Blood flow imaging device and blood flow imaging program

Abstract

To further reduce a blooming artifact in a blood flow image being a Doppler image expressing a blood flow.SOLUTION: A Doppler processing unit 40 generates a Doppler signal on the basis of a reception beam data string obtained with transmission / reception of an ultrasonic wave to / from a subject. A two-dimensional data space is formed by the reception beam data string. A distribution data calculation unit 42 calculates at least one of power of the Doppler signal, a speed of a tissue in the subject and a dispersion of the speed of the tissue in the subject for each data element in the two-dimensional data space on the basis of the Doppler signal. A discrimination index map generation unit 44 generates a discrimination index map expressing a probability of being a blood flow region A in the two-dimensional data space formed by the reception beam data string on the basis of the distribution data for each ROI 52 set in the two-dimensional data space. A blood flow image formation unit 46 forms a blood flow image in which a blooming artifact is reduced on the basis of the Doppler signal and the discrimination index map.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] This specification discloses improvements to a blood flow image forming apparatus and a blood flow image forming program.

Background Art

[0002] An ultrasonic diagnostic apparatus is an apparatus that transmits ultrasonic waves toward a subject, receives reflected waves from scatterers (e.g., tissues in the subject), and forms an ultrasonic image based on the received reflected waves. Various ultrasonic images can be formed in an ultrasonic diagnostic apparatus. For example, an ultrasonic tomographic image (B-mode image) can be formed by measuring the distance to a scatterer from the time required for transmission and reception and the speed of sound and converting the signal intensity (sound pressure) of the reflected wave into luminance.

[0003] As one type of ultrasonic image, there is a Doppler image that represents the movement of tissues in a living body as the subject. As Doppler images, there are color Doppler images formed by a technique called Color Doppler Imaging (CDI) that represents the direction and speed of tissue movement in a living body in color, and power images that represent the power, which is the signal intensity of Doppler signals, in color or the brightness of colors. Doppler images are formed based on the Doppler effect. Specifically, first, multiple ultrasonic transmissions and receptions (packet transmissions and receptions) are performed in a blood flow region from an ultrasonic probe to obtain received signals. Next, the amount of phase rotation (phase change amount) is calculated by autocorrelation operation between the received signals to detect a Doppler shift. A blood flow image is formed by coloring according to the intensity and sign of the obtained Doppler shift, or the intensity of the Doppler signal, and this is superimposed on the B-mode and displayed.

[0004] In the received signals, Doppler shift signals other than blood flow are mixed due to tissue movement, reflection, refraction, scattering, and attenuation of ultrasonic beams by tissue structures such as blood vessel walls. As a result, in a blood flow image, which is a Doppler image representing blood flow, artifacts (false images) may appear where blood flow is displayed in a region where there is no blood flow originally. As an artifact, there is something called a blooming artifact that appears below a blood vessel.

[0005] There is more than one cause of blooming artifacts, but here we will explain some typical causes with reference to Figure 20. The position of a scattering body is determined by the time between the transmission of ultrasound and the reception of the reflected wave from the scattering body by the ultrasound probe (since the velocity of ultrasound is considered constant within the subject, this can be considered as the distance from the ultrasound probe to the scattering body). Here, ultrasound transmitted from the ultrasound probe may be reflected by the blood vessel wall (especially the lower blood vessel wall), and this reflected wave may be further reflected by the blood flow at position S, and the ultrasound probe may receive this reflected wave. The path of the ultrasound and reflected wave is shown by the dashed line in Figure 20. In this case, the ultrasound probe may mistakenly consider the received reflected wave as a reflected wave from position S', which is in the direction of ultrasound transmission and half the distance along the dashed line path. As a result, the blood flow component that should be at position S is plotted at position S', which is the blooming artifact.

[0006] Conventionally, techniques have been proposed to reduce such artifacts. For example, Patent Document 1 describes a technique for reducing blooming artifacts by automatically setting a threshold for the power or velocity variance of the Doppler signal for vascular visualization using statistical values ​​of the power or velocity variance of the entire received signal for one frame corresponding to one ultrasound image. [Prior art documents] [Patent Documents]

[0007] [Patent Document 1] Japanese Patent Publication No. 2021-104301 [Overview of the Initiative] [Problems that the invention aims to solve]

[0008] Blooming artifacts can also be reduced by the technology described in Patent Document 1. However, since the power, velocity, or velocity dispersion of artifacts differs from location to location even within the same frame, artifacts may remain even if a uniform threshold is applied to the entire frame. Therefore, there is a need for new technology that can further reduce blooming artifacts in blood flow images.

[0009] The purpose of the blood flow imaging apparatus disclosed herein is to further reduce blooming artifacts in blood flow images, which are Doppler images representing blood flow. [Means for solving the problem]

[0010] The blood flow imaging apparatus disclosed herein is characterized by comprising: a received beam data acquisition unit that acquires a sequence of received beam data corresponding to each transmitted beam forming the beam scanning plane, generated based on a received signal from an ultrasonic probe that transmits and receives ultrasonic waves to a beam scanning plane within a subject; a distribution data calculation unit that calculates distribution data for each of a plurality of regions of interest set in a two-dimensional data space composed of the received beam data sequence, which is at least one of the power distribution of the Doppler signal obtained from the received beam data, the velocity distribution of the tissue within the subject, or the variance distribution of the velocity of the tissue within the subject; a discrimination index map generation unit that generates a discrimination index map representing the likelihood that a region of interest is a blood flow region in the two-dimensional data space based on the distribution data for each region of interest; and a blood flow imaging unit that forms a blood flow image representing the blood flow within the subject based on the Doppler signal obtained from the received beam data sequence and the discrimination index map.

[0011] The two-dimensional data space, composed of the received beam data stream, can be conceptually divided into a blood flow region corresponding to blood flow (blood vessels), a background region corresponding to subject tissue other than blood flow, and a blooming region located below the blood flow region that causes blooming artifacts in Doppler images. The distribution data of regions of interest set within the blood flow region, the distribution data of regions of interest set within the background region, and the distribution data of regions of interest set within the blooming region have distinct characteristics from each other. Therefore, based on the distribution data of each region of interest, a discriminant index map representing the likelihood of a region being a blood flow region in the two-dimensional data space can be generated. This discriminant index map makes it possible to distinguish between the blood flow region and other regions (i.e., the background region and the blooming region). In other words, based on the discriminant index map, a blood flow image with reduced blooming artifacts can be formed.

[0012] The discriminant index map generation unit may generate the discriminant index map based on the degree of variation of power near the mode in the power distribution for each region of interest, the degree of variation of velocity near the mode in the velocity distribution for each region of interest, or the degree of variation of variance near the mode in the variance distribution for each region of interest.

[0013] The distribution data of the region of interest set within the blood flow region and the distribution data of the region of interest set in other regions differ, particularly in the degree of variation of power near the mode of power, the degree of variation of velocity near the mode of velocity, and the degree of variation of variance near the mode of velocity variance. Therefore, this configuration makes it possible to more preferably generate a discriminant index map that can distinguish between the blood flow region and other regions.

[0014] The discrimination index map generation unit normalizes the discrimination indexes in the discrimination index map, and the blood flow image formation unit forms a blood flow image based on the Doppler signal and the discrimination index map having the normalized discrimination indexes.

[0015] With this configuration, even if the discrimination index for a certain region of interest becomes considerably larger than that for other regions of interest, it is possible to suitably distinguish between the blood flow region and other regions (background region and blooming region) (i.e., to obtain a blood flow image in which blooming artifacts are suitably reduced).

[0016] It is preferable that parameters related to the process of forming the blood flow image, including a parameter representing the size of the region of interest and a parameter related to normalization, be configurable based on user specifications.

[0017] With this configuration, the user can adjust the degree to which blooming artifacts in blood flow images are reduced.

[0018] It is preferable to further include a display control unit that displays the aforementioned discrimination indicator map on the display unit.

[0019] With this configuration, users can view the discriminant index map used to reduce blooming artifacts.

[0020] Furthermore, the blood flow imaging apparatus disclosed herein is characterized by comprising: a received beam data acquisition unit that acquires a sequence of received beam data corresponding to each transmitted beam forming the beam scanning plane, generated based on a received signal from an ultrasonic probe that transmits and receives ultrasonic waves to a beam scanning plane within a subject; a distribution data calculation unit that calculates, based on the received beam data sequence, the power distribution of the Doppler signal obtained from the received beam data, the velocity distribution of the tissue within the subject, and the dispersion distribution of the velocity of the tissue within the subject for each of a plurality of regions of interest set in a two-dimensional data space composed of the received beam data sequence; a discrimination index map generation unit that generates a discrimination index map representing the likelihood that a region is a blood flow region in the two-dimensional data space based on the power distribution, the velocity distribution, and the dispersion distribution; and a blood flow imaging unit that forms a blood flow image representing the blood flow within the subject based on the Doppler signal obtained from the received beam data sequence and the discrimination index map.

[0021] Furthermore, the blood flow image formation program disclosed herein is characterized in that a computer functions as: a received beam data acquisition unit that acquires a sequence of received beam data corresponding to each transmitted beam forming the beam scanning plane, generated based on a received signal from an ultrasonic probe that transmits and receives ultrasonic waves to the beam scanning plane within a subject; a distribution data calculation unit that calculates distribution data for each of a plurality of regions of interest set in a two-dimensional data space composed of the received beam data sequence, which is at least one of the power distribution of the Doppler signal obtained from the received beam data, the velocity distribution of the tissue within the subject, or the variance distribution of the velocity of the tissue within the subject; a discrimination index map generation unit that generates a discrimination index map representing the likelihood that a region of interest is a blood flow region in the two-dimensional data space based on the distribution data for each region of interest; and a blood flow image formation unit that forms a blood flow image representing the blood flow within the subject based on the Doppler signal obtained from the received beam data sequence and the discrimination index map. [Effects of the Invention]

[0022] According to the blood flow image forming apparatus disclosed in this specification, in a blood flow image which is a Doppler image representing blood flow, blooming artifacts can be further reduced.

Brief Description of the Drawings

[0023] [Figure 1] It is a schematic configuration diagram of the ultrasonic diagnostic apparatus according to this embodiment. [Figure 2] It is a schematic configuration diagram of the Doppler image forming unit. [Figure 3] It is a conceptual diagram showing an example of a Doppler signal. [Figure 4] It is a conceptual diagram showing an example of a power map. [Figure 5A] It is a graph showing an example of the power distribution in the ROI set in the blood flow region. [Figure 5B] It is a graph showing an example of the power distribution in the ROI set in the background region. [Figure 5C] It is a graph showing an example of the power distribution in the ROI set in the blooming region. [Figure 6A] It is a graph showing an example of the velocity distribution in the ROI set in the blood flow region. [Figure 6B] It is a graph showing an example of the velocity distribution in the ROI set in the background region. [Figure 6C] It is a graph showing an example of the velocity distribution in the ROI set in the blooming region. [Figure 7A] It is a graph showing an example of the variance distribution of the velocity in the ROI set in the blood flow region. [Figure 7B] It is a graph showing an example of the variance distribution of the velocity in the ROI set in the background region. [Figure 7C] It is a graph showing an example of the variance distribution of the velocity in the ROI set in the blooming region. [Figure 8] It is a graph showing the width of the peak constituting the most frequent value in the power distribution. [Figure 9]This is a conceptual diagram showing an example of a discriminant index map. [Figure 10] This graph shows the fluctuations in the discriminant index along line D in Figure 9. [Figure 11] This graph shows the relationship between the discriminant index and the gain. [Figure 12] This is a conceptual diagram illustrating the process by which a blood flow image is formed based on a power image and a gain map. [Figure 13A] This figure shows an example of a blood flow image when blooming artifact reduction processing according to this embodiment is not performed. [Figure 13B] This figure shows an example of a blood flow image after applying the blooming artifact reduction process according to this embodiment. [Figure 14] This figure shows an example of a blood flow image display. [Figure 15] This figure shows an example of a gain map display. [Figure 16] This figure shows an example of a user interface. [Figure 17] This graph shows the estimated Doppler shift spectrum. [Figure 18A] This graph shows an example of the Doppler shift spectrum of data elements included in the blood flow region. [Figure 18B] This graph shows an example of the Doppler shift spectrum of data elements included in the background region. [Figure 18C] This graph shows an example of the Doppler shift spectrum of data elements included in the blooming region. [Figure 19] This flowchart shows the processing flow of the ultrasound diagnostic device according to this embodiment. [Figure 20] This figure shows an example of what causes blooming artifacts. [Modes for carrying out the invention]

[0024] Figure 1 is a schematic diagram of the configuration of the ultrasound diagnostic device 10 as a blood flow image forming device according to this embodiment. The ultrasound diagnostic device 10 is a device installed in a medical institution such as a hospital. The ultrasound diagnostic device 10 transmits and receives ultrasound waves to a living subject, and forms and displays an ultrasound image based on the received signal obtained thereby.

[0025] In particular, the ultrasound diagnostic device 10 detects a Doppler shift based on the amount of phase change between received signals and forms a Doppler image, which is an ultrasound image representing the velocity, velocity dispersion, or power of tissues within the subject, according to the Doppler shift. Doppler images include color Doppler images, which represent the direction and magnitude of tissue velocity or velocity dispersion with color, and power images, which represent power with color, etc. Power represents the intensity of the Doppler signal that represents the Doppler shift, and power images have advantages over color Doppler images, such as being able to display even slow blood flow brightly. In this specification, Doppler images that represent blood flow within a subject are called blood flow images.

[0026] The probe 12, which is an ultrasonic probe, is a device that transmits ultrasonic waves and receives reflected waves. Specifically, the probe 12 is in contact with the surface of the subject's body, transmits an ultrasonic beam toward the subject, and receives reflected waves reflected from the tissue within the subject. Inside the probe 12 is a vibrating element array consisting of multiple vibrating elements. Each vibrating element in the vibrating element array is supplied with a transmission signal, which is an electrical signal, from the transmission unit 14 (described later), thereby generating an ultrasonic beam (transmission beam). As the ultrasonic beam is scanned, a beam scanning surface is formed within the subject. In addition, each vibrating element in the vibrating element array receives reflected waves from the subject, converts the reflected waves into received signals, which are electrical signals, and transmits them to the receiving unit 16 (described later).

[0027] The transmitting unit 14 functions as a transmitting beamformer. When transmitting ultrasound, the transmitting unit 14 supplies multiple transmitting signals in parallel to the probe 12 (more specifically, the vibrating element array). As a result, an ultrasonic beam is transmitted from the probe 12.

[0028] The receiving unit 16 functions as a receiving beamformer. When receiving reflected waves, the receiving unit 16 receives multiple received signals in parallel from the probe 12 (more specifically, the vibrating element array) corresponding to each transmitted beam that forms the beam scanning plane. The receiving unit 16 performs processing such as layer addition on the multiple received signals, thereby generating multiple received beam data (received beam data sequences). Thus, in this embodiment, the receiving unit 16 corresponds to the received beam data acquisition unit. Each received beam data consists of multiple signals (data) indicating the signal intensity of the reflected wave, arranged in the depth direction of the subject. That is, a two-dimensional data space can be defined by the received beam data sequences, arranged in the depth direction and the azimuth direction (scanning direction of the transmitted beam). A single B-mode image is formed by converting the signal intensity of the received beam data sequences (referred to as received frame data in this specification) obtained from the entire beam scanning plane into brightness values. In this specification, the data portion of the received beam data sequences corresponding to each pixel of the B-mode image is called a data element.

[0029] The signal processing unit 18 performs various signal processing on each received beam data from the receiving unit 16, including detection processing, logarithmic amplification processing, gain correction processing, and filtering processing.

[0030] The cine memory 20 is a memory that stores multiple received frame data processed by the signal processing unit 18. The cine memory 20 is a FIFO (First In First Out) buffer that outputs the received frame data from the signal processing unit 18 in the order in which it was input.

[0031] The tomography image forming unit 22 forms an ultrasonic tomography image (i.e., a B-mode image) based on the frame data received from the cine memory 20. Specifically, the tomography image forming unit 22 forms the B-mode image by converting the signal intensity of each data element of each received beam data included in the received frame data into a brightness value.

[0032] The Doppler image forming unit 24 forms a Doppler image based on the Doppler shift between multiple received signals obtained by transmitting and receiving ultrasonic waves to the subject. Details of the processing performed by the Doppler image forming unit 24 will be described later.

[0033] The display control unit 26 displays the B-mode image formed by the tomography image forming unit 22 on a display unit 28, which is made of, for example, a liquid crystal panel. The display control unit 26 also superimposes the Doppler image formed by the Doppler image forming unit 24 onto the B-mode image formed by the tomography image forming unit 22 and displays it on the display 28.

[0034] The input interface 30 consists of, for example, buttons, a trackball, or a touch panel. The input interface 30 is for inputting user instructions to the ultrasound diagnostic device 10.

[0035] Memory 32 is composed of components such as an HDD (Hard Disk Drive), SSD (Solid State Drive), eMMC (embedded Multi Media Card), ROM (Read Only Memory), or RAM (Random Access Memory). Memory 32 stores blood flow image formation programs for operating each part of the ultrasound diagnostic device 10. The blood flow image formation programs can also be stored on a computer-readable non-temporary storage medium such as a USB (Universal Serial Bus) memory or CD-ROM. The ultrasound diagnostic device 10 can read and execute blood flow image formation programs from such storage media.

[0036] The control unit 34 is comprised of at least one general-purpose processor (e.g., a CPU (Central Processing Unit)) and a dedicated processor (e.g., a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a programmable logic device). The control unit 34 may not consist of a single processing unit, but rather of multiple processing units located in physically separate locations working together. The control unit 34 controls each part of the ultrasound diagnostic apparatus 10 according to the ultrasound image processing program stored in the memory 32.

[0037] The transmitting unit 14, receiving unit 16, signal processing unit 18, tomographic image forming unit 22, Doppler image forming unit 24, and display control unit 26 are each composed of one or more processors, chips, electrical circuits, etc. These units may also be realized through the cooperation of hardware and software.

[0038] Figure 2 is a schematic diagram of the configuration of the Doppler image formation unit 24. As shown in Figure 2, the Doppler image formation unit 24 performs the functions of a Doppler processing unit 40, a distribution data calculation unit 42, a discrimination index map generation unit 44, and a blood flow image formation unit 46.

[0039] The Doppler processing unit 40 performs quadrature detection processing to separate the received beam data from the cine memory 20 into complex signals (real part signal (I component) and imaginary part signal (Q component)), filtering processing to apply a wall filter to the complex signal obtained by quadrature detection processing to remove noise (clutter component) caused by the subject's body movement, and autocorrelation calculation to calculate the correlation between the I component and the Q component in order to calculate the amount of phase change between the received beam data.

[0040] In this specification, the received beam data processed by the Doppler processing unit 40 is referred to as the Doppler signal. More specifically, since the signal obtained by quadrature detection processing or autocorrelation calculation is a signal in which tissue components and blood flow components are mixed, the signal obtained by applying a wall filter to this signal to extract only the blood flow component is called the Doppler signal. The Doppler signal is a signal that shows the signal strength for each Doppler shift (shift frequency) for each data element. Figure 3 is a graph showing an example of a Doppler signal for a certain data element. In Figure 3, the horizontal axis represents the Doppler shift (shift frequency), and the vertical axis represents the signal strength. As shown in Figure 3, the signal strength of the Doppler signal is generally distributed around the center frequency f. Note that the processing target of the Doppler processing unit 40 (and other processing units included in the Doppler image forming unit 24) does not have to be the entire received frame data, but only a part of it (for example, a region of interest specified by the user).

[0041] The distribution data calculation unit 42 calculates at least one of the following for each data element based on the Doppler signal shown in Figure 3 for each data element: the power of the Doppler signal, the velocity of the tissue in the subject, or the variance of the velocity of the tissue in the subject. Specifically, the distribution data calculation unit 42 calculates the power of the data element based on the integral value of the signal intensity (the colored portion of the graph). Furthermore, since the Doppler shift with signal intensity has width, the distribution data calculation unit 42 calculates the average velocity calculated from the Doppler shift with signal intensity as the velocity of the data element. In addition, the distribution data calculation unit 42 calculates the variance of the velocity of the data element based on the width of the Doppler signal graph.

[0042] The distribution data calculation unit 42 calculates the power, velocity, or velocity variance for each data element, thereby calculating a power map showing the power distribution, a velocity map showing the velocity distribution, or a variance map showing the velocity variance distribution in a two-dimensional data space composed of the received beam data sequence (i.e., a two-dimensionally arranged group of data elements).

[0043] Figure 4 is a conceptual diagram showing an example of Power Map 50. In Figure 4 (and similarly in Figure 9 described later), the X-axis represents the azimuth direction, and the Z-axis represents the depth direction.

[0044] In a power map 50 (or a velocity map or dispersion map), the image can be conceptually divided into three regions: blood flow region A, which corresponds to blood flow (blood vessels); background region B, which corresponds to the subject's tissues other than blood flow; and blooming region C, which is located below blood flow region A (positive Z-axis side) and causes blooming artifacts in Doppler images.

[0045] The distribution data calculation unit 42 sets up multiple regions of interest (ROIs) 52 in a two-dimensional data space (i.e., a power map 50, a velocity map, or a dispersion map) composed of the received beam data stream. Note that in Figure 4, only some of the ROIs 52 are shown. In particular, the distribution data calculation unit 42 sets up each ROI 52 such that each ROI 52 contains multiple data elements. In this way, the distribution data calculation unit 42 can obtain distribution data for each of the multiple ROIs 52 that is at least one of a power distribution showing the distribution of power, a velocity distribution showing the distribution of velocity, or a velocity dispersion distribution showing the distribution of velocity dispersion.

[0046] The important point here is that the distribution data for ROI52a in blood flow region A, the distribution data for ROI52b in background region B, and the distribution data for ROI52c in blooming region C have different characteristics from each other.

[0047] Figure 5A is a graph showing an example of the power distribution in ROI52a set within the blood flow region A, Figure 5B is a graph showing an example of the power distribution in ROI52b set within the background region B, and Figure 5C is a graph showing an example of the power distribution in ROI52c set within the blooming region C. In Figures 5A to 5C, the horizontal axis represents power and the vertical axis represents frequency (number of data elements). In other words, Figures 5A to 5C represent histograms of power in each ROI52.

[0048] As shown in Figure 5A, the power distribution in ROI52a, set in blood flow region A, exhibits large power variability, with no particular power frequency being exceptionally high. In other words, the power graph has the shape of a wide, low-height peak. In contrast, as shown in Figure 5B, the power distribution in ROI52b, set in background region B, exhibits small power variability, with a particularly high frequency of a specific power (low power). In other words, the power graph has the shape of a narrow, high-height peak. The power distribution in ROI52c, set in blooming region C, combines the characteristics of the power distributions in blood flow region A and background region B. Specifically, as shown in Figure 5C, the power distribution in ROI52c, set in blooming region C, exhibits a shape that combines a narrow peak with small power variability and an exceptionally high frequency of a specific power (low power), with a wide, low-height peak (lower than the narrow peak).

[0049] Figure 6A is a graph showing an example of velocity distribution in ROI52a set within blood flow region A, Figure 6B is a graph showing an example of velocity distribution in ROI52b set within background region B, and Figure 6C is a graph showing an example of velocity distribution in ROI52c set within blooming region C. In Figures 6A to 6C, the horizontal axis represents velocity, and the vertical axis represents frequency (number of data elements). In other words, Figures 6A to 6C represent histograms of velocity in each ROI52.

[0050] As shown in Figure 6A, the velocity distribution in ROI52a, set in blood flow region A, is the opposite of the power distribution, with low velocity variability and a high frequency of specific velocities. In other words, the velocity graph has the shape of a narrow, high peak. In contrast, as shown in Figure 6B, the velocity distribution in ROI52b, set in background region B, is the opposite of the power distribution, with high velocity variability and no high frequency of specific velocities. In other words, the velocity graph has the shape of a wide, low peak. The velocity distribution in ROI52c, set in blooming region C, combines the characteristics of the velocity distributions in blood flow region A and background region B. Specifically, as shown in Figure 6C, the velocity distribution in ROI52c, set in blooming region C, has a shape that combines a narrow peak with low velocity variability and a high frequency of specific velocities, and a wide, low peak (lower than the narrow peak).

[0051] The velocity variance distribution exhibits generally similar characteristics to the velocity distribution. Figure 7A is a graph showing an example of the velocity variance distribution in ROI52a set within blood flow region A, Figure 7B is a graph showing an example of the velocity variance distribution in ROI52b set within background region B, and Figure 7C is a graph showing an example of the velocity variance distribution in ROI52c set within blooming region C. In Figures 7A to 7C, the horizontal axis represents the velocity variance, and the vertical axis represents the frequency (number of data elements). In other words, Figures 7A to 7C represent histograms of the velocity variance in each ROI52.

[0052] As shown in Figure 7A, the velocity variance distribution in ROI52a, set in blood flow region A, shows low variability in velocity variance and a disproportionately high frequency of a particular variance. In other words, the velocity variance graph has a narrow, high-peak shape. In contrast, as shown in Figure 7B, the velocity variance distribution in ROI52b, set in background region B, shows high variability in variance and no disproportionately high frequency of a particular variance. In other words, the velocity variance graph has a wide, low-peak shape. The velocity variance distribution in ROI52c, set in blooming region C, combines the characteristics of the velocity variance distributions in blood flow region A and background region B. Specifically, as shown in Figure 7C, the velocity variance distribution in ROI52c, set in blooming region C, has a shape that combines a narrow peak with low variability and a disproportionately high frequency of a particular variance, and a wide, low-peak (lower peak than the narrow peak).

[0053] The discriminant index map generation unit 44 generates a discriminant index map that represents the likelihood of being in blood flow region A in a two-dimensional data space composed of received beam data sequences, based on the distribution data for each ROI 52 calculated by the distribution data calculation unit 42. Specifically, a discriminant index map is a map generated by assigning a discriminant index that represents the likelihood of being in blood flow region A to each data element in a two-dimensional data space composed of received beam data sequences. As described above, since the characteristics of the distribution data of ROI 52 in blood flow region A, background region B, and blooming region C are different from each other, the discriminant index map generation unit 44 assigns a discriminant index (value) that represents the likelihood of being in blood flow region A to each ROI 52 (i.e., each data element that constitutes each ROI 52) based on the characteristics of the distribution data in each ROI 52.

[0054] When the power distribution of each ROI 52 has been calculated by the distribution data calculation unit 42, the discriminant index map generation unit 44 generates a discriminant index map based on the degree of variation in power near the mode in the power distribution for each ROI 52.

[0055] Figure 8 is a graph showing the power distribution of a certain ROI52. The discriminant index map generation unit 44 first identifies the mode in the power distribution. Then, based on the width w of the peak containing the mode in the graph, it determines the discriminant index to be assigned to the ROI52. Specifically, the discriminant index is determined such that the larger the width w, the larger the discriminant index; in other words, the smaller the width w, the smaller the discriminant index.

[0056] In this embodiment, the peak width w is defined as the difference between two power values ​​whose frequency is determined based on the mode (specifically, the difference between two power values ​​that take the value of mode × 0.6). However, the peak width w may be calculated using other indicators. For example, the value of 0.6 may be changed to another value.

[0057] As described above, in the graph showing the power distribution in ROI52a set within blood flow region A (see Figure 5A), the width w of the peak containing the mode is quite large. On the other hand, in the graph showing the power distribution in ROI52b set within background region B (see Figure 5B), the width w of the peak containing the mode is quite small. Furthermore, in the graph showing the power distribution in ROI52c set within blooming region C (see Figure 5C), although there are some wide peaks, if we focus on the peak constituting the mode, the width w of that peak is quite small, similar to background region B. In other words, by determining the discriminant index based on the width w of the peak constituting the mode, a relatively large discriminant index can be assigned to ROI52a set within blood flow region A, while a relatively small discriminant index can be assigned to both background region B and blooming region C.

[0058] When the velocity distribution of each ROI 52 has been calculated by the distribution data calculation unit 42, the discriminant index map generation unit 44 generates a discriminant index map based on the degree of velocity variation near the mode in the velocity distribution for each ROI 52. Even when a velocity distribution has been calculated, similar to the case of the power distribution, the discriminant index map generation unit 44 determines the discriminant index to be assigned to the ROI 52 based on the width w of the peak containing the mode in the graph showing the velocity distribution. However, in the case of the velocity distribution, the discriminant index map generation unit 44 determines the discriminant index such that the smaller the width w, the larger the discriminant index; in other words, the larger the width w, the smaller the discriminant index.

[0059] As described above, in the graph showing the velocity distribution in ROI52a set within blood flow region A (see Figure 6A), the width of the peak w containing the mode is quite small. On the other hand, in the graph showing the velocity distribution in ROI52b set within background region B (see Figure 6B), the width of the peak w containing the mode is quite large. Furthermore, in the graph showing the velocity distribution in ROI52c set within blooming region C (see Figure 5C), the width of the peak w containing the mode is smaller than in background region B, but larger than in blood flow region A. In other words, by determining the discriminant index based on the width w of the peak constituting the mode, a relatively large discriminant index can be assigned to ROI52a set within blood flow region A, while a relatively small discriminant index can be assigned not only to background region B but also to blooming region C.

[0060] When the distribution data calculation unit 42 calculates the variance distribution of the velocity for each ROI 52, the discriminant index map generation unit 44 generates a discriminant index map based on the degree of variability in the vicinity of the mode in the variance distribution for each ROI 52. Even when a variance distribution is calculated, similar to the case of power distributions or velocity distributions, the discriminant index map generation unit 44 determines the discriminant index to be assigned to the ROI 52 based on the width w of the peak containing the mode in the graph showing the variance distribution. In the case of variance distributions, the opposite of the case of power distributions and similar to the case of velocity distributions, the discriminant index is determined such that the smaller the width w, the larger the discriminant index; in other words, the larger the width w, the smaller the discriminant index.

[0061] As described above, in the graph showing the variance distribution for ROI52a set within blood flow region A (see Figure 7A), the width of the peak w containing the mode is quite small. On the other hand, in the graph showing the variance distribution for ROI52b set within background region B (see Figure 7B), the width of the peak w containing the mode is quite large. Furthermore, in the graph showing the variance distribution for ROI52c set within blooming region C (see Figure 7C), the width of the peak w containing the mode is smaller than in background region B, but larger than in blood flow region A. In other words, by determining the discriminant index based on the width w of the peak constituting the mode, a relatively large discriminant index can be assigned to ROI52a set within blood flow region A, while a relatively small discriminant index can be assigned not only to background region B but also to blooming region C.

[0062] Figure 9 is a conceptual diagram showing an example of a discrimination index map 54 generated by the discrimination index map generation unit 44. Figure 10 is a graph showing the fluctuation of the discrimination index along a line D parallel to the Z-axis direction in Figure 9. In the discrimination index map 54, the discrimination index in the part corresponding to blood flow region A is large, while the discrimination index in the parts corresponding to background region B and blooming region C is small.

[0063] In this embodiment, the discrimination index map generation unit 44 performs a process to normalize the discrimination index assigned to each data element. For example, as a normalization process, the discrimination index map generation unit 44 performs a process in the discrimination index map 54 to set the discrimination index of data elements whose discrimination index is below a predetermined threshold (see Figure 10) to 0. This is because data elements corresponding to discrimination index values ​​below the threshold (i.e., discrimination index values ​​that are quite small) are unlikely to be data elements corresponding to blood flow region A.

[0064] Furthermore, depending on the calculation method, the discriminant index may become a considerably large value, such as 10,000. In other words, the range of values ​​that the discriminant index can take is quite wide. If the variability of the discriminant index is large, it may become difficult to suitably distinguish between the blood flow region A and other regions (background region B and blooming region C) in the blood flow image formation unit 46 described later. Therefore, as a normalization process, the discriminant index map generation unit 44 converts the discriminant index of each data element of the discriminant index map 54 to a value between 0 and 1. The discriminant index map 54 in which the discriminant index has been converted (normalized) in this way is called a gain map. In this embodiment, the discriminant index map generation unit 44 normalizes (converts) the discriminant index using a gain function. Normalization can be expressed, for example, by the following equation 1.

number

[0065] In this embodiment, the discriminant index for each data element in the gain map will have a value between 0 and 1. In particular, in the gain map 56, the data element corresponding to the blood flow region A will have a discriminant index of 1 or close to it, while the data elements corresponding to the background region B and the blooming region C will have a discriminant index of 0 or close to it.

[0066] The blood flow image forming unit 46 forms a blood flow image representing the blood flow within the subject based on the Doppler signal obtained by the processing of the Doppler processing unit 40 and the discrimination index map generated by the discrimination index map generation unit 44. In this embodiment, since the distribution data calculation unit 42 calculates a power map, velocity map, or dispersion map, the blood flow image forming unit 46 forms a blood flow image based on the power map, velocity map, or dispersion map and the discrimination index map.

[0067] Specifically, as shown in Figure 12, the blood flow image forming unit 46 forms a power image 58 as a blood flow image with reduced blooming artifacts by multiplying the power map 50 by the gain map 56 (normalized discriminant index map). Multiplying the power map 50 by the gain map 56 means multiplying the power of the data elements in the power map 50 by the discriminant index (0 to 1) of the corresponding data elements in the gain map 56, and using the result of this calculation as the signal value of the corresponding data element in the power image 58. As described above, in the gain map 56, the data elements corresponding to blood flow region A have a discriminant index of 1 or close to it, and the data elements corresponding to background region B and blooming region C have a discriminant index of 0 or close to it. Therefore, in the power image 58, the signal value of the data element corresponding to blood flow region A remains almost the same as the power of the power map 50, while the signal values ​​of the data elements corresponding to background region B and blooming region C are almost 0.

[0068] Similarly, the blood flow image forming unit 46 can obtain a velocity image as a blood flow image with reduced blooming artifacts by multiplying the velocity map and the gain map 56 instead of the power map 50. Furthermore, the blood flow image forming unit 46 can obtain a dispersion image as a blood flow image with reduced blooming artifacts by multiplying the dispersion map and the gain map 56 instead of the power map 50.

[0069] As described above, according to this embodiment, a blood flow image (power image or color Doppler image (velocity image or dispersion image)) with reduced blooming artifacts can be obtained. Figures 13A and 13B illustrate the effects of this embodiment. Figure 13A is a diagram showing an example of a power image obtained without the blooming reduction processing described above according to this embodiment. In Figure 13A, it can be seen that a blooming artifact 62 has occurred below the blood vessel 60. Figure 13B is a diagram showing an example of a power image obtained with the blooming artifact reduction processing according to this embodiment. In Figure 13B, it can be seen that the blooming artifact 62 that was present in Figure 13A has been considerably reduced.

[0070] The display control unit 26 displays the blood flow image formed by the Doppler image forming unit 24 on the display 28. For example, the display control unit 26 superimposes the blood flow image onto the B-mode image formed by the tomographic image forming unit 22 and displays it on the display 28.

[0071] The display control unit 26 may display on the display 28 a blood flow image with reduced blooming artifacts and a blood flow image with unreduced blooming artifacts. For example, as shown in Figure 14, the display control unit 26 may display the power image 58 with reduced blooming artifacts and the power image with unreduced blooming artifacts (i.e., the power map 50) side by side. This allows the user to understand how much the blooming artifacts have been reduced and to also see the original power image before the blooming artifact reduction process was performed.

[0072] Furthermore, the display control unit 26 may display the discrimination index map generated by the discrimination index map generation unit 44 on the display 28. For example, as shown in Figure 15, the display control unit 26 may display the power image 58 with reduced blooming artifacts and the gain map 56 used to obtain it side by side. Alternatively, the discrimination index map before normalization may be displayed instead of the gain map 56. This allows the user to confirm the gain map 56 (or discrimination index map) used to reduce blooming artifacts.

[0073] The Doppler image formation unit 24 may be able to set parameters related to the process of forming the blood flow image according to this embodiment, in other words, the blooming artifact reduction process, based on user specifications. These parameters are not limited to these, but include, for example, a parameter representing the size of the ROI 52 (see Figure 4) set by the distribution data calculation unit 42, and parameters related to the normalization of the discrimination index by the discrimination index map generation unit 44. Parameters related to the normalization of the discrimination index include, for example, the threshold shown in Figure 10, or the gain value of the sigmoid function (see Figure 11) as a gain function.

[0074] For example, as shown in Figure 16, multiple combinations of the above-mentioned parameters can be pre-set, and multiple preset buttons 70 corresponding to each preset can be provided as the input interface 30. When a user selects and operates a desired preset button 70, the Doppler image forming unit 24 sets each parameter indicated by the preset corresponding to the operated preset button 70 as parameters for the blooming artifact reduction process. The display control unit 26 may display the set values ​​of each parameter on the display 28. The display 28 may also be a touch panel, and each parameter may be set individually by operating the display 28.

[0075] In the above-described embodiment, the discrimination index map generation unit 44 generated the discrimination index map using one of the power map, velocity map, or variance map calculated by the distribution data calculation unit 42. However, the distribution data calculation unit 42 may calculate the power map, velocity map, and variance map, and then the discrimination index map generation unit 44 may generate the discrimination index map based on the power map, velocity map, and variance map.

[0076] In this case, the discriminant index map generation unit 44 estimates the spectrum of the Doppler shift ω for each data element based on the power, velocity, and velocity variance calculated for each data element. Specifically, first, the discriminant index map generation unit 44 assumes that the spectrum of the Doppler shift ω is a Gaussian distribution and sets the Gaussian S0(ω) as shown in Equation 2 below.

number

[0077] Next, the discriminant index map generation unit 44 calculates a parameter A by dividing the power by the total power of the Gaussian S0(ω), as shown in Equation 3 below.

number

[0078] The discriminant index map generation unit 44 then estimates the spectrum S(ω) of the Doppler shift ω using the following equation 4.

number

[0079] Here, it is important to note that the characteristics of the spectrum S(ω) of the data elements included in blood flow region A, the spectrum S(ω) of the data elements included in background region B, and the spectrum S(ω) of the data elements included in blooming region C are all different from each other.

[0080] Figure 18A is a graph showing an example of the spectrum S(ω) of a data element included in blood flow region A, Figure 18B is a graph showing an example of the spectrum S(ω) of a data element included in background region B, and Figure 18C is a graph showing an example of the spectrum S(ω) of a data element included in blooming region C. In Figures 18A to 18C, the horizontal axis represents Doppler shift ω, and the vertical axis represents power.

[0081] The spectrum S(ω) of the data elements included in blood flow region A has peaks where the Doppler shift ω is larger and the power is higher compared to background region B and blooming region C. Therefore, the discriminant index map generation unit 44 calculates the first moment of the spectrum S(ω), which is larger for the spectrum S(ω) that has a peak at a larger Doppler shift ω, and uses this as the discriminant index for the data element. The first moment M1 of the spectrum S(ω) is calculated by the following equation 5.

number

[0082] As a result, data elements included in blood flow region A can be assigned relatively large discriminant indicators, while background region B and blooming region C can be assigned relatively small discriminant indicators. Furthermore, when assigning discriminant indicators based on the spectrum S(ω) of the Doppler shift ω, processing is performed for each data element as described above, so the distribution data calculation unit 42 does not need to set ROI 52 and does not need to obtain distribution data for each ROI 52.

[0083] In the above embodiment, the first moment M1 of the spectrum S(ω) was used as the discriminant index, but the discriminant index may also be calculated by considering the second and subsequent moments. n This is calculated using the following formula 6.

number

[0084] The overview of the ultrasound diagnostic device 10 according to this embodiment is as described above. The processing flow of the ultrasound diagnostic device 10 will now be explained according to the flowchart shown in Figure 19.

[0085] In step S10, the transmitting unit 14 supplies multiple transmission signals to the probe 12, and the probe 12 transmits ultrasound to the subject based on these signals. The probe 12 receives the reflected wave from the subject and sends multiple received signals to the receiving unit 16. The receiving unit 16 generates a received beam data train based on the multiple received signals.

[0086] In step S12, the Doppler processing unit 40 generates a Doppler signal based on each received beam data that constitutes the received beam data sequence. The distributed data calculation unit 42 calculates the power, velocity, or velocity variance for each data element based on the Doppler signal for each data element. Here, the distributed data calculation unit 42 calculates the power of each data element and generates a power map 50 (see Figure 4). The distributed data calculation unit 42 also sets multiple ROIs 52 in the power map 50 and obtains the power distribution for each ROI 52.

[0087] In step S14, the discrimination index map generation unit 44 selects a target ROI from among the multiple ROIs 52 set in step S12.

[0088] In step S16, the discriminant index map generation unit 44 calculates the discriminant index for the target ROI (i.e., the data elements included in the target ROI) based on the power distribution of the target ROI selected in step S14.

[0089] In step S18, the discriminant index map generation unit 44 determines whether the calculation of discriminant indexes for all ROI52 set in step S12 has been completed. If there are still ROI52 for which the discriminant index has not been calculated, the process returns to step S14, and in step S14 again, the discriminant index map generation unit 44 selects the ROI52 for which the discriminant index has not been calculated as the target ROI. If the calculation of discriminant indexes for all ROI52 has been completed, the process proceeds to step S20.

[0090] In step S20, the discriminant index map generation unit 44 normalizes the discriminant index calculated for each data element and generates a gain map 56.

[0091] In step S22, the blood flow image forming unit 46 multiplies the power map 50 generated in step S12 with the gain map 56 generated in step S20 to form a power image 58 as a blood flow image with reduced blooming artifacts.

[0092] In step S22, the display control unit 26 superimposes the Doppler image formed in step S22 onto the B-mode image formed by the tomographic image forming unit 22 and displays it on the display 28.

[0093] Although the blood flow imaging apparatus described herein has been explained above, the blood flow imaging apparatus described herein is not limited to the embodiments described above, and various modifications are possible as long as they do not deviate from the spirit of the invention.

[0094] For example, in this embodiment, the blood flow image forming device was an ultrasound diagnostic device 10, but the blood flow image forming device is not limited to an ultrasound diagnostic device 10 and may be any other computer. In this case, the computer acting as the blood flow image forming device performs the function of the Doppler image forming unit 24. Specifically, the computer acting as the blood flow image forming device acquires a stream of received beam data from the ultrasound diagnostic device (in this case, the computer interface corresponds to the received beam data acquisition unit), and the Doppler image forming unit 24 performs the above-mentioned processing based on the received beam data stream, thereby forming a blood flow image with reduced blooming artifacts. [Explanation of symbols]

[0095] 10 Ultrasound diagnostic device, 12 Probe, 14 Transmitter, 16 Receiver, 18 Signal processing unit, 20 Cine memory, 22 Tomography image formation unit, 24 Doppler image formation unit, 26 Display control unit, 28 Display, 30 Input interface, 32 Memory, 34 Control unit, 40 Doppler processing unit, 42 Distribution data calculation unit, 44 Discrimination index map generation unit, 46 Blood flow image formation unit.

Claims

1. A received beam data acquisition unit acquires a sequence of received beam data corresponding to each transmitted beam forming the beam scanning surface, which is generated based on the received signal from an ultrasonic probe that transmits and receives ultrasonic waves to and from the beam scanning surface within the subject. A distribution data calculation unit calculates distribution data for each of a plurality of regions of interest set in the two-dimensional data space composed of the received beam data sequence, which is at least one of the power distribution of the Doppler signal obtained from the received beam data sequence, the velocity distribution of the tissue in the subject, or the variance distribution of the velocity of the tissue in the subject, based on the received beam data sequence. A discrimination index map generation unit generates a discrimination index map that represents the likelihood of a blood flow region in the two-dimensional data space based on the distribution data for each region of interest, A blood flow image forming unit that forms a blood flow image representing blood flow within the subject based on the Doppler signal obtained from the received beam data sequence and the discrimination index map, Equipped with, The discriminant index map generation unit generates the discriminant index map based on the degree of variation of power near the mode in the power distribution for each region of interest, the degree of variation of velocity near the mode in the velocity distribution for each region of interest, or the degree of variation of variance near the mode in the variance distribution for each region of interest. A blood flow imaging apparatus characterized by the following features.

2. The discrimination index map generation unit normalizes the discrimination indexes in the discrimination index map, The blood flow image forming unit forms a blood flow image based on the Doppler signal and the discrimination index map having a normalized discrimination index. The blood flow image forming apparatus according to feature 1.

3. Parameters related to the process of forming the blood flow image, including a parameter representing the size of the region of interest and a parameter relating to normalization, can be set based on user specifications. The blood flow imaging apparatus according to feature 2.

4. A display control unit that displays the aforementioned discrimination index map on the display unit, The blood flow image forming apparatus according to claim 1, further comprising the features described above.

5. Computers, A received beam data acquisition unit acquires a sequence of received beam data corresponding to each transmitted beam forming the beam scanning surface, which is generated based on the received signal from an ultrasonic probe that transmits and receives ultrasonic waves to and from the beam scanning surface within the subject. A distribution data calculation unit calculates distribution data for each of a plurality of regions of interest set in the two-dimensional data space composed of the received beam data sequence, which is at least one of the power distribution of the Doppler signal obtained from the received beam data sequence, the velocity distribution of the tissue in the subject, or the variance distribution of the velocity of the tissue in the subject, based on the received beam data sequence. A discrimination index map generation unit generates a discrimination index map that represents the likelihood of a blood flow region in the two-dimensional data space based on the distribution data for each region of interest, A blood flow image forming unit that forms a blood flow image representing blood flow within the subject based on the Doppler signal obtained from the received beam data sequence and the discrimination index map, To make it function as, The discriminant index map generation unit generates the discriminant index map based on the degree of variation of power near the mode in the power distribution for each region of interest, the degree of variation of velocity near the mode in the velocity distribution for each region of interest, or the degree of variation of variance near the mode in the variance distribution for each region of interest. A blood flow image formation program characterized by the following features.

Images