Medical image processing apparatus, medical image processing method, and 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 from 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 this specification and the drawings relate to a medical image processing apparatus and a medical image processing program.

Background Art

[0002] Conventionally, in an ultrasonic diagnostic apparatus, a contrast echo method called contrast harmonic imaging (CHI) has been performed. In the contrast echo method, for example, in examinations of the heart, liver, etc., a contrast agent is injected from a vein for imaging. Many of the contrast agents used in the contrast echo method use microbubbles as a reflection source. By the contrast echo method, for example, blood vessels in a subject can be clearly depicted.

[0003] In addition, there is a technique for displaying the trajectory of bubbles by tracking each microbubble (hereinafter, also simply referred to as "bubble") contained in a contrast agent on a time-series image. In this technique, the moving speed and moving direction of the bubbles can be analyzed by calculating the moving vector of each bubble.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

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

[0006] The medical image processing apparatus according to the embodiment comprises 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 for the medical image. The calculation unit 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. [Brief explanation of the drawing]

[0007] [Figure 1] Figure 1 is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus according to an embodiment. [Figure 2] Figure 2 is a flowchart illustrating the processing procedure in the ultrasound diagnostic apparatus according to the embodiment. [Figure 3] Figure 3 is a diagram illustrating the processing of the setting function and the first calculation function according to the embodiment. [Figure 4] Figure 4 is a diagram illustrating the processing of the tracking function according to the embodiment. [Figure 5] Figure 5 is a diagram illustrating the processing of the second calculation function according to the embodiment. [Figure 6] Figure 6 is a diagram illustrating the processing of the second calculation function according to the embodiment. [Figure 7A] Figure 7A is a diagram illustrating the processing of the second calculation function according to the embodiment. [Figure 7B] Figure 7B is a diagram illustrating the processing of the second calculation function according to the embodiment. [Figure 8] Figure 8 is a diagram illustrating the processing of the second calculation function according to the embodiment. [Figure 9A] Figure 9A is a diagram illustrating the processing of the display control function according to the embodiment. [Figure 9B] Figure 9B is a diagram illustrating the processing of the display control function according to the embodiment. [Figure 10] Figure 10 is a block diagram showing an example configuration of a medical image processing apparatus according to another embodiment. [Modes for carrying out 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 those described below. Furthermore, the contents described in one embodiment are, in principle, applicable to other embodiments as well.

[0009] In the following embodiments, an ultrasound diagnostic device will be described as an example of a medical image processing device, but the embodiments are not limited to this. For example, in addition to ultrasound diagnostic devices, other medical image processing devices that can be used include X-ray diagnostic devices, X-ray CT (Computed Tomography) devices, MRI (Magnetic Resonance Imaging) devices, SPECT (Single Photon Emission Computed Tomography) devices, PET (Positron Emission Computed Tomography) devices, SPECT-CT devices that integrate a SPECT device and an X-ray CT device, PET-CT devices that integrate a PET device and an X-ray CT device, or groups of these devices. Furthermore, the medical image processing device is not limited to a medical image processing device; any information processing device can be used.

[0010] (Embodiment) Figure 1 is a block diagram showing an example configuration of an ultrasound diagnostic apparatus 1 according to an embodiment. As shown in Figure 1, the ultrasound diagnostic apparatus 1 according to the embodiment includes a 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 main body 100. Note that the subject P is not included in the configuration of the ultrasound diagnostic apparatus 1.

[0011] The ultrasonic probe 101 has multiple transducers (e.g., piezoelectric transducers), which generate ultrasound based on drive signals supplied from a transmitting / receiving circuit 110 in the main body 100 of the device, which will be described later. The multiple transducers of 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 and a backing material to prevent the propagation of ultrasound backward from the transducer.

[0012] When ultrasound is transmitted from the ultrasound probe 101 to the subject P, the transmitted ultrasound is reflected one after another by discontinuities in acoustic impedance within the subject P's internal tissues, and the reflected wave signals (echo signals) are received by multiple transducers of the ultrasound probe 101. The amplitude of the received reflected wave signals depends on the difference in acoustic impedance at the discontinuities where the ultrasound is reflected. Furthermore, when the transmitted ultrasound pulse is reflected by a moving blood flow or the surface of the heart wall, the reflected wave signal undergoes a frequency shift due to the Doppler effect, depending on the velocity component of the moving object relative to the ultrasound transmission direction.

[0013] Furthermore, the embodiment is applicable to any of the following cases where the ultrasonic probe 101 shown in Figure 1 is a one-dimensional ultrasonic probe in which a plurality of piezoelectric transducers are arranged in a line, a one-dimensional ultrasonic probe in which a plurality of piezoelectric transducers arranged in a line are mechanically oscillated, or a two-dimensional ultrasonic probe in which a plurality of piezoelectric transducers are arranged in a grid in two dimensions.

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

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

[0016] The apparatus main body 100 is a device that generates ultrasonic image data based on the reflected wave signals received by the ultrasonic probe 101. As shown in FIG. 1, it 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, signal processing circuit 120, image generation circuit 130, image memory 140, storage circuit 150, and processing circuit 160 are connected to be mutually communicable.

[0017] The transmission / reception circuit 110 has a pulse generator, a transmission delay unit, a pulsar, etc., and supplies a drive signal to the ultrasonic probe 101. The pulse generator repeatedly generates rate pulses for forming transmitted ultrasonic waves at a predetermined rate frequency. Also, the transmission delay unit focuses the ultrasonic waves generated from the ultrasonic probe 101 into a beam shape, and gives the delay time for each piezoelectric vibrator necessary for determining the transmission directivity to each rate pulse generated by the pulse generator. Further, the pulsar applies a drive signal (drive pulse) to the ultrasonic probe 101 at the timing based on the rate pulse. That is, the transmission delay unit arbitrarily adjusts the transmission direction of the ultrasonic waves transmitted from the piezoelectric vibrator surface by changing the delay time given to each rate pulse.

[0018] Furthermore, the transmitting / receiving circuit 110 has the 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 the transmission drive voltage is achieved by a linear amplifier type oscillator circuit that can switch its value instantaneously, or by a mechanism that electrically switches multiple power supply units.

[0019] Furthermore, the transmitting and receiving circuit 110 includes a preamplifier, an A / D (Analog / Digital) converter, a receiving delay unit, an adder, etc., and performs various processing on the reflected wave signal received by the ultrasonic probe 101 to generate reflected wave data. The preamplifier amplifies the reflected wave signal for each channel. The A / D converter performs A / D conversion on the amplified reflected wave signal. The receiving delay unit provides the delay time necessary to determine the receiving directivity. The adder generates reflected wave data by summing the reflected wave signals processed by the receiving delay unit. Through the summing process of the adder, the reflected component from the direction corresponding to the receiving directivity of the reflected wave signal is emphasized, and an overall beam for ultrasonic transmission and reception is formed by the receiving directivity and the transmitting directivity.

[0020] When scanning a two-dimensional area of ​​the subject P, the transmitting / receiving circuit 110 causes the ultrasonic probe 101 to transmit an ultrasonic beam in a two-dimensional direction. The transmitting / receiving circuit 110 then generates two-dimensional reflected wave data from the reflected wave signal received by the ultrasonic probe 101. When scanning a three-dimensional area of ​​the subject P, the transmitting / receiving circuit 110 causes the ultrasonic probe 101 to transmit an ultrasonic beam in a three-dimensional direction. The transmitting / receiving circuit 110 then generates three-dimensional reflected wave data from the reflected wave signal received by the ultrasonic probe 101.

[0021] The signal processing circuit 120 performs logarithmic amplification, envelope detection, and other processes on the reflected wave data received from the transmitting / receiving circuit 110 to generate data (B-mode data) in which the signal intensity for each sample point is represented by 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 filtering. By using the functions of this signal processing circuit 120, contrast-enhanced echo imaging, such as contrast harmonic imaging (CHI), can be performed. That is, the signal processing circuit 120 can separate the reflected wave data of a subject P into two parts: the reflected wave data (harmonic components or divided frequency components) from the microbubbles (contrast agent) that act as the reflecting source, and the reflected wave data (fundamental wave components) from the tissue within the subject P that acts as the reflecting source. As a result, the signal processing circuit 120 can extract the harmonic components or divided frequency components from the reflected wave data of the subject P and generate B-mode data for generating contrast-enhanced image data. The B-mode data for generating contrast-enhanced image data is data in which the signal intensity of the reflected wave with the contrast agent as the reflecting source is represented in terms of brightness. Furthermore, the signal processing circuit 120 can extract the fundamental wave component from the reflected wave data of the subject P and generate B-mode data for generating tissue image data.

[0023] Furthermore, when performing CHI, the signal processing circuit 120 can extract harmonic components using a method different from the filtering method described above. Harmonic imaging employs imaging methods such as amplitude modulation (AM), phase modulation (PM), and the AM / PM method, which combines AM and PM. In the AM, PM, and AM / PM methods, ultrasonic transmissions with different amplitudes and phases are performed multiple times (multiple rates) on the same scan line. As a result, the transmitting / receiving circuit 110 generates and outputs multiple reflected wave data for each scan line. The signal processing circuit 120 then extracts harmonic components by performing addition and subtraction processing on the multiple reflected wave data for each scan line according to the modulation method. The signal processing circuit 120 then generates B-mode data by performing envelope detection processing on the reflected wave data of the harmonic components.

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

[0025] Furthermore, the signal processing circuit 120 generates data (Doppler data) extracted from the reflected wave data received from the transmitting / receiving circuit 110, for example, based on the Doppler effect of moving objects, at each sample point within the scanning area. Specifically, the signal processing circuit 120 performs frequency analysis on 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) extracted for multiple points, including average velocity, dispersion, and power of moving objects. Here, moving objects include, for example, blood flow, tissue such as the heart wall, and contrast agents. 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, dispersion image, power image, or a combination of these images.

[0026] The image generation circuit 130 generates ultrasonic image data from the data generated by the signal processing circuit 120. The image generation circuit 130 generates B-mode image data, which represents the intensity of reflected waves in terms of brightness, from the B-mode data generated by the signal processing circuit 120. The image generation circuit 130 also generates Doppler image data representing moving object information from the Doppler data generated by the signal processing circuit 120. The Doppler image data is either velocity image data, dispersion image data, power image data, or a combination of these.

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

[0028] In other words, the B-mode data and Doppler data are ultrasonic image data before scan conversion processing, while the data generated by the image generation circuit 130 is ultrasonic image data for display after scan conversion processing. When the signal processing circuit 120 generates 3D data (3D B-mode data and 3D Doppler data), the image generation circuit 130 generates volume data by performing coordinate transformation according to the ultrasonic scanning pattern of the ultrasonic probe 101. The image generation circuit 130 then performs various rendering processes on the volume data to generate 2D image data for display.

[0029] The image memory 140 is a memory that stores display image data 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 retrieved by the operator after a diagnosis, for example, and become display ultrasound image data via the image generation circuit 130.

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

[0031] The processing circuit 160 controls the entire processing of the ultrasound diagnostic device 1. Specifically, the processing circuit 160 controls the processing of the transmitting / receiving circuit 110, the signal processing circuit 120, and the image generation circuit 130 based on various setting requests input from the operator via the input device 102, and various control programs and data read from the memory circuit 150. The processing circuit 160 also controls the display of ultrasound image data stored in the image memory 140 on the display 103.

[0032] Furthermore, as shown in Figure 1, the processing circuit 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, each processing function executed by the components of the processing circuit 160 shown in Figure 1—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—is recorded in the storage device (e.g., storage circuit 150) of the ultrasound diagnostic device 1 in the form of a program that can be executed by a computer. The processing circuit 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 circuit 160 in the state where each program has been read has the functions shown in the processing circuit 160 of Figure 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 will be described later.

[0033] In Figure 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. However, it is also acceptable to configure a processing circuit by combining multiple independent processors, with each processor executing a program to realize each function.

[0034] The basic configuration of the ultrasound diagnostic apparatus 1 according to this embodiment has been described above. With this configuration, the ultrasound diagnostic apparatus 1 according to this embodiment can provide index values ​​based on the distribution of contrast agent through the process described below.

[0035] For example, ultrasound diagnostic device 1 detects and tracks each individual microbubble used as a contrast agent in contrast-enhanced ultrasound. Based on the detection and / or tracking results, ultrasound diagnostic device 1 calculates an index value based on the distribution of the contrast agent. In the following, the contrast agent will also be referred to as "contrast agent bubbles" or "bubbles."

[0036] In the following embodiments, we will describe the case in which bubble tracking is performed, but the embodiments are not limited to this. For example, even when bubble tracking is not performed, it is possible to calculate index values ​​based on the distribution of the contrast agent.

[0037] Furthermore, the following embodiment describes a case in which a contrast agent is injected into a subject P and a medical image (ultrasound image) is processed in near real-time to visualize the flow of the contrast agent. However, the embodiment is not limited to this, and it is also possible to process already acquired ultrasound images (or reflected wave data, etc.) retrospectively.

[0038] The processing procedure in the ultrasound diagnostic apparatus 1 according to this embodiment will be explained using Figure 2. Figure 2 is a flowchart for explaining the processing procedure in the ultrasound diagnostic apparatus 1 according to this embodiment. In addition, Figure 2 will be explained with reference to Figures 3 to 9B.

[0039] The processing procedure shown in Figure 2 is initiated, for example, when a request for calculation of an indicator value is received from the operator. Note that the processing procedure shown in Figure 2 does not begin until a calculation request is received; it remains in a waiting state.

[0040] As shown in Figure 2, the detection function 161 reads out medical images (step S101). For example, the detection function 161 reads out multiple ultrasound images arranged in chronological order from the image memory 140 as medical images. The ultrasound images are, for example, contrast-enhanced images taken after injecting a contrast agent into the subject P.

[0041] In conventional contrast-enhanced ultrasound, a sufficient amount of contrast agent is injected so that the microbubbles overlap each other in order to clearly visualize the blood vessels of subject P. However, in this embodiment, if the microbubbles overlap, it becomes impossible to detect individual bubbles. Therefore, in this embodiment, a smaller amount of contrast agent is injected compared to conventional contrast-enhanced ultrasound. The amount of contrast agent is preferably determined according to the diameter of the blood vessels and the blood flow velocity, but it may also be determined according to the imaging site. Alternatively, the amount may be gradually increased during injection.

[0042] Next, the detection function 161 corrects for tissue movement (step S102). For example, the detection function 161 calculates a correction amount to match the coordinate system of the Nth frame ultrasound image to the coordinate system of the N-1 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 for tissue movement for each of the multiple ultrasound images arranged in time series.

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

[0044] The detection function 161 then detects the contrast agent (bubbles) (step S105). For example, the detection function 161 detects the contrast agent from a medical image. Specifically, the detection function 161 detects areas with brightness values ​​above a predetermined threshold in an ultrasound image from which harmonic components have been removed as bubble locations. The detection function 161 detects bubbles for each of multiple ultrasound images arranged in time series. Note that the method of detecting bubbles is not limited to this, and they can be detected by known detection processes, 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 a medical image. Here, the first region of interest and the second region of interest are regions that overlap with each other in at least part. More preferably, the first region of interest is a region that encompasses the second region of interest. The processing of the setting function 162 will be described later in Figure 3.

[0046] The first calculation function 163 then calculates the density and density ratio of the contrast agent (step S106). For example, the 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, the 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. The first calculation function 163 also 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, the 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 explained using Figure 3. Figure 3 is a diagram for explaining the processing of the setting function 162 and the first calculation function 163 according to the embodiment. Figure 3 shows an example of the contrast-enhanced image of the Nth frame. In Figure 3, the black circles indicate the positions of individual bubbles.

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

[0049] Furthermore, the setting function 162 sets a region 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] The first calculation function 163 then sets an inner circle region and an outer circle region as the measured ROI to be used for calculating the index value. Here, the inner circle region is the area inside the measured ROI(2). The outer circle region is the annular area of ​​the measured ROI(1) excluding the measured ROI(2). In other words, the outer circle region is the annular area surrounding the inner circle region. The outer circle region is an example of the first region of interest. The inner circle region is an example of the second region of interest.

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

[0052]

number

[0053] For example, in Figure 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 Figure 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] The first calculation function 163 then calculates the bubble density ratio by taking the ratio of the bubble density of the inner circular region to the bubble density of the outer circular region. For example, the first calculation function 163 calculates the bubble density ratio by dividing the bubble density of the outer circular region by the bubble density of the inner circular region.

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

[0056] The details described in Figure 3 are merely an example, and the embodiments are not limited to this. For example, Figure 3 illustrates a case where measurement ROI(1) and measurement ROI(2) are set automatically, but they may also be set manually by the operator.

[0057] Furthermore, while Figure 3 illustrates the case where the measurement ROI(1) is set along the contour of the tumor, the embodiments are 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 it may be set at the operator's discretion regardless of any structure.

[0058] Furthermore, while Figure 3 illustrates the case where the measurement ROI(1) is calculated using its centroid as the center, this is not the only option. For example, the intersection of the long and short sides of the measurement ROI(1) may be used as the center. Also, the center of the measurement ROI(1) is not necessarily set automatically; it may be set manually by the operator.

[0059] Furthermore, Figure 3 illustrates the case where the measured ROI (2) is set by setting the distance from the center of gravity to each point on the measured ROI (1) to 50%, but this ratio can be changed arbitrarily. Alternatively, instead of setting it by a ratio, the measured ROI (2) can be set by shortening it by a fixed distance.

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

[0061] Furthermore, in Figure 3, the bubble density ratio was calculated by dividing the bubble density of the outer circular region by the bubble density of the inner circular region, but this is not the only option. For example, the bubble density ratio could also be calculated by dividing the bubble density of the inner circular region by the bubble density of the outer circular region.

[0062] Returning to the explanation of Figure 2, the tracking function 164 performs the contrast agent tracking process (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 multiple medical images arranged in time series.

[0063] The processing of the tracking function 164 according to the embodiment will be explained using Figure 4. Figure 4 is a diagram for explaining the processing of the tracking function 164 according to the embodiment. Figure 4 explains the case where the movement of a certain bubble from the N-1 frame to the N frame is tracked.

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

[0065] The tracking function 164 then identifies the bubble positions within this search area as the bubble positions after the movement of the bubble in the N-1 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-1 frame to the bubble position in the N frame, and uses this as the movement vector of the 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. This allows the tracking function 164 to track the occurrence, movement, and disappearance of each bubble.

[0067] It should be noted that the content explained in Figure 4 is merely an example, and the embodiments are not limited to this. For example, the technology described in Patent Document 2 can be arbitrarily applied as the tracking process. Also, although Figure 4 explains the case where "one" bubble is detected in the search area of ​​the Nth frame, it is not necessarily limited to "one". For example, if there are "two or more" bubbles in the search area, it is preferable to identify one bubble based on the distance traveled or the similarity of their shapes. Furthermore, if there are no bubbles in the search area, it is preferable to identify it as a bubble that has disappeared.

[0068] Returning to the explanation of Figure 2, the second calculation function 165 calculates the inflow and outflow ratio of the contrast agent (step S108). For example, the 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, the second calculation function 165 calculates the inflow and outflow ratio of bubbles in the region of interest based on the number of inflow bubbles and the number of outflow bubbles.

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

[0070] The processing of the second calculation function 165 according to this embodiment will be explained using Figures 5 to 8. Figures 5 to 8 are diagrams for explaining the processing of the second calculation function 165 according to this embodiment.

[0071] First, the second calculation function 165 calculates the angle θ for each bubble within the measured ROI, representing the direction of movement of the bubble relative to the reference position, as shown in Figure 5. Here, the reference position (black circle in Figure 5) corresponds to the center of the measured ROI, such as the center of a tumor. The method for setting the center of the measured ROI is the same as explained in Figure 3. The angle θ is represented by the angle between the line connecting the bubble position in frame N-1 and the reference position, and the movement vector of the bubble in frame N. The angle θ becomes closer to 0° as the bubble approaches the reference position, and closer to 180° (-180°) as the bubble moves away from the reference position.

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

[0073] The second calculation function 165 then counts inflow bubbles, outflow bubbles, and inflow / outflow bubbles based on either bubble counting method 1 or bubble counting method 2, as shown in Figures 7A and 7B. Figures 7A and 7B illustrate the case where bubble ID "01" moves from left to right in the figure for a given measurement ROI. In Figures 7A and 7B, frame (t1), frame (t2), frame (t3), and frame (t4) correspond to four consecutive frames. The notation frame (t1~t4) represents the interval including frame (t1), frame (t2), frame (t3), and frame (t4).

[0074] Figure 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 towards the center of the measured ROI and is therefore identified as an "inflow bubble". For this reason, in frame (t1), the number of inflow bubbles is "1", the number of outflow bubbles is "0", and the total number of inflow and outflow bubbles is "1". The total number of inflow and outflow bubbles is the sum of the inflow and outflow bubbles.

[0075] Furthermore, in frame (t2), the bubble with bubble ID "01" is moving towards the center of the measured ROI and is therefore identified as an "inflow bubble". For this reason, in frame (t2), the number of inflow bubbles is "1", the number of outflow bubbles is "0", and the total number of inflow and outflow bubbles is "1".

[0076] Furthermore, in frame (t3), the bubble with bubble ID "01" is identified as an "outflow bubble" because it is moving away from the center of the measured ROI. Therefore, in frame (t3), the number of inflow bubbles is "0", the number of outflow bubbles is "1", and the total number of inflow and outflow bubbles is "1".

[0077] Furthermore, in frame (t4), the bubble with bubble ID "01" is identified as an "outflow bubble" because it is moving away from the center of the measured ROI. Therefore, in frame (t4), the number of inflow bubbles is "0", the number of outflow bubbles is "1", and the total number of inflow and outflow bubbles is "1".

[0078] Furthermore, the number of inflow bubbles, outflow bubbles, and cumulative number of inflow and outflow bubbles in each frame (t1-t4) are calculated by summing the values ​​for each frame. In other words, the cumulative number of inflow bubbles in each frame (t1-t4) is "2", the cumulative number of outflow bubbles is "2", and the cumulative number of inflow and outflow bubbles is "4".

[0079] Furthermore, the number of inflow bubbles, outflow bubbles, and the average number of inflow and outflow bubbles in each frame (t1-t4) are calculated by dividing the sum (cumulative) of the values ​​for each frame by the number of frames. In other words, the average number of inflow bubbles in each frame (t1-t4) is "0.5", the average number of outflow bubbles is "0.5", and the average number of inflow and outflow bubbles is "1".

[0080] Figure 7B describes bubble counting method 2. Bubble counting method 2 is a counting method that uses bubble IDs. In other words, the second calculation function 165 calculates by eliminating duplicates of the same bubble using bubble IDs. Note that in bubble counting method 2, the values ​​for the number of incoming bubbles, outgoing bubbles, and inflow / outgoing bubbles in each frame are the same as in bubble counting method 1, so the explanation is omitted.

[0081] The cumulative number of incoming bubbles in frames (t1-t4) is calculated by summing the number of bubbles identified by the identification information among the incoming bubbles in frames (t1-t4). In the example in Figure 7B, there is one incoming bubble in frames (t1-t4) with bubble ID "01". Therefore, the cumulative number of incoming bubbles in frames (t1-t4) is "1".

[0082] Furthermore, the cumulative number of outflowing bubbles in frames (t1~t4) is calculated by summing the number of outflowing bubbles in frames (t1~t4) that are identified by their identification information. In the example in Figure 7B, there is one outflowing bubble in frames (t1~t4) with bubble ID "01". Therefore, the cumulative number of outflowing bubbles in frames (t1~t4) is "1".

[0083] Furthermore, the cumulative number of inflow and outflow bubbles in a frame (t1~t4) is calculated by adding the number of inflow and outflow bubbles in the same period. In other words, the cumulative number of inflow and outflow bubbles in a frame (t1~t4) is "2".

[0084] Furthermore, the number of inflow bubbles, outflow bubbles, and the average number of inflow and outflow bubbles in each frame (t1-t4) are calculated by dividing the sum (cumulative) value of each frame by the number of frames. In other words, the average number of inflow bubbles in each frame (t1-t4) is "0.25", the average number of outflow bubbles is "0.25", and the average number of inflow and outflow bubbles is "0.5".

[0085] Thus, the second calculation function 165 counts inflow bubbles, outflow bubbles, and inflow / outflow bubbles using either bubble counting method 1 or bubble counting method 2. The second calculation function 165 then calculates the inflow / outflow ratio for the measured 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 given measured ROI using the following formula (2).

[0087]

number

[0088] The calculation of the inflow / outflow ratio will be explained using Figure 8. Figure 8 illustrates the bubbles detected at an arbitrary measurement ROI (circle in Figure 8) and the movement vector of those bubbles in frames (t5), (t6), and (t7). In Figure 8, frames (t5), (t6), and (t7) correspond to three consecutive frames. The notation (t5~t7) represents the interval including frames (t5), (t6), and (t7). Frames (t5~t7) in Figure 8 are different frames from frames (t1~t4) in Figures 7A and 7B.

[0089] In the example shown in Figure 8, the number of inflow bubbles is "6", the number of outflow bubbles is "2", and the total number of inflow and outflow bubbles is "8". In this case, the second calculation function 165 calculates the inflow bubble ratio of "0.75" by dividing "6" by "8" based on equation (2).

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

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

[0092] Furthermore, while Figure 7B illustrates a case where the cumulative number of inflow and outflow bubbles is calculated by summing the number of inflow bubbles and the number of outflow bubbles, the embodiment is not limited to this. For example, the number of inflow and outflow bubbles may be calculated by summing the number of inflow and outflow bubbles in each frame (t1 to t4) that are identified by the identification information. In the example in Figure 7B, the inflow and outflow bubbles in each frame (t1 to t4) are one bubble with bubble ID "01". In other words, the cumulative number of inflow and outflow bubbles in each frame (t1 to t4) may be calculated as "1".

[0093] Furthermore, while Figure 8 illustrates the calculation of the inflow / outflow ratio over a three-frame interval (t5~t7), it is not limited to this. For example, the second calculation function 165 may calculate the inflow / outflow ratio for an interval from the start frame to the current (or last) frame among multiple ultrasound images arranged in time series, or it may calculate the inflow / outflow ratio for any interval. In addition, the second calculation function 165 may calculate the inflow / outflow ratio for any single frame, not limited to an interval. In other words, the second calculation function 165 may calculate the inflow / outflow ratio as a value at a predetermined time phase, or as a cumulative value or average value at a predetermined interval.

[0094] Furthermore, although Figure 8 illustrates the case where cumulative values ​​or average values ​​are calculated without using bubble IDs, the embodiments are not limited to this. For example, the second calculation function 165 may calculate cumulative values ​​or average values ​​in a predetermined interval, excluding duplicates of the same bubble. The process for excluding duplicates of the same bubble is the same as described in Figure 7B.

[0095] Furthermore, while Figure 8 illustrates the calculation of the inflow / outflow ratio for an arbitrary measurement ROI, the embodiments are not limited to this. For example, the second calculation function 165 may also calculate the inflow / outflow ratio for the outer and / or inner circular regions described above. In other words, the second calculation function 165 may calculate the inflow / outflow ratio of the contrast agent in at least one of the first and second regions of interest based on the movement vector.

[0096] Furthermore, while the above example described a case where the denominator of the inflow bubble ratio and outflow bubble ratio is the "number of inflow and outflow bubbles," the embodiments are 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 outflow bubbles. The outflow bubble ratio may be the value obtained by dividing the number of outflow bubbles by the number of inflow bubbles.

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

[0098] The processing of the display control function 166 according to the embodiment will be explained using Figures 9A and 9B. 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] As shown in Figure 9A, the display control function 166 displays a graph showing the changes over time in the bubble density of the inner circle region, the bubble density of the outer circle region, and the bubble density ratio. For example, the display control function 166 generates and displays the graph in Figure 9A by plotting the bubble density of the inner circle region, the bubble density of the outer circle region, and the bubble density ratio calculated for each frame in chronological order.

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

[0101] The contents described in Figures 9A and 9B are merely examples, and the embodiments are 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, not limited to the index values ​​shown in Figures 9A and 9B.

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

[0103] As described above, the ultrasound diagnostic apparatus 1 according to this embodiment performs each of the processes in steps S101 to S109 in Figure 2. Note that the processing procedure shown in Figure 2 is not limited to the order shown and can be arbitrarily changed as long as there is no inconsistency in the processing content. For example, the process in step S106 may be performed after step S107 or step S108.

[0104] As described above, in the ultrasound diagnostic apparatus 1 according to this embodiment, the detection function 161 detects the contrast agent from the medical image. The setting function 162 sets a first region of interest and a second region of interest for the medical image. The 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. As a result, the ultrasound diagnostic apparatus 1 can provide an index value based on the distribution of the contrast agent.

[0105] For example, in malignant tumors, it is known that contrast agents entering from outside the tumor reach the center relatively quickly. On the other hand, in benign tumors, even if contrast agents enter from outside the tumor, they are known to temporarily linger near the outer edge of the tumor and reach the center more slowly compared to malignant tumors. Therefore, the ultrasound diagnostic device 1 calculates the bubble density for the outer circular region including the outer edge of the tumor and the inner circular region including the center of the tumor, and also calculates the ratio between the two (bubble density ratio). The ultrasound diagnostic device 1 then presents the calculated bubble density of the outer circular region, the bubble density of the inner circular region, and the bubble density ratio to the operator. As a result, the operator can easily determine whether the tumor is benign or malignant.

[0106] Furthermore, in the ultrasound diagnostic device 1 according to this embodiment, the tracking function 164 calculates the 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 and outflow ratio of the contrast agent in the region of interest based on the movement vector. As a result, the ultrasound diagnostic device 1 can provide an index value based on the distribution of the contrast agent.

[0107] For example, it is known that malignant tumors have a greater blood inflow than benign tumors, and benign tumors have a greater blood outflow than malignant tumors. Therefore, the ultrasound diagnostic device 1 calculates the inflow / outflow ratio and presents it to the operator. This makes it possible for the operator to easily determine whether the tumor is benign or malignant.

[0108] In this embodiment, the case in which the ultrasound diagnostic device 1 is equipped with both the first calculation function 163 and the second calculation function 165 simultaneously has been described, but it may be equipped with only one of them. If the ultrasound diagnostic device 1 is equipped with only the first calculation function 163, the tracking function 164 does not need to be provided. Also, if the ultrasound diagnostic device 1 is equipped with only the second calculation function 165, the setting function 162 only needs to set at least one region of interest.

[0109] (Variation 1) In the above embodiment, the case of calculating density and density ratio in a predetermined time phase has been described, but the embodiment is not limited thereto. For example, the first calculation function 163 may calculate the cumulative value or average value in a predetermined interval as density and density ratio.

[0110] For example, the first calculation function 163 calculates the cumulative density of the outer circular region over any three frames by dividing the number of bubbles (cumulative value) detected in the outer circular region (or inner circular region) over 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 over 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 and average density between the outer circular region and the inner circular region.

[0111] In other words, the first calculation function 163 can calculate the density and density ratio as values ​​at a predetermined time phase, or as cumulative values ​​or average values ​​at a predetermined interval.

[0112] (Modification 2) Furthermore, the first calculation function 163 can calculate the cumulative value or average value in a predetermined interval, as explained in the modified example 1, while excluding overlaps of the same bubble.

[0113] For example, the first calculation function 163 calculates the cumulative density of the outer circular region over any three frames by dividing the number of bubbles identified by the identification information among the bubbles detected in the outer circular region (or inner circular region) over 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 over 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 and average density between the outer circular region and the inner circular region.

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

[0115] In Modification 2, the bubble ID output by the bubble tracking process is used. Therefore, it is preferable that the first calculation function 163 in Modification 2 is executed after the tracking process by the tracking function 164 has been performed.

[0116] (Other embodiments) In addition to the embodiments described above, the device may be implemented in various other forms.

[0117] (Medical image processing equipment) Furthermore, although the above-described embodiment explained the case in which the disclosed technology is applied to an ultrasound diagnostic apparatus 1, the embodiments are not limited thereto. For example, the disclosed technology may also be applied to a medical image processing apparatus 200. The medical image processing apparatus 200 may correspond to, for example, a workstation or a PACS (Picture Archiving Communication System) viewer. Note that the medical image processing apparatus 200 is just one example of an image processing apparatus.

[0118] Figure 10 is a block diagram showing an example configuration of a medical image processing apparatus 200 according to another embodiment. As shown in Figure 10, the medical image processing apparatus 200 includes an input interface 201, a display 202, a storage circuit 210, and a processing circuit 220. The input interface 201, the display 202, the storage circuit 210, and the processing circuit 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 that receives various instructions and setting requests from the operator, such as a mouse, keyboard, or touch panel. The display 202 is a display device that displays medical images and a GUI for the operator to input various setting requests using the input interface 201.

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

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

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

[0123] As a result, the medical image processing device 200 can provide index values ​​based on the distribution of the contrast agent. 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] Each component of the illustrated device is a functional concept and does not necessarily have to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions. Furthermore, each processing function performed by each device can be implemented, all or any part of it, by a CPU and the program that is analyzed and executed by that CPU, or by 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 may be performed manually, or all or part of the processes described as being performed manually may be performed automatically by known methods. In addition, the processing procedures, control procedures, specific names, and information including various data and parameters shown in the above document and drawings may be changed at will unless otherwise specified.

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

[0127] Furthermore, in the above embodiments and modifications, "approximately real-time" means that each processing is performed immediately each time each piece of data to be processed is generated. For example, the concept of displaying an image in approximately real-time is not limited to cases where the time the subject is imaged and the time the image is displayed perfectly coincide, but also includes cases where the image is displayed with a slight delay due to the time required for each processing step, such as image processing.

[0128] It should be noted that the terms "image data" and "image" used in the above embodiments are strictly different. Specifically, "image data" is a set of coordinates between each pixel position and the brightness value of each pixel position. "Image," on the other hand, is a display on a display device where the color corresponding to the brightness value of each pixel position is mapped to each pixel position. However, many general image processing techniques affect both "image data" and "images," and few affect only one of them. For this reason, unless specifically mentioned, "image data" and "images" may not be strictly distinguished in their usage.

[0129] According to at least one embodiment described above, it is possible to provide index values ​​based on the distribution of the contrast agent.

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

[0131] 1. Ultrasound diagnostic equipment 160 Processing Circuits 161 Detection Function 162 Settings Function 163 First Calculation Function 164 Tracking function 165 Second Calculation Function 166 Display control function

Claims

1. A detection unit for detecting bubbles in a first region of interest of a medical image and bubbles in a second region of interest that overlaps with at least a portion of the first region of interest, A calculation unit calculates a first index value representing the distribution of bubbles in the first region of interest and a second index value representing the distribution of bubbles in the second region of interest based on the detection results from the detection unit, An output unit that outputs information representing the relationship between the first index value and the second index value, Equipped with, The calculation unit calculates the density of bubbles in the first region of interest as the first index value, and calculates the density of bubbles in the second region of interest as the second index value. The output unit outputs the density of bubbles in the first region of interest and the density of bubbles in the second region of interest as information representing the relationship between the first index value and the second index value. Medical image processing equipment.

2. A detection unit for detecting bubbles in a first region of interest of a medical image and bubbles in a second region of interest that overlaps with at least a portion of the first region of interest, A calculation unit calculates a first index value representing the distribution of bubbles in the first region of interest and a second index value representing the distribution of bubbles in the second region of interest based on the detection results from the detection unit, An output unit that outputs information representing the relationship between the first index value and the second index value, Equipped with, Each of the aforementioned medical images arranged in chronological order represents an individual contrast agent bubble. The system further includes a tracking unit that calculates the movement vector of the bubble by tracking it in a time series. The calculation unit calculates the inflow and outflow ratio of the bubble in the first region of interest as the first indicator value based on the movement vector, and calculates the inflow and outflow ratio of the bubble in the second region of interest as the second indicator value. Medical image processing equipment.

3. The aforementioned first area of ​​interest encompasses the entirety of the aforementioned second area of ​​interest. The medical image processing apparatus according to claim 1 or 2.

4. The output unit outputs the density ratio of the bubble density in the first region of interest to the bubble density in the second region of interest as information representing the relationship between the first index value and the second index value. The medical image processing apparatus according to claim 1.

5. The output unit outputs information showing the change over time in the relationship between the bubble density in the first region of interest and the bubble density in the second region of interest, or information showing the change over time in the density ratio between the bubble density in the first region of interest and the bubble density in the second region of interest. The medical image processing apparatus according to claim 4.

6. The output unit outputs information showing the change over time in the relationship between the inflow and outflow ratio of the bubble in the first region of interest and the inflow and outflow ratio of the bubble in the second region of interest. The medical image processing apparatus according to claim 2.

7. The system further includes a setting unit for setting the first region of interest and the second region of interest based on the structures included in the medical image. The medical image processing apparatus according to claim 1 or 2.

8. The structure included in the aforementioned medical image is a tumor. The medical image processing apparatus according to claim 7.

9. A step of detecting bubbles in a first region of interest of a medical image and bubbles in a second region of interest that overlaps with at least a portion of the first region of interest, A calculation step that calculates a first index value representing the distribution of bubbles in the first region of interest and a second index value representing the distribution of bubbles in the second region of interest, based on the detection results from the above detection step. An output step that outputs information representing the relationship between the first index value and the second index value, It has, The calculation step involves calculating the density of bubbles in the first region of interest as the first index value, and calculating the density of bubbles in the second region of interest as the second index value. The output step outputs the density of bubbles in the first region of interest and the density of bubbles in the second region of interest as information representing the relationship between the first index value and the second index value. Medical image processing methods.

10. Computers, A detection unit that detects bubbles in a first region of interest of a medical image and bubbles in a second region of interest that overlaps with at least a portion of the first region of interest. A calculation unit calculates a first index value representing the distribution of bubbles in the first region of interest and a second index value representing the distribution of bubbles in the second region of interest based on the detection results from the detection unit. An output unit that outputs information representing the relationship between the first index value and the second index value. To make it function as, The calculation unit calculates the density of bubbles in the first region of interest as the first index value, and calculates the density of bubbles in the second region of interest as the second index value. The output unit outputs the density of bubbles in the first region of interest and the density of bubbles in the second region of interest as information representing the relationship between the first index value and the second index value. program.

11. A step of detecting a bubble in a first region of interest of a medical image and a bubble in a second region of interest that overlaps with at least a portion of the first region of interest, A calculation step that calculates a first index value representing the distribution of bubbles in the first region of interest and a second index value representing the distribution of bubbles in the second region of interest, based on the detection results from the above detection step. An output step that outputs information representing the relationship between the first index value and the second index value, It has, Each of the aforementioned medical images arranged in chronological order represents an individual contrast agent bubble. The system further includes a tracking step to calculate the movement vector of the bubble by tracking it in a time series, The calculation step involves calculating the inflow / outflow ratio of the bubble in the first region of interest as a first indicator value based on the movement vector, and calculating the inflow / outflow ratio of the bubble in the second region of interest as a second indicator value. Medical image processing methods.

12. A computer, A detection unit that detects bubbles in a first region of interest of a medical image and bubbles in a second region of interest that overlaps with at least a portion of the first region of interest. A calculation unit calculates a first index value representing the distribution of bubbles in the first region of interest and a second index value representing the distribution of bubbles in the second region of interest based on the detection results from the detection unit. An output unit that outputs information representing the relationship between the first index value and the second index value. To make it function as, Each of the aforementioned medical images arranged in chronological order represents an individual contrast agent bubble. By tracking the bubble's movement vector over time, it further functions as a tracking unit that calculates the bubble's movement vector. The calculation unit calculates the inflow and outflow ratio of the bubble in the first region of interest as the first indicator value based on the movement vector, and calculates the inflow and outflow ratio of the bubble in the second region of interest as the second indicator value. program.

Images