Ultrasound diagnostic device and attenuation map generation method

Abstract

Ensure that non-focus areas (structure images, shadows, etc.) are excluded from the attenuation map. [Solution] Based on the first data group 58 within the first region of interest 48, a luminance average map 60 and a luminance SD map 64 are generated. A first extraction process 62 using a first threshold Th1 and a second threshold Th2 is applied to the luminance average map 60, thereby generating a first mask M1. A second extraction process 66 is applied to the luminance SD map 64, thereby generating a second mask M2. An attenuation map 70 is generated according to a composite mask M3 based on the first mask M1 and the second mask M2.

Description

Technical Field

[0001] The present disclosure relates to an ultrasonic diagnostic apparatus and an attenuation map generation method, and particularly relates to generation of a mask used when generating an attenuation map.

Background Art

[0002] An ultrasonic diagnostic apparatus has an attenuation measurement function. For example, in an ultrasonic examination of the liver, particularly in an ultrasonic examination of the liver for evaluating the presence or degree of fatty liver, the attenuation measurement function is utilized. Specifically, based on echo data obtained from the liver, an attenuation rate representing the properties of the liver is calculated, and the calculated attenuation rate is displayed as a numerical value. The attenuation rate is attenuation information and corresponds to an attenuation coefficient or an attenuation amount. Hereinafter, depending on the case, the attenuation rate may simply be referred to as attenuation. Various methods have been conventionally proposed as methods for calculating the attenuation rate.

[0003] An ultrasonic diagnostic apparatus having an attenuation map display function is known. The attenuation map is, for example, a color two-dimensional map representing the attenuation rate at each position in the liver. The attenuation rate at each position can be recognized from the hue at each position in the attenuation map. Through observation of the attenuation map, a measurement region for measuring the attenuation rate as numerical information is determined, or the spread or degree of a disease in the liver is evaluated.

[0004] Patent Document 1 discloses an ultrasonic diagnostic apparatus having an attenuation map display function. Patent Document 2 also discloses an ultrasonic diagnostic apparatus having an attenuation map display function. In the ultrasonic diagnostic apparatus disclosed in Patent Document 2, a dispersion ratio (a numerical value based on a dispersion value and an average value) is calculated over the entire region of interest, and structures in the liver are specified based on the dispersion ratio. In Patent Document 2, the distribution of a plurality of dispersion ratios or the dispersion ratio map actually functions as a mask.

[0005] Patent documents 1 and 2 do not disclose the synthesis of multiple masks. Patent documents 1 and 2 do not disclose masks for areas other than structural images (for example, shadows as weak echo regions). [Prior art documents] [Patent Documents]

[0006] [Patent Document 1] International Publication No. 2017-068892 [Patent Document 2] Japanese Patent Publication No. 2017-158917 [Overview of the project] [Problems that the invention aims to solve]

[0007] Tomographic images representing tissues such as the liver include areas of interest and areas of non-interest. Examples of areas of non-interest include vascular wall images, diaphragm images, and tumor contour images. These are generally areas with high brightness and a large standard deviation. Other examples of areas of non-interest include shadows, blood smears, and cystic fluid images. Shadows are low-brightness areas that occur in the deep parts of the tomographic image, or low-brightness areas that occur at the edges of the tomographic image due to reduced adhesion between the probe and the biological surface.

[0008] When non-target areas are color-represented as part of the attenuation map, it becomes difficult to correctly define the measurement area for precisely measuring the attenuation rate. Alternatively, it becomes difficult to accurately evaluate the properties of the tissue through observation of the attenuation map.

[0009] The purpose of this disclosure is to ensure that non-focus areas are excluded from the attenuation map. Alternatively, the purpose of this disclosure is to ensure that low-luminance areas such as shadows, in addition to structural images, are excluded from the attenuation map. [Means for solving the problem]

[0010] The ultrasound diagnostic apparatus according to this disclosure includes a processor, the processor generating an ultrasound image based on a first dataset acquired by transmitting and receiving a first ultrasound, generating a plurality of masks for excluding a plurality of non-focus regions from a first region of interest set in the beam scanning plane based on the first dataset, generating a composite mask by combining the plurality of masks, identifying attenuation display regions within the first region of interest based on the composite mask, and generating an attenuation map representing the attenuation distribution within the attenuation display regions based on a second dataset acquired by transmitting and receiving a second ultrasound different from the first ultrasound.

[0011] The attenuation map generation method according to this disclosure is an attenuation map generation method performed in an information processing device, and is characterized by comprising: generating an ultrasonic image based on a first data set obtained by transmitting and receiving a first ultrasonic wave; generating a plurality of types of masks for excluding a plurality of types of non-attention regions from a first region of interest set in a beam scanning plane based on the first data set; generating a composite mask by combining the plurality of types of masks; identifying an attenuation display region in the first region of interest based on the composite mask; and generating an attenuation map representing the attenuation distribution in the attenuation display region based on a second data set obtained by transmitting and receiving a second ultrasonic wave different from the first ultrasonic wave. [Effects of the Invention]

[0012] According to this disclosure, non-focus areas can be excluded from the attenuation map. Alternatively, according to this disclosure, low-luminance areas such as shadows can be excluded from the attenuation map in addition to structural images. [Brief explanation of the drawing]

[0013] [Figure 1] This is a block diagram showing an example configuration of an ultrasound diagnostic apparatus according to an embodiment. [Figure 2] This figure shows multiple regions of interest set on a tomographic image. [Figure 3]A diagram showing an algorithm executed in a mask generator. [Figure 4] A diagram showing an example of a luminance histogram. [Figure 5] A diagram showing a composite mask and an attenuation map. [Figure 6] A diagram showing an example of an image displayed on a display.

Embodiments for Carrying Out the Invention

[0014] Hereinafter, embodiments will be described based on the drawings.

[0015] (1) Outline of the Embodiment The ultrasonic diagnostic apparatus according to the embodiment includes a processor. The processor generates an ultrasonic image based on a first dataset acquired by transmitting and receiving a first ultrasonic wave, generates a plurality of types of masks for excluding a plurality of types of non-target regions from a first region of interest set within a beam scanning plane based on the first dataset, generates a composite mask by synthesizing the plurality of types of masks, identifies an attenuation display region within the first region of interest based on the composite mask, and generates an attenuation map representing an attenuation distribution within the attenuation display region based on a second dataset acquired by transmitting and receiving a second ultrasonic wave different from the first ultrasonic wave.

[0016] According to the above configuration, various non-target regions in the living body are excluded from the attenuation map. Therefore, it becomes easy to set a measurement region while avoiding non-target regions. Alternatively, it is possible to avoid an incorrect evaluation based on the attenuation information within non-target regions. For example, in the liver, the region of interest corresponds to the liver parenchyma having uniformity. Non-target regions are, for example, images of the contour of a structure, images inside a structure, shadows, etc. They are, respectively, high-luminance regions or low-luminance regions in the ultrasonic image.

[0017] Also, according to the above configuration, multiple types of masks are generated individually. Therefore, individual masks can be easily generated, or the effects of individual masks can be easily adjusted. Depending on the situation, the number or combination of multiple masks to be synthesized may be changed. Each individual mask has the effect of masking non-target areas. A filter having the effect of extracting a target area substantially corresponds to a mask. When generating multiple masks, all of the first dataset may be referenced, or a part of the first dataset may be referenced.

[0018] In an embodiment, the processor generates a luminance average map representing multiple luminance averages within a first region of interest based on the first dataset, and generates a first mask included in multiple types of maps based on the luminance average map.

[0019] In an embodiment, the processor calculates a reference value based on the first dataset, calculates a first threshold value and a second threshold value different from each other based on the reference value, applies an extraction process using the first threshold value and the second threshold value to the luminance average map, and generates a first mask in which the result of the extraction process is reflected.

[0020] By setting the first threshold value and the second threshold value based on the reference value, it becomes possible to determine appropriate first threshold value and second threshold value that conform to the situation. Therefore, the result of the extraction process is optimized. When generating the reference value, all or a part of the first dataset is referenced.

[0021] In an embodiment, the processor generates a luminance average map based on the data group within the first region of interest in the first dataset, and sets a reference value based on the data group within the second region of interest in the first dataset. The second region of interest corresponds to a part of the first region of interest. According to this configuration, when setting the reference value, it is possible to reduce the possibility that data within a non-target area is referenced.

[0022] In this embodiment, the processor sets a measurement region within the first region of interest and calculates attenuation information as numerical information based on the data set within the measurement region in the second dataset. The second region of interest is an intermediate region that is encompassed by both the first region of interest and the measurement region. Shadows tend to occur in the deep region, the rightmost region, and the leftmost region within the first region of interest. The second region of interest is defined in a region other than these areas.

[0023] In this embodiment, the depth range of the second region of interest is the same as the depth range of the measurement region. This configuration makes it less susceptible to the influence of the structural image when calculating the reference value. The size of the beam scanning direction of the second region of interest may be set within the range of 1 / 4 to 3 / 4 of the size of the beam scanning direction of the first region of interest.

[0024] In this embodiment, the first threshold is a threshold for extracting high-luminance regions as mask regions. The second threshold is a threshold for extracting low-luminance regions as mask regions. In the extraction process, the processor extracts from the luminance average map multiple luminance averages that exceed the first threshold and multiple luminance averages that fall below the second threshold.

[0025] In one embodiment, the processor generates a luminance variation map representing multiple luminance variations within a first region of interest based on a first dataset, and generates a second mask containing multiple types of maps based on the luminance variation map. The luminance variation is, for example, the luminance standard deviation or the luminance variance.

[0026] In one embodiment, the processor extracts multiple luminance variations exceeding a third threshold from the luminance variation map, thereby generating a second mask. In another embodiment, the second mask has the function of masking the edges of the structural image and the vicinity of those edges.

[0027] In this embodiment, the center frequency of the second ultrasound is higher than the center frequency of the first ultrasound, and the frequency bandwidth of the second ultrasound is narrower than the frequency bandwidth of the first ultrasound. This configuration allows for maintaining or improving the quality of the ultrasound image and increasing the accuracy of the attenuation calculation.

[0028] The attenuation map generation method according to the embodiment is an attenuation map generation method performed in an information processing device, and is characterized by including the steps of: generating an ultrasonic image based on a first data set obtained by transmitting and receiving a first ultrasonic wave; generating a plurality of types of masks for excluding a plurality of types of non-interest regions from a first region of interest set in the beam scanning plane based on the first data set; generating a composite mask by combining the plurality of types of masks; identifying an attenuation display region in the first region of interest based on the composite mask; and generating an attenuation map representing the attenuation distribution in the attenuation display region based on a second data set obtained by transmitting and receiving a second ultrasonic wave different from the first ultrasonic wave.

[0029] A program for implementing the above method is installed on the information processing device via a network or a portable storage medium. The information processing device is a device having a processor, for example, an ultrasound diagnostic device. The information processing device has a storage medium for non-temporarily storing the above program. The above program corresponds to a program product.

[0030] (2) Details of the embodiment Figure 1 shows an example configuration of an ultrasound diagnostic device according to an embodiment. The ultrasound diagnostic device 10 is a medical device used during ultrasound examinations of a patient. Specifically, the ultrasound diagnostic device 10 is used in ultrasound examinations of the liver. The ultrasound diagnostic device 10 may also be used in ultrasound examinations of other tissues. The ultrasound diagnostic device 10 is an information processing device.

[0031] The ultrasound diagnostic device 10 has a processor 12. The processor 12 is actually composed of one or more processing devices. Each device executes a program. The processor 12 may be composed of a CPU. In Figure 1, multiple functions performed by the processor 12 are represented by multiple blocks. A transmitting circuit 14, a receiving circuit 16, a display 42, and an operation panel 44 are connected to the processor 12. Memory, not shown, is also connected to the processor 12. The processor 12 may have its own memory.

[0032] The transmitting circuit 14 and the receiving circuit 16 are connected to the probe 18. The probe 18 has a transducer array consisting of multiple transducers. An ultrasonic beam is formed by the transducer array, and this ultrasonic beam is electronically scanned. The electronic scanning of the ultrasonic beam forms a beam scanning surface within the subject. The beam scanning surface is a two-dimensional echo data acquisition area. The probe 18 is a so-called convex probe. Other types of probes may be used as the probe 18. The probe 18 may be equipped with a 2D transducer array.

[0033] In this embodiment, a first ultrasonic beam and a second ultrasonic beam, which are different from each other, are formed. The electronic scanning of the first ultrasonic beam and the electronic scanning of the second ultrasonic beam may be repeated alternately. The formation of the first ultrasonic beam and the formation of the second ultrasonic beam may be repeated alternately with each electronic scanning. In any case, first received frame data is obtained for each electronic scanning of the first ultrasonic beam, and second received frame data is obtained for each electronic scanning of the second ultrasonic beam.

[0034] More specifically, the first ultrasonic beam is an ultrasonic beam used for tomographic imaging. The first ultrasonic beam (first transmitting beam and first receiving beam) is formed by the transmission and reception of the first ultrasound. The second ultrasonic beam is an ultrasonic beam used for attenuation measurement. The second ultrasonic beam (second transmitting beam and second receiving beam) is formed by the transmission and reception of the second ultrasound. The center frequency of the second ultrasound is higher than the center frequency of the first ultrasound. The frequency bandwidth of the second ultrasound is narrower than the frequency bandwidth of the first ultrasound.

[0035] The transmitting circuit 14 supplies multiple transmitting signals to the oscillator array in parallel during transmitting beam formation. The receiving circuit 16 is a circuit that processes multiple receiving signals output in parallel from the oscillator array during receiving beam formation. Specifically, the receiving circuit 16 applies phase-correcting summation to the multiple receiving signals. This yields received beam data. The multiple received beam data arranged in the electronic scanning direction constitute the received frame data.

[0036] In the illustrated configuration example, the first received frame data output from the receiving circuit 16 is sent to the first data processor 22, and the second received frame data output from the receiving circuit 16 is sent to the second data processor 30. The first data processor 22 processes each beam data to form a tomographic image (B-mode tomographic image). This beam data processing includes processes such as envelope detection and logarithmic compression. The second data processor 30 processes each beam data prior to attenuation calculations.

[0037] In this embodiment, as will be described later, a first region of interest is set within the beam scanning plane, and a second region of interest is set within the first region of interest. Furthermore, a measurement area is set within the first region of interest, and more specifically, a measurement area is set within the second region of interest. The beam scanning plane is formed by the electronic scanning of the first ultrasonic beam. The first region of interest is the area where the electronic scanning of the second ultrasonic beam takes place. The first region of interest corresponds to the maximum range of the attenuation display area (attenuation map display area). The second region of interest corresponds to the intermediate area between the first region of interest and the measurement area. The second region of interest is the area referenced when calculating the reference value, which will be described later.

[0038] The first converter 24 applies coordinate transformations and the like to the first received frame data output from the first data processor 22. This generates the first display frame data. The first display frame data is sent to the display processor 26. In practice, the display processor 26 receives a sequence of first display frame data consisting of multiple first display frame data arranged on the time axis. The sequence of first display frame data corresponds to a moving image (tomographic image).

[0039] The mask generator 28 generates multiple types of masks based on the first received frame data (the first beam data set corresponding to the beam scanning plane) and combines them to produce a composite mask. The composite mask extracts the region of interest and masks the region of non-interest. The generation of the composite mask will be described in detail later. The composite mask may also be generated based on the first display frame data.

[0040] The sub-attenuation calculator 32 applies attenuation calculations to the unmasked data set, i.e., the extracted data set, within the second received frame data (second beam dataset corresponding to the first region of interest) output from the second data processor 30, thereby generating an attenuation map. The attenuation map represents the attenuation distribution within the attenuation display region. The individual attenuations constituting the attenuation distribution correspond to the attenuation rate, attenuation coefficient, attenuation amount, etc.

[0041] The second converter 34 applies coordinate transformations to the attenuation map. As will be described later, the attenuation map in the rθ coordinate system is converted to an attenuation map in the xy coordinate system. The first converter 24 and the second converter 34 each correspond to digital scan converters (DSCs).

[0042] The display processor 26 has a color converter 36. The color converter 36 generates a color attenuation map based on the attenuation map output from the second converter. The degree of attenuation is expressed by a change in hue.

[0043] The main attenuation calculator 38 calculates the attenuation rate as attenuation information and numerical information based on the beam data sequence within the measurement area set within the first region of interest. The measurement area is determined based on the user's specification by referring to the attenuation map. For example, the measurement area is defined within a region with uniformity (liver parenchyma region) within the attenuation map.

[0044] The main attenuation calculator 38 calculates attenuation information with high precision. In contrast, the sub-attenuation calculator 32 calculates attenuation information simply and quickly. The attenuation calculation formula used in the main attenuation calculator 38 and the attenuation calculation formula used in the sub-attenuation calculator 32 may be the same, or they may be different. When using the same attenuation calculation formula, the reference range and reference resolution may be different.

[0045] The display unit 42 is composed of, for example, an organic EL display device, a liquid crystal display, etc. A monochrome tomographic image with a color attenuation map superimposed is displayed on the screen of the display unit 42, and the attenuation rate is also displayed as numerical information. Graphics representing multiple regions of interest are also displayed.

[0046] The controller 40 controls the operation of each component in the ultrasound diagnostic device. The control panel 44 includes multiple switches, multiple knobs, a keyboard, a trackball, and the like.

[0047] Figure 2 shows a plurality of regions of interest. θ indicates the beam scanning direction, and r indicates the depth direction.

[0048] The beam scanning surface 46 has a fan-shaped form. The beam scanning surface 46 is formed by the electronic scanning of the first ultrasonic beam B1. The central frequency of the first ultrasonic beam is represented by f1. The range of the beam scanning direction on the beam scanning surface 46 is from θ1 to θ2. The range of the depth direction on the beam scanning surface 46 is from r0 to r1. The beam scanning surface 46 includes a plurality of structures.

[0049] Based on user specification or automatically, a first region of interest 48 is defined within the beam scanning surface 46. The first region of interest 48 corresponds to the electronic scanning range of the second ultrasonic beam B2. The central frequency of the second ultrasonic beam is represented by f2. f1 < f2. The range of the beam scanning direction in the first region of interest 48 is from θ3 to θ4. The range of the depth direction in the first region of interest 48 is from r2 to r^{3}.

[0050] A measurement region 50 is defined within the first region of interest 48. The measurement region 50 is the range referred to when calculating the attenuation rate as numerical information. The range of the beam scanning direction in the measurement region 50 is from θ5 to θ6. The range of the depth direction in the measurement region 50 is from r4 to r5. The measurement region 50 is a region straddling a plurality of second ultrasonic beams arranged in the electronic scanning direction.

[0051] In an embodiment, a second region of interest 52 referred to when calculating the above reference value is set within the beam scanning surface 46. The second region of interest 52 is an intermediate region that is included in the first region of interest 48 and includes the measurement region 50. The range of the beam scanning direction in the second region of interest 52 is from θ7 to θ8. The range of the depth direction in the second region of interest 52 is from r6 to r7.

[0052] In the illustrated example, θ7 is set between θ3 and θ5, and θ8 is set between θ6 and θ4. r4 coincides with r6, and r5 coincides with r7. The illustrated second region of interest 52 is an example.

[0053] Shadows are likely to occur in the deeper parts of the beam scanning plane 46, and structural images are likely to appear in the deeper parts of the liver tomographic images. Shadows are likely to occur at the right and left edges of the beam scanning plane 46 due to the probe moving away from the biological surface. In addition, multiple reflections are likely to occur in the vicinity of the ultrasound probe, and in the liver, the skin layer and fat layer appear in the vicinity. By setting the second region of interest 52 while avoiding several such non-focus areas, it becomes possible to set appropriate first and second thresholds through the setting of appropriate reference values.

[0054] Figure 3 shows the algorithm performed by the mask generator 28. As already explained, a first region of interest 48 is set within the beam scanning plane 46, and a second region of interest 52 is set within the first region of interest 48. In addition, a measurement region 50 is set within the first region of interest 48. To assist in setting the measurement region 50, a masked color attenuation map is displayed according to the algorithm described below.

[0055] From the first beam dataset corresponding to the beam scanning plane 46, a first data set 58 corresponding to the first region of interest 48 is extracted. The first data set 58 follows a coordinate system defined by the electron scanning direction θ and the depth direction r.

[0056] By applying a filter F as a spatial operator to the first data set 58, a luminance average map 60 and a luminance standard deviation map (luminance SD map) 62 are generated. Filter F has a two-dimensional size centered on individual coordinates and calculates the mean (average value) and standard deviation. The standard deviation is luminance variability information, and variance may be calculated instead of the standard deviation. Here, luminance corresponds to echo intensity. The size of filter F is determined according to the size of the structure image to be detected.

[0057] On the other hand, a second data set 54 corresponding to the second region of interest 52 is extracted from the first beam data set corresponding to the beam scanning plane 46. The second data set 54 also follows a coordinate system defined by the electron scanning direction θ and the depth direction r. The second data set 54 may also be extracted from the first data set 58.

[0058] The reference value ST is obtained by averaging based on the second data group 54. Prior to averaging, the second data group 54 may be preprocessed. The first threshold Th1 is calculated by adding the first coefficient to the reference value ST. The first threshold Th1 is the threshold for masking high-luminosity structures. The second threshold Th2 is calculated by subtracting the second coefficient from the reference value ST. The second threshold Th2 is the threshold for masking low-luminosity structures (blood images, cystic fluid images, etc.) and poor echo areas, i.e., shadows.

[0059] The first extraction process 62 extracts non-focus regions using a first threshold and a second threshold. Specifically, data with a brightness exceeding the first threshold is extracted, and at the same time, data with a brightness below the second threshold is extracted. The first extraction process 62 extracts high-brightness non-focus regions and low-brightness non-focus regions. The first extraction process 62 generates a first mask M1.

[0060] In the second extraction process 66, data with luminance variations exceeding the third threshold are extracted from the luminance SD map 64. According to the second extraction process 66, not only the edges of the structure image but also the vicinity of the edges are extracted. The first extraction process 62 cannot extract the vicinity of the edges, but the second extraction process 66 can extract up to the vicinity of the edges. By masking up to the vicinity of the edges, it becomes possible to visualize the edges of the structure image on the tomographic image without being obstructed by the color attenuation map. In addition, it becomes easier to define the measurement area with a certain margin from the structure image.

[0061] A combined mask M3 is generated by combining the first mask M1 and the second mask M2, specifically by adding the first mask M1 and the second mask M2. Three or more types of masks may be combined.

[0062] The sub-attenuation calculator 32 generates an attenuation map 70 based on the unmasked data from the first data set 68 within the first region of interest. In other words, the attenuation map 70 is a map that avoids the non-attention region. In the second converter 34, the attenuation map 70 following the rθ coordinate is converted to an attenuation map 72 following the xy coordinate. The converted attenuation map 72 is converted to a color attenuation map. The color attenuation map is superimposed on the grayscale tomographic image. The measurement region 50 is determined while referring to the color attenuation map.

[0063] In one embodiment, for example, the attenuation rate may be calculated as follows. Based on a one-dimensional received intensity sequence P(x), a one-dimensional attenuation sequence A is defined by the following equation (1).

number

[0064] Here, f is the frequency of the ultrasound (typically the center frequency), and x is the depth (coordinate in the depth direction). The received intensity series P(x) consists of multiple received intensities obtained from multiple observation points aligned in the depth direction within the region of interest.

[0065] In equation (1), the received intensity sequence P(x) is equal to the reference intensity sequence (reference signal) P ref It is being compared with (x). Reference strength column P ref (x) is defined, for example, by equation (2) below. The following γ is a coefficient.

number

[0066] Reference strength sequence P by other functions ref (x) may be defined. The reference strength column may be given as a numerical column.

[0067] Attenuation rate sequence α r This is calculated, for example, according to equation (3) below.

number

[0068] i represents the depth number. The decay rate sequence α r Each of the attenuation rates that make up the equation is a relative attenuation rate. A large value may be given to M in the main attenuation calculator, and a small value may be given to M in the sub-attenuation calculator.

[0069] The absolute attenuation rate sequence α is calculated according to equation (4) below.

number

[0070] Here, k2 is the reference intensity sequence P ref This is a known damping rate corresponding to (x). k1 and k3 are adjustment coefficients, respectively. The damping rate α may be calculated by methods other than those described above.

[0071] Figure 4 shows a histogram 74 based on the second data set. The horizontal axis represents luminance (intensity), and the vertical axis represents the number of elements. A reference value ST is determined based on the second data set, and the first threshold Th1 and second threshold Th2 are determined based on the reference value ST. Since the reference value ST is determined adaptively, the first threshold Th1 and second threshold Th2 are automatically set to suit the situation.

[0072] Figure 5 shows an example of a composite mask M3 and an example of a color attenuation map 82. In the composite mask M3, the gray area 75 is the masked area, and the white area 76 is the unmasked area. The color attenuation map 82 is superimposed on the tomographic image. The tomographic image contains several structural images, but the color attenuation map 82 is displayed in a way that avoids them. Reference numeral 80 indicates areas that are not subject to attenuation calculation or areas outside the color attenuation map display area. It is possible to determine the measurement area 84 in an appropriate position while referring to the color attenuation map 82.

[0073] Figure 6 shows the image 86 displayed on the display unit. A color attenuation map 92 is superimposed on the tomographic image 88. Graphic element 90 indicates the first region of interest. For example, the measurement region is defined by moving the azimuth cursor 94 as indicated by symbol 96 while referring to the color attenuation map 92. The proximal end of the measurement region is represented by marker 98, and the distal end of the measurement region is represented by marker 100.

[0074] As indicated by the symbol 97, the position of the first region of interest may be changed based on the color attenuation map 92. A color bar 102 is displayed near the tomographic image 88. The color bar shows the correspondence between the magnitude of attenuation and the change in hue. Symbol 104 indicates the attenuation rate calculated based on the data within the measurement region.

[0075] According to the above embodiment, non-focus areas can be excluded from the attenuation map. In particular, low-luminance areas such as shadows, in addition to structural images, can also be excluded from the attenuation map. [Explanation of Symbols]

[0076] 10 ultrasound diagnostic devices, 12 processors, 28 mask generators, 32 sub-attenuation calculators, 36 color converters, 38 main attenuation calculators.

Claims

1. Including the processor, The aforementioned processor, Based on the first dataset acquired by transmitting and receiving the first ultrasound, an ultrasound image is generated. Based on the first dataset, multiple types of masks are generated to exclude multiple types of non-interest regions from the first region of interest set within the beam scanning plane. A composite mask is generated by combining the aforementioned multiple types of masks. Based on the composite mask, the attenuation display region within the first region of interest is identified. Based on a second dataset obtained by transmitting and receiving a second ultrasound different from the first ultrasound, an attenuation map representing the attenuation distribution within the attenuation display region is generated. An ultrasound diagnostic device characterized by the following features.

2. In the ultrasound diagnostic apparatus according to claim 1, The aforementioned processor, Based on the first dataset, a luminance average map is generated that represents the average luminance of multiple luminances within the first region of interest. Based on the luminance average map, a first mask included in the plurality of types of maps is generated. An ultrasound diagnostic device characterized by the following features.

3. In the ultrasound diagnostic apparatus according to claim 2, The aforementioned processor, Based on the first dataset described above, a reference value is calculated, Based on the aforementioned reference value, two different first and second threshold values ​​are calculated. An extraction process using the first and second thresholds is applied to the luminance average map. The first mask is generated, which reflects the results of the extraction process. An ultrasound diagnostic device characterized by the following features.

4. In the ultrasound diagnostic apparatus according to claim 3, The aforementioned processor, Based on the data set within the first region of interest in the first dataset, the luminance average map is generated. Based on the data set within the second region of interest in the first dataset, the reference value is set, The aforementioned second region of interest corresponds to a part of the aforementioned first region of interest. An ultrasound diagnostic device characterized by the following features.

5. In the ultrasound diagnostic apparatus according to claim 4, The aforementioned processor, A measurement area is set within the first region of interest, Based on the data set within the measurement area in the second dataset, attenuation information is calculated as numerical information. The second region of interest is an intermediate region that is included in the first region of interest and also includes the measurement region. An ultrasound diagnostic device characterized by the following features.

6. In the ultrasound diagnostic apparatus according to claim 5, The depth range of the second region of interest is the same as the depth range of the measurement region. An ultrasound diagnostic device characterized by the following features.

7. In the ultrasound diagnostic apparatus according to claim 3, The first threshold is a threshold for extracting high-luminance regions as mask regions. The second threshold is a threshold for extracting low-luminance regions as mask regions. The aforementioned processor, In the extraction process, multiple luminance averages exceeding the first threshold and multiple luminance averages below the second threshold are extracted from the luminance average map. An ultrasound diagnostic device characterized by the following features.

8. In the ultrasound diagnostic apparatus according to claim 1, The aforementioned processor, Based on the first dataset, a luminance variation map is generated that represents multiple luminance variations within the first region of interest. Based on the luminance variation map, a second mask is generated that is included in the plurality of types of maps. An ultrasound diagnostic device characterized by the following features.

9. In the ultrasound diagnostic apparatus according to claim 8, The processor extracts multiple luminance variations exceeding a third threshold from the luminance variation map, and thereby generates the second mask. An ultrasound diagnostic device characterized by the following features.

10. In the ultrasound diagnostic apparatus according to claim 8, The second mask has the function of masking the edges of the structural image and the vicinity of those edges. An ultrasound diagnostic device characterized by the following features.

11. In the ultrasound diagnostic apparatus according to claim 1, The center frequency of the second ultrasound is higher than the center frequency of the first ultrasound. The frequency band of the second ultrasound is narrower than the frequency band of the first ultrasound. An ultrasound diagnostic device characterized by the following features.

12. A method for generating an attenuation map performed in an information processing device, A step of generating an ultrasound image based on a first dataset acquired by transmitting and receiving a first ultrasound, A step of generating multiple types of masks to exclude multiple types of non-interest regions from a first region of interest set within the beam scanning plane based on the first dataset, A step of generating a composite mask by combining the aforementioned multiple types of masks, A step of identifying an attenuation display region within the first region of interest based on the composite mask, A step of generating an attenuation map representing the attenuation distribution within the attenuation display region based on a second data set obtained by transmitting and receiving a second ultrasound different from the first ultrasound, A method for generating an attenuation map, characterized by including the following:

13. A program for executing a decay map generation method in an information processing device, A function to generate an ultrasound image based on a first dataset acquired by transmitting and receiving a first ultrasound, Based on the first dataset, a function is provided to generate multiple types of masks for excluding multiple types of non-interest regions from a first region of interest set within the beam scanning plane, A function to generate a composite mask by combining the aforementioned multiple types of masks, Based on the composite mask, a function to identify the attenuation display region within the first region of interest, A function to generate an attenuation map representing the attenuation distribution within the attenuation display region based on a second data set obtained by transmitting and receiving a second ultrasound different from the first ultrasound, A program characterized by including the following.

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