system according to the first embodiment comprises an X-ray CT device 100, a storage device 201, and a medical image processing device 300.

[0013] For example, the medical image processing device 300 according to the first embodiment is connected to the X-ray CT device 100 and the image storage device 200 via a network 400, as shown in Fig. 1 shown. The medical image processing system can further be connected to another medical diagnostic imaging device, such as an MRI device and a positron emission tomography (PET) device, via the 400 network.

[0014] The X-ray CT scanner 100 collects CT image data (volume data) of a patient. Specifically, the X-ray CT scanner rotates an X-ray tube and an X-ray detector around the patient, essentially at its center, and detects X-rays passing through the patient, thereby collecting projection data. The X-ray CT scanner 100 then generates chronological, three-dimensional CT image data based on the collected projection data.

[0015] The image storage device 200 stores image data acquired by various types of medical diagnostic imaging devices. For example, the image storage device 200 is implemented by a computer device such as a server. In the present embodiment, the image storage device 200 acquires the CT image data (volume data) from the X-ray CT device 100 via the network 400 and directs a memory provided inside or outside the device to store the acquired CT image data.

[0016] The medical image processing device 300 acquires image data from various types of medical diagnostic imaging devices via the network 400 and processes the acquired image data. For example, the medical image processing device 300 is implemented by a computer device such as a workstation. In the present embodiment, the medical image processing device 300 acquires the CT image data from the X-ray CT device 100 or the image storage device 200 via the network 400 and performs various types of image processing on the acquired CT image data. The medical image processing device 300 displays the CT image data on a display or similar device before or after image processing. The medical image processing device 300 can be located in various locations.For example, the medical image processing device 300 is located in a CT room in which the X-ray CT device 100 is located, a catheterization room in which various treatments are performed using catheters, an interpretation room for interpreting images, or something similar. If the device is located in more than one place, the medical image processing device 300 is located at each location.

[0017] Fig. Figure 2 shows an example of a configuration of the medical image processing device 300 according to the first embodiment. For example, as shown in Fig. As shown in Figure 2, the medical image processing device 300 comprises a communication interface 310, a memory 320, an input interface 330, a display 340 and a processing circuit 350.

[0018] The communication interface 310 is connected to the processing circuit 350 and controls the transmission and communication of various types of data between the processing circuit 350 itself and various types of medical diagnostic imaging devices or the image storage device 200, which are connected via the network 400. For example, the communication interface 310 is implemented by a network card, a network adapter, a network interface controller (NIC), or something similar. In the present embodiment, the communication interface 310 receives the CT image data from the X-ray CT device 100 or the storage device 200 and outputs the received CT image data to the processing circuit 350.

[0019] Memory 320 is connected to processing circuit 350 and stores various types of data. For example, memory 320 is implemented by a semiconductor storage device such as main memory (RAM) and flash memory, a hard drive, an optical disk, or something similar. In the present embodiment, memory 320 stores the CT image data received from the X-ray CT device 100 or the image storage device 200. Memory 320 also stores the results of processing performed by processing circuit 350.

[0020] The input interface 330 is connected to the processing circuit 350 and converts an input operation received from an operator into an electrical signal for output to the processing circuit 350. For example, the input interface 330 can be implemented by a control ball, a switch button, a mouse, a keyboard, a touchpad (where an input operation is performed by touching a user interface), a touchscreen (which integrates a display screen and a touchpad), a non-contact input interface using an optical sensor, a speech input interface, or something similar. The input interface 330 is connected to the processing circuit 350 and converts an input operation received from an operator into an electrical signal for output to the processing circuit 350.The input interface 330 in this specification is not limited to one that includes a physical control element such as a mouse and a keyboard. For example, a processing circuit that receives an electrical signal belonging to an input operation from an external input device separate from the medical image processing device 300, and that outputs this electrical signal to the processing circuit 350, is also included in examples of the input interface 330.

[0021] Display 340 is connected to processing circuit 350 and displays various types of information and image data output by processing circuit 350. For example, display 340 can be implemented as a liquid crystal monitor, a cathode ray tube (CRT) monitor, a touch panel, or something similar.

[0022] The processing circuit 350 controls the respective components included in the medical image processing device 300 according to an operation assumed by an operator via the input interface 330. For example, the processing circuit 350 is implemented by a processor. In the present embodiment, the processing circuit 350 caused the memory 320 to store the CT image data, which is output by the communication interface 310. In addition, the processing circuit reads the CT image data from the memory 320 for display on the display 340.

[0023] With these components, the 300 medical image processing device enables the display of a color image, which facilitates the observation of blood flow indices. Specifically, the 300 medical image processing device switches to a color image display mode, reflecting blood flow indices, based on external information, thereby displaying a color image that facilitates observation. In other words, the 300 medical image processing device allows for the display of a color image that is easy for an observer to view, by displaying a color image appropriate to a given situation. The external information for switching the color image display mode is also referred to as switching information.

[0024] To implement the processing described above, a processing circuit 350 of the medical image processing device 300, according to the first embodiment, performs a control function 351, an analysis function 352, a detection function 353, a generation function 354, and a display control function 355, as shown in Fig. Figure 2 shows the processing circuit 350 as an example of a processing circuit in the claims.

[0025] Control function 351 performs overall control of the medical image processing device 300. For example, control function 351 controls various types of processing according to an electrical signal received from input interface 330. As an example, control function 351 controls the acquisition of CT image data via communication interface 310, the storage of acquired CT image data in memory 320, and similar operations. Furthermore, control function 351 reads CT image data stored in memory 320 and controls the generation of a display image from the read CT image data. As an example, control function 351 generates an image of a blood vessel by subjecting the CT image data to various types of image processing.For example, control function 351 generates a clinical image, such as a volume rendering image, a curved multiplane reconstruction (CPR) image, a multiplane reconstruction (MPR) image, and a stretched multiplane reconstruction (SBR) image, by performing image processing on CT image data. Furthermore, control function 351 generates, for example, a model image of a blood vessel contained in CT image data by subjecting the CT image data to image processing.

[0026] Analysis function 352 performs a fluid analysis based on CT image data. Specifically, analysis function 352 performs a fluid analysis on the structure of a blood vessel included in the acquired image data and records index values ​​relating to blood flow at each position of the blood vessel. Specifically, analysis function 352 first extracts chronological vessel shape data, which depicts the shape of a blood vessel, from three-dimensional CT image data. For example, analysis function 352 reads CT image data from multiple temporal phases, which are collected chronologically, from memory 320 and performs image processing on the read-out CT image data from multiple temporal phases, thereby extracting chronological vessel shape data.

[0027] Analysis function 352 sets a target area for which a blood flow index is calculated within a blood vessel region included in the CT image data. Specifically, analysis function 352 sets a target area within a blood vessel region according to an instruction or image processing action performed by an operator via input interface 330. Analysis function 352 then extracts, for example, a centerline (coordinate information of a centerline) of the blood vessel, a cross-sectional area of ​​the blood vessel, or the brightness of a cross-section perpendicular to the centerline, a distance from the centerline to an internal wall in a cylindrical direction across a cross-section perpendicular to the centerline, a distance from the centerline to an external wall, and similar information from the CT image data as the vessel shape data of the set target area.Analysis function 352 can extract various other vessel shape data according to an analysis procedure.

[0028] Furthermore, analysis function 352 sets analysis conditions for the liquid analysis. Specifically, analysis function 352 sets physical properties of blood, conditions for iterative calculation, initial values ​​for the analysis, and similar parameters as the analysis conditions. For example, analysis function 352 sets the viscosity, density, and similar parameters of blood as the physical properties of the blood. Specifically, analysis function 352 sets a maximum iteration, a relaxation coefficient, a residual tolerance, and similar parameters for the iterative calculation as the conditions for the iterative calculation. Furthermore, analysis function 352 sets initial values ​​of a flow rate, a pressure, a fluid resistance, a pressure limit, and similar parameters as the initial values ​​for the analysis.Different types of values ​​used by the analysis function 352 can be pre-programmed in the system or can be dialogically determined by an operator.

[0029] Analysis function 352 calculates indices of blood flow in a blood vessel through fluid analysis using image data encompassing the blood vessel (for example, a coronary artery or similar). Specifically, analysis function 352 performs fluid analysis using vessel shape data and analysis conditions to calculate the indices of blood flow in a target region of the blood vessel.For example, the analysis function 352 calculates indices such as pressure, blood flow rate, blood flow velocity, a vector, and shear stress at each predetermined blood vessel position based on vessel shape data such as the outline of a lumen or external wall, cross-sectional area, and midline of the blood vessel, the physical properties of the blood, and the set conditions such as conditions for iterative calculation and initial values ​​of the analysis. Furthermore, the analysis function 352 calculates temporal variations in the indices such as pressure, blood flow rate, blood flow velocity, a vector, and shear stress using temporal variations in the vessel shape data such as the outline of a lumen or external wall, cross-sectional area, and midline of the blood vessel.

[0030] Fig. Figure 3 is a diagram illustrating an example of processing performed by the analysis function 352, according to the first embodiment. As in Fig. As shown in Figure 3, analysis function 352 extracts, for example, the vessel shape data for a target LAD from three-dimensional CT image data, which includes a coronary artery. Furthermore, analysis function 352 sets the analysis conditions for analyzing the extracted LAD. Analysis function 352 then performs the fluid analysis using the extracted vessel shape data from the LAD and the set analysis conditions, calculating indices such as pressure, blood flow rate, blood flow velocity, vector, and shear stress for each predetermined position along the centerline, for example, from an edge of the inlet of the target LAD to an edge of the outlet. That is, analysis function 352 calculates distributions of pressure, blood flow rate, blood flow velocity, vector, shear stress, and similar parameters for the target area.

[0031] As described above, analysis function 352 extracts relevant vessel shape data from CT image data of multiple temporal phases acquired over time and performs fluid analysis using this extracted vessel shape data and the analysis conditions, thereby calculating the blood flow indices. Analysis function 352 obtains a highly accurate analysis result using CT image data of multiple temporal phases within a predetermined cardiac phase range.

[0032] The fluid analysis performed by analysis function 352 is not limited to fluid analysis using the analysis conditions described above. For example, analysis function 352 can also calculate blood flow indices using machine learning. When calculating blood flow indices using machine learning, analysis function 352 stores a large number of blood flow index distributions when blood flows into a simulated part that simulates the shape of a portion of a blood vessel in memory 320 and performs learning. Specifically, analysis function 352 predefines a fluid analysis using boundary conditions on the inlet side of the simulated part, boundary conditions on the outlet side of the simulated part, and the shape of the simulated part.Furthermore, analysis function 352 generates a distinguishing element that derives the blood flow index distribution from the simulated part's shape and boundary conditions by storing a relationship between the simulated part's shape, the boundary conditions, and the blood flow index distribution in memory and performing a learning process. Analysis function 353 performs the storage and learning described above for simulated parts with different shapes and boundary conditions. When a patient's blood vessel shape data and boundary conditions are input, analysis function 352 derives the blood flow index distribution from the patient's blood vessel shape data by inputting the blood vessel shape data to the distinguishing element.

[0033] Fig. Figure 4 is a diagram illustrating temporal phases used in the fluid analysis according to the first embodiment. Fig. Figure 4 shows an upper section representing heartbeats, a middle section showing the movement of the heart, and a lower section showing a portion of a coronary artery. Additionally, a horizontal direction represents time. Fig. 4 and temporal changes in heartbeats, cardiac motion, and a region of the coronary artery are linked. For example, analysis function 352 performs fluid analysis using CT image data of cardiac phases, which encompass a range of 70% to 90% of a cardiac phase. The 70% to 90% cardiac phases are temporal phases in which cardiac motion is not favorable and variations occur within a region of the coronary artery. Hearts move by contraction and expansion, and the motion becomes stable in a later half-period of an expanding period (range of 70% to 90% of a cardiac phase), as in the mid-segment in Fig. Figure 4 shows that the analysis function 352 can use CT image data where any movement occurring during heartbeats is small, using CT image data of a cardiac phase which in this range comprises 70 to 90% of cardiac phases, where any movement is stable.

[0034] Furthermore, as in the section below in Fig. As shown in Figure 4, the coronary artery is largest at 70% of the cardiac phase and smallest at 99%. This is because blood begins to flow into the coronary artery at approximately 70% of the cardiac phase and begins to flow out as the phase approaches 99%. Analysis function 352 captures highly accurate analysis results by using CT image data from multiple temporal phases in the 70% to 90% range of the cardiac phase, thus encompassing these variations as much as possible within a single coronary artery region.

[0035] Furthermore, analysis function 352 calculates a fraction of a flow reserve (FFR) based on the pressure distribution in the target area. That is, analysis function 352 calculates an FFR, which is an index for estimating the extent to which blood flow is impaired by an injury, based on pressure on an upstream side and pressure on a downstream side of a predetermined position in a blood vessel (for example, an injured segment such as a stenosis and plug). According to the present application, function 352 calculates various pressure index values ​​as the FFR.

[0036] First, the definition of FFR is explained. As described above, FFR is an index used to estimate the extent to which blood flow is restricted by an injury (such as a stenosis, plug, or similar obstruction) and is defined as the ratio between a flow rate without injury and a flow rate with injury. This is calculated using equation (one) below. "Qn" in equation (one) represents a flow rate without injury, and "Qs" represents a flow rate with injury. FFR≡Qs / Qn

[0037] FFR is determined by an equation that divides "Qs" by "Qn", as shown in equation (1). In calculating FFR, a flow rate and pressure are established proportionally by inducing a state of maximum congestion (stress state) by generally administering adenosine to a patient, and the definition of pressure can thereby be substituted for FFR. That is, by proportionalizing the flow rate and pressure within a blood vessel, equation (1) can be expressed as equation (2). "Pa" in equation (2) indicates a pressure on an upstream side of an injury, and "Pd" indicates a pressure on a downstream side of the injury. Furthermore, "Pv" indicates the pressure of a right atrium, into which venous blood from the entire body drains. FFR≡Qs / Qn=(Pd−Pv) / (Pa−Pv)

[0038] For example, by proportionalizing the relationship between a flow rate and a pressure within a blood vessel, “Qs” can be represented as “Pd - Pv” and “Qn” as “Pa - Pv”, as shown in equation (2). That is, the FFR is represented by a ratio of values ​​obtained by subtracting a baseline pressure from a pressure on an upstream side and a pressure on a downstream side of an injury.

[0039] In the stress state in which adenosine is administered to a patient, this can be assumed to be "Pa greater than sign greater than sign Pv" and "Pd greater than sign greater than sign Pv" and therefore equation (2) can be assumed to be like equation (3) below. FFR≡Qs / Qn=(Pd−Pv) / (Pa−Pv)≈Pd / Pa

[0040] That is, as shown in equation (3), the FFR is calculated by an equation for dividing "Pd" by "Pa". For example, the analysis function 352 calculates a value of FFR at each position of the blood vessel by substituting the calculated upstream pressure and the downstream pressure of the injury in equation (3) above.

[0041] The FFR calculation method described above is merely an example, and the FFR value according to the present embodiment is not limited to using the method described above. That is, the FFR value according to the present embodiment can be any type, as long as it is a pressure index value that indicates a comparison between the pressure at a point on an upstream side of a blood vessel and the pressure at a point on a downstream side of the blood vessel. For example, the FFR value according to the present embodiment can be a pressure ratio calculated in a patient at rest.Similarly, according to the present embodiment, the FFR value can be a pressure ratio based on a pressure value (at least a pressure value from an upstream page and / or a pressure value from a downstream page) which is estimated using another value. Furthermore, according to the present embodiment, the FFR value can be a pressure ratio based on a pressure value (at least a pressure value from an upstream page and / or a pressure value from a downstream page) which is replaced by another value.

[0042] The pressure index values ​​described above are collectively referred to as FFR below.

[0043] In addition, the analysis function 352 calculates ΔFFR, which is obtained by subtracting between FFR values ​​of respective positions, which are calculated as described above. Fig. 5A to Fig. Figure 5C contains diagrams illustrating a calculation example of ΔFFR using the analysis function 352 according to the first embodiment. Fig. Figure 5A shows a blood vessel for which ΔFFR has been calculated, and a calculation range of ΔFFR for the blood vessel. It further shows Fig. 5B a graph of FFR in which in Fig. Blood vessel shown in 5A. Fig. Figure 5C shows an example of ΔFFR calculated using the analysis function 352.

[0044] For example, the analysis function 352 sets the computation width for calculating ΔFFR to "1.0 cm" for a blood vessel for which ΔFFR is being calculated. The computation width is a width used to determine positions between which a difference in FFR values ​​is taken. For example, with a computation width of "1 cm", as shown in Fig. 5A calculates a difference between an FFR value at the position of arrow 61 and an FFR value at the position of arrow 62 of the blood vessel. That is, the analysis function 352 calculates a difference at the respective positions while the in Fig. 5A shows the calculation width being shifted along the blood vessel by a predetermined distance.

[0045] As an example, the analysis function 352 first calculates a difference (ΔFFR) between a value of FFR at the position of arrow 61 and a value of FFR at the position of arrow 62 at the position of the calculation width, shown in Fig. 5A. Analysis function 352 then shifts the computation width along the blood vessel (in a right-handed direction of the drawing) by "1 mm" and, at a position after the shift, calculates a difference (ΔFFR) between a value of FFR at the position of arrow 61 and a value of FFR at the position of arrow 62. In the same way, analysis function 352 sequentially calculates ΔFFR at each position, shifting the computation width along the blood vessel by "1 mm" each time.

[0046] Thus, the analysis function 352 can detect ΔFFR of any position (distance from a starting section) of the blood vessel, as in a curved line L2 in Fig. Figure 5C shows that the computation width used in the calculation of ΔFFR can be set arbitrarily. For example, analysis function 352 can extract a stenosis or plug from CT image data and can set the computation width according to the size of the extracted stenosis or plug. As an example, analysis function 352 sets the computation width to a width substantially identical to the width of a stenosis or plaque in one longitudinal direction of a blood vessel.

[0047] As described, ΔFFR, which is calculated by the analysis function 352, can be used, for example, to evaluate multiple stenoses, as in Fig. 5A shown. For example, if a stenosis 51 and a stenosis 52 are present in a blood vessel, as in Fig. Figure 5A shows a graph of the blood vessel's FFR, which reveals a value of FFR that is reduced at the position of each stenosis, as shown in curve L1 in Fig. 5B shown. If the stenosis 51 and the stenosis 52 are only shown with the graph of FFR, which is in Fig. As shown in 5B, it is difficult to assess which stenosis has a greater impact on blood flow.

[0048] Using the ΔFFR values ​​calculated by analysis function 352, it becomes apparent that a change at position 53 with a larger change in ΔFFR (a significant decrease in the FFR value) has a greater impact on the flow rate than both change at position 53 and change at position 54. This means that stenosis 51, associated with change at position 53, has a greater impact on the flow rate and therefore requires higher treatment priority.

[0049] Furthermore, according to the first embodiment, analysis function 352 can also calculate a diameter stenosis rate based on the internal diameter of a blood vessel. For example, analysis function 352 calculates the internal diameter of a blood vessel at each position of the blood vessel using CT image data and calculates the diameter stenosis rate (% DS) using the calculated internal diameter of each position.

[0050] Back to Fig. 2. The acquisition function 353 acquires switching information for switching a display mode at the time an index value is displayed. Specifically, the acquisition function 353 acquires information specifying a display condition for the index value as the switching information. That is, the acquisition function 353 acquires information that makes it possible to determine the state for displaying the index value. The switching information acquired by the acquisition function 353 is used to determine a display mode for a color image in which a value of an index relating to a flow rate is indicated by color information. For example, the acquisition function 353 acquires at least index type information, examination information, and / or patient information as the switching information.In addition, the detection function 353 captures display information (for example, an image or something similar) which is displayed together with the index value, or information from an application which is activated together with a display of the index value, as the switching information.

[0051] The index type information includes, for example, information such as FFR, instantaneous FFR, ΔFFR, pressure, flow rate, and stenosis rate. The acquisition function 353 acquires an index value type, which is determined by an operator via the input interface 330, and reports the acquired information to the generation function 354. Alternatively, the acquisition function 353 acquires a standard index value type and reports the acquired information about the type to the generation function 354.

[0052] The examination information also includes, for example, information such as the type of examination and the person responsible for it. The capture function 353 captures information about the type of examination, such as whether the examination is routine or urgent, or the physician responsible for the examination, from information entered via the input interface 330. The capture function 253 then reports the captured examination information to the generation function 354. Alternatively, the capture function 353 captures the examination information described above from a server device that manages a hospital information system (HIS) or a radiology information system (RIS) applied to the medical image processing system, and reports the captured examination information to the generation function 354.

[0053] Furthermore, patient information includes, for example, details such as the number of times the patient has had this examination, past examination results, treatment history, body type, nationality, ethnicity, place of residence, organizational affiliation, current medications, results of medical examinations, and similar information. Past examination results include, for example, information on whether a stenosis was found in a computed tomography angiography (CTA) scan, the area and diameter of a blood vessel where a stenosis was found, the location of a stenosis (for example, whether it is triple vascular disease in which stenoses were found in three coronary arteries), and similar information. The treatment history includes, for example, information indicating whether coronary artery surgery was performed, and similar information.The body type information also includes, for example, information on chest compressions, body weight, body mass index (BMI), and similar data. The acquisition function 353 captures the patient information described above from information entered via the input interface 330 and reports the captured patient information to the generation function 354. Alternatively, the acquisition function 353 captures the patient information described above from a server device that manages a HIS or RIS applied to the medical image processing system and reports the captured patient information to the generation function 354.

[0054] Furthermore, the capture function 353 captures, for example, information about an image to be displayed along with an index value, information about an application to be used with a display of an index value, information indicating the display purpose of an index value, and similar information. For example, the capture function 353 captures information about an image to be displayed on the display 340 alongside the display of an index value. For instance, the capture function 353 captures information about the type of image (for example, a volume reproduction image, a PR image, a CPR image, an electrocardiograph fresh perfusion image, or similar) to be displayed on the display 340, a part to be displayed in an image (for example, an image showing the entire heart, including coronary arteries, or a local image of a coronary artery), and similar information.Capture function 353 can capture a tip or part of an image, for example, from supplementary information within the image data. Furthermore, capture function 353 can capture information indicating that an image is a local image, for example, by accepting a range selection operation with reference to the displayed image via the input interface. Additionally, capture function 353 can capture a position within an image, for example, by accepting a position determination operation with reference to a displayed image, also via the input interface.

[0055] Furthermore, capture function 353 captures information about an application that is enabled, in addition to an application used to display an index value. For example, capture function 353 captures information about an analysis application that is enabled, in addition to the application used to display an index value. The information about an application captured by capture function 353 can be an application that is linked to the application used to display an index value (for example, another application included in the same software as the application used to display an index value), or it can be an application that is not linked to the application used to display an index value (for example, an application included in different software than the application used to display an index value).

[0056] Furthermore, capture function 353, for example, captures information specifying the display purpose of an index value from an application. As an example, capture function 353 captures a display purpose of an index based on an operation in an application that differs from the application used to display the index value. An example of capturing the display purpose of an index value will be described in detail later.

[0057] The generation function 354 produces a color image in which an index value is displayed, in a display mode according to the switching information for an image showing a patient's blood vessel. Specifically, generation function 354 produces a color image in which an index value is displayed, in a display mode according to a condition for displaying an index value. That is, generation function 354 generates a color image based on a color table that is set according to a condition for displaying an index value. For example, generation function 354 produces a color image in which an index value is displayed, in a display mode according to at least one piece of information from the group of type information, examination information, and patient information for an index value.This means that the generation function 354 determines a display mode for a color image based on the switching information reported by the detection function 353, and generates a color image in the specified display mode. A color image is generated using the following function. Fig. 6A to Fig. 6F explains which is generated by the generating function 354. Fig. 6A to Fig. Figure 6F shows an example of a color image generated by the generation function 354 according to the first embodiment.

[0058] For example, the generation function 354 sets a reference value for the index value according to the switching information and generates a color image in which the color changes as a border at the set reference value. As an example, the generation function 354 sets "0.8" as the reference value of FFR, as in Fig. Figure 6A shows this, and generates a two-color image in which the color changes at the set reference value of "0.8" to represent a boundary. That is, the generation function 354 classifies FFR values ​​analyzed by the analysis function 352 for each position of a patient's coronary artery into two ranges based on "0.8" as a boundary. The generation function 354 assigns a color to each of the two ranges (for example, red for values ​​less than 0.8 and blue for values ​​equal to or greater than 0.8, or something similar) and generates a color image in which each position in a model image of the patient's blood vessel is colored with the specified color. Thus, the generation function 354 produces a color image that makes it possible to identify, at a glance, a range in which an FFR value is less than "0.8".As a result, an observer can easily make a diagnosis as to whether a percutaneous coronary intervention (PCI) should be performed, or whether pharmacological treatment should be administered to the patient, or something similar.

[0059] The reference value set by generation function 354 can be adjusted according to the switching information. That is, the number of reference values ​​or a numerical value for the reference value can be set so that it changes according to the switching information. For example, the number of reference values ​​can be set according to information about the performing physician included in the examination information, information about the number of examinations included in the patient information, and so on. For example, if the examination is performed several times for follow-up, or if a predetermined responsible physician is specified, generation function 354 sets "0.8" and "0.75" as the reference values, as shown in Fig. Figure 6B shows a three-color image in which the color changes at the set reference values ​​of "0.8" and "0.75" as the edges. This means that the generation function 354 classifies FFR values, analyzed by the analysis function 352, for each position of a patient's coronary artery into three ranges: "less than 0.75," "equal to or greater than 0.75 and less than 0.8," and "0.8 or greater." The generation function 354 then determines a color for each of the three ranges and generates a color image in which each position in a model image of the patient's blood vessel is colored with the specified color.

[0060] Furthermore, in the case of the first investigation, for example, the generating function provides 354 respective values, which are obtained by dividing values ​​from "0.5" to "1.0" into nine groups as the reference values, as in Fig. Figure 6C shows that this function generates a 9-color image in which the color changes at the respective reference values ​​set as edges. That is, the generation function 354 classifies FFR values, which are analyzed by the analysis function 352, into nine regions for each position of a patient's coronary artery. The generation function 354 then determines a color for each of the new regions and generates a color image in which each position in a model image of a patient's blood vessel is colored with the specified color.

[0061] A numerical value of the reference value, which is set by the generation function 354, can be determined according to the switching information. For example, an example is in Fig. Figure 6B shows that "0.8" and "0.75" are determined as the reference values; these values ​​can be appropriately modified according to information about a patient's test results, body type information, and similar factors. For example, if the instantaneous FFR is used as the index value, generating function 354 can determine "0.86" and "0.93" as the reference values.

[0062] Furthermore, if a patient's heart mass, body weight, and BMI are high, for example, the generating function 354 can adjust the two reference values ​​"0.8" and "0.75" to higher values.

[0063] Furthermore, the generating function 354 can determine the reference values ​​based on various other types of switching information. For example, the generating function 354 sets the reference value to relatively high levels for a patient who has suffered a heart attack, a patient with an arrhythmia, a patient prescribed medication such as an antiplatelet agent and an anticoagulant, a patient with high cholesterol, and similar conditions. The generating function 354 can also modify the reference value based on the results of any patient's medical examination. Additionally, the generating function 354 can determine the reference value based on factors such as a patient's nationality, ethnicity, region of residence, and organizational affiliation.

[0064] The ranges of an index value that are colored by the generation function 354 can also be set according to the switching information. For example, although the case in which the range of FFR to be colored is set to "0 to 1.0" in Fig. 6A and Fig. As shown in 6B, this can be set to "0.5 to 1.0" according to the switching information, as shown in Fig. Figure 6C shows that, as an example, if FFR values ​​are checked precisely, the generating function 354 can set the range of FFR to be colored to a narrow range and can produce a color-coded color image based on several reference values.

[0065] Furthermore, although the case of varying colors (hues) using the reference values ​​as boundaries has been explained, the colors used can be determined to highlight an area of ​​interest. For example, generating function 354 assigns a color such that the area in which an FFR value is "less than 0.75" is highlighted, or arranges colors such that the area "less than 0.75" and the area "0.75 and greater" are clearly distinguishable. That is, generating function 354 produces a color image in which an index value within a predetermined range, based on the reference value, is highlighted. Thus, an observer can identify the position of an area of ​​interest at a glance.

[0066] Furthermore, the generation function 354 can change the brightness or transparency, also based on the reference value as a boundary. Specifically, generation function 354 sets the reference value for an index value according to the switching information and generates a color image in which the brightness of a color changes at the set reference value as a boundary. For example, generation function 354 generates a color image in which the area of ​​an FFR value that is "less than 0.75" has a higher brightness. Furthermore, generation function 354 sets the reference value for an index value according to the switching information and generates a color image in which the transparency changes at the set reference value as a boundary.For example, generation function 354 produces a color image where the area with an FFR value of "0.75 and greater" has low transparency, and the area with an FFR value of "less than 0.75" has high transparency. As described above, generation function 354 can highlight an area of ​​interest in a color image by generating a color image where the brightness or transparency varies based on the reference value as a border.

[0067] The example above explained the use of FFR as an index value. Generation function 354 can generate a color image using an index such as ΔFFR, pressure, flow rate, and stenosis rate in addition to FFR. For example, generation function 354 sets a reference value for ΔFFR and generates a color image in which the color is varied based on the set reference value as a margin, as shown in Fig. Figure 6D illustrates this. As an example, the generation function 354 sets "0.2" as the reference value for ΔFFR and generates a two-color image in which the color changes at the set reference value of "0.2" as a boundary. That is, the generation function 354 classifies ΔFFR values, which are analyzed by the analysis function 352 for each position of a patient's blood vessel, into two ranges based on "0.2" as a boundary. The generation function 354 then determines a color for each of the two ranges (for example, red for values ​​equal to or greater than 0.2 and white for values ​​less than 0.2, or something similar) and generates a color image in which each position in a model image of the patient's blood vessel is colored with the specified color. Thus, an observer can identify the area of ​​a high ΔFFR value (i.e., a section where the FFR changes significantly) at a glance.

[0068] The generation function 354 can produce various types of color images using a pressure, flow rate, stenosis rate, or something similar as an index, which differ from the ΔFFR described above. The number of reference values ​​for the numerical value of the reference value is set appropriately according to the switching information, as is the case for indices such as ΔFFR, pressure, flow rate, and stenosis rate.

[0069] In the above described Fig. 6A to Fig. In Figure 6D, the case of a color image was described in which colors are reproduced in a model image of a blood vessel, generated based on a volume image of a patient. However, the embodiment is not limited to this. The generation function 354 can generate a color image in which colors are reproduced for various types of clinical images. For example, the generation function 354 sets "0.8" as the reference value of FFR, as in Fig. Figure 6E shows that this function generates a two-color image in which the color changes at the set reference value of "0.8" as a border, based on a volume rendering image. That is, the generation function 354 classifies FFR values, analyzed by the analysis function 352, for each position of a patient's coronary artery into two ranges based on "0.8" as a border. The generation function 354 determines a color for each of the two ranges and generates a color image in which each position in the volume rendering image, which includes the patient's heart and blood vessels, is colored with the specified color.

[0070] Furthermore, for example, the generation function 354 sets "0.8" as the reference value of FFR, as in Fig. 6F is shown, and generates a two-color image in which the color changes at the set reference value of "0.8" as a border, based on a CPR image. That is, the generation function 354 classifies FFR values, which are analyzed by the analysis function 352, for each position of a patient's coronary artery, into two ranges based on "0.8" as a border. The generation function 354 determines a color for each of the two ranges and generates a color image in which each position in the patient's blood vessel in the CPR image is colored with the determined color.

[0071] Furthermore, the generation function 354 can generate a color image according to the switching information of an image to be displayed together with an index value, information of an application which is to be used with the index value, a display purpose of the index value, a display range of the index value and something similar. Fig. 7A to Fig. Figure 9B shows an example of a color image generated by the generation function 354, according to the first embodiment. Fig. 7A and Fig. Figure 7B shows an example of a case for displaying an image along with an index value. Furthermore, they show Fig. 8 on Fig. 8B is an example of a case for using information that specifies the display purpose of an index value. Further, show Fig. 9A and Fig. 9B is an example of a case for using a display range of an index value.

[0072] For example, the generating function 354 displays an index value in a display area R1 on the display 340, as in Fig. 7A shows, and when an image is displayed in display area R2, it generates a color image to be displayed in display area R1, corresponding to the type of image to be displayed in display area R2. For example, if a volume rendering image of an entire heart, including coronary arteries, is displayed in display area R1, as shown in Fig. As shown in Figure 7A, the generation function 354 sets the reference value of FFR to "0.8" and generates a color image based on a two-color table, in which the color changes as a border at the set reference value of "0.8". That is, generation function 354 produces a color image with few colors (for example, two colors or something similar), which makes it easy to determine the state of blood flow when an image showing the entire heart is displayed. For example, if an MPR image, in which a coronary artery is magnified, or something similar, is displayed in the R2 display area, generation function 354 sets corresponding values, obtained by dividing values ​​from "0.5" to "1.0" into nine groups, as the reference values, as shown in Figure 7A. Fig. 6C shows, and generates a color image based on a 9-color table, in which the color changes at the respective set reference values ​​as edges. That is, the generation function 354 generates a color image with many colors (for example, nine colors or something similar), which makes it possible to determine the state of blood flow more accurately when a detailed image is displayed. The generation function 354 can also generate a color image according to other types of images, a part displayed in an image, and something similar. In addition, the generation function 354 can generate a color image according to various types of operations performed with reference to the displayed image, not just according to the type of image to be displayed on the display 340. For example, if the acquisition function 353 performs an operation to determine a coronary artery area with reference to a volume rendering image of a Fig. Assuming that the heart shown in 7A is received via the input interface 330, the generation function 354 determines that this has switched to a local image and generates a 9-color image as a color image to be displayed in the display area R1.

[0073] For example, if the acquisition function 353 accepts a position determination operation or operation with reference to a displayed image via the input interface, the generation function 354 creates a color image according to the operation or operation assumed for the image. As an example, if the acquisition function 353 performs an operation to determine a segment of position P1 relative to position P2 along a blood vessel in a coronary artery in a volume rendering image, as in Fig. As shown in Figure 7B, if the acquisition function 353 assumes an operation to determine two points at position P1 and position P2, the generation function 354 generates a color image showing the difference (ΔFFR) between an FFR value at the determined position P1 and an FFR value at the determined position P2. Furthermore, if the acquisition function 353 assumes an operation to determine two points at position P1 and position P2, the generation function 354 generates a color image showing the difference (ΔFFR) between an FFR value at the determined position P1 and an FFR value at the determined position P2. As described, the generation function 354 can generate a color image corresponding to a type of image displayed with an index value or to an operation related to an image.When a color image is generated according to a position determined on an image (for example, a color image showing ΔFFR), an image displayed in the Air 2 display area is an image generated based on medical image data obtained by analyzing an index value.

[0074] Furthermore, the generation function 354 creates a color image according to information regarding the display purpose of an index value, which is captured by the acquisition function 353. The acquisition function 353 captures information regarding the display purpose of an index value based on an operation from various types of applications. For example, in recent years, an administrative application has been used that manages patient information chronologically and allows users to search through different types of examination information. The acquisition function 353 captures the switching information regarding the display purpose of an index value from an operation in this type of management application.As an example, the capture function 353 captures a display purpose of an index value from information about an operation in an application which manages various types of information about a patient, from entering to leaving a hospital, and which presents the information to a user, as in an area R3 of . Fig. 8A and Fig. 8B shown.

[0075] For example, when a display operation of an index value is performed using different types of information about a patient, which is shown chronologically, the capture function 353 captures a display purpose of the index value based on the operation performed. For example, as in Fig. Figure 8 shows that when a user selects "Analysis" from various types of patient information, displayed chronologically, as a display operation to show an index value, the acquisition function 353 captures "Analysis" as the information indicating the display purpose of the index value. That is, the acquisition function 353 captures the above display operation as information indicating that the index value is being displayed for the purpose of performing an analysis. When the acquisition function 353 accepts the operation to select "Analysis," the generation function 354 generates a color image with many images (for example, nine colors or something similar), which makes it possible to accurately determine the state of blood flow, suitable for analyzing blood flow, as shown in Fig. 8A shown.

[0076] On the other hand, if a user selects "conference" from the various types of patient information, which is shown chronologically, as a display operation to show an index value, as in Fig. As shown in Figure 8B, when selected, the acquisition function 353 "Conference" is captured as information indicating the display purpose of the index. That is, acquisition function 353 captures the above display operation as information indicating that the index value to be used in a conference is displayed. When cases are observed by multiple people at a conference, color images are often displayed, which facilitate diagnosis. Therefore, when acquisition function 353 accepts an operation to select "Conference," the generation function 354 produces a color image with few colors (for example, two rides or something similar), which makes it easy to determine the state of blood flow, thus being suitable for blood flow analysis.

[0077] Since various types of applications are frequently activated for a patient during a conference, this information can be used as the switching information. For example, if the capture function 353 determines the number of simultaneously activated applications, and if the number of activated applications is equal to or greater than a threshold, it can be trained to determine that the display purpose is "Conference".

[0078] Furthermore, the generation function 354 can also determine a color image based on a display area of ​​a color image on the display 340. In particular, the generation function 354 generates a color image according to a size of the display area, a position of the display area, or something similar of a color image. For example, if the display area R1 on the display 340 is large, as in Fig. As shown in Figure 9A, the generation function 354 produces a color image with many colors (for example, nine colors), which makes it possible to accurately determine the state of blood flow, thus making it suitable for blood flow analysis. Furthermore, if the display area R1 is located in the center of the display 340, or if the display area R1 is the entire screen, the generation function 354 produces a color image with many colors (for example, nine colors), which makes it possible to accurately determine the state of blood flow, thus making it suitable for blood flow analysis.

[0079] On the other hand, if the display area R1 on display 340 is small, or if a display area R4 is additionally arranged to display something other than a color image, as in Fig. As shown in Figure 9B, the generation function 354 produces a color image with a few colors (for example, two colors), which makes it easy to determine the state of blood flow. Furthermore, if the display area R1 is located at an end section of a display 430, the generation function 354 produces a color image with a few colors (for example, two colors), which makes it easy to determine the state of blood flow.

[0080] As described above, the generation function 354 creates a color image according to the information of a display for a specific index value. For the information regarding a display purpose, not only the example described above but also various other types of information can be used. For example, the display purpose can be determined using the display time of a color image.

[0081] In this case, for example, the acquisition function 353 captures the display time of a color image. Consequently, if the display time of the color image exceeds a threshold (for example, 10 minutes), the generation function 354 produces a color image with many colors (for example, nine colors), which makes it possible to accurately determine the state of blood flow, thus being suitable for blood flow analysis. On the other hand, if the display time of the color image is equal to or less than the threshold (for example, 1 minute), the generation function 354 produces a color image with few colors (for example, two colors), which makes it possible to easily determine the state of blood flow. This can be configured to produce a color image with many colors (or a color image with few colors) when color images exceed the threshold (or are equal to or less than the threshold).

[0082] Furthermore, this can be controlled to switch color filters according to the display time, for example. In this case, for instance, the generation function 354 creates a color image with few colors. The detection function 353 then detects the display time of the color image with few colors. If the display time of the color image with few colors exceeds the threshold, the generation function 354 generates a color image with many colors. That is, the generation function 354 determines how precisely the color image is observed and controls the generation of an accurate color image when it is determined that the image has been observed for a long time.

[0083] Furthermore, this can be controlled to change the color image to be generated, depending on how many times the observation has been performed. For example, if an index value is stored, it can be linked to information indicating that the analysis has been performed. The acquisition function 353 captures information indicating whether an index value used in generating a color image is linked to the information indicating that the analysis has been performed, as the switching information. If the information indicating that the analysis has been performed is linked to the index value, the generation function 354 generates a color image with a few colors (for example, two colors), which makes it easy to determine the state of blood flow.On the other hand, if the information indicating that an analysis has been performed is not linked to the index value (if this is the first analysis), generation function 354 produces a color image with many colors (for example, nine colors), which makes it possible to accurately determine the state of a blood flow.

[0084] As described above, the generation function 354 creates a color image in which index values ​​are colored, in a display mode according to the switching information. A quality ranking can be determined for the switching information used by the generation function 354. For example, if the acquisition function 353 reports several types of switching information to the generation function 354, the priority ranking for determining which switching information to use to determine the display mode of a color image can be determined by the generation function 354. For example, if "urgent" is specified in the examination information and "first examination" in the patient information, the priority ranking can be determined such that "urgent" is assigned a priority.In this case, if "urgent" and "first investigation" are reported as the switching information by the detection function 353, the generation function 354 produces a 2-color image with priority on "urgent".

[0085] Back to Fig. 2. The display control function 355 causes the display 340 to display a color image. Specifically, the display control function 355 causes the display 340 to display a color image generated by the generation function 354. The display control function 355 switches between color images to be displayed according to a switching operation for color images. For example, if the switching information is entered via the input interface 330 after a color image generated by the generation function 354 has been displayed on the display 340, the display control function 355 switches to a color image generated based on the switching information entered by the input interface 330, from a color image that is being displayed.

[0086] As an example, suppose that the generation function 354 produces a color image displaying FFR values, and the display control function 355 causes the display 340 to show the generated color image. If the input interface 330 accepts an input of ΔFFR as the switching information for this situation, the generation function 354 first produces a color image displaying ΔFFR values. Consequently, the display control function 355 causes the display 340 to show the newly generated color image of ΔFFR.

[0087] As described, the medical image processing device 300 can switch between color images to be displayed based on switching information received from an operator via the input interface 330. The switching information entered by an operator via the input interface 330 includes information about the number of reference values ​​and a numerical value, in addition to the index type information, examination information, and patient information described above. That is, the operator can select an index type, enter examination or patient information, and set the number of reference values ​​(the number of colors used in a color image) or a numerical value thereof at any given time.

[0088] Next, a processing method performed by the medical image processing device 300, according to the first embodiment, will be explained. Fig. Figure 10 is a flowchart showing a process performed by the medical image processing device 300 according to the first embodiment. Steps S101 and S102 in Fig. Steps 10 and 10 are implemented, for example, by calling a program belonging to the analysis function 352 from memory 320 and executing it through the processing circuit 350. Furthermore, step ST103 is implemented, for example, by calling a program belonging to the acquisition function 353 from memory 320 and executing it through the processing circuit 350. Steps S100 and S105 are also implemented by calling a program belonging to the generation function 354 from memory 320 and executing it through the processing circuit 350. Finally, step ST106 is implemented by calling a program belonging to the display control function 355 from memory 320 and executing it through the processing circuit 350.

[0089] In the medical image processing device 300 according to the present embodiment, the processing circuit 350 first performs the fluid analysis using collected CT image data (step S101) and calculates an index value (for example, FFR) relating to blood flow (step S102). Subsequently, the processing circuit 350 acquires external information (step S1003) and determines the display mode based on the external information (step S1004).

[0090] The processing circuit 350 then generates a color image based on the specified display mode (step S105) and displays the generated color image (step ST106).

[0091] As described above, according to the first embodiment, the analysis function 352 performs a fluid analysis of an image comprising a patient's blood vessel to determine an index value relating to blood flow at each position of the blood vessel. The detection function 353 detects the switching information for switching the display mode when the index value is displayed. The generation function 354 generates a color image in which the index value is displayed, in the display mode according to the switching information for an image showing the patient's blood vessel. The display control function 355 causes a display unit to display the color image.Therefore, the medical image processing device 300 according to the first embodiment can generate and display a color image in a display mode according to the switching information and enables the display of a color image which facilitates the observation of an index relating to blood flow.

[0092] Furthermore, according to the first embodiment, the acquisition function 353 captures at least the index type information, the examination information, and / or the patient information as the switching information. The generation function 354 generates a color image in which the index value is reproduced, in a display mode corresponding to at least the index type information, the examination information, and / or the patient information. Therefore, according to the first embodiment, the medical image processing device 300 enables the generation and display of a color image in a flexible manner according to various types of situations.

[0093] Furthermore, according to the first embodiment, the generation function 354 sets a reference value for an index value according to the switching information and generates a color image in which the color changes as a border at the set reference value. Therefore, according to the first embodiment, the medical image processing device 300 can generate and display a color image suitable for diagnosis in a given situation.

[0094] Furthermore, according to the first embodiment, the generation function 354 sets a reference value for an index value according to the switching information and generates a color image in which the brightness of a color changes as a border at the set reference value. Furthermore, the generation function 354 sets a reference value for an index value according to the switching information and generates a color image in which the transparency changes as a border at the set reference value. In addition, the generation function 354 generates a color image in which index values ​​within a predetermined range are highlighted based on the reference value.Therefore, the medical image processing device 300 according to the first embodiment can generate and display a color image in which an area of ​​interest is highlighted, and can display a color image which facilitates observation of an index relating to blood flow.

[0095] Furthermore, according to the first embodiment, the generation function 354 sets a reference value for each type of index value. Therefore, according to the first embodiment, the medical image processing device 300 can generate and display a color image suitable for diagnosing a type of index value and enables the display of a color image that facilitates the observation of an index relating to blood flow.

[0096] Furthermore, according to the first embodiment, the generation function 354 produces a color image that represents an internal section of a blood vessel in an image depicting the patient's blood vessel, with colors corresponding to index values ​​relating to blood flow at each position. Therefore, according to the first embodiment, the medical image processing device 300 can generate and display a color image for which differences in a color within the image can be easily determined, and enables the display of a color image that facilitates the observation of an index relating to blood flow. Second embodiment

[0097] In the first embodiment described above, the case for generating a color image in which an entire internal section of a blood vessel is colored was explained. In a second embodiment, a case for displaying information is explained in which an index value is represented by a color at each position of a blood vessel along the blood vessel. The configuration of the medical image processing device 300 according to the second embodiment is essentially identical to the configuration of the device described in [reference missing]. Fig. 2 medical image processing device 300 shown. Therefore, mainly points which differ from the medical image processing device 300 according to the first embodiment are explained below, and the same reference numerals are assigned to components which have a similar role to that of the in . Fig. The two components shown are used, and a detailed explanation of them is omitted.

[0098] The generation function 354 according to the second embodiment generates a color image in which a line along a blood vessel in an image representing a patient's blood vessel is colored by a color that corresponds to an index value relating to blood flow at each position in a longitudinal direction of the blood vessel. That is, the generation function 354 generates a color image in which a line along a blood vessel is colored, and not an entire internal section of the blood vessel.

[0099] Fig. Figure 11 shows an example of a color image generated by the generation function 354 according to the second embodiment. Fig. Figure 11 shows an example of a color image in which a model image of a patient's blood vessel is colored in two colors. For example, the generation function 354 produces a color image in which a midline of a blood vessel is specified in an image, and each midline is colored with a color corresponding to a value of an index value, as in Fig. Figure 11 shows that, as an example, the generation function 354 sets a reference value to "0.8" and generates a color image of the midline of a blood vessel, colored based on a value of FFR at each position in the longitudinal direction of a coronary artery, as shown in Fig. Figure 11 shows that the generation function 354 generates a color image in which a curve L3 along a section where the value of FFR is "less than 0.8" is colored with a color corresponding to "less than 0.8", and a curved line L4 along a section where the value of FFR is "0.8 or greater" is colored with a color corresponding to "0.8 or greater", as shown in Fig. 11 shown.

[0100] For example, in an area where blood vessels have a complex course, it may be difficult to see where the blood vessels run if the entire internal section of each blood vessel is colored. Therefore, according to the second embodiment, the medical image processing device 300 only scans a line along a blood vessel, as shown in Fig. 11 shown, which makes it possible to detect where the blood vessels run, simply and to display a color image, which facilitates observation of an index regarding blood flow.

[0101] It is pointed out that the in Fig. The example shown in Figure 11 is just one example, and the generating function 354 can generate various other types of color images. Fig. 12A to Fig. Figure 12C shows an example of a color image generated by the generation function 354 according to the second embodiment. Fig. 12A to Fig. 12C is simply an area shown in a color image.

[0102] For example, the generating function 354 shows a line L5 along a blood vessel on the outside of the blood vessel, as in Fig. 12A is shown and can generate a color image in which line L5 is represented by a color corresponding to a value of the index. That is, the generation function 354 can produce a color image in which color information is shown, not only on the outside of the blood vessel, but also by coloring the inner section of the blood vessel.

[0103] The line indicating an index value on the outside of a blood vessel can be arranged to show a difference in that index value not only through color but also through line thickness. For example, generation function 354 can display a line along a segment where the FFR value is "less than 0.75" in a coronary artery, thicker than a line along a segment where the FFR is "0.75 or greater". Furthermore, generation function 354 can, for example, generate an image where the number of points corresponding to an index value is arranged in a direction perpendicular to the length of a blood vessel. For example, generation function 354 generates an image where the number of points arranged next to a blood vessel increases as the FFR value decreases.

[0104] Furthermore, the generation function can display 354 lines in various shapes within an area where blood vessels intersect. For example, as in Fig. As shown in Figure 12B, when a blood vessel 71 and a blood vessel 72 intersect, and blood vessel 71 passes in front of blood vessel 72, the generating function 354 can produce a color image in which a line L6 along blood vessel 71 is displayed above a line L7 along blood vessel 72 to accurately show the positional relationship of the blood vessels. Furthermore, the generating function 354 can produce a color image in which an entire segment of line L7 is displayed, as shown in Figure 12B. Fig. Figure 12C is shown to indicate the entire section of line L7, which is partially obscured by blood vessel 71.

[0105] As described above, according to the second embodiment, the generating function 354 produces a color image in which a line along a blood vessel is displayed in an image showing the patient's blood vessel, with a color corresponding to an index value relating to blood flow at each position along the length of the blood vessel. Therefore, according to the second embodiment, the medical image processing device 300 enables the display of a color image that facilitates the observation of an index relating to blood flow, while also allowing for the simple detection of the arrangement of the blood vessels. Third embodiment

[0106] The first and second embodiments have been explained. In addition to the first and second embodiments described above, various other embodiments are possible.

[0107] In the embodiments described above, the case was explained as an example where the FFR or the ΔFFR is displayed as an index relating to blood flow. However, the embodiments are not limited to this and, for example, a color image relating to another index such as a flow rate, flow velocity, or pressure can be displayed.

[0108] The embodiments described above further explain the case in which a single color table is used, in which the color changes at a reference value as a border. However, the embodiments are not limited to this, and an applicable color table can be changed according to the position of an index value that specifies the same value as the reference value at a blood vessel. In particular, the detection function 353 detects a position that specifies the same value as the reference value of the index value at a blood vessel, as the switching information for the index value relating to a blood vessel at each position of the blood vessel. The generation function 354 then generates a color image in which an arrangement of colors is changed according to the position of the index value that specifies the same value as the reference value of the index value at the blood vessel, from the index values ​​at the respective positions of the blood vessel.

[0109] For example, detection function 353 detects a position where the index value is the same as the reference value of the index value at the blood vessel, i.e., for the index value relating to blood flow at each position of the blood vessel based on an analysis result obtained by analysis function 352. As an example, detection function 353 detects a position (e.g., a distance from a starting segment) at a blood vessel where the FFR value is "0.7". That is, detection function 353 detects a position at the blood vessel where the FFR value is "0.7" from an analysis result of the vessel shape data and the FFR.

[0110] The generation function 354 modifies a color table according to the position detected by the detection function 353. The color tables used by the generation function 354 have different color arrangements, suitable for example, according to severity. For example, in a color table where a color indicating a high level of severity is used, several colors assigned as a border based on the reference value are colors in the red range. On the other hand, in a normal color table, various hues such as red, yellow, green, and blue are assigned.For example, if the distance to a position where the value of FFR is equal to "0.7" from a starting section is less than a threshold (when close to the starting section), the generation function 354 produces a color image using the color table, which uses colors that indicate that it is a level of severity. On the other hand, if the distance to a position where the value of SF is equal to "0.7" from a starting section exceeds the threshold (when far from the starting section), the generation function 354 produces a color image using the normal color table.

[0111] This means that if a position where the FFR value is "0.7" is close to the starting point, the area (perfusion area) dominated by blood vessels with FFR values ​​less than "0.7" is large, and therefore the severity level is high. However, if a position where the FFR value is "0.7" is far from the starting point, the area (perfusion area) dominated by blood vessels with FFR values ​​less than "0.7" is small, and therefore the severity level is lower. As described above, the generation function 354 can produce a color image where the difference in severity is represented by changing the color tables corresponding to a position detected by the detection function 353.Although the case where the color tables are changed according to a distance from a starting section was explained in the example above, the embodiments are not limited to this. For example, the color tables can be changed according to a blood flow area.

[0112] Furthermore, for a correspondence between the switching information, which specifies the conditions of an index value in a display (as explained in the embodiments), and the display mode (setting a reference value, a color arrangement, and something similar) of a color image, predetermined correspondences can be stored in memory 320 in order to be read out in advance as needed by the generation function 354; however, a correspondence relationship can also be used which is updated by machine learning as needed.

[0113] Furthermore, the above embodiments described the case in which the medical image processing device 300 performs different types of processing. However, the embodiments are not limited to this. For example, the X-ray CT device 100 can perform various types of processing. Fig. Figure 13 shows an example of a configuration of the X-ray CT device according to a third embodiment.

[0114] As in Fig. As shown in Figure 13, the X-ray CT device 100 according to the third embodiment comprises a frame 10, a table device 20, and a console 30. The frame 10 is a device which emits X-rays onto a patient P and detects X-rays that have passed through the patient P in order to output them to the console 30, and comprises an X-ray irradiation control circuit 11, an X-ray generating device 12, a detector 13, a data acquisition circuit (ADAS) 14, a rotating frame 15, and a frame drive circuit 16.

[0115] The rotation frame 15 is a ring-shaped frame which holds the X-ray generating device twelve and the detector 13 so that they are positioned opposite each other around the patient P, and which rotates at high speed in a circular motion around the patient P in the middle by the scaffold drive circuit 16 described later.

[0116] The X-ray irradiation control circuit 11 is a device that applies a high voltage to an X-ray tube 12a, which acts as a high-voltage generating unit. The X-ray tube 12a generates X-rays using the high voltage supplied by the X-ray irradiation control circuit 11. The X-ray irradiation control circuit 11 sets the amount of X-rays with which the patient P is to be irradiated by adjusting a tube voltage and a tube current, which are supplied to the X-ray tube 12a under the control of a scan control circuit 33 described later.

[0117] Furthermore, the X-ray irradiation control circuit 11 switches a part 12b. The X-ray irradiation control circuit 11 also sets an irradiation area (a fan angle or a cone angle) of X-ray radiation by adjusting the aperture of a collimator 12c. It should be noted that in the present embodiment, this can be arranged such that more than one type of wedge 12b is switched manually by an operator.

[0118] The X-ray generating device 12 is a device which generates X-ray radiation and emits the generated X-ray radiation onto the patient P and comprises the X-ray tube 12a, the wedge 12b and the collimator 12c.

[0119] The X-ray tube 12a is a vacuum tube that irradiates the patient P with an X-ray beam by means of a high voltage supplied under the control of the X-ray irradiation control circuit 11. The X-ray beam is directed onto the patient P by a rotation of the rotating frame 15. The X-ray tube 12a generates an X-ray beam that emits in a fan angle and a cone angle. For example, the X-ray tube 12a can continuously emit X-rays around the entire patient P for a complete reconstruction, or it can continuously emit X-rays in an irradiation area (180 degrees + fan angle), thus enabling a partial reconstruction by the control of the X-ray irradiation control circuit 11.Furthermore, the X-ray tube 12a can emit X-rays with interruptions (pulsed X-rays) at a predetermined position (tube position) by means of the X-ray irradiation control circuit 11. The X-ray irradiation control circuit 11 can also modulate the intensity of the X-rays emitted by the X-ray tube 12a. For example, the X-ray irradiation control circuit 11 increases the intensity of the X-rays emitted by the X-ray tube 12a at a specific tube position and decreases the intensity of the X-rays emitted by the X-ray tube 12a in a different region than that specific tube position.

[0120] The wedge 12b is an X-ray filter for adjusting the amount of X-ray radiation emitted by the X-ray tube 12a. Specifically, the wedge 12b is a filter through which the X-ray radiation emitted by the X-ray tube 12a passes to be attenuated, so that the X-ray radiation directed at the patient P from the X-ray tube 12a has a predetermined distribution. For example, the wedge 12b is a filter obtained by processing aluminum to have a predetermined aiming angle and thickness. The wedge is also called a wedge filter or butterfly filter.

[0121] The collimator twelve c is a slot for narrowing an irradiation area of ​​an X-ray radiation, the amount of which is set by the wedge 12b, by the control of the X-ray irradiation control circuit 11.

[0122] The scaffold drive circuit 16 rotates the X-ray generating device twelve and the detector 13 on a circular path around the patient P in the center by operating the rotating frame 15.

[0123] The detector 13 is a two-dimensional array detector (surface detector that detects X-rays that have passed through the patient P) and has rows of detection devices in which X-ray detectors for multiple channels are arranged aligned along a Z-axis direction. In particular, the detector 13 has X-ray detector devices arranged in multiple rows of 320 rows along the Z-axis direction and is, for example, suitable for detecting X-rays that have passed through the patient P over a wide area, such as an area encompassing the lungs and heart of the patient P. The Z-axis direction specifies a direction of rotation about the central axis of the rotating frame 15 in a state where the frame 10 is not inclined.

[0124] The data acquisition circuit 14 is a data acquisition system (DAS) and collects projection data from X-ray detection data recorded by the detector 13. For example, the data acquisition circuit 14 performs gain processing, analog-to-digital (A / D) conversion processing, sensitivity correction processing, and similar operations on X-ray intensity distribution data detected by the detector 13 to generate projection data and transmits the generated projection data to the console 30, which will be described later. For example, if X-rays are continuously emitted by the X-ray tube 12a while the rotating frame 15 rotates, the data acquisition circuit 14 collects a set of projection data covering the entire circumference (360 degrees). Furthermore, the data acquisition circuit 14 transmits the respective collected projection data associated with a specific tube position to the console 30, which will be described later.The tube position is information that specifies the projection direction of the projection data. It should be noted that the sensitivity correction processing from channels is performed by a new processing circuit 34, which will be described later.

[0125] The table device 20 is a device on which the patient P is positioned, and, as in Fig. Figure 13 shows a table drive device 21 and a tabletop 22. The table drive device 21 moves the tabletop 22 in the Z-axis direction and moves the patient into the rotating frame 15. The tabletop 22 is a platform onto which the patient P is placed. Although it has been explained that a change in the relative position of the frame 10 and the tabletop 22 is achieved by controlling the tabletop 22 in the present embodiment, the embodiments are not limited to this. For example, if the frame 10 is itself driven, the change in the relative position of the frame 10 and the tabletop 22 can be achieved by controlling a movement of the frame 10.

[0126] For example, the scaffold 10 rotates the rotation frame 15 while the tabletop 22 is moved, performing a helical scan in which the patient is scanned in a helical pattern. Alternatively, the scaffold 10 performs a conventional scan in which the patient P is scanned in a circular motion by rotating the rotation frame 15 while the patient P's position is fixed after the tabletop 22 has been moved. Alternatively, the scaffold 10 performs a stepwise acquisition in which the conventional scan is performed in more than one scan area while the position of the tabletop 22 is changed at regular intervals.

[0127] Console 30 is a device that accommodates an operator performing an operation on the X-ray CT device 100 and reconstructs X-ray CT image data using projection data collected by the scaffold 10. Console 30 comprises, as shown in Fig. 13 shown, an input interface 31, a display 32, the scan control circuit 33, the new processing circuit 34, a memory 35, an image reconstruction circuit 36 ​​and a processing circuit 37.

[0128] The input interface 31 is used by a mouse, a keyboard, a tractor, a switch, a button, a joystick, a touchpad (where an input operation is performed by touching a user surface), a touchscreen (where a display screen and a touchpad are integrated), a non-contact input interface using an optical sensor, a voice input interface, and similar devices. It is used by an operator of the X-ray CT device 100 to input various types of instructions and settings. The input interface 31 is connected to the processing circuit 37 and converts a received input operation into an electrical signal for output to the processing circuit 37. The input interface 31 in the present application is not limited to one with a physical control element such as a mouse and a keyboard.For example, a processing circuit which receives an electrical signal which is used for an input operation from an external input device which is separate from the medical X-ray CT device 100 and which outputs this electrical signal to the processing circuit 37 is also included in the examples of the input interface 31.

[0129] For example, input interface 31 accepts an imaging condition for CT image data, a reconstruction condition at the time of reconstruction of CT image data, an image processing condition for CT image data, and similar operations from the operator. Furthermore, input interface 31 accepts an operation to select an examination for patient P. Additionally, input interface 31 accepts a determination operation to identify a section on an image.

[0130] Display 32 is a monitor used by an operator to show image data generated from CT image data to the operator, or a graphical user interface (GUI) for receiving various types of instructions and settings, and similar information from the operator via input interface 31, which controls the processing circuit 37. In addition, display 32 shows a plan screen of a scan plan, a screen during a scan, and similar information.

[0131] The scan control circuit 33 controls a collective processing of projection data in the scaffold 10 by controlling an operation of the X-ray irradiation control circuit 11, the scaffold drive circuit 16, the data collection circuit 14 and the table drive device 21 under the control of the processing circuit 37. In particular, the scan control circuit 33 controls an imaging to collect a positioning image (scan image) and a processing of projection data in an actual imaging (scan) to collect an image to be used for a diagnosis.

[0132] The new processing circuit 34 performs correction processing, such as logarithmic conversion processing, offset correction, sensitivity correction, and radiation hardening correction, on the projection data generated by the data collection circuit 14 to produce corrected projection data. In particular, the new processing circuit 34 generates corrected projection data for each element of the projection data of the positioning error image generated by the data collection circuit 14 and of projection data collected in the actual image, for storage in the memory 35.

[0133] Memory 35 stores the projection data generated by the new processing circuit 34. Specifically, memory 35 stores the projection data of a positioning image and the projection data for a diagnosis, which are collected during the actual imaging process generated by the new processing circuit 34. Furthermore, memory 35 stores CT image data reconstructed by the image reconstruction circuit 36, which will be described later. Additionally, memory 35 stores, as needed, a processing result from the processing circuit 37, which will be described later.

[0134] The image reconstruction circuit 36 ​​reconstructs X-ray CT image data by using the projection data stored in its memory. Specifically, the image reconstruction circuit 36 ​​reconstructs CT image data from each element of the projection data of the positioning image and the projection data of an image used for diagnosis. Various methods are available as reconstruction techniques, and backprojection processing is one example. Furthermore, backprojection processing can, for example, be applied using filtered backprojection (BIP). Alternatively, the image reconstruction circuit 36 ​​can reconstruct CT image data using a successive approximation technique.

[0135] Furthermore, the image reconstruction circuit 36 ​​generates image data by performing various types of image processing on CT image data. The reconstruction circuit 36 ​​stores the reconstructed CT image data and the image data generated by various types of image processing in memory 35.

[0136] The processing circuit 37 performs overall control of the X-ray CT scanner 100 by controlling the operation of the frame 10, the table 20, and the console 30. Specifically, the processing circuit 37 controls a CT scan performed in the frame 10 by controlling the scan control circuit 33. Furthermore, the processing circuit 37 controls the image reconstruction processing and image generation processing in the console 30 by controlling the image reconstruction circuit 36. Finally, the processing circuit 37 controls the display of various types of image data stored in the memory 35 on the display 32.

[0137] Furthermore, for the processing circuit 37 a control function 37a, an analysis function 37b, a detection function 37c, a generation function 37d and a display control function 37e are provided, as in Fig. Figure 13 shows that control function 37a performs overall control of the X-ray CT device 100 and performs processing similar to that of control function 351, described above, when generating a color image. Analysis function 37b performs processing similar to that of analysis function 352, described above. Acquisition function 37c performs processing similar to that of acquisition function 353, described above. Generation function 37b performs processing similar to that of generation function 354, described above. Display control function 37e performs processing similar to that of display control function 355, described above.

[0138] Although the above embodiments describe an example in which the respective processing functions are implemented by individual processing circuits (processing circuit 350 and processing circuit 37), the embodiments are not limited to this. For example, the processing circuit described above can be configured by combining several independent processors such that the corresponding processors implement the respective processing functions by executing appropriate programs. Furthermore, the respective processing functions of the processing circuit described above can be suitably implemented by distributing or integrating them across one or more processing circuits.

[0139] Furthermore, the term "processor," as used in the explanation of the respective embodiments described above, refers to a central processing unit (CPU), a graphics processing unit (GPU), or an integrated circuit such as an application-specific integrated circuit (ASIC), a programmable logic device (for example, a simple programmable logic device (SPLD) and a complex programmable logic device (CPLD), and a field-programmable gate array (FPGA). The programs may be designed to be installed directly on a circuit within the processor, rather than being stored in memory. In this case, the processor performs the functions by reading and executing the programs installed on the circuit.The corresponding processors of the present embodiment are not limited to being designed as individual circuits per processor, but can also be designed as one processor by combining several independent circuits to implement the functions.

[0140] A medical image processing program, executed by a processor, is initially stored in read-only memory (ROM), storage, or similar media. The medical image processing program can be stored as a file in a format that allows it to be installed or run on a computer-readable storage medium such as a compact floppy disk (CD-ROM), a flexible floppy disk (FD), a writable CD (CD-R), or a digital versatile disk (DVD). Furthermore, the medical image processing program can be stored on a computer connected to a network, such as the internet, and can be made available or distributed via download over the network. For example, the medical image processing program is structured with modules that encompass the respective functions.As actual hardware, a CPU reads and executes the program from a storage medium such as a ROM, and the corresponding modules are thereby loaded into a main memory device and created in the main memory device.

[0141] Furthermore, although it has been explained that a single unit of memory 320 stores the programs which correspond to the respective processing functions in Fig. 2, this can be configured such that several memories are arranged in a distributed manner and the processing circuit 350 reads an associated program from a single memory. Furthermore, although it has been explained that a single unit of memory 35 contains the data for the respective processing functions in Fig.13. If the corresponding programs are stored, they can be designed such that several memories are arranged in a distributed manner and the processing circuit 37 reads a corresponding program from a single memory.

[0142] According to at least the embodiments described above, a color image can be displayed, which facilitates the observation of an index relating to blood flow.

Claims

[1] Medical image processing device (30, 300) with a processing circuit (37, 350) designed to Acquiring image data that includes a patient’s blood vessel, Acquiring an index value regarding a blood flow at each position of the blood vessel by performing a fluid analysis of a structure of the blood vessel included in the acquired image data, Detecting switching information for determining a display mode of a color image in which a value of an index relating to a blood flow or a variable dependent thereon is indicated by color information, based on the switching information, setting at least one reference value at which the color changes as an edge, Generating a result image using the set reference value for an image indicating a blood vessel of the patient, and Cause an ad to show the result image. [2] The medical image processing apparatus according to claim 1, wherein the processing circuit is configured to set the reference value of the index value according to the switching information and generate a color image in which colors are changed at the set reference value as an edge. [3] The medical image processing apparatus according to claim 1, wherein the processing circuit is configured to set the reference value of the index value according to the switching information and generate a color image in which a brightness of a color is changed at the set reference value as an edge. [4] The medical image processing apparatus according to claim 1, wherein the processing circuit is configured to set the reference value of the index value according to the switching information and generate a color image in which a transparency is changed at the set reference value as a border. [5] The medical image processing apparatus according to claim 2, wherein the processing circuit is configured to set the reference value for each type of the index value included in the switching information. [6] The medical image processing apparatus according to claim 2, wherein the processing circuit is configured to generate a color image in which an index value within a predetermined range is highlighted from the index values based on the reference value. [7] The medical image processing apparatus according to claim 1, wherein the processing circuit is configured to generate a color image in which an internal portion of the blood vessel in the image indicating the patient's blood vessel is represented by a color corresponding to an index value regarding blood flow at each position. [8] The medical image processing apparatus according to claim 1, wherein the processing circuit is configured to generate a color image in which a line along the blood vessel in the image indicating the patient's blood vessel is represented by a color corresponding to an index value regarding blood flow at each position in a length direction of the blood vessel. [9] The medical image processing apparatus according to claim 1, wherein the processing circuit is configured to acquire examination information as the switching information, the examination information indicating whether an examination for the patient is an urgent examination or a normal examination different from the urgent examination. [10] The medical image processing apparatus according to claim 1, wherein the processing circuit is configured to acquire examination information as the switching information, the examination information indicating a total number of times of examination for acquiring an index of blood flow for the patient. [11] The medical image processing apparatus according to claim 1, wherein the processing circuit is configured to acquire patient information as the switching information, the patient information indicating a body type of the patient. [12] The medical image processing apparatus according to claim 1, wherein the processing circuit is configured to acquire examination information as the switching information, the examination information indicating an examination result of the patient. [13] The medical image processing apparatus according to claim 1, wherein the processing circuit is configured to acquire, as the switching information, information of an image displayed together with the index value. [14] The medical image processing apparatus according to claim 13, wherein the processing circuit is configured to acquire information of a position determined on the image as the switching information. [15] The medical image processing apparatus according to claim 1, wherein the processing circuit is configured to acquire information of an application used together with displaying the index value as the switching information. [16] The medical image processing apparatus according to claim 1, wherein the processing circuit is configured to acquire information indicating a display purpose of the index value as the switching information. [17] Medical image processing device according to claim 1, wherein the processing circuit is configured to Detecting a position on the blood vessel at which an index value is an identical value to a reference value of the index value from index values at respective positions of the blood vessel as the switching information, and Creating a color image in which a color arrangement is changed according to a position on the blood vessel in which an index value is an identical value to a reference value of the index value from index values at respective positions of the blood vessel. [18] X-ray computed tomography (CT) device comprising a processing circuit designed to Acquiring image data that includes a patient’s blood vessel, Acquiring an index value regarding a blood flow at each position of the blood vessel by performing a fluid analysis of a structure of the blood vessel included in the acquired image data, Detecting switching information for determining a display mode of a color image in which a value of an index relating to a blood flow or a variable dependent thereon is indicated by color information, based on the switching information, setting at least one reference value at which the color changes as an edge, Generating a color image using the set reference value for an image indicating a blood vessel of the patient, and Cause a display to show the color image. [19] Medical image processing method, comprising: Acquiring image data comprising a patient's blood vessel; Acquiring an index value regarding a blood flow at each position of the blood vessel by performing a fluid analysis of a structure of the blood vessel included in the acquired image data; detecting switching information for determining a display mode of a color image in which a value of an index relating to a blood flow or a quantity dependent thereon is indicated by color information; based on the switching information, setting at least one reference value at which the color changes as an edge; Generating a color image using the reference value for an image indicating a blood vessel of the patient; and Cause a display to show the color image.

Images