Medical image processing device and medical image processing program

Abstract

To provide an index value based on the distribution of a contrast medium.SOLUTION: A medical image processing device according to an embodiment comprises a detection unit, a setting unit, and a calculation unit. The detection unit detects a contrast medium out of a medical image. The setting unit sets a first region of interest and a second region of interest to the medical image. The calculation unit calculates a density ratio between the density of the contrast medium included in the first region of interest and the density of the contrast medium included in the second region of interest.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The embodiments disclosed in the present specification and drawings relate to a medical image processing device and a medical image processing program. [Background technology]

[0002] Conventionally, ultrasound diagnostic devices have performed a contrast echo method called contrast harmonic imaging (CHI). In contrast echo method, for example, in examinations of the heart, liver, etc., an imaging is performed by injecting a contrast agent into a vein. Most contrast agents used in contrast echo method use microbubbles as a reflection source. For example, contrast echo method can clearly depict blood vessels in a subject.

[0003] There is also a technology that tracks individual microbubbles (hereinafter simply referred to as "bubbles") contained in a contrast agent on time-series images to display the trajectory of the bubbles. This technology calculates the movement vector of each bubble, making it possible to analyze the speed and direction of movement of the bubbles. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2000-126182 [Patent Document 2] Japanese Patent Application Publication No. 2018-015155 Summary of the Invention [Problem to be solved by the invention]

[0005] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to provide an index value based on the distribution of a contrast agent. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described below can also be positioned as other problems. [Means for solving the problem]

[0006] A medical image processing apparatus according to an embodiment includes a detection unit, a setting unit, and a calculation unit. The detection unit detects a contrast agent from a medical image. The setting unit sets a first region of interest and a second region of interest in the medical image. The calculation unit calculates a density ratio between the density of the contrast agent contained in the first region of interest and the density of the contrast agent contained in the second region of interest. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus according to an embodiment. [Figure 2] FIG. 2 is a flowchart for explaining the processing procedure in the ultrasound diagnostic apparatus according to the embodiment. [Figure 3] FIG. 3 is a diagram for explaining the processing of the setting function and the first calculation function according to the embodiment. [Figure 4] FIG. 4 is a diagram for explaining the process of the tracking function according to the embodiment. [Figure 5] FIG. 5 is a diagram for explaining the processing of the second calculation function according to the embodiment. [Figure 6] FIG. 6 is a diagram for explaining the processing of the second calculation function according to the embodiment. [Figure 7A] FIG. 7A is a diagram for explaining the processing of the second calculation function according to the embodiment. [Figure 7B] FIG. 7B is a diagram for explaining the processing of the second calculation function according to the embodiment. [Figure 8] FIG. 8 is a diagram for explaining the processing of the second calculation function according to the embodiment. [Figure 9A] FIG. 9A is a diagram for explaining the processing of the display control function according to the embodiment. [Figure 9B] FIG. 9B is a diagram for explaining the processing of the display control function according to the embodiment. [Figure 10] FIG. 10 is a block diagram showing an example of the configuration of a medical image processing apparatus according to another embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, a medical image processing apparatus and a medical image processing program according to an embodiment will be described with reference to the drawings. Note that the embodiments are not limited to the following embodiments. Furthermore, the content described in one embodiment can, in principle, be applied to other embodiments as well.

[0009] In the following embodiments, an ultrasound diagnostic apparatus will be described as an example of a medical image processing apparatus, but the embodiments are not limited thereto. For example, in addition to an ultrasound diagnostic apparatus, other medical image processing apparatuses may be used, such as an X-ray diagnostic apparatus, an X-ray CT (Computed Tomography) apparatus, an MRI (Magnetic Resonance Imaging) apparatus, a SPECT (Single Photon Emission Computed Tomography) apparatus, a PET (Positron Emission Computed Tomography) apparatus, a SPECT-CT apparatus in which a SPECT apparatus and an X-ray CT apparatus are integrated, a PET-CT apparatus in which a PET apparatus and an X-ray CT apparatus are integrated, or a group of these apparatuses. Furthermore, the medical image processing apparatus is not limited to a medical image diagnostic apparatus, and any information processing apparatus may be used.

[0010] (Embodiment) 1 is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus 1 according to an embodiment. As shown in FIG. 1, the ultrasound diagnostic apparatus 1 according to the embodiment includes an apparatus main body 100, an ultrasound probe 101, an input device 102, and a display 103. The ultrasound probe 101, the input device 102, and the display 103 are connected to the apparatus main body 100. Note that a subject P is not included in the configuration of the ultrasound diagnostic apparatus 1.

[0011] The ultrasonic probe 101 has a plurality of transducers (for example, piezoelectric transducers), which generate ultrasonic waves based on drive signals supplied from a transmission / reception circuit 110 included in the device main body 100, which will be described later. The plurality of transducers included in the ultrasonic probe 101 also receive reflected waves from the subject P and convert them into electrical signals. The ultrasonic probe 101 also has a matching layer provided on the transducer, a backing material that prevents ultrasonic waves from propagating backward from the transducer, and the like.

[0012] When ultrasonic waves are transmitted from the ultrasonic probe 101 to the subject P, the transmitted ultrasonic waves are reflected successively by discontinuous surfaces of acoustic impedance in the tissues of the subject P, and are received as reflected wave signals (echo signals) by multiple transducers of the ultrasonic probe 101. The amplitude of the received reflected wave signals depends on the difference in acoustic impedance at the discontinuous surfaces where the ultrasonic waves are reflected. When the transmitted ultrasonic pulses are reflected by the surface of a moving blood flow, heart wall, or the like, the reflected wave signals undergo a frequency shift due to the Doppler effect, depending on the velocity component of the moving object in the direction of ultrasonic transmission.

[0013] The embodiment is applicable to any of the cases where the ultrasonic probe 101 shown in FIG. 1 is a one-dimensional ultrasonic probe in which a plurality of piezoelectric vibrators are arranged in a row, a one-dimensional ultrasonic probe in which a plurality of piezoelectric vibrators arranged in a row are mechanically oscillated, and a two-dimensional ultrasonic probe in which a plurality of piezoelectric vibrators are arranged two-dimensionally in a lattice pattern.

[0014] The input device 102 includes a mouse, keyboard, buttons, panel switches, a touch command screen, a foot switch, a trackball, a joystick, etc., and receives various setting requests from the operator of the ultrasound diagnostic device 1 and transfers the received setting requests to the device main body 100.

[0015] The display 103 displays a GUI (Graphical User Interface) that allows the operator of the ultrasound diagnostic device 1 to input various setting requests using the input device 102, and displays ultrasound image data generated in the device main body 100, etc.

[0016] The device main body 100 is a device that generates ultrasound image data based on reflected wave signals received by the ultrasound probe 101, and as shown in Fig. 1, has a transmission / reception circuit 110, a signal processing circuit 120, an image generation circuit 130, an image memory 140, a storage circuit 150, and a processing circuit 160. The transmission / reception circuit 110, the signal processing circuit 120, the image generation circuit 130, the image memory 140, the storage circuit 150, and the processing circuit 160 are connected to each other so that they can communicate with each other.

[0017] The transmission / reception circuit 110 includes a pulse generator, a transmission delay unit, a pulser, etc., and supplies a drive signal to the ultrasonic probe 101. The pulse generator repeatedly generates rate pulses at a predetermined rate frequency to form transmitted ultrasonic waves. The transmission delay unit focuses the ultrasonic waves generated from the ultrasonic probe 101 into a beam and provides a delay time for each piezoelectric transducer required to determine the transmission directivity to each rate pulse generated by the pulse generator. The pulser applies a drive signal (drive pulse) to the ultrasonic probe 101 at a timing based on the rate pulse. In other words, the transmission delay unit changes the delay time provided to each rate pulse to arbitrarily adjust the transmission direction of the ultrasonic waves transmitted from the piezoelectric transducer surface.

[0018] The transmitter / receiver circuit 110 has a function of instantaneously changing the transmission frequency, transmission drive voltage, etc. in order to execute a predetermined scan sequence based on instructions from the processing circuit 160, which will be described later. In particular, the change in transmission drive voltage is realized by a linear amplifier type oscillation circuit that can instantaneously switch its value, or a mechanism that electrically switches between multiple power supply units.

[0019] The transmission / reception circuit 110 also has a preamplifier, an A / D (Analog / Digital) converter, a reception delay unit, an adder, etc., and performs various processes on the reflected wave signals received by the ultrasound probe 101 to generate reflected wave data. The preamplifier amplifies the reflected wave signals for each channel. The A / D converter performs A / D conversion on the amplified reflected wave signals. The reception delay unit provides the delay time required to determine the reception directivity. The adder performs addition processing on the reflected wave signals processed by the reception delay unit to generate reflected wave data. The addition processing by the adder emphasizes the reflected components from the direction corresponding to the reception directivity of the reflected wave signals, and an overall beam for ultrasound transmission and reception is formed based on the reception directivity and transmission directivity.

[0020] When scanning a two-dimensional region of the subject P, the transmission and reception circuit 110 causes the ultrasonic probe 101 to transmit ultrasonic beams in two-dimensional directions. Then, the transmission and reception circuit 110 generates two-dimensional reflected wave data from the reflected wave signals received by the ultrasonic probe 101. When scanning a three-dimensional region of the subject P, the transmission and reception circuit 110 causes the ultrasonic probe 101 to transmit ultrasonic beams in three-dimensional directions. Then, the transmission and reception circuit 110 generates three-dimensional reflected wave data from the reflected wave signals received by the ultrasonic probe 101.

[0021] The signal processing circuit 120 performs, for example, logarithmic amplification, envelope detection processing, etc. on the reflected wave data received from the transmission / reception circuit 110 to generate data (B-mode data) in which the signal intensity at each sample point is expressed as brightness. The B-mode data generated by the signal processing circuit 120 is output to the image generation circuit 130.

[0022] Furthermore, the signal processing circuit 120 can change the frequency band to be visualized by changing the detection frequency through filter processing. Using this function of the signal processing circuit 120, a contrast echo method, for example, contrast harmonic imaging (CHI), can be performed. That is, the signal processing circuit 120 can separate reflected wave data (harmonic components or sub-harmonic components) whose reflection source is microbubbles (microbubbles) of the contrast agent from reflected wave data of the subject P into which a contrast agent has been injected, and reflected wave data (fundamental wave component) whose reflection source is tissue within the subject P. Thus, the signal processing circuit 120 can extract the harmonic components or sub-harmonic components from the reflected wave data of the subject P and generate B-mode data for generating contrast image data. The B-mode data for generating contrast image data is data in which the signal intensity of the reflected wave whose reflection source is the contrast agent is expressed as brightness. Furthermore, the signal processing circuit 120 can extract fundamental wave components from the reflected wave data of the subject P and generate B-mode data for generating tissue image data.

[0023] When performing CHI, the signal processing circuit 120 can extract harmonic components (higher harmonic components) using a method different from the above-mentioned filter processing method. Harmonic imaging employs an imaging method called the Amplitude Modulation (AM) method, the Phase Modulation (PM) method, or an AMPM method that combines the AM and PM methods. In the AM, PM, and AMPM methods, ultrasonic waves with different amplitudes and phases are transmitted multiple times (at multiple rates) along the same scanning line. This allows the transmission / reception circuit 110 to generate and output multiple pieces of reflected wave data for each scanning line. The signal processing circuit 120 then performs addition and subtraction processing on the multiple pieces of reflected wave data for each scanning line according to the modulation method to extract the higher harmonic components. The signal processing circuit 120 then performs envelope detection processing or the like on the reflected wave data of the higher harmonic components to generate B-mode data.

[0024] For example, when the PM method is performed, the transmission / reception circuitry 110 transmits ultrasound waves of the same amplitude with inverted phase polarity, such as (-1, 1), twice on each scan line according to the scan sequence set by the processing circuitry 160. The transmission / reception circuitry 110 then generates reflected wave data resulting from the transmission of "-1" and reflected wave data resulting from the transmission of "1," and the signal processing circuitry 120 adds these two pieces of reflected wave data together. This removes the fundamental wave component, generating a signal in which the second-order harmonic component remains. The signal processing circuit 120 then performs envelope detection processing or the like on this signal to generate CHI B-mode data (B-mode data for generating contrast-enhanced image data). The CHI B-mode data represents the signal intensity of the reflected wave, which is reflected from a contrast agent as a reflection source, as brightness. Furthermore, when the PM method is performed with the CHI, the signal processing circuitry 120 can generate B-mode data for generating tissue image data by, for example, filtering the reflected wave data resulting from the transmission of "1."

[0025] Furthermore, the signal processing circuit 120 generates data (Doppler data) by extracting motion information based on the Doppler effect of a moving object at each sample point within the scanning region from, for example, the reflected wave data received from the transmitting / receiving circuit 110. Specifically, the signal processing circuit 120 frequency-analyzes velocity information from the reflected wave data, extracts blood flow, tissue, and contrast agent echo components due to the Doppler effect, and generates data (Doppler data) by extracting moving object information such as average velocity, variance, and power for multiple points. Here, the moving object refers to, for example, blood flow, tissue such as the heart wall, or contrast agent. The motion information (blood flow information) obtained by the signal processing circuit 120 is sent to the image generation circuit 130 and displayed in color on the display 103 as an average velocity image, variance image, power image, or a combination of these.

[0026] The image generation circuit 130 generates ultrasound image data from the data generated by the signal processing circuit 120. The image generation circuit 130 generates B-mode image data that represents the intensity of the reflected wave as brightness from the B-mode data generated by the signal processing circuit 120. The image generation circuit 130 also generates Doppler image data that represents moving object information from the Doppler data generated by the signal processing circuit 120. The Doppler image data is velocity image data, variance image data, power image data, or image data that is a combination of these.

[0027] Here, the image generation circuit 130 generally converts (scan converts) a scan line signal sequence of an ultrasonic scan into a scan line signal sequence of a video format typified by a television or the like, and generates ultrasound image data for display. Specifically, the image generation circuit 130 generates ultrasound image data for display by performing coordinate conversion according to the ultrasound scanning form of the ultrasound probe 101. In addition to scan conversion, the image generation circuit 130 also performs various image processing, such as image processing (smoothing processing) that regenerates an average brightness image using multiple image frames after scan conversion, and image processing (edge ​​enhancement processing) that uses a differential filter within the image. In addition, the image generation circuit 130 combines incidental information (text information of various parameters, scales, body marks, etc.) with the ultrasound image data.

[0028] That is, the B-mode data and Doppler data are ultrasound image data before scan conversion processing, and the data generated by the image generation circuit 130 is ultrasound image data for display after scan conversion processing. When the signal processing circuit 120 generates three-dimensional data (three-dimensional B-mode data and three-dimensional Doppler data), the image generation circuit 130 generates volume data by performing coordinate conversion according to the ultrasound scanning form of the ultrasound probe 101. Then, the image generation circuit 130 performs various rendering processes on the volume data to generate two-dimensional image data for display.

[0029] The image memory 140 is a memory that stores image data for display generated by the image generation circuit 130. The image memory 140 can also store data generated by the signal processing circuit 120. The B-mode data and Doppler data stored in the image memory 140 can be called up by the operator after diagnosis, for example, and becomes ultrasound image data for display via the image generation circuit 130.

[0030] The memory circuitry 150 stores control programs for transmitting and receiving ultrasound, image processing, and display processing, as well as various data such as diagnostic information (e.g., patient ID, doctor's findings, etc.), diagnostic protocols, and various body marks. The memory circuitry 150 is also used, as necessary, for storing image data stored in the image memory 140. The data stored in the memory circuitry 150 can be transferred to an external device via an interface (not shown).

[0031] The processing circuitry 160 controls the overall processing of the ultrasound diagnostic apparatus 1. Specifically, the processing circuitry 160 controls the processing of the transmission / reception circuitry 110, the signal processing circuitry 120, and the image generation circuitry 130 based on various setting requests input by the operator via the input device 102 and various control programs and various data read from the storage circuitry 150. The processing circuitry 160 also controls the display 103 to display ultrasound image data for display stored in the image memory 140.

[0032] 1, the processing circuitry 160 executes a detection function 161, a setting function 162, a first calculation function 163, a tracking function 164, a second calculation function 165, and a display control function 166. Here, for example, the processing functions executed by the detection function 161, the setting function 162, the first calculation function 163, the tracking function 164, the second calculation function 165, and the display control function 166, which are components of the processing circuitry 160 shown in FIG. 1, are recorded in the form of a computer-executable program in a storage device (e.g., the storage circuitry 150) of the ultrasound diagnostic apparatus 1. The processing circuitry 160 is a processor that reads each program from the storage device and executes it to realize the function corresponding to each program. In other words, the processing circuitry 160 in a state in which each program has been read has each function shown in the processing circuitry 160 of FIG. 1. The processing functions executed by the detection function 161, the setting function 162, the first calculation function 163, the tracking function 164, the second calculation function 165, and the display control function 166 will be described later.

[0033] In FIG. 1, the processing functions performed by the detection function 161, setting function 162, first calculation function 163, tracking function 164, second calculation function 165, and display control function 166 are described as being realized by a single processing circuit 160, but it is also possible to configure a processing circuit by combining multiple independent processors, and realize each function by each processor executing a program.

[0034] The above has described the basic configuration of the ultrasound diagnostic device 1 according to the embodiment. With this configuration, the ultrasound diagnostic device 1 according to the embodiment can provide an index value based on the distribution of a contrast agent by the processing described below.

[0035] For example, the ultrasound diagnostic device 1 detects and tracks each of the microbubbles used as a contrast agent in the contrast echo method. Then, the ultrasound diagnostic device 1 calculates an index value based on the distribution of the contrast agent based on the detection result and / or tracking result. Note that, hereinafter, the contrast agent will also be referred to as "contrast agent bubbles" or "bubbles."

[0036] In the following embodiment, a case where bubble tracking processing is performed will be described, but the embodiment is not limited to this. For example, even if bubble tracking processing is not performed, it is possible to calculate an index value based on the distribution of the contrast agent.

[0037] In the following embodiment, a case will be described in which the flow of contrast agent is visualized by performing substantially real-time processing on medical images (ultrasound images) captured after injecting a contrast agent into a subject P. However, the embodiment is not limited to this, and it is also possible to perform post-processing on already captured ultrasound images (or reflected wave data, etc.).

[0038] The processing procedure in the ultrasound diagnostic device 1 according to the embodiment will be described with reference to Fig. 2. Fig. 2 is a flowchart for explaining the processing procedure in the ultrasound diagnostic device 1 according to the embodiment. Note that Fig. 2 will be described with reference to Figs. 3 to 9B.

[0039] The processing procedure shown in Fig. 2 is started, for example, when a calculation request for an index value is received from an operator. Note that the processing procedure shown in Fig. 2 does not start and is in a standby state until the calculation request is received.

[0040] 2, the detection function 161 reads out a medical image (step S101). For example, the detection function 161 reads out, as the medical image, a plurality of ultrasound images arranged in time series from the image memory 140. Note that the ultrasound images are, for example, contrast-enhanced images captured by injecting a contrast agent into the subject P.

[0041] In a typical contrast-enhanced echocardiogram, a contrast agent is injected in an amount sufficient to cause microbubbles to overlap each other in order to clearly visualize the blood vessels of the subject P. On the other hand, in this embodiment, if the microbubbles overlap each other, individual bubbles cannot be detected. For this reason, in this embodiment, a smaller amount of contrast agent is injected than in a typical contrast-enhanced echocardiogram. Strictly speaking, the amount of contrast agent is preferably determined according to the blood vessel size and blood flow velocity, but it may also be determined according to the region to be imaged. Furthermore, a method in which the amount of contrast agent is gradually increased during actual injection may also be used.

[0042] Next, the detection function 161 corrects the movement of the tissue (step S102). For example, the detection function 161 calculates a correction amount for matching the coordinate system of the Nth frame ultrasound image with the coordinate system of the N-1th frame ultrasound image. Then, the detection function 161 corrects the coordinate system of the Nth frame ultrasound image using the calculated correction amount. The detection function 161 corrects the movement of the tissue for each of the multiple ultrasound images arranged in chronological order.

[0043] Then, the detection function 161 removes harmonic components based on the fixed position (step S103). For example, the detection function 161 removes harmonic components based on the fixed position from the ultrasound image after the tissue movement has been corrected based on statistical processing of signals in the frame direction. The detection function 161 removes harmonic components based on the fixed position from each of the multiple ultrasound images arranged in time series.

[0044] Then, the detection function 161 detects the contrast agent (bubbles) (step S105). For example, the detection function 161 detects the contrast agent from the medical image. As a specific example, the detection function 161 detects, as the bubble position, an area having a brightness value equal to or greater than a predetermined threshold in the ultrasound image from which the harmonic components have been removed. The detection function 161 detects bubbles in each of the multiple ultrasound images arranged in time series. Note that the method for detecting bubbles is not limited to this, and they can be detected by known detection processing, such as image analysis processing using the shape of the bubbles.

[0045] Then, the setting function 162 sets a region of interest (ROI) (step S105). For example, the setting function 162 sets a first region of interest and a second region of interest for the medical image. Here, the first region of interest and the second region of interest are regions that at least partially overlap each other. More preferably, the first region of interest is a region that includes the second region of interest. The processing of the setting function 162 will be described later with reference to FIG. 3.

[0046] Then, first calculation function 163 calculates the density and density ratio of the contrast agent (step S106). For example, first calculation function 163 counts the number of bubbles in the first region of interest and the number of bubbles in the second region of interest. Then, first calculation function 163 calculates the bubble density in the first region of interest based on the number of bubbles in the first region of interest and the area of ​​the first region of interest. Also, first calculation function 163 calculates the bubble density in the second region of interest based on the number of bubbles in the second region of interest and the area of ​​the second region of interest. Then, first calculation function 163 calculates the density ratio between the density of the contrast agent contained in the first region of interest and the density of the contrast agent contained in the second region of interest.

[0047] The processing of the setting function 162 and the first calculation function 163 according to the embodiment will be described with reference to Fig. 3. Fig. 3 is a diagram for explaining the processing of the setting function 162 and the first calculation function 163 according to the embodiment. Fig. 3 illustrates an example of a contrast image of the Nth frame. In Fig. 3, black circles indicate the positions of individual bubbles.

[0048] 3, the setting function 162 sets a measurement ROI (1) and a measurement ROI (2). Here, the measurement ROI (1) is preferably set along the contour of a structure depicted in a medical image, such as a tumor. For example, the setting function 162 sets the measurement ROI (1) by segmentation processing on an ultrasound image.

[0049] Furthermore, the setting function 162 sets an area that is a predetermined size smaller than the measurement ROI (1) as the measurement ROI (2). For example, the setting function 162 calculates the center (center of gravity) of the measurement ROI (1). Then, the setting function 162 sets the measurement ROI (2) by setting the distance from the center of gravity to each point on the measurement ROI (1) to 50%.

[0050] Then, the first calculation function 163 sets an inner circular region and an outer circular region as measurement ROIs for which index values ​​are to be calculated. Here, the inner circular region is the region inside the measurement ROI (2). Also, the outer circular region is a circular region of the measurement ROI (1) excluding the measurement ROI (2). In other words, the outer circular region is a circular region surrounding the inner circular region. Note that the outer circular region is an example of a first region of interest. Also, the inner circular region is an example of a second region of interest.

[0051] Then, the first calculation function 163 calculates the bubble density [ / cm^2] of each of the inner and outer circular regions using the following formula (1). In formula (1), the "total number of bubbles in the measurement ROI" is the count value of the bubbles detected inside the target region. The "measurement ROI area" is the area inside the target region.

[0052]

number

[0053] For example, in FIG. 3, the number of bubbles in the inner circular region is "3." The first calculation function 163 calculates the bubble density of the inner circular region by dividing "3" by the area of ​​the inner circular region. Also, in FIG. 3, the number of bubbles in the outer circular region is "4." The first calculation function 163 calculates the bubble density of the outer circular region by dividing "4" by the area of ​​the outer circular region.

[0054] Then, the first calculation function 163 calculates the bubble density ratio by taking the ratio of the bubble density in the inner circular region to the bubble density in the outer circular region. For example, the first calculation function 163 calculates the bubble density ratio by dividing the bubble density in the outer circular region by the bubble density in the inner circular region.

[0055] In this way, the first calculation function 163 calculates the bubble density and bubble density ratio in each measurement ROI for each of a plurality of ultrasound images arranged in time series.

[0056] Note that the content described in Fig. 3 is merely an example, and the embodiment is not limited to this. For example, Fig. 3 describes a case where measurement ROI (1) and measurement ROI (2) are automatically set, but they may also be set manually by an operator.

[0057] 3, the case where the measurement ROI (1) is set along the contour of the tumor has been described, but the embodiment is not limited to this. For example, the measurement ROI (1) may be set along the contour of any structure depicted in the medical image, or may be set arbitrarily by the operator regardless of the structure.

[0058] 3, the calculation is performed using the center of gravity of the measurement ROI (1) as the center, but this is not limited to this. For example, the center may be the intersection of the long and short sides of the measurement ROI (1). Furthermore, the center of the measurement ROI (1) does not necessarily have to be set automatically, but may be set manually by the operator.

[0059] 3, the case where measurement ROI (2) is set by setting the distance from the center of gravity to each point on measurement ROI (1) to 50% has been described, but this ratio can be changed arbitrarily. Also, measurement ROI (2) may be set by shortening it by a certain distance instead of setting it by a ratio.

[0060] 3, the outer circular region is set as a circular region of the measurement ROI (1) excluding the measurement ROI (2), but the embodiment is not limited to this. For example, the first calculation function 163 may set the region inside the measurement ROI (1) (including the measurement ROI (2)) as the outer circular region (first region of interest).

[0061] 3, the bubble density ratio is calculated by dividing the bubble density in the outer circular region by the bubble density in the inner circular region, but this is not limiting. For example, the bubble density ratio may be calculated by dividing the bubble density in the inner circular region by the bubble density in the outer circular region.

[0062] Returning to the description of Fig. 2, the tracking function 164 executes a process of tracking the contrast agent (step S107). For example, the tracking function 164 calculates a movement vector representing the movement of the contrast agent by tracking the position of the contrast agent in each of a plurality of medical images arranged in time series.

[0063] The processing of the tracking function 164 according to the embodiment will be described with reference to Fig. 4. Fig. 4 is a diagram for explaining the processing of the tracking function 164 according to the embodiment. Fig. 4 describes a case where movement of a bubble is tracked from the N-1th frame to the Nth frame.

[0064] 4, the tracking function 164 sets a search area (the area indicated by the dashed line in FIG. 4) in the ultrasound image of the Nth frame based on the bubble position in the N-1th frame. This search area is, for example, a rectangular area centered on the bubble position in the N-1th frame, and its size is set based on the distance that the bubble can move during one frame.

[0065] The tracking function 164 then identifies the bubble position within this search area as the bubble position after the movement of the bubble in the N-1th frame, and assigns the same (common) identification information (bubble ID) to both. The tracking function 164 then calculates a vector V representing the movement from the bubble position in the N-1th frame to the bubble position in the Nth frame as the movement vector of this bubble.

[0066] In this way, the tracking function 164 performs tracking processing on all bubbles detected from each of the multiple ultrasound images arranged in time series, thereby enabling the tracking function 164 to track the appearance, movement, and disappearance of each bubble.

[0067] Note that the content described in FIG. 4 is merely an example, and embodiments are not limited thereto. For example, the technology described in Patent Document 2 can be applied as desired for tracking processing. Also, while FIG. 4 describes a case where "one" bubble is detected from the search area in the Nth frame, this does not necessarily mean "one." For example, if there are "two or more" bubbles in the search area, it is preferable to identify one bubble based on the movement distance and shape similarity of the bubbles. Also, if there are no bubbles in the search area, it is preferable to identify the bubble as having disappeared.

[0068] Returning to the description of FIG. 2, second calculation function 165 calculates the inflow / outflow ratio of the contrast agent (step S108). For example, second calculation function 165 identifies whether each bubble in the region of interest is an inflow bubble or an outflow bubble based on the movement vector of each bubble. Then, second calculation function 165 calculates the inflow / outflow ratio of bubbles in the region of interest based on the number of inflow bubbles and the number of outflow bubbles.

[0069] The calculation target region (measurement ROI) for the inflow / outflow ratio is preferably set along the contour of any structure, such as a tumor. Therefore, typically, the calculation target region for the inflow / outflow ratio is preferably the measurement ROI (1) set in step S105, but the embodiment is not limited to this. For example, the calculation target region for the inflow / outflow ratio may be set separately from the calculation target region for the bubble density.

[0070] The processing of the second calculation function 165 according to the embodiment will be described with reference to Fig. 5 to Fig. 8. Fig. 5 to Fig. 8 are diagrams for explaining the processing of the second calculation function 165 according to the embodiment.

[0071] First, as shown in Fig. 5, the second calculation function 165 calculates the angle θ for each bubble in the measurement ROI, which represents the movement direction of the bubble relative to the reference position. Here, the reference position (black circle in Fig. 5) corresponds to the center of the measurement ROI, such as the center of the tumor. The method for setting the center of the measurement ROI is the same as that described for Fig. 3. The angle θ is represented by the angle between the line connecting the bubble position in the N-1th frame and the reference position and the movement vector of the bubble in the Nth frame. The angle θ approaches 0° as the bubble approaches the reference position, and approaches 180° (-180°) as the bubble moves away from the reference position.

[0072] Next, as shown in Fig. 6, the second calculation function 165 identifies whether each bubble is an inflowing bubble or an outflowing bubble based on the movement direction of each bubble. For example, the second calculation function 165 identifies bubbles whose angle θ shown in Fig. 5 falls within the range of -60° to 60° (0° to 60°, 300° to 360°) as "inflowing bubbles." Furthermore, the second calculation function 165 identifies bubbles whose angle θ shown in Fig. 5 falls within the range of 120° to 240° (120° to 180°, -180° to -120°) as "outflowing bubbles." Note that the second calculation function 165 does not identify bubbles that do not fall within either angle range as inflowing or outflowing bubbles.

[0073] Then, as shown in FIGS. 7A and 7B, the second calculation function 165 counts inflow bubbles, outflow bubbles, and inflow / outflow bubbles based on either bubble counting method 1 or bubble counting method 2. FIGS. 7A and 7B illustrate a case where a bubble with bubble ID "01" moves from the left side to the right side of a measurement ROI. In FIGS. 7A and 7B, frame (t1), frame (t2), frame (t3), and frame (t4) correspond to four consecutive frames. Furthermore, the notation "frames (t1-t4)" represents a section including frame (t1), frame (t2), frame (t3), and frame (t4).

[0074] FIG. 7A illustrates bubble counting method 1. Bubble counting method 1 is a counting method that does not use bubble IDs. For example, in frame (t1), the bubble with bubble ID "01" is moving toward the center of the measurement ROI, so it is identified as an "inflowing bubble." Therefore, in frame (t1), the number of inflowing bubbles is "1," the number of outflowing bubbles is "0," and the number of inflowing and outflowing bubbles is "1." Note that the number of inflowing and outflowing bubbles (total number) is the sum of the inflowing and outflowing bubbles.

[0075] In addition, in frame (t2), the bubble with bubble ID "01" is moving toward the center of the measurement ROI, so it is identified as an "inflow bubble." Therefore, in frame (t2), the number of inflow bubbles is "1," the number of outflow bubbles is "0," and the number of inflow / outflow bubbles is "1."

[0076] In addition, in frame (t3), the bubble with bubble ID "01" is moving away from the center of the measurement ROI, so it is identified as an "outflow bubble." Therefore, in frame (t3), the number of inflowing bubbles is "0," the number of outflowing bubbles is "1," and the number of inflowing and outflowing bubbles is "1."

[0077] In addition, in frame (t4), the bubble with bubble ID "01" is moving away from the center of the measurement ROI, so it is identified as an "outflow bubble." Therefore, in frame (t4), the number of inflowing bubbles is "0," the number of outflowing bubbles is "1," and the number of inflowing and outflowing bubbles is "1."

[0078] The cumulative number of incoming bubbles, outgoing bubbles, and incoming / outgoing bubbles in frames (t1 to t4) is calculated by adding up the values ​​for each frame. That is, the cumulative number of incoming bubbles in frames (t1 to t4) is 2, the cumulative number of outgoing bubbles is 2, and the cumulative number of incoming / outgoing bubbles is 4.

[0079] The average number of incoming bubbles, outgoing bubbles, and incoming / outgoing bubbles in frames (t1 to t4) is calculated by dividing the sum (cumulative value) of the values ​​for each frame by the number of frames. In other words, the average number of incoming bubbles in frames (t1 to t4) is "0.5," the average number of outgoing bubbles is "0.5," and the average number of incoming / outgoing bubbles is "1."

[0080] FIG. 7B illustrates bubble counting method 2. Bubble counting method 2 is a counting method that uses bubble IDs. That is, second calculation function 165 uses bubble IDs to eliminate duplicates of the same bubble for calculation. In bubble counting method 2, the values ​​of the number of inflowing bubbles, the number of outflowing bubbles, and the number of inflowing and outflowing bubbles in each frame are the same as in bubble counting method 1, so explanations will be omitted.

[0081] The cumulative value of the number of incoming bubbles in frames (t1 to t4) is calculated by adding up the number of incoming bubbles identified by identification information among the incoming bubbles in frames (t1 to t4). In the example of Figure 7B, there is one incoming bubble in frames (t1 to t4) with a bubble ID of "01". In other words, the cumulative value of the number of incoming bubbles in frames (t1 to t4) is "1".

[0082] Furthermore, the cumulative value of the number of outflowing bubbles in frames (t1 to t4) is calculated by adding up the number of outflowing bubbles identified by identification information among the outflowing bubbles in frames (t1 to t4). In the example of Figure 7B, there is one outflowing bubble in frames (t1 to t4) with a bubble ID of "01". In other words, the cumulative value of the number of outflowing bubbles in frames (t1 to t4) is "1".

[0083] The cumulative number of incoming and outgoing bubbles in frames (t1 to t4) is calculated by adding up the number of incoming and outgoing bubbles in the same interval. In other words, the cumulative number of incoming and outgoing bubbles in frames (t1 to t4) is "2."

[0084] The average number of inflowing bubbles, outflowing bubbles, and inflowing / outflowing bubbles in frames (t1 to t4) is calculated by dividing the sum (cumulative value) of the values ​​for each frame by the number of frames. In other words, the average number of inflowing bubbles in frames (t1 to t4) is 0.25, the average number of outflowing bubbles is 0.25, and the average number of inflowing / outflowing bubbles is 0.5.

[0085] In this way, the second calculation function 165 counts inflow bubbles, outflow bubbles, and inflow / outflow bubbles using bubble counting method 1 or bubble counting method 2. Then, the second calculation function 165 calculates the inflow / outflow ratio for the measurement ROI. Here, the inflow / outflow ratio is a term that encompasses the inflow ratio (inflow bubble ratio) and the outflow ratio (outflow bubble ratio).

[0086] For example, the first calculation function 163 calculates the inflow bubble ratio for a certain measurement ROI using the following formula (2).

[0087]

number

[0088] The calculation of the inflow / outflow ratio will be described using FIG. 8. FIG. 8 illustrates an example of bubbles detected in an arbitrary measurement ROI (circle in FIG. 8) in frame (t5), frame (t6), and frame (t7), and the movement vector of the bubble. Note that in FIG. 8, frame (t5), frame (t6), and frame (t7) correspond to three consecutive frames. Furthermore, the notation "frames (t5-t7)" indicates a section including frame (t5), frame (t6), and frame (t7). Frames (t5-t7) in FIG. 8 are different from frames (t1-t4) in FIGS. 7A and 7B.

[0089] 8, the number of inflowing bubbles is "6," the number of outflowing bubbles is "2," and the number of inflowing and outflowing bubbles is "8." In this case, the second calculation function 165 calculates an inflowing bubble ratio of "0.75" by dividing "6" by "8" based on equation (2).

[0090] Similarly to the inflow bubble ratio, the second calculation function 165 can calculate the outflow bubble ratio. For example, the second calculation function 165 calculates an outflow bubble ratio of "0.25" by dividing the number of outflow bubbles "2" by the number of inflow / outflow bubbles "8".

[0091] In this way, the second calculation function 165 calculates the inflow / outflow ratio of bubbles. Note that the contents described in Figures 5 to 8 are merely examples, and the embodiment is not limited to these. For example, the angle range for identifying inflow bubbles and outflow bubbles described in Figure 6 is merely an example, and can be changed to any angle range.

[0092] Also, in FIG. 7B, the cumulative number of inflowing and outflowing bubbles is calculated by adding up the number of inflowing bubbles and the number of outflowing bubbles, but the embodiment is not limited to this. For example, the number of inflowing and outflowing bubbles may be calculated by adding up the number of inflowing and outflowing bubbles identified by identification information in frames (t1 to t4). In the example of FIG. 7B, the number of inflowing and outflowing bubbles in frames (t1 to t4) is one bubble with bubble ID "01." In other words, the cumulative number of inflowing and outflowing bubbles in frames (t1 to t4) may be calculated as "1."

[0093] 8 illustrates a case where the inflow / outflow ratio is calculated for a section of three frames (t5 to t7), but the present invention is not limited to this. For example, the second calculation function 165 may calculate the inflow / outflow ratio for a section from the start frame to the current (or last) frame among a plurality of ultrasound images arranged in time series, or may calculate the inflow / outflow ratio for an arbitrary section. Furthermore, the second calculation function 165 may calculate the inflow / outflow ratio for an arbitrary frame, not limited to a section. In other words, the second calculation function 165 may calculate the inflow / outflow ratio as a value at a predetermined time phase, or a cumulative value or average value for a predetermined section.

[0094] 8 illustrates a case where a cumulative value or an average value is calculated without using a bubble ID, but the embodiment is not limited to this. For example, the second calculation function 165 may calculate a cumulative value or an average value in a predetermined section by eliminating duplicates of the same bubble. The process of eliminating duplicates of the same bubble is the same as that described in FIG. 7B.

[0095] 8 illustrates a case where the inflow / outflow ratio is calculated for an arbitrary measurement ROI, but the embodiment is not limited to this. For example, the second calculation function 165 may calculate the inflow / outflow ratio for the outer circular region and / or the inner circular region. That is, the second calculation function 165 may calculate the inflow / outflow ratio of the contrast agent in at least one of the first region of interest and the second region of interest based on the movement vector.

[0096] In the above example, the denominator of the inflow bubble ratio and the outflow bubble ratio is the "number of inflowing / outflowing bubbles," but the embodiment is not limited to this. For example, the inflow bubble ratio may be the value obtained by dividing the number of inflow bubbles by the number of outflowing bubbles. The outflow bubble ratio may be the value obtained by dividing the number of outflowing bubbles by the number of inflowing bubbles.

[0097] Returning to the explanation of Fig. 2, the display control function 166 displays the measurement results (step S109). For example, the display control function 166 displays information indicating changes over time in the values ​​calculated by the first calculation function 163 and the second calculation function 165. Specifically, the display control function 166 displays information indicating changes over time in the density or density ratio. The display control function 166 also displays information indicating changes over time in the inflow / outflow ratio.

[0098] 9A and 9B, the processing of the display control function 166 according to the embodiment will be described. Figures 9A and 9B are diagrams for explaining the processing of the display control function 166 according to the embodiment. In Figures 9A and 9B, the horizontal axis corresponds to time (elapsed time), and the vertical axis corresponds to the measurement result.

[0099] 9A, the display control function 166 displays a graph showing changes over time in the bubble density of the inner circular region, the bubble density of the outer circular region, and the bubble density ratio. For example, the display control function 166 generates and displays the graph of FIG. 9A by plotting the bubble density of the inner circular region, the bubble density of the outer circular region, and the bubble density ratio calculated for each frame in chronological order.

[0100] 9B, the display control function 166 displays a graph showing the inflow bubble ratio of each frame and the change over time in the cumulative value of the inflow bubble ratio from the start frame. For example, the display control function 166 generates and displays the graph of FIG. 9B by plotting the inflow bubble ratio calculated for each frame and the cumulative value of the inflow bubble ratio from the start frame in chronological order.

[0101] 9A and 9B are merely examples, and the embodiment is not limited thereto. For example, the display control function 166 can display any index value calculated by the first calculation function 163 and the second calculation function 165 as a graph, in addition to the index values ​​illustrated in FIG. 9A and 9B.

[0102] Furthermore, the display format is not limited to a graph. For example, the display control function 166 can also display the numerical values ​​of each index value as text data (numbers). In this case, although the numerical values ​​for all frames can be displayed as text data, it is preferable to display the numerical values ​​for a representative frame or a frame specified by the operator.

[0103] In this way, the ultrasound diagnostic apparatus 1 according to the embodiment executes the processes of steps S101 to S109 in Fig. 2. The processing procedure shown in Fig. 2 is not limited to the order shown, and can be changed as desired as long as no contradiction occurs in the processing content. For example, the processing of step S106 may be executed after step S107 or step S108.

[0104] As described above, in the ultrasound diagnostic apparatus 1 according to the embodiment, the detection function 161 detects a contrast agent from a medical image. Then, the setting function 162 sets a first region of interest and a second region of interest in the medical image. Then, the first calculation function 163 calculates a density ratio between the density of the contrast agent contained in the first region of interest and the density of the contrast agent contained in the second region of interest. This allows the ultrasound diagnostic apparatus 1 to provide an index value based on the distribution of the contrast agent.

[0105] For example, it is known that in the case of a malignant tumor, a contrast agent that enters the tumor from the outside reaches the tumor's center relatively quickly. On the other hand, it is known that in the case of a benign tumor, even if a contrast agent enters the tumor from the outside, it temporarily remains near the tumor's outer edge and reaches the tumor's center more slowly than in the case of a malignant tumor. Therefore, the ultrasound diagnostic device 1 calculates the bubble densities of an outer circular region including the tumor's outer edge and an inner circular region including the tumor's center, and calculates the ratio between the two (the bubble density ratio). The ultrasound diagnostic device 1 then presents the calculated bubble densities of the outer circular region, the inner circular region, and the bubble density ratio to the operator. This allows the operator to easily determine whether the tumor is benign or malignant.

[0106] Furthermore, in the ultrasound diagnostic apparatus 1 according to the embodiment, the tracking function 164 calculates a movement vector of the contrast agent by tracking the position of the contrast agent in each of a plurality of medical images arranged in time series. Then, the second calculation function 165 calculates the inflow / outflow ratio of the contrast agent in the region of interest based on the movement vector. This allows the ultrasound diagnostic apparatus 1 to provide an index value based on the distribution of the contrast agent.

[0107] For example, it is known that malignant tumors have a larger inflow of blood than benign tumors, and benign tumors have a larger outflow of blood than malignant tumors. Therefore, the ultrasound diagnostic device 1 calculates the inflow / outflow ratio and displays it to the operator. This allows the operator to easily distinguish between benign and malignant tumors.

[0108] In the embodiment, the ultrasound diagnostic device 1 is described as having both the first calculation function 163 and the second calculation function 165 at the same time, but it may be provided with only one of them. If the ultrasound diagnostic device 1 is provided with only the first calculation function 163, it does not need to be provided with the tracking function 164. If the ultrasound diagnostic device 1 is provided with only the second calculation function 165, it is sufficient that the setting function 162 sets at least one region of interest.

[0109] (Variation 1) In the above embodiment, the case where the density and density ratio in a predetermined time phase are calculated has been described, but the embodiment is not limited to this. For example, the first calculation function 163 may calculate a cumulative value or an average value in a predetermined section as the density and density ratio.

[0110] For example, the first calculation function 163 calculates the cumulative density of the outer circular area in any three frames by dividing the number (cumulative value) of bubbles detected in the outer circular area (or inner circular area) during any three frames by the area of ​​the outer circular area (or inner circular area). The first calculation function 163 also calculates the average density of the outer circular area by dividing the cumulative density of the outer circular area in these three frames by the number of frames, "3." Furthermore, the first calculation function 163 calculates the density ratio by taking the ratio of the cumulative density or average density between the outer circular area and the inner circular area.

[0111] That is, the first calculation function 163 can calculate, as the density and density ratio, a value at a predetermined time phase, or a cumulative value or average value in a predetermined section.

[0112] (Variation 2) Furthermore, the first calculation function 163 can calculate the cumulative value or average value in the predetermined section described in the first modification example while eliminating overlaps of the same bubble.

[0113] For example, the first calculation function 163 calculates the cumulative density of the outer circular region in any three frames by dividing the number of bubbles identified by identification information among bubbles detected in the outer circular region (or inner circular region) during any three frames by the area of ​​the outer circular region (or inner circular region).The first calculation function 163 also calculates the average density of the outer circular region by dividing the cumulative density of the outer circular region in these three frames by the number of frames, "3".Furthermore, the first calculation function 163 calculates the density ratio by taking the ratio of the cumulative density or average density between the outer circular region and the inner circular region.

[0114] In this way, the first calculation function 163 can count the number of bubbles identified by the identification information, eliminate duplicates of the same bubble using the bubble ID, and calculate the cumulative value or average value for a specified interval.

[0115] Note that in Modification 2, a bubble ID output by the bubble tracking process is used. Therefore, it is preferable that first calculation function 163 according to Modification 2 executes processing after tracking function 164 executes tracking processing.

[0116] (Other embodiments) In addition to the above-described embodiment, the present invention may be implemented in various different forms.

[0117] (Medical image processing equipment) Furthermore, for example, in the above-described embodiment, the disclosed technology is applied to the ultrasound diagnostic device 1, but the embodiment is not limited to this. For example, the disclosed technology may be applied to a medical image processing device 200. The medical image processing device 200 corresponds to, for example, a workstation or a PACS (Picture Archiving Communication System) viewer. The medical image processing device 200 is an example of an image processing device.

[0118] Fig. 10 is a block diagram showing an example of the configuration of a medical image processing apparatus 200 according to another embodiment. As shown in Fig. 10, the medical image processing apparatus 200 includes an input interface 201, a display 202, a storage circuitry 210, and a processing circuitry 220. The input interface 201, the display 202, the storage circuitry 210, and the processing circuitry 220 are connected to each other so as to be able to communicate with each other.

[0119] The input interface 201 is an input device such as a mouse, keyboard, touch panel, etc., for receiving various instructions and setting requests from an operator. The display 202 is a display device for displaying medical images and a GUI for the operator to input various setting requests using the input interface 201.

[0120] The storage circuitry 210 is, for example, a NAND (Not AND) type flash memory or an HDD (Hard Disk Drive), and stores various programs for displaying medical image data and GUIs, as well as information used by the programs.

[0121] The processing circuitry 220 is an electronic device (processor) that controls the overall processing in the medical image processing apparatus 200. The processing circuitry 220 executes a detection function 221, a setting function 222, a first calculation function 223, a tracking function 224, a second calculation function 225, and a display control function 226. The detection function 221, the setting function 222, the first calculation function 223, the tracking function 224, the second calculation function 225, and the display control function 226 are recorded in the storage circuitry 210 in the form of programs executable by a computer, for example. The processing circuitry 220 reads and executes each program to realize a function corresponding to the read program (the detection function 221, the setting function 222, the first calculation function 223, the tracking function 224, the second calculation function 225, and the display control function 226).

[0122] Note that the processing functions of the detection function 221, the setting function 222, the first calculation function 223, the tracking function 224, the second calculation function 225, and the display control function 226 are similar to the processing functions of the detection function 161, the setting function 162, the first calculation function 163, the tracking function 164, the second calculation function 165, and the display control function 166 shown in Figure 1, so their explanations will be omitted.

[0123] This allows the medical image processing device 200 to provide an index value based on the distribution of the contrast agent. Note that the ultrasound diagnostic device 1 described in the above embodiment corresponds to an ultrasound diagnostic device equipped with the medical image processing device 200.

[0124] The components of each device shown in the figure are conceptual functional units and do not necessarily have to be physically configured as shown. In other words, the specific form of distribution and integration of each device is not limited to that shown, and all or part of each device can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc. Furthermore, all or any part of the processing functions performed by each device can be realized by a CPU and a program analyzed and executed by the CPU, or can be realized as hardware using wired logic.

[0125] Furthermore, among the processes described in the embodiments and modifications, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using a known method.In addition, the information including the processing procedures, control procedures, specific names, various data and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified.

[0126] Furthermore, the medical image processing methods described in the embodiments and modifications can be realized by executing a prepared medical image processing program on a computer such as a personal computer or a workstation. This medical image processing program can be distributed via a network such as the Internet. Furthermore, this medical image processing program can be recorded on a non-transitory computer-readable recording medium such as a hard disk, flexible disk (FD), CD-ROM, MO, or DVD, and executed by being read from the recording medium by a computer.

[0127] Furthermore, in the above-described embodiment and modified examples, "nearly real time" means that each process is performed immediately each time data to be processed is generated. For example, the process of displaying an image in near real time is not limited to the case where the time when the subject is imaged and the time when the image is displayed are exactly the same, but also includes the case where the image is displayed with a slight delay due to the time required for each process, such as image processing.

[0128] It should be noted that the terms "image data" and "image" described in the above embodiment are, strictly speaking, different. In other words, "image data" refers to data in which each pixel position corresponds to a luminance value at that pixel position. Furthermore, an "image" refers to data in which a color corresponding to the luminance value at that pixel position is mapped to that pixel position and displayed on a display device such as a monitor. However, many general image processing techniques affect both "image data" and "images," and few affect only one of them. For this reason, unless otherwise specified, "image data" and "images" may be referred to without a strict distinction.

[0129] According to at least one of the embodiments described above, an index value based on the distribution of a contrast agent can be provided.

[0130] Although several embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, modifications, and combinations of embodiments can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0131] 1. Ultrasound diagnostic equipment 160 Processing Circuit 161 Detection Function 162 Setting Function 163 First calculation function 164 Tracking Function 165 Second calculation function 166 Display Control Function

Claims

1. a detector for detecting individual contrast agent bubbles represented by the medical image; a setting unit that sets a first region of interest and a second region of interest that at least partially overlaps the first region of interest in the medical image; a tracking unit that calculates a movement vector of each bubble by tracking, in time series, each bubble of the contrast agent represented by each of the plurality of medical images arranged in time series; a calculation unit that calculates an inflow / outflow ratio of the bubble in at least one of the first region of interest and the second region of interest based on the movement vector; A medical image processing device comprising:

2. the first region of interest is a region that includes the second region of interest; The medical image processing device according to claim 1 .

3. The calculation unit further calculates a ratio between a density of the bubbles included in the first region of interest and a density of the bubbles included in the second region of interest. The medical image processing device according to claim 1 or 2.

4. Further, a display control unit is provided that displays the information calculated by the calculation unit.

4. The medical image processing device according to claim 1.

5. a detection unit that detects individual contrast agent bubbles represented by each of a plurality of time-series medical images; a setting unit for setting a region of interest in the medical image; a tracking unit that tracks the individual bubbles in each of the time-series medical images between the medical images; a calculation unit that calculates inflow / outflow information based on the number of bubbles flowing into the region of interest and the number of bubbles flowing out of the region of interest based on the tracking result by the tracking unit; A medical image processing device comprising:

6. the inflow / outflow information is an inflow / outflow ratio based on the number of bubbles flowing into the region of interest and the number of bubbles flowing out of the region of interest; Further, a display control unit is provided that displays information indicating a change over time in the inflow / outflow ratio. The medical image processing device according to claim 5 .

7. Detecting individual contrast agent bubbles represented by the medical image; setting a first region of interest and a second region of interest at least partially overlapping the first region of interest in the medical image; Calculating a movement vector of each bubble by tracking the individual contrast agent bubbles represented by each of the plurality of medical images arranged in time series; Calculating an inflow / outflow ratio of the bubble in at least one of the first region of interest and the second region of interest based on the movement vector. A medical image processing program that causes a computer to perform each process.

8. Detecting individual contrast agent bubbles represented by each of a plurality of time-series medical images; setting a region of interest in the medical image; tracking the individual bubbles in each of the time-series medical images between the medical images; Based on the tracking results, flow-in / out information is calculated based on the number of bubbles flowing into the region of interest and the number of bubbles flowing out of the region of interest. A medical image processing program that causes a computer to perform each process.

Images