Ultrasonic diagnostic apparatus and method of setting action condition

Abstract

The present invention relates to an ultrasonic diagnostic apparatus and an operation condition setting method. A reception data string (78) containing a plurality of reception data corresponding to a plurality of transmission / reception conditions is generated. A plurality of data processes following a plurality of data processing conditions are applied to each reception data. A blood flow data set (79) is generated from the reception data string (78) by this. An optimal transmission / reception condition and an optimal data processing condition are determined by evaluating the blood flow data set (79).

Description

Technical Field

[0001] This disclosure relates to an ultrasound diagnostic device and a method for setting operating conditions, and particularly to the optimization of operating conditions. Background Technology

[0002] Ultrasound diagnostic devices have multiple operating modes. Among these modes, color flow mapping (CFM) mode is commonly included. CFM mode displays a composite image consisting of a black-and-white tomographic image and a color blood flow image superimposed on it. CFM mode is also known as color Doppler mode.

[0003] In CFM mode, to obtain good blood flow images, the operating conditions of the ultrasound diagnostic device need to be optimized according to the patient and the purpose of the examination. In particular, the transmission / reception conditions and data processing conditions need to be optimized.

[0004] Transmission and reception conditions refer to the ultrasonic wave transmission and reception conditions used to acquire Doppler information. Data processing conditions refer to the signal and data processing conditions used to image the Doppler information. As an example of transmission conditions, the pulse repetition time (PRT) (pulse repetition frequency (PRF)) can be cited. As an example of data processing conditions, the cutoff frequency of a filter used to suppress clutter components (strong components originating from low-speed moving parts) in the received signal can be cited.

[0005] For example, when veins in the kidneys or lower limbs are the subjects of observation, if the transmission and reception conditions and data processing conditions are not set appropriately, the veins will hardly be represented in color on the CFM image, or even the soft tissue will be over-represented in color.

[0006] It is not always easy for users (physicians, medical technicians, etc.) to manually optimize data transmission and reception conditions and data processing conditions in accordance with various situations. The more parameters that need to be adjusted, the greater the problem becomes.

[0007] The ultrasound diagnostic apparatus disclosed in Document 1 (JP Patent Application Publication No. 2013-27454) has the function of automatically setting the PRF based on Doppler frequency shift distribution data. The ultrasound diagnostic apparatus disclosed in Document 2 (JP Patent Application Publication No. 2004-73672) has the function of automatically setting conditions for removing clutter components. The ultrasound diagnostic apparatus disclosed in Document 3 (JP Patent Application Publication No. Hei 8-154935) has a CFM calculation unit equipped with a decimator. None of these documents disclose a technique for simultaneously optimizing transmission and reception conditions and data processing conditions in CFM mode.

[0008] To obtain good blood flow images, both transmission and reception conditions and data processing conditions need to be optimized. Optimizing both transmission and reception conditions manually at the same time is not easy. Summary of the Invention

[0009] The purpose of this disclosure is to automatically optimize send / receive conditions and data processing conditions to reduce the burden on users. Alternatively, the purpose of this disclosure is to automatically and quickly optimize send / receive conditions and data processing conditions when executing CFM mode.

[0010] The ultrasound diagnostic apparatus disclosed herein is characterized by comprising: a first generator for generating a received data string containing a plurality of received data corresponding to a plurality of transmit and receive conditions; a second generator for generating a plurality of blood flow data by applying a plurality of data processing according to a plurality of data processing conditions to each of the received data, thereby generating a blood flow dataset from the received data string; an evaluator for determining optimal transmit and receive conditions and optimal data processing conditions by evaluating the blood flow dataset; and a setter for setting the optimal transmit and receive conditions and the optimal data processing conditions for the ultrasound diagnostic apparatus.

[0011] The method for setting operating conditions of an ultrasound diagnostic device disclosed herein is characterized by comprising the following steps: generating a received data string containing multiple received data corresponding to multiple transmit and receive conditions; applying multiple data processing methods to each received data according to multiple data processing conditions to generate multiple blood flow data, thereby generating a blood flow dataset from the received data string; determining the optimal transmit and receive conditions and the optimal data processing conditions by evaluating the blood flow dataset; and setting the optimal transmit and receive conditions and the optimal data processing conditions for the ultrasound diagnostic device. Attached Figure Description

[0012] Figure 1 This is a block diagram illustrating the ultrasonic diagnostic apparatus involved in the implementation.

[0013] Figure 2 This is a block diagram illustrating a structural example of the blood flow image formation section.

[0014] Figure 3 This is a graph representing the filter characteristics of a clutter filter.

[0015] Figure 4 This is a graph representing the transformation characteristics of a logarithmic transformer.

[0016] Figure 5 This is a diagram illustrating the first method for receiving and processing data.

[0017] Figure 6 This is a diagram illustrating the second method for receiving and processing data.

[0018] Figure 7 This is a diagram illustrating the third method for receiving and processing data.

[0019] Figure 8 This is a diagram illustrating an example of the structure of the optimal condition search unit.

[0020] Figure 9 This is a flowchart representing an example of an action.

[0021] Figure 10 It is a graph used to illustrate the effect of optimization. Detailed Implementation

[0022] The following description of the implementation method is based on the accompanying drawings.

[0023] (1) Overview of the implementation method

[0024] The ultrasound diagnostic apparatus according to the embodiment includes a first generation unit, a second generation unit, an evaluation unit, and a setting unit. The first generation unit generates a received data string containing multiple received data corresponding to multiple transmission and reception conditions. The second generation unit applies multiple data processing methods following multiple data processing conditions to each received data to generate multiple blood flow data, thereby generating a blood flow dataset from the received data string. The evaluation unit evaluates the blood flow dataset to determine the optimal transmission and reception conditions and the optimal data processing conditions. The setting unit sets the optimal transmission and reception conditions and the optimal data processing conditions for the ultrasound diagnostic apparatus. The first generation unit functions as a first generator. The second generation unit functions as a second generator. The evaluation unit functions as an evaluator. The setting unit functions as a setting unit.

[0025] Multiple condition combinations are defined based on various transmit / receive and data processing conditions. According to this structure, multiple blood flow data points corresponding to these condition combinations are automatically generated. The optimal transmit / receive and data processing conditions are automatically determined and set through the evaluation of these multiple blood flow data points. Therefore, the quality of blood flow images can be improved without burdening the user.

[0026] Even with optimal transmit and receive conditions, the quality of blood flow images cannot be improved without optimal data processing conditions. Similarly, even with optimal data processing conditions, the quality of blood flow images cannot be improved without optimal transmit and receive conditions. Based on the above structure, both transmit and receive conditions and data processing conditions can be optimized simultaneously.

[0027] Transmission and reception conditions are generally defined by one or more parameters specifying the transmission and reception of ultrasound waves. Data processing conditions are generally defined by one or more parameters specifying data processing (including signal processing). Setting optimal conditions means making them effective. The object of setting optimal transmission and reception conditions and optimal data processing conditions is the ultrasound diagnostic device, specifically, the transceiver unit and the data processing unit within the ultrasound diagnostic device. To achieve high-speed data processing, received data is stored in a memory, and multiple data processing steps are sequentially applied to the same received data read from the memory.

[0028] In this embodiment, the first generation unit includes a transceiver unit and a processing unit. At least one actual transceiver condition is set for the transceiver unit. The transceiver unit outputs at least one actual received data corresponding to the at least one actual transceiver condition. The processing unit processes the at least one actual received data to generate at least one virtual received data corresponding to at least one virtual transceiver condition. The aforementioned multiple transceiver conditions consist of at least one actual transceiver condition and at least one virtual transceiver condition. The aforementioned received data string consists of at least one actual received data and at least one virtual received data. The transceiver unit is equivalent to a transceiver circuit. The processing unit functions as a processor.

[0029] If one or more virtual received data can be generated from one actual received data, the number of transmissions can be reduced. Virtual received data can be considered pseudo received data.

[0030] Furthermore, the transceiver unit and the preprocessing unit described later correspond to the first generation unit (first generator), or the transceiver unit described later corresponds to the first generation unit (first generator). The blood flow image forming unit described later corresponds to the second generation unit (second generator).

[0031] In this implementation, the aforementioned at least one actual transmit / receive condition can be multiple actual transmit / receive conditions. The aforementioned at least one actual received data can be multiple actual received data. The aforementioned at least one virtual transmit / receive condition can be multiple virtual transmit / receive conditions. The aforementioned at least one virtual received data can be multiple virtual received data. Based on this structure, a large amount of received data corresponding to a large number of condition combinations can be easily generated.

[0032] In this implementation, each actual received data contains multiple packets arranged on a timeline, obtained under the same actual transmission and reception conditions. The processing unit performs inter-packet division processing on each actual received data, thereby generating one or more virtual received data from each actual received data.

[0033] In virtual measurements used to search for the optimal combination of conditions, ultrasonic waves are transmitted along one or more sound rays and reflected waves are received. Multiple received beam data acquired sequentially from the same sound ray under the same actual transmission and reception conditions constitute a packet string. Generally, motion information is generated by applying autocorrelation operations, etc., to the Doppler data strings extracted from the packet string. Inter-packet processing is equivalent to increasing the pulse repetition period (PRT) (decreasing the pulse repetition frequency (PRF)). Based on the above structure, without actually varying the PRT, the same received data can be obtained as if the PRT had been varied.

[0034] A formal measurement (actual measurement) is performed after a virtual measurement. Both virtual and formal measurements are performed consecutively on the same subject. When the examiner manually searches for the optimal combination of conditions, this search can take a long time, or the optimal combination may not be determined. The ultrasound diagnostic apparatus according to the implementation method avoids these problems and reduces the burden on both the examiner and the subject.

[0035] In this implementation, the evaluation unit includes a calculation unit and a determination unit. The calculation unit calculates an evaluation value for each blood flow data point. The determination unit determines the optimal transmission and reception conditions and the optimal data processing conditions based on multiple evaluation values ​​corresponding to multiple blood flow data points. Various evaluation methods can be employed when evaluating each blood flow data point, i.e., evaluating each combination of conditions. For example, evaluation values ​​reflecting the ratio of blood flow signals to non-blood flow signals (SN ratio), evaluation values ​​reflecting the proportion of blood flow images within the blood flow region, and evaluation values ​​reflecting the amount of blood flow images exceeding the blood flow region can be used. The calculation unit functions as an arithmetic unit. The determination unit functions as a determination unit. Furthermore, the optimal condition search unit, described later, corresponds to both the evaluation unit (evaluator) and the setting unit (setting unit), and also corresponds to both the calculation unit (arithmetic unit) and the determination unit (determiner).

[0036] In this implementation, a reference region is defined for the blood flow area on the beam scanning plane. The aforementioned calculation unit references the portion of each blood flow data point corresponding to the reference region as blood flow information, and references all or other portions of each blood flow data point as comparison information. Based on this, an evaluation value is calculated for each blood flow data point, using both the blood flow information and the comparison information.

[0037] The reference region can be set manually or automatically. The reference region can be one-dimensional, two-dimensional, or three-dimensional. It can consist of several or dozens of pixels arranged along a specific acoustic chord. The reference region can be set across multiple acoustic chords. A comparison region can be set separately from the reference region. The comparison region is the area compared to the reference region and can be one-dimensional, two-dimensional, or three-dimensional. The comparison region can be set to a different area that does not contain the reference region; if the reference region appears relatively small, the comparison region can be set to include the reference region. Furthermore, the portion of the blood flow data corresponding to the reference region is the region of interest, while other portions of the blood flow data are different from the region of interest.

[0038] In this implementation, each transmit / receive condition includes a pulse repetition period. Each data processing condition includes filter characteristics. The optimal transmit / receive condition includes an optimal pulse repetition period. The optimal data processing condition includes optimal filter characteristics.

[0039] The method for setting operating conditions for an ultrasound diagnostic device according to the embodiment includes a first generation step, a second generation step, an evaluation step, and a setting step. In the first generation step, a received data string containing multiple received data corresponding to multiple transmit / receive conditions is generated. In the second generation step, multiple blood flow data are generated by applying multiple data processing methods following multiple data processing conditions to each received data. Thus, a blood flow dataset is generated from the received data string. In the evaluation step, the optimal transmit / receive conditions and optimal data processing conditions are determined by evaluating the blood flow dataset. In the setting step, the optimal transmit / receive conditions and optimal data processing conditions are set for the ultrasound diagnostic device.

[0040] Based on the above method, when the CFM mode is selected, the optimal combination of conditions for the subject can be determined and set quickly before the formal measurement of the subject.

[0041] (2) Details of the implementation method

[0042] exist Figure 1 The image shows an ultrasound diagnostic apparatus according to an embodiment. This ultrasound diagnostic apparatus is a medical device used to perform ultrasound examinations on patients in medical institutions such as hospitals. The ultrasound diagnostic apparatus has multiple operating modes, including a CFM mode. The CFM mode is a mode that overlays a color blood flow image onto a black-and-white tissue tomographic image and displays the resulting synthetic image. The structure and operation related to the CFM mode are described in detail below.

[0043] The ultrasonic probe 10 transmits ultrasonic waves into the organism 12 while in contact with it, and receives reflected waves from within the organism 12. The ultrasonic probe 10 has an array of vibrating elements comprising multiple transducers arranged in a linear or arcuate pattern. An ultrasonic beam 14 is formed by the transducer array, and the ultrasonic beam 14 is electronically scanned. Electronic linear scanning and electronic sector scanning are known methods. The beam scanning surface 16 is repeatedly formed by repeatedly electronically scanning the ultrasonic beam. Alternatively, a two-dimensional transducer array can be provided within the ultrasonic probe 10, thereby obtaining volumetric data from within the organism 12.

[0044] The ultrasound diagnostic apparatus described in this embodiment has the following function: when CFM mode is selected, a virtual measurement is performed before the formal measurement, thereby setting the optimal combination of conditions. During the virtual measurement, an ultrasound beam can be repeatedly formed along a specific acoustic ray (a specific scan line), or an electronic scan of the ultrasound beam can be repeatedly performed within a narrow scan range corresponding to the reference area described later. Furthermore, the formal measurement corresponds to the examination procedure of performing an ultrasound examination on the subject, while the virtual measurement corresponds to the preparation procedure (or tuning procedure) before the formal measurement.

[0045] In the illustrated example, a cross-section of a blood vessel 18 is included within the beam scanning plane 16. Blood vessel 18 is, for example, a vein within a kidney or a vein in a lower limb. When imaging the blood flow within these vessels, numerous parameters need to be optimized. Such an operation is generally difficult and time-consuming. To eliminate or mitigate this problem, a function is provided to set the optimal combination of the aforementioned conditions.

[0046] The transceiver unit 19 comprises a transmitting unit 20 and a receiving unit 22. The transmitting unit 20 is an electronic circuit that supplies multiple transmitting signals in parallel to multiple vibrating elements during transmission. A transmitting beam is formed by supplying multiple transmitting signals. The receiving unit 22 is an electronic circuit that generates received beam data by processing multiple received signals output in parallel from multiple vibrating elements during reception. The processing in the receiving unit 22 includes phase alignment and summing (delay and summing), orthogonal detection, etc., and the received beam data consists of multiple echo data arranged in the depth direction.

[0047] Multiple receiving beam data for forming tomographic images are sequentially output from the receiving unit 22 to the tomographic image forming unit 30. The tomographic image forming unit 30 has a digital scan converter (DSC) that forms a tomographic image based on the multiple receiving beam data. The DSC has coordinate transformation, pixel interpolation, and frame rate conversion functions. A tomographic image is an image representing the soft tissue structure within a living organism. Data characterizing the tomographic image is sent from the tomographic image forming unit 30 to the display processing unit 38.

[0048] During formal measurement, the preprocessor 32 does not function, and outputs multiple received beam data for blood flow image formation from the receiving unit 22 to the blood flow image forming unit 36. The blood flow image forming unit 36 ​​forms a blood flow image based on the multiple received beam data. The blood flow image forming unit 36 ​​includes a clutter filter, an autocorrelation unit, and a DSC (Dynamic Segmentation Characteristic).

[0049] Specifically, during formal measurements, under the same transmit and receive conditions, multiple receive beam data (multiple packets) are continuously acquired for each sound ray. In other words, one packet string is acquired for each sound ray. The packet strings are repeatedly acquired while switching the sound ray address along the electronic scanning direction. The blood flow image forming unit 36 ​​generates a blood flow image based on the multiple packet strings thus obtained.

[0050] The blood flow image forming unit 36 ​​according to the embodiment has the function of forming various types of blood flow images. These various types of blood flow images include blood flow images characterizing the velocity distribution (two-dimensional distribution of blood flow velocity) on the beam scanning plane, auxiliary blood flow images characterizing the variance distribution (two-dimensional distribution of blood flow velocity variance) on the beam scanning plane, and blood flow images characterizing the power distribution (two-dimensional distribution of blood flow power) on the beam scanning plane. A specific blood flow image selected by the user is displayed. Blood flow images representing both velocity and variance distributions can also be displayed. Data characterizing the blood flow images is sent to the display processing unit 38.

[0051] In the processing of blood flow information, a single block string constitutes a data unit in the data processing. In the following, depending on the circumstances, the block string will be represented as received data.

[0052] During virtual measurement, multiple received data (multiple packet strings) are generated corresponding to multiple transmit and receive conditions, and multiple data processing conditions are applied to each received data (packet string). This generates multiple blood flow data corresponding to combinations of multiple conditions.

[0053] For example, when only PRT is optimized as a transmit / receive condition, at least one received data packet is obtained from a specific ray passing through the reference area described later. When both PRT and wavenumber are optimized as transmit / receive conditions, at least two received data packets are obtained from the specific ray. Furthermore, in either case, multiple packet streams can be obtained from multiple rays passing through the reference area.

[0054] The preprocessor 32 has the function of performing inter-packet division processing. Through inter-packet division processing, one or more received data (virtual received data) corresponding to one or more virtual PRTs can be generated from the received data (actual received data) actually obtained under the actual set PRT (actual PRT).

[0055] For example, a 1 / 2 PRT can be virtually achieved by dividing by 1 / 2, and a 1 / 3 PRT can be virtually achieved by dividing by 1 / 3. The virtual packet string can also be described as an artificial packet string or a pseudo-packet string. Through the above packet division processing, the number of transmissions and receptions can be reduced during the search for the optimal combination of conditions, thereby shortening the virtual determination time.

[0056] The preprocessor 32 has a memory 34. Actual received data is stored in the memory 34. Additionally, one or more generated virtual received data sets are stored in the memory 34. Each stored received data set is repeatedly read out. Alternatively, multiple PRTs can be sequentially configured without using inter-packet demultiplexing processing.

[0057] During virtual measurement, a received data string containing actual received data and one or more virtual received data is generated. In the blood flow image forming unit 36, multiple data processing is applied to each received data constituting the received data string. This generates a blood flow dataset containing multiple blood flow data. Each blood flow data constituting the blood flow dataset is sent to the optimal condition search unit 28.

[0058] The data processing in the blood flow image forming unit 36 ​​is defined by multiple parameters. These parameters include, for example, parameters that determine the characteristics of the clutter filter, parameters that determine the threshold level in threshold processing, parameters that determine the gain of the blood flow data, and parameters that determine the characteristics of the logarithmic transform. All or some of these parameters become the object of optimization.

[0059] The display processing unit 38 has image synthesis and color processing functions. During formal measurements, the display processing unit 38 generates a CFM image by overlaying a color blood flow image onto a black-and-white tomographic image. The CFM image is displayed on the monitor 40. During virtual measurements, for example, blood flow information is not displayed, and only the tomographic image is displayed as a still image. However, it is also possible to display individual blood flow data generated during virtual measurements. For example, multiple blood flow images corresponding to multiple condition combinations can be displayed at a glance.

[0060] The arithmetic control unit 24 is, for example, composed of a processor (specifically, a CPU) that executes programs. The arithmetic control unit 24 controls... Figure 1 The operation of each structure shown. The arithmetic control unit 24 has multiple functions. In Figure 1 Among these functions, two representative functions are the transceiver control unit 26 and the optimal condition search unit 28.

[0061] The transceiver control unit 26 sets the transmission and reception conditions for the transmitting unit 20 and the receiving unit 22. The transmission and reception conditions include pulse repetition period (PRT), wave number (the number of waves constituting the transmitted pulse), transmission voltage, and reception gain. Each of these is a parameter, and all or some of them become the object of optimization.

[0062] The optimal condition search unit 28 controls the virtual measurement. Specifically, during the virtual measurement, the transceiver control unit 26 controls the transmission and reception of ultrasound waves and controls the data processing in the blood flow image forming unit 36. The optimal condition search unit 28 functions as both an evaluation unit (evaluator) and a setting unit (setter). Specifically, the optimal condition search unit 28 calculates multiple evaluation values ​​based on multiple blood flow data, and determines the optimal transmission and reception conditions and the optimal data processing conditions based on these multiple evaluation values. Then, the optimal condition search unit 28 instructs the transceiver control unit 26 on the optimal transmission and reception conditions and instructs the blood flow image forming unit 36 ​​on the optimal data processing conditions. Based on this, the formal measurement is performed.

[0063] The operation panel 42 includes a trackball, multiple switches, a keyboard, etc. The operation panel 42 includes a button indicating the start of the optimal condition search. The display 40 is, for example, an organic EL device, a liquid crystal display, etc. Furthermore, the tomographic image forming unit 30, the preprocessor 32, the blood flow image forming unit 36, and the display processing unit 38 can each be configured as a processor. The tomographic image forming unit 30, the preprocessor 32, the blood flow image forming unit 36, and the display processing unit 38 can be implemented as functions of the arithmetic control unit (CPU) 24.

[0064] exist Figure 2 An example of the structure of the blood flow image forming unit 36 ​​is shown. Figure 2 The clutter filter 44, threshold processor 48, blood flow information processor 52, and DSC 54 are shown. Their operation is controlled by the aforementioned arithmetic control unit. The blood flow image forming unit 36 ​​further includes a gain adjuster, a logarithmic transformer, etc., which are not illustrated.

[0065] Clutter filter 44 is a filter that removes or suppresses clutter components contained in the blood flow data (specifically, the data from each received beam) 46. Clutter components are generated by echoes from soft tissue moving at low speeds. Clutter filter 44 is also called a wall motion filter. The cutoff frequency is changed by altering the first parameter of clutter filter 44, and the steepness of the filter characteristics is changed by altering the second parameter of clutter filter 44.

[0066] The threshold processor 48 applies threshold processing to the blood flow data output from the clutter filter 44. For example, it removes components below the threshold or components above the threshold. The threshold is changed by modifying the parameters provided by the threshold processor 48.

[0067] The blood flow information processor 52 includes an autocorrelation unit, a velocity processor, a variance processor, and a power processor. Within the blood flow information processor 52, blood flow data 56 is generated from the received data. The blood flow data 56 includes velocity information v, variance information σ, and power information P.

[0068] During the formal measurement, in the DSC54, blood flow image data 58 is generated based on multiple spatially arranged blood flow data. The blood flow image data is then sent to the display processing unit. The blood flow image data may be, for example, data representing a two-dimensional distribution of velocity, data representing a two-dimensional distribution of velocity and variance, or data representing a two-dimensional distribution of power.

[0069] During virtual measurement, blood flow data 60 output from blood flow information processor 52 or blood flow image data 62 output from DSC 54 is sent to the optimal condition search unit 28. For example, if the gain adjuster and logarithmic converter are located after DSC 54, and the processing performed in these components is also optimized, the blood flow image data 62 that has passed through them is sent to the optimal condition search unit 28.

[0070] exist Figure 3 The filter characteristics 68 of the clutter filter are shown in the figure. The horizontal axis is the velocity axis, and the vertical axis is the intensity axis. In the two-dimensional space defined by these two axes, the intensity of the blood flow component 64 is relatively small compared to the intensity of the clutter component 66. Therefore, the aim is to effectively suppress the clutter component 66. Corresponding to the blood flow component 64 and the clutter component 66, for example, the cutoff frequency can be increased (refer to reference numeral 68A). In addition, for example, the steepness of the filter characteristics (gradient angle of the rising edge) can be increased (refer to reference numeral 68B). Such adjustments can be made by changing the first and second parameters mentioned above.

[0071] exist Figure 4The characteristics of the logarithmic transformer 70 are shown in the figure. The horizontal axis is the input axis, and the vertical axis is the output axis. When its characteristics are defined by the mathematical formula shown in the figure, the parameters a and c contained in the mathematical formula change according to the conditions.

[0072] While it is possible to optimize all of the multiple parameters assigned to the blood flow image forming unit 36, it is preferable to optimize only a portion of them to shorten the virtual measurement time. The remaining parameters can be adjusted manually as needed.

[0073] Next, the data receiving and processing method will be explained. Figure 5 The first received data processing method is shown. In the first received data processing method, no inter-packet division processing is performed.

[0074] (A) indicates the setting of reference region 74. For example, while referencing a tomographic image, the user sets a one-dimensional reference region 74 within the beam scanning plane 72. The acoustic ray (scan line, beam azimuth) passing through reference region 74 is shown as θ1. Reference region 74 can be set automatically. In the illustrated example, comparison regions 76A and 76B are automatically set before and after reference region 74 along acoustic ray θ1. These can be set by the user. Alternatively, acoustic ray θ1 as a whole can be used as a comparison region. Alternatively, reference region 74 and comparison regions 76A and 76B can each be used as two-dimensional regions.

[0075] (B) represents multiple distinct transmit / receive conditions. In the illustrated example, m transmit / receive conditions, from transmit / receive condition 1 to transmit / receive condition m, are set sequentially. (C) represents m received data points, i.e., received data 1 to received data m, obtained sequentially under the m transmit / receive conditions. These constitute the received data string 78. (D) represents n distinct data processing conditions applied to each received data point, i.e., data processing condition 1 to data processing condition n. Here, m and n are integers greater than or equal to 2.

[0076] (E) represents the m×n blood flow data generated by applying n data processing methods to m received data, namely blood flow data 11 to blood flow data mn. They constitute the blood flow dataset 79. (F) represents the m×n evaluation values ​​calculated based on the m×n blood flow data, namely evaluation value 11 to evaluation value mn.

[0077] Among m×n blood flow data points, the blood flow data point that generated the best evaluation value is identified. Based on this blood flow data point, the optimal combination of conditions is determined. That is, the optimal transmission and reception conditions and the optimal data processing conditions are determined.

[0078] exist Figure 6The diagram illustrates a second received data processing method. In this method, inter-packet processing is performed. In the illustrated example, the only transmit / receive parameter subject to change is PRT.

[0079] (A) indicates the setting of reference region 74. Comparison regions 76A and 76B are set before and after reference region 74 on the acoustic ray θ1 within the scanning plane 72. One received beam data obtained from acoustic ray θ1 constitutes one packet 80. (C0) indicates the actual packet string (actual received data) obtained from acoustic ray θ1. The actual packet string consists of multiple packets 80' arranged on the time axis.

[0080] One or more virtual blocks are generated by applying inter-block division to the actual blocks. (C1) represents the virtual block generated with an inter-block division rate of 1 / 2, (C2) represents the virtual block generated with an inter-block division rate of 1 / 3, and (C3) represents the virtual block generated with an inter-block division rate of 1 / 4. An inter-block division rate of 1 / i is equivalent to i times the PRT (1 / i of the PRF). i is an integer greater than or equal to 2.

[0081] The received data string 82 consists of the actual data packets and multiple virtual data packets generated from them. The received data string 82 consists of m received data packets. Each received data packet undergoes n data processing steps. This generates m×n blood flow data points, and their individual evaluations determine the optimal PRF and optimal data processing conditions.

[0082] exist Figure 7 The diagram illustrates the third received data processing method. In this method, inter-packet division processing is performed. In the illustrated example, the transmit / receive parameters that are optimized are PRT and wavenumber. Wavenumber is the number of waves constituting the transmitted pulse, equivalent to wave train length. (B1) represents wavenumbers 1 to j. j is an integer greater than or equal to 2.

[0083] By fixing the PRF and repeatedly transmitting and receiving while changing the wavenumber, as shown in (C0), the j actual packet strings from actual packet string 84-1 to actual packet string 84-j are obtained.

[0084] By applying inter-group division to j actual group strings, one or more virtual group strings are generated for each actual group string. (C1) represents the j virtual group strings generated with an inter-group division rate of 1 / 2, (C2) represents the j virtual group strings generated with an inter-group division rate of 1 / 3, and (C3) represents the j virtual group strings generated with an inter-group division rate of 1 / 4.

[0085] The received data string 86 consists of the actual data packets and multiple virtual data packets generated from them. The received data string 86 consists of m received data packets. Each received data packet is processed by n data processing steps. As a result, m×n blood flow data packets are generated, and their individual evaluations are used to determine the optimal transmission and reception conditions (optimal PRF and optimal wavenumber) and the optimal data processing conditions.

[0086] exist Figure 8 The operation of the optimal condition search unit 28 is schematically shown. During virtual measurement, the optimal condition search unit 28 performs switching settings for m transmit and receive conditions, switching control for n data processing, evaluation of m×n blood flow data, determination of the optimal condition combination, and setting of the optimal condition combination.

[0087] exist Figure 8 The diagram shows blood flow data 86-1 to 86-mn corresponding to condition combinations #1 to #mn. Each blood flow data consists of multiple pixel data 88. Each pixel data 88 contains velocity information, variance information, power information, etc. A portion within a reference region 74 is extracted from each blood flow data as reference information. The reference region 74 is set within the blood flow region. The reference region 74 has a size of, for example, several or tens of pixels. Comparison regions 76A and 76B are set separately from the reference region 74, and comparison information is extracted from them. Comparison regions 76A and 76B are set within the non-blood flow region.

[0088] The optimal condition search unit 28 includes an evaluation value calculator 90, a decision 98, and a setting unit 100. The evaluation unit 89 is composed of the evaluation value calculator 90 and the decision 98. The evaluation value calculator 90 has a first calculator 92, a second calculator 94, and a third calculator 96. The first calculator 92 calculates a first coefficient S based on reference information for each blood flow data point. B The second arithmetic unit 94 calculates the second coefficient S based on comparison information for each blood flow data point. C In the first coefficient S B And the second coefficient S C During calculations, you can refer to all or part of the speed, variance, and power information. Additionally, p1 to pk represent k parameters. These k parameters include one or more parameters specifying transmission and reception conditions, and one or more parameters specifying data processing conditions.

[0089] The third arithmetic unit 96, for example, performs the operation S. B / S CThe evaluation value E is calculated. Evaluation value E represents the degree of quality of the blood flow image. Various evaluation values ​​can be used, such as those representing the signal-to-noise ratio, the proportion of the blood flow image relative to the blood flow region, and the amount by which the blood flow image extends beyond the blood flow region. A comprehensive evaluation value can be calculated based on multiple evaluation values.

[0090] The decision maker 98 determines the best evaluation value, such as the largest evaluation value, from m×n evaluation values. The transmission and reception conditions and data processing conditions that generate the largest evaluation value are determined to be the optimal transmission and reception conditions and the optimal data processing conditions. The setting device 100 instructs the transmission and reception control unit on the optimal transmission and reception conditions and the blood flow image forming unit on the optimal data processing conditions. Then, the formal measurement begins.

[0091] exist Figure 9 This demonstrates an example of the operation of an ultrasound diagnostic device. S10 corresponds to a virtual measurement procedure, and S24 corresponds to a formal measurement procedure. In S12, the user sets a reference area based on a tomographic image. In S13, it is determined whether the automatic optimization button has been pressed. If so, ultrasound transmission and reception are performed in S14, generating m received data points. At this point, inter-group division processing is performed as needed. In S16, n data processing steps are applied to each of the m received data points, thereby generating m×n blood flow data points. In S18, m×n evaluation values ​​are calculated based on the m×n blood flow data points. In S20, the optimal combination of conditions is determined by selecting the best evaluation value from the m×n evaluation values. In S22, the optimal combination of conditions, namely the optimal transmission and reception conditions and the optimal data processing conditions, is set for the ultrasound diagnostic device. The formal measurement is then performed.

[0092] exist Figure 10 Several CFM images are shown. In the CFM image shown in (A), image 104, which shows almost no blood flow within vessel 102, is in a state of being too small. On the other hand, in the CFM image shown in (C), image 110, which shows blood flow in addition to vessel 102, is in a state of being too large. To eliminate the state of being too small or too large, in other words, to obtain a good CFM image, manually adjusting multiple parameters is tedious and time-consuming.

[0093] According to the method involved in the implementation, the optimal combination of conditions is automatically set in a short time, thereby obtaining... Figure 10A good CFM image is shown in (B). In this CFM image, image 108 shows clear blood flow within blood vessel 102. According to the implementation, the burden on both the examiner and the examinee can be reduced. For example, if m×n is kept within 500 or several thousand, the virtual measurement can be completed within one second or several seconds, and the delay in starting the formal measurement is no longer a problem. Since both the virtual and formal measurements are performed on the same examinee, the advantage of being able to set the optimal combination of conditions for each examinee can also be obtained.

Claims

1. An ultrasonic diagnostic device, characterized in that, Include: The first generator (19, 32) generates a received data string containing m received data corresponding to m different send and receive conditions, where m is an integer greater than 2; The second generator (36) generates m×n blood flow data by applying n data processing conditions that follow different n data processing conditions to each of the m received data, thereby generating a blood flow dataset containing the m×n blood flow data from the received data string, where n is an integer greater than 2; The evaluator (89) determines the optimal combination of optimal transmission and reception conditions and optimal data processing conditions by evaluating the blood flow dataset; and The setting device (100) sets the optimal transmission and reception conditions and the optimal data processing conditions for the ultrasound diagnostic device.

2. The ultrasonic diagnostic device according to claim 1, characterized in that, The first generator (19, 32) includes: The transceiver circuit (19) sets at least one actual transmission and reception condition and outputs at least one actual received data. and The processor (32) generates at least one virtual received data corresponding to at least one virtual transmit / receive condition by processing the at least one actual received data. The m transmit / receive conditions consist of at least one actual transmit / receive condition and at least one virtual transmit / receive condition. The received data string consists of at least one actual received data and at least one virtual received data.

3. The ultrasonic diagnostic device according to claim 2, characterized in that, The at least one actual send / receive condition can be multiple actual send / receive conditions. The at least one actually received data can be multiple actually received data. The at least one virtual send / receive condition can be multiple virtual send / receive conditions. The at least one virtual received data can be multiple virtual received data.

4. The ultrasonic diagnostic device according to claim 2, characterized in that, Each of the aforementioned actual received data comprises multiple packets arranged on a timeline, obtained under the same actual transmission and reception conditions. The processor (32) performs inter-group division processing on each of the actual received data, thereby generating one or more virtual received data from each of the actual received data.

5. The ultrasonic diagnostic device according to claim 1, characterized in that, The evaluator (89) includes: The arithmetic unit (90) calculates an evaluation value based on each of the m×n blood flow data points; and The decision maker (98) determines the optimal combination of the optimal transmission and reception conditions and the optimal data processing conditions based on the m×n evaluation values ​​corresponding to the m×n blood flow data.

6. The ultrasonic diagnostic device according to claim 5, characterized in that, A reference region is set for the blood flow area on the beam scanning plane. The arithmetic unit (90) executes: For each blood flow data point, the portion of the blood flow data corresponding to the reference region is used as reference for blood flow information. For each blood flow data point, the entire blood flow data point or other portions thereof are used as comparative information. The evaluation value is calculated for each blood flow data point based on the blood flow information and the comparison information.

7. The ultrasonic diagnostic device according to claim 1, characterized in that, Each of the aforementioned transmit and receive conditions includes the transmit pulse repetition period. Each of the aforementioned data processing conditions includes filter characteristics. The optimal transmit and receive conditions include the optimal transmit pulse repetition period. The optimal data processing conditions include optimal filter characteristics.

8. A method for setting action conditions, characterized in that, Include: Step (S14) generates a received data string containing m received data corresponding to m different transmit and receive conditions, where m is an integer greater than 2; Step (S16): For each of the m received data, n data processing methods following n different data processing conditions are applied to generate m×n blood flow data, thereby generating a blood flow dataset containing the m×n blood flow data from the received data string, where n is an integer greater than 2; Steps (S18, S20) determine the optimal combination of optimal transmission and reception conditions and optimal data processing conditions by evaluating the blood flow dataset; and Step (S22) sets the optimal transmission and reception conditions and the optimal data processing conditions for the ultrasonic diagnostic device.

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