Ultrasonic diagnostic apparatus, ultrasonic diagnostic program, and method for displaying information of ultrasonic diagnostic apparatus

Abstract

To make a measurement item feasible as a user desires.SOLUTION: An ultrasonic diagnostic apparatus includes: an ultrasonic probe for transmitting and receiving an ultrasonic wave to a subject; a generation part for generating ultrasonic image data on the basis of reception signals obtained from an observation area; a measurement item estimation part for estimating a measurement item candidate that can be measured or cannot be measured; and a display part for displaying a measurement item candidate.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an ultrasonic diagnostic apparatus, an ultrasonic diagnostic program, and an information display method for an ultrasonic diagnostic apparatus. [Background technology]

[0002] 2. Description of the Related Art There is known an ultrasound diagnostic apparatus that transmits and receives ultrasound waves to and from a subject such as a living body using an ultrasound probe, and generates ultrasound image data for diagnosis based on signals obtained from ultrasound echoes resulting from reflection of the ultrasound waves.

[0003] In recent years, ultrasound diagnostic equipment has been using AI (Artificial Intelligence) technology to automatically recognize target organs and tissues from ultrasound image data and to perform automatic measurements using the recognition results, and AI technology is being used for a variety of purposes.

[0004] For example, Patent Document 1 describes using AI technology to estimate candidate measurement conditions for ultrasound image data, determine measurement conditions from the estimated candidate measurement conditions, and perform measurements on the ultrasound image data based on the determined measurement conditions.

[0005] Furthermore, Patent Document 2 describes using AI technology to determine whether a cross-sectional image taken by ultrasound is an image of a target cross section, and if it is determined that the cross-sectional image is an image of the target cross section, a predetermined measurement process is performed on the image of the determined target cross section. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Patent Publication No. 2022-47609 [Patent Document 2] JP 2019-154654 A Summary of the Invention [Problem to be solved by the invention]

[0007] In Patent Documents 1 and 2, AI technology is used to estimate candidate measurement conditions and determine the measurement conditions, or to determine that the cross-sectional image is an image of the target cross-section, and then measurement is automatically performed using the determined measurement conditions and the determined cross-sectional image, and the measurement results are displayed.

[0008] However, when multiple measurement items exist for a region displayed in a cross-sectional image, a measurement other than the measurement item desired by the user may be performed. For example, when a cross-sectional image of the abdomen of a fetus is used to measure its major axis, the circumference may be measured instead.

[0009] An object of the present invention is to provide an ultrasonic diagnostic apparatus, an ultrasonic diagnostic program, and an information display method for an ultrasonic diagnostic apparatus, which are capable of executing measurement items desired by a user. [Means for solving the problem]

[0010] The ultrasonic diagnostic apparatus according to the present invention comprises: an ultrasonic probe for transmitting and receiving ultrasonic waves to and from a subject; A generator that generates ultrasound image data based on a reception signal obtained from the observation region; a measurement item estimation unit that estimates measurable or non-measurable measurement item candidates; A display unit that displays the measurement item candidates; Equipped with.

[0011] The ultrasonic diagnostic apparatus according to the present invention comprises: an ultrasonic probe for transmitting and receiving ultrasonic waves to and from a subject; A generator that generates ultrasound image data based on a reception signal obtained from the observation region; A designation section for designating a measurement item; an estimation unit that estimates whether the specified measurement item is measurable; A display unit that displays information on whether or not the measurement is possible; Equipped with.

[0012] The ultrasonic diagnostic program according to the present invention comprises: On the computer, A transmission / reception process for transmitting and receiving ultrasonic waves to and from the subject using an ultrasonic probe; A generation process for generating ultrasound image data based on a reception signal obtained from the observation region; A measurement item estimation process for estimating measurable or non-measurable measurement item candidates; A display process for displaying the measurement item candidates; Execute the command.

[0013] The ultrasonic diagnostic program according to the present invention comprises: On the computer, A transmission / reception process for transmitting and receiving ultrasonic waves to and from the subject using an ultrasonic probe; A generation process for generating ultrasound image data based on a reception signal obtained from the observation region; A process for designating measurement items; an estimation process for estimating whether the specified measurement item is measurable; A display process for displaying information on whether or not the measurement is possible on a display unit; Execute the command.

[0014] The information display method for an ultrasonic diagnostic apparatus according to the present invention comprises the steps of: An ultrasonic probe transmits and receives ultrasonic waves to and from the subject, generating ultrasound image data based on a received signal obtained from the observation region; Estimate potential measurement items that are measurable or non-measurable; The measurement item candidates are displayed.

[0015] The information display method for an ultrasonic diagnostic apparatus according to the present invention comprises the steps of: An ultrasonic probe transmits and receives ultrasonic waves to and from the subject, generating ultrasound image data based on a received signal obtained from the observation region; Specify the measurement item, Estimating whether the specified measurement item is measurable; The information on whether or not measurement is possible is displayed on the display unit. Effect of the Invention

[0016] According to the present invention, it is possible to carry out measurement items that the user desires. [Brief description of the drawings]

[0017] [Figure 1] FIG. 1 is a block diagram showing an example of the main components of an ultrasonic diagnostic apparatus according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a block diagram for explaining an example of an information display method of the ultrasonic diagnostic apparatus shown in FIG. [Diagram 3] FIG. 3 is a diagram illustrating an example of an AI technique used in the measurability estimation unit of the ultrasound diagnostic apparatus shown in FIG. [Figure 4] FIG. 4 is an example of a learning data set used in the AI ​​technology shown in FIG. [Diagram 5] FIG. 5 is a diagram showing an example of a display image and measurement item candidates displayed on the display unit of the ultrasound diagnostic apparatus shown in FIG. [Figure 6] FIG. 6 is a diagram showing another example of a display image and measurement item candidates displayed on the display unit of the ultrasound diagnostic apparatus shown in FIG. [Figure 7] FIG. 7 is a diagram showing another example of a display image and measurement item candidates displayed on the display unit of the ultrasound diagnostic apparatus shown in FIG. [Figure 8] FIG. 8 is a diagram showing another example of a display image and measurement item candidates displayed on the display unit of the ultrasound diagnostic apparatus shown in FIG. [Figure 9] FIG. 9 is a block diagram showing another example (variation 1) of the main parts of an ultrasound diagnostic apparatus according to an embodiment of the present invention. [Figure 10] FIG. 10 is a block diagram for explaining an example of an information display method of the ultrasonic diagnostic apparatus shown in FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0018] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[0019] [Ultrasound diagnostic equipment] An ultrasonic diagnostic device according to this embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing an example of the main parts of an ultrasonic diagnostic device 1 according to this embodiment.

[0020] The ultrasonic diagnostic apparatus 1 is used for visualizing the shape, properties, or dynamics of biological tissue inside a subject such as a living organism as an ultrasonic image and for image diagnosis.

[0021] 1, the ultrasonic diagnostic device 1 includes a device main body 10, an ultrasonic probe (ultrasonic probe in the present invention) 20, etc. In the ultrasonic diagnostic device 1, the ultrasonic probe 20 is connected to the device main body 10 via a cable, but may also be connected to the device main body 10 via wireless communication.

[0022] [Device body] As shown in FIG. 1, the device main body 10 includes an operation input unit 11, a transmission unit 12, a reception unit 13, an image generation unit 14, a display unit 15, a control unit 16, a storage unit 17, and the like.

[0023] The operation input unit 11 is a user interface that allows a user (e.g., a medical professional such as a doctor or a laboratory technician) to perform input operations, converts the input operations performed by the user into operation signals, and inputs them to the control unit 16. The operation input unit 11 is composed of, for example, a control panel having a plurality of keys (buttons), a keyboard, a mouse, and the like. When a touch panel display is used as the display unit 15, the touch panel portion functions as a part of the operation input unit 11, and detects, for example, touch inputs for selecting measurement items described below.

[0024] In the operation input unit 11, the user performs input operations such as operations during measurement of the ultrasound diagnostic apparatus 1, operations during diagnosis, and operations for information to be displayed on the display unit 15.

[0025] The transmission unit 12 is a transmission circuit that generates a voltage pulse, which is a drive signal, and outputs it to each acoustic element of the ultrasonic probe 20. The transmission unit 12 sets the voltage amplitude, pulse width, and timing of the voltage pulse for each channel (each acoustic element).

[0026] For example, the transmission unit 12 changes the delay time of a voltage pulse supplied to each acoustic element so that the ultrasonic waves output from each acoustic element are focused on a focal point set within the subject (delay processing).

[0027] Moreover, the transmission unit 12 scans the inside of the subject with ultrasonic waves by switching channels and sequentially driving the acoustic elements.

[0028] The receiving unit 13 is a receiving circuit that receives and processes reception signals generated by each acoustic element when an ultrasonic echo is received due to reflection of ultrasonic waves.

[0029] The receiving unit 13 amplifies the received signal of each channel, performs A / D conversion, and provides a delay time to the received signal after A / D conversion. At this time, the receiving unit 13 provides a delay time so that the phases of the received signals generated by ultrasonic echoes from a focus set in the subject are aligned (delay processing). As a result, the receiving unit 13 combines the received signals of multiple channels into one (hereinafter referred to as a "phased sum signal"). The receiving unit 13 then performs filter processing on the phased sum signal and outputs it to the image generating unit 14.

[0030] The image generating unit 14 performs a process of generating image data of an ultrasound image (hereinafter, ultrasound image data) that becomes two-dimensional frame data based on the phased addition signal (received data) output from the receiving unit 13. The image generating unit 14 generates ultrasound image data such as a B-mode image, a Doppler image (a color Doppler image, a pulsed Doppler image, a continuous wave Doppler image, a tissue Doppler image, etc.), an M-mode image, an elastogram, etc., depending on the scanning mode. Measurement items described later relate to the observation areas of these image data.

[0031] The image generating unit 14 generates ultrasound image data after performing, for example, logarithmic compression processing, detection processing, FFT analysis processing, etc. The processing for generating ultrasound image data in the image generating unit 14 may be the same as known processing, and therefore the description thereof will be omitted here. The generated ultrasound image data may be stored in, for example, the storage unit 17.

[0032] Moreover, the image generating unit 14 converts the ultrasound image data generated by the image generating unit 14 into a display signal corresponding to the display unit 15, and outputs it as a display image. The image generating unit 14 also converts measurement item candidates, which will be described later, into a display signal corresponding to the display unit 15, and outputs it.

[0033] The display unit 15 is configured with, for example, a liquid crystal display, an organic EL display, a CRT display, a touch panel display, etc. The display unit 15 displays the display image input from the image generating unit 14 as an ultrasound image. Note that the display unit 15 is not limited to being fixed to the device main body 10, and may be an external display connected to the device main body 10 by a wire, a tablet connected wirelessly to the device main body 10, etc.

[0034] The control unit 16 is a so-called computer, and although not shown, includes a CPU (Central Processing Unit) as a calculation / control device, a ROM (Read Only Memory) and a RAM (Random Access Memory) as main storage devices.

[0035] The ROM stores programs and setting data. The CPU reads out a program corresponding to the processing contents from the ROM, loads it into the RAM, and executes the loaded program to centrally control the operation of each functional block of the ultrasound diagnostic device 1. In other words, the control unit 16 controls the operation input unit 11, the transmission unit 12, the reception unit 13, the image generation unit 14, and the display unit 15 according to their respective functions, thereby controlling the entire ultrasound diagnostic device 1.

[0036] In this embodiment, the control unit 16 has a measurement item estimation unit 161 and a measurement unit 163 in addition to a control block that controls each unit.

[0037] The measurement item estimation unit 161 estimates measurable or non-measurable measurement item candidates, for example, based on the received data from the receiving unit 13. Here, the measurement items that are the measurement item candidates are items of measurement of the observation area of ​​the subject, and include the area and length of the observation area, as well as, for example, the major axis, the imaging part, the imaging range, and the periodicity of the movement of the imaging subject. The measurement item estimation unit 161 will be described in detail later.

[0038] The measurement unit 163 measures the measurement items in the observation area of ​​the subject. The measurement unit 163 has a measurement process (e.g., a measurement program) corresponding to each measurement item. The measurement unit 163 has an automatic measurement mode and a manual measurement mode, and when the measurement item estimation unit 161 can estimate a measurable measurement item candidate, the measurement unit 163 operates in the automatic measurement mode and, for example, performs measurement of the selected measurement item.

[0039] On the other hand, when the measurement item estimation unit 161 cannot estimate a measurable measurement item candidate, or can only estimate an unmeasurable measurement item candidate, the measurement unit 163 is switched to manual measurement mode, for example, by a user operation. In this case, if the automatic measurement mode is left in, the measurement of the unmeasurable measurement item may be possible, but the measurement accuracy may be low and the measurement accuracy may not be guaranteed. Therefore, by switching to manual measurement mode and the user specifying the measurement item of the observation area, the measurement unit 163 executes measurement of the specified measurement item. In this case, for example, the measurement accuracy can be improved by the user specifying the part to be measured.

[0040] The storage unit 17 is, for example, a storage device such as a hard disk drive (HDD), a solid state drive (SSD), or a flash memory, and stores the ultrasound image data generated by the image generation unit 14 and the measurement results measured by the measurement unit 163.

[0041] The transmitting unit 12, receiving unit 13, image generating unit 14, measurement item estimating unit 161, and measuring unit 163 described above may be configured as dedicated or general-purpose hardware (electronic circuits) according to each process, and realize each function in cooperation with the control unit 16.

[0042] For example, the transmitting unit 12, the receiving unit 13, the image generating unit 14, the measurement item estimating unit 161, and the measuring unit 163 are configured with hardware such as an ASIC (Application Specific Integrated Circuit), a DSP (Digital Signal Processor), a PLD (Programmable Logic Device), etc. Examples of PLDs include an FPGA (Field Programmable Gate Array), etc. When the transmitting unit 12, the receiving unit 13, the image generating unit 14, the measurement item estimating unit 161, and the measuring unit 163 are configured with a DSP, a PLD, etc., they have processing programs for those.

[0043] The transmission unit 12, the reception unit 13, the image generation unit 14, the measurement item estimation unit 161, and the measurement unit 163 may be configured to execute the processing of each unit using a CPU or a GPU (Graphics Processing Unit). In this case, the CPU or GPU has a processing program for executing the processing of each unit.

[0044] [Ultrasound probe] The ultrasonic probe 20 is, for example, a convex probe, a linear probe, a sector probe, a three-dimensional probe, etc. Although not shown in the figures, the ultrasonic probe 20 includes a plurality of acoustic elements, etc. Each acoustic element is, for example, a piezoelectric element capable of converting an electrical signal into a mechanical vibration and converting the mechanical vibration into an electrical signal and capable of transmitting and receiving ultrasonic waves.

[0045] The ultrasonic probe 20 converts the voltage pulse output from the transmitting unit 12 into ultrasonic waves, transmits the ultrasonic echoes reflected from within the subject, and outputs the received signals to the receiving unit 13. At this time, as described above, the ultrasonic probe 20 scans the subject with ultrasonic waves by sequentially driving the acoustic elements through channel switching. Then, based on the received signals, the image generating unit 14 generates ultrasonic image data that becomes two-dimensional frame data.

[0046] [Method of displaying information on an ultrasound diagnostic device] The ultrasound diagnostic device 1 has the configuration described above. When a user brings the ultrasound probe 20 into contact with the surface (epidermis) of a subject, the ultrasound diagnostic device 1 acquires ultrasound image data from inside the subject using the ultrasound probe 20, the transmitting unit 12, and the receiving unit 13. Then, the ultrasound diagnostic device 1 generates a display image, for example, a cross-sectional image, based on the acquired ultrasound image data using the image generating unit 14, and displays it on the display unit 15 as an ultrasound image.

[0047] The ultrasound image data is generated as two-dimensional frame data, and real-time display is possible by displaying display images corresponding to the frame data in real time in a chronological order. Furthermore, the ultrasound diagnostic device 1 can measure, for example, the major axis and circumference of the abdomen of a fetus by performing measurements on the received data input from the receiving unit 13, the ultrasound image data generated by the image generating unit 14, the display image, etc., in response to a user's operation.

[0048] However, for example, when a plurality of measurement items exist for a region displayed in a display image such as a cross-sectional image, a measurement other than the measurement item desired by the user may be performed.

[0049] Therefore, in this embodiment, in the control unit 16, the measurement item estimation unit 161 estimates candidate measurement items that are measurable or non-measurable in the observation area, and the display unit 15 displays the candidate measurement items for the observation area. Since the display unit 15 displays the candidate measurement items for the observation area, the user can select a desired measurement item from the candidate measurement items, and the control unit 16 can use the measurement unit 163 to measure the selected desired measurement item.

[0050] The display and selection of such measurement item candidates and the measurement of the selected measurement item will be described with reference to Fig. 2. Fig. 2 is a block diagram for explaining an example of an information display method of the ultrasound diagnostic device 1.

[0051] In the ultrasonic diagnostic device 1, reception data acquired using the ultrasonic probe 20, the transmission unit 12, and the reception unit 13 is input to the image generation unit 14. The input reception data is generated by the image generation unit 14 into ultrasonic image data and a display image, and the display image, for example, a cross-sectional image, is output to the display unit 15, which displays the display image in real time.

[0052] At this time, when the measurement item estimation unit 161 is activated by a user's operation, it uses the received data from the receiving unit 13 as input data to estimate measurable or non-measurable measurement item candidates. Since the processing here is performed in real time in accordance with the displayed image, it is desirable to estimate the measurement item candidates using the received data. Depending on the processing capacity of the control unit 16 (when the processing capacity is high), the measurement item candidates may be estimated using the ultrasound image data and the displayed image generated by the image generating unit 14. The measurement item candidates estimated by the measurement item estimation unit 161 are output to the display unit 15, and the display unit 15 displays the measurement item candidates in real time.

[0053] Display unit 15 displays candidate measurement items in real time along with the display image. For example, as shown in FIG. 2, three candidate measurement items, "Measurement A," "Measurement B," and "Measurement C," are displayed on display unit 15. When the user selects a desired measurement item from "Measurement A," "Measurement B," or "Measurement C," measurement unit 163 is started and the measurement of the selected measurement item is performed. For example, when the user selects "Measurement A," measurement unit 163 is started and the measurement of the selected "Measurement A" is performed.

[0054] Here, the estimation in the measurement item estimation unit 161 will be described with reference to Fig. 3 and Fig. 4. Fig. 3 is a diagram for explaining an example of an AI technique used in the measurement item estimation unit 161 of the ultrasound diagnostic device 1. Fig. 4 is an example of a learning data set used in the AI ​​technique shown in Fig. 3.

[0055] The measurement item estimation unit 161 performs estimation using AI technology. The measurement item estimation unit 161 is, for example, a trained model or a classifier using a neural network, and the trained model or the classifier is, for example, a model trained by associating ultrasound images (cross-sectional images) with measurement item candidates (see FIGS. 3 and 4).

[0056] Note that the trained model here is a model trained by associating ultrasound images (cross-sectional images) with candidate measurement items, but it may also be a model trained by associating received data or ultrasound image data with candidate measurement items.

[0057] In this embodiment, the neural network has an input layer, a hidden layer, an output layer, and a Softmax activation function.

[0058] The input layer is a layer that propagates information such as an ultrasound image to the hidden layer. The hidden layer is a layer that extracts the features of the information. The output layer is a layer that determines the probability of the label to be classified. The Softmax activation function converts the output value of the label into a value in the range of 0 (0%) to 1 (100%), and the sum of the output values ​​of all labels is 1 (100%).

[0059] In a neural network, the weights and thresholds of the neurons in the hidden layer and output layer are adjusted by learning so that the labels of the information of the input correct data match the labels of the output results.

[0060] In the above-mentioned neural network, for example, as shown in FIG. 4, learning is performed using a training data set consisting of an ultrasound image and N pieces of correct answer data, each set consisting of an ultrasound image and a measurement item with a probability of 1 (100%) that can be measured in that image.

[0061] For example, when an ultrasound image generated by the image generator 14 is input to the neural network that has undergone such learning, the probability for each measurement item for the input ultrasound image is output, as shown in Fig. 3. In the example shown in Fig. 3, the probability of measurement A is 80%, and it can be estimated as a measurable measurement item candidate, and the probabilities of measurements C and D are 2% and 1%, respectively, and they can be estimated as non-measurable measurement item candidates.

[0062] In this manner, the measurement item estimation unit 161 estimates measurable or non-measurable measurement item candidates. In other words, the measurement item estimation unit 161 can automatically estimate measurable measurement items as measurement item candidates. Then, the display unit 15 displays the measurement item candidates in real time together with the display image, as shown in FIG.

[0063] At this time, the measurement item estimation unit 161 estimates that measurement items with a predetermined probability or higher are measurable, and outputs the measurement items as candidate measurement items to the display unit 15. For example, as shown in Fig. 3, assuming that the probabilities of Measurement A, Measurement B, Measurement C, and Measurement D are 80%, 17%, 2%, and 1%, respectively, and it is estimated that measurement items with 80% or more are measurable, the measurement item estimation unit 161 outputs Measurement A as a candidate measurement item to the display unit 15. In this case, the display unit 15 displays Measurement A, which is a measurement item with a predetermined probability or higher, as a candidate measurement item.

[0064] Furthermore, when there are multiple measurement items with a predetermined probability or higher, the measurement item estimation unit 161 outputs the multiple measurement items as measurement item candidates to the display unit 15. In this case, the display unit 15 displays, for example, measurement A and measurement B, which are measurement items with a predetermined probability or higher, as measurement item candidates, as shown in Fig. 2. In this case, the display unit 15 may display the measurement item candidates from left to right in descending order of probability as shown in Fig. 2, or may display the measurement item candidates from top to bottom in descending order of probability as shown in Fig. 5.

[0065] Furthermore, the display unit 15 may display a predetermined number of measurement items in order of decreasing probability, as shown in Fig. 6. In the example shown in Fig. 6, the predetermined number is three, and if the probabilities of measurement A, measurement B, measurement C, and measurement D are 80%, 17%, 2%, and 1%, respectively, as shown in Fig. 3, the top three measurements A, B, and C are displayed from top to bottom in order of decreasing probability. In this case, the display unit 15 may display the order of probability together with the measurement items.

[0066] Furthermore, the display unit 15 may display a predetermined number of measurement items in order of decreasing probability, which are measurement items having a predetermined probability or higher.

[0067] Furthermore, as shown in FIG. 7, the display unit 15 may display the probability of each measurement item together with the measurement item.

[0068] Furthermore, the display unit 15 may change the display mode according to the probability of a measurement item as well as the measurement item, as shown in Fig. 8. For example, the color of the area in which the measurement item is displayed or the color of the measurement item itself may be changed according to the probability of the measurement item, so that the user can visually identify measurement items with high probability. For example, in the example shown in Fig. 8, the area in which measurement A with high probability is displayed is brightened, and the areas in which measurements B and C with low probability are displayed are darkened, so that the user can visually identify measurement A with high probability.

[0069] In this manner, the display unit 15 displays the measurement item candidates in real time so that the user can visually confirm the measurement items with high probability.

[0070] The user checks the measurement item candidates displayed on the display unit 15 and selects the desired measurement item. For example, as shown in FIG. 2, if the desired measurement item is measurement A, the user selects measurement A using, for example, a control panel or a touch panel. An operation signal resulting from this selection is input to the control unit 16 via the operation input unit 11, and the control unit 16 starts the measurement unit 163. Specifically, the control unit 16 starts the measurement process (for example, a measurement program) for measurement A in the measurement unit 163, and while displaying the display image on the display unit 15 in real time, performs measurement A on the display image in real time, and displays the measurement results in real time.

[0071] If the measurement item estimation unit 161 cannot estimate a measurable measurement item candidate, or can only estimate a non-measurable measurement item candidate, it displays on the display unit 15 that measurement is not possible or that the ultrasound image is unsuitable for measurement.

[0072] As described above, in the ultrasonic diagnostic device 1 of this embodiment, the measurement item estimation unit 161 infers measurable or non-measurable measurement item candidates in the control unit 16, thereby automatically estimating measurable measurement item candidates, and the display unit 15 displays the measurement item candidates. Since the display unit 15 displays the measurement item candidates for the observation area, the user can select a desired measurement item from the measurement item candidates, and the control unit 16 can use the measurement unit 163 to instantly measure the selected desired measurement item.

[0073] Currently, many ultrasound diagnostic devices are equipped with multiple automatic measurements that utilize AI technology. However, since organ / tissue recognition requires a large computational load, it is difficult to simultaneously execute AI engines corresponding to multiple measurement items and perform automatic measurement in real time. In contrast, in this embodiment, AI technology is used to estimate measurement item candidates, so the computational load is smaller than when AI engines corresponding to multiple measurement items are simultaneously executed, and automatic measurement in real time is possible.

[0074] In addition, the operation input unit 11 has a limited number of operation buttons, and the touch panel display has a limited number of operation buttons that can be displayed on the display unit 15. Therefore, even if a desired automatic measurement is to be performed from among a plurality of automatic measurements installed by operating the buttons, it cannot be performed immediately, which increases the examination time and increases the burden on the patient and user. In contrast, in this embodiment, the measurement item estimation unit 161 automatically estimates measurable measurement item candidates, and the display unit 15 displays the measurement item candidates. Therefore, the user can immediately perform automatic measurement by selecting the desired measurement item from the displayed measurement item candidates. As a result, the examination time can be shortened and the burden on the patient and user can be reduced.

[0075] Conventionally, the desired measurement item was searched for from a menu in which many measurement items were defined for each observation site. In contrast, in this embodiment, the measurement item estimation unit 161 automatically estimates measurable measurement item candidates, and the display unit 15 displays the measurement item candidates. Therefore, there is no need to search for the desired measurement item, which shortens the examination time and reduces the burden on the patient and user.

[0076] <Variation 1> FIG. 9 is a block diagram showing another example of the main parts of the ultrasound diagnostic apparatus 1A according to an embodiment of the present invention.

[0077] In this modification, the ultrasound diagnostic device 1A has the same configuration as the ultrasound diagnostic device 1 shown in Fig. 1, except for the measurability estimation unit 162. Therefore, a description of the configuration of the ultrasound diagnostic device 1A that overlaps with that of the ultrasound diagnostic device 1 will be omitted.

[0078] In this modification, ultrasound diagnostic device 1A has a measurability estimation unit 162 instead of the measurement item estimation unit 161 in ultrasound diagnostic device 1 shown in Fig. 1. Also, in this modification, operation input unit 11 functions as a designation unit that designates a measurement item.

[0079] The measurability estimation unit 162 (estimation unit in the present invention) estimates whether or not a measurement item specified using the operation input unit 11 is measurable in the observation area. In other words, unlike the present embodiment described above, it does not estimate measurement item candidates, but estimates whether or not the specified measurement item is measurable.

[0080] The estimation in the measurability estimation unit 162 is similar to that in the above-mentioned measurement item estimation unit 161, and the estimation is performed using AI technology. Specifically, as an example, the measurability estimation unit 162 is a trained model or classifier using a neural network, similar to the measurement item estimation unit 161. Furthermore, this trained model or classifier is also a model trained by associating ultrasound images (cross-sectional images) with measurement item candidates, similar to the measurement item estimation unit 161 (see FIGS. 3 and 4).

[0081] In this modification, the measurability estimation unit 162 in the control unit 16 estimates whether or not a measurement item designated by the user (desired by the user) is measurable in the observation area, and the display unit 15 displays information on whether or not the designated measurement item is measurable. Since the display unit 15 displays information on whether or not the designated measurement item is measurable, the user can select a desired measurement item based on the information, and the control unit 16 can use the measurement unit 163 to measure the selected measurement item.

[0082] Here, the display of information regarding measurement items, selection, and measurement of the selected measurement items in this modified example will be described with reference to Fig. 10. Fig. 10 is a block diagram for explaining an example of an information display method of the ultrasound diagnostic apparatus 1A shown in Fig. 9.

[0083] In the ultrasonic diagnostic device 1A as well, reception data acquired using the ultrasonic probe 20, the transmitting unit 12, and the receiving unit 13 is input to the image generating unit 14. The input reception data is generated by the image generating unit 14 into ultrasonic image data and a display image, and the display image, for example, a cross-sectional image, is output to the display unit 15, which displays the display image in real time.

[0084] At this time, the measurability estimation unit 162 is started by the user's operation, and at least one measurement item is input (specified) by the user. The measurability estimation unit 162 uses the received data from the receiving unit 13 as input data to estimate whether the specified measurement item is measurable in the observation area. Since the processing here is also performed in real time in accordance with the display image, it is desirable to estimate whether the specified measurement item is measurable using the received data. Depending on the processing capacity of the control unit 16 (when the processing capacity is high), it may be possible to estimate whether the specified measurement item is measurable using the ultrasound image data and the display image generated by the image generation unit 14. Information on whether the measurement item is measurable or not, for example, probability information, estimated by the measurement item estimation unit 161, is output to the display unit 15, and the display unit 15 displays the measurement item and the probability information in real time.

[0085] The measurement items and probability information are displayed in real time together with the display image on the display unit 15. For example, as shown in Fig. 10, three measurement items, "Measurement A", "Measurement B", and "Measurement C", are specified and displayed on the display unit 15. In this case, the probability information is also displayed on the display unit 15 together with the measurement items.

[0086] The user refers to the probability information along with the measurement items and selects a desired measurement item from the specified measurement items, which starts the measurement unit 163 and executes the measurement of the selected measurement item. For example, when the user selects "Measurement A", the measurement unit 163 starts and executes the measurement of the selected "Measurement A".

[0087] To estimate whether a specified measurement item is measurable, a trained model using the above-mentioned neural network is used to obtain the measurement item and its probability as probability information.

[0088] In this way, the measurability estimation unit 162 estimates whether the specified measurement item is measurable or not. Then, the display unit 15 displays the probability indicating the measurability of the measurement item in real time together with the display image and the measurement item, as shown in FIG.

[0089] The user checks the measurement items and probabilities indicating the measurability of the measurement items displayed on the display unit 15, and selects the desired measurement item. For example, as shown in FIG. 10, when the desired measurement item is measurement A, the user selects measurement A using, for example, a control panel or a touch panel. An operation signal resulting from this selection is input to the control unit 16 via the operation input unit 11, and the control unit 16 starts the measurement unit 163. Specifically, the control unit 16 starts the measurement process (for example, a measurement program) of measurement A possessed by the measurement unit 163, and while displaying a display image on the display unit 15 in real time, performs measurement A on the display image in real time, and displays the measurement results in real time.

[0090] If the measurability estimation unit 162 estimates that the specified measurement item is not measurable, it causes the display unit 15 to display that the measurement is not possible or that the ultrasound image is not suitable for measurement.

[0091] As described above, in the ultrasonic diagnostic device 1A of this modification, in the control unit 16, the measurability estimation unit 162 estimates whether or not a measurement item specified by the user is measurable in the observation area, and the display unit 15 displays information on whether or not the specified measurement item is measurable. Since the display unit 15 displays the measurement item and information on whether or not it is measurable, the user can select a desired measurement item from among the measurement items, and the control unit 16 can use the measurement unit 163 to instantly measure the selected desired measurement item.

[0092] Furthermore, the ultrasound diagnostic apparatus 1A of this modified example also uses AI technology to estimate whether a measurement item is measurable or not, so the computational load is smaller and automatic measurement can be performed in real time compared to the case where AI engines corresponding to multiple measurement items are run simultaneously.

[0093] Also in the ultrasonic diagnostic device 1A of this modification, the measurability estimation unit 162 estimates whether the specified measurement item is measurable or not, and the display unit 15 displays information on whether the specified measurement item is measurable or not. Therefore, the user can immediately perform automatic measurement by selecting a desired measurement item from the displayed measurement items. As a result, the examination time can be shortened and the burden on the patient and the user can be reduced.

[0094] Also in the ultrasonic diagnostic apparatus 1A of this modification, the measurability estimation unit 162 estimates whether or not a specified measurement item is measurable, and the display unit 15 displays information on whether or not the specified measurement item is measurable. Therefore, there is no need to search for a desired measurement item, and the examination time can be shortened and the burden on the patient or user can be reduced.

[0095] The above-mentioned embodiments are merely examples of the embodiment of the present invention, and the technical scope of the present invention should not be interpreted as being limited by these. In other words, the present invention can be embodied in various forms without departing from the gist or main characteristics of the present invention.

[0096] For example, the measurement item estimation unit 161 and the measurability estimation unit 162 use a neural network as an example of AI technology, but other AI technology may also be used. [Explanation of symbols]

[0097] 1. 1A Ultrasound diagnostic equipment 10. Device body 11 Operation input section 12 Transmitter 13 Receiving section 14 Image Generation Unit 15 Display 16 Control section 161 Measurement Item Estimation Section 162 Measurability Estimation Section 163 Measurement Division 17 Memory section 20 Ultrasound Probe

Claims

1. an ultrasonic probe for transmitting and receiving ultrasonic waves to and from a subject; A generator that generates ultrasound image data based on a reception signal obtained from the observation region; a measurement item estimation unit that estimates measurable or non-measurable measurement item candidates; A display unit that displays the measurement item candidates; An ultrasound diagnostic device comprising:

2. The display unit displays the measurement item candidates in real time.

2. The ultrasonic diagnostic apparatus according to claim 1.

3. The generating unit generates the ultrasound image data in real time, The measurement item estimation unit estimates the measurement item candidates in real time for the ultrasound image data generated in real time.

3. The ultrasonic diagnostic apparatus according to claim 1.

4. The measurement item estimation unit estimates a probability as to whether the measurement item candidate is measurable or not using the ultrasound image data as input data.

3. The ultrasonic diagnostic apparatus according to claim 1.

5. The display unit is Displaying the measurement item candidates whose probability is equal to or higher than a predetermined probability or a predetermined number of measurement item candidates in descending order of the probability, a predetermined number of candidate measurement items are displayed in descending order of probability, the candidate measurement items being those whose probability is equal to or greater than a predetermined probability; 5. The ultrasonic diagnostic apparatus according to claim 4.

6. The ultrasound image data is data relating to at least one of a B-mode image, a Doppler image, an M-mode image, and an elastography image; The Doppler image includes a color Doppler image, a pulsed Doppler image, a continuous wave Doppler image, and a tissue Doppler image.

3. The ultrasonic diagnostic apparatus according to claim 1.

7. the display unit has a touch panel and detects a touch input for selecting the displayed measurement item candidates.

3. The ultrasonic diagnostic apparatus according to claim 1.

8. A control panel having keys for selecting the measurement item candidates displayed on the display unit.

3. The ultrasonic diagnostic apparatus according to claim 1.

9. The measurement item estimation unit is a trained model using a neural network.

3. The ultrasonic diagnostic apparatus according to claim 1.

10. The trained model is a model trained by associating ultrasound images with candidate measurement items.

10. The ultrasonic diagnostic apparatus according to claim 9.

11. When the measurement item estimation unit cannot estimate a measurable measurement item candidate or can estimate only a non-measurable measurement item candidate, the measurement item estimation unit displays that the image is non-measurable or that the image is unsuitable for measurement.

3. The ultrasonic diagnostic apparatus according to claim 1.

12. A measurement unit that measures the measurement item of the observation area even if the measurement item estimation unit cannot estimate a measurable measurement item candidate or can only estimate an unmeasurable measurement item candidate.

3. The ultrasonic diagnostic apparatus according to claim 1.

13. an ultrasonic probe for transmitting and receiving ultrasonic waves to and from a subject; A generator that generates ultrasound image data based on a reception signal obtained from the observation region; A designation section for designating a measurement item; an estimation unit that estimates whether the specified measurement item is measurable; A display unit that displays information on whether or not the measurement is possible; An ultrasound diagnostic device comprising:

14. The display unit displays the information on whether or not the measurement is possible in real time. The ultrasonic diagnostic apparatus according to claim 13.

15. The generating unit generates the ultrasound image data in real time, The estimation unit estimates in real time whether the specified measurement item is measurable for the ultrasound image data generated in real time.

15. The ultrasonic diagnostic apparatus according to claim 13 or 14.

16. The estimation unit estimates a probability as to whether the measurement item is measurable or not using the ultrasound image data as input data.

15. The ultrasonic diagnostic apparatus according to claim 13 or 14.

17. The display unit is Displaying the measurement items whose probability is equal to or higher than a predetermined probability or a predetermined number of measurement items in descending order of the probability as information on whether or not the measurement is possible; a predetermined number of measurement items in descending order of probability, the measurement items being those whose probability is equal to or higher than a predetermined probability, are displayed as information on whether or not the measurement is possible; 17. The ultrasonic diagnostic apparatus according to claim 16.

18. The measurement items include at least one of measurement items related to a B-mode image, a Doppler image, an M-mode image, and an elastography image; The Doppler image includes a color Doppler image, a pulsed Doppler image, a continuous wave Doppler image, and a tissue Doppler image.

15. The ultrasonic diagnostic apparatus according to claim 13 or 14.

19. The estimation unit is a classifier that is trained by using a neural network to associate ultrasound images with measurement items.

15. The ultrasonic diagnostic apparatus according to claim 13 or 14.

20. the estimation unit, when it is estimated that the specified measurement item is not measurable, displays that the measurement is not possible or that the ultrasound image is not suitable for measurement.

15. The ultrasonic diagnostic apparatus according to claim 13 or 14.

21. a measurement unit that enables measurement of the measurement item in the observation area even when the estimation unit estimates that the specified measurement item is not measurable; 15. The ultrasonic diagnostic apparatus according to claim 13 or 14.

22. On the computer, A transmission / reception process for transmitting and receiving ultrasonic waves to and from the subject using an ultrasonic probe; A generation process for generating ultrasound image data based on a reception signal obtained from the observation region; A measurement item estimation process for estimating measurable or non-measurable measurement item candidates; A display process for displaying the measurement item candidates; An ultrasound diagnostic program that performs the following:

23. The display process displays the measurement item candidates in real time. The ultrasonic diagnostic program according to claim 22.

24. The generation process generates the ultrasound image data in real time; The measurement item estimation process estimates the measurement item candidates in real time for the ultrasound image data generated in real time.

24. The ultrasonic diagnostic program according to claim 22 or 23.

25. The measurement item estimation process estimates a probability that the measurement item candidate is measurable or not using the ultrasound image data as input data.

24. The ultrasonic diagnostic program according to claim 22 or 23.

26. The display process includes: Displaying the measurement item candidates whose probability is equal to or higher than a predetermined probability or a predetermined number of measurement item candidates in descending order of the probability, a predetermined number of candidate measurement items are displayed in descending order of probability, the candidate measurement items being those whose probability is equal to or greater than a predetermined probability; The ultrasonic diagnostic program according to claim 25.

27. The ultrasound image data is data relating to at least one of a B-mode image, a Doppler image, an M-mode image, and an elastography image; The Doppler image includes a color Doppler image, a pulsed Doppler image, a continuous wave Doppler image, and a tissue Doppler image.

24. The ultrasonic diagnostic program according to claim 22 or 23.

28. the display process detects a touch input for selecting the displayed measurement item candidates by a touch panel.

24. The ultrasonic diagnostic program according to claim 22 or 23.

29. The display process detects an input for selecting a displayed candidate measurement item by a control panel having keys.

24. The ultrasonic diagnostic program according to claim 22 or 23.

30. The measurement item estimation process is performed using a trained model using a neural network.

24. The ultrasonic diagnostic program according to claim 22 or 23.

31. The trained model is a model trained by associating ultrasound images with candidate measurement items. The ultrasonic diagnostic program according to claim 30.

32. When the measurement item estimation process cannot estimate a measurable measurement item candidate or can estimate only a non-measurable measurement item candidate, the measurement item estimation process displays that the ultrasound image is non-measurable or unsuitable for measurement.

24. The ultrasonic diagnostic program according to claim 22 or 23.

33. A measurement process for measuring the measurement item of the observation area even if a measurable measurement item candidate cannot be estimated by the measurement item estimation process or only a non-measurable measurement item candidate can be estimated; causing the computer to execute 24. The ultrasonic diagnostic program according to claim 22 or 23.

34. On the computer, A transmission / reception process for transmitting and receiving ultrasonic waves to and from the subject using an ultrasonic probe; A generation process for generating ultrasound image data based on a reception signal obtained from the observation region; A process for designating measurement items; an estimation process for estimating whether the specified measurement item is measurable; A display process for displaying information on whether or not the measurement is possible on a display unit; An ultrasound diagnostic program that performs the following:

35. The display process displays the information on whether or not the measurement is possible in real time.

35. The ultrasonic diagnostic program according to claim 34.

36. The generation process generates the ultrasound image data in real time; The estimation process estimates in real time whether the specified measurement item is measurable for the ultrasound image data generated in real time.

36. The ultrasonic diagnostic program according to claim 34 or 35.

37. The estimation process estimates a probability as to whether the measurement item is measurable or not using the ultrasound image data as input data.

36. The ultrasonic diagnostic program according to claim 34 or 35.

38. The display process includes: Displaying the measurement items whose probability is equal to or higher than a predetermined probability or a predetermined number of measurement items in descending order of the probability as information on whether or not the measurement is possible; a predetermined number of measurement items in descending order of probability, the measurement items being those whose probability is equal to or higher than a predetermined probability, are displayed as information on whether or not the measurement is possible; 38. The ultrasonic diagnostic program according to claim 37.

39. The measurement items include at least one of measurement items related to a B-mode image, a Doppler image, an M-mode image, and an elastography image; The Doppler image includes a color Doppler image, a pulsed Doppler image, a continuous wave Doppler image, and a tissue Doppler image.

36. The ultrasonic diagnostic program according to claim 34 or 35.

40. The estimation process is performed using a classifier that has been trained by a neural network to associate ultrasound images with measurement items.

36. The ultrasonic diagnostic program according to claim 34 or 35.

41. When the specified measurement item is estimated to be unmeasurable, the estimation process displays that the measurement item is unmeasurable or that the ultrasound image is unsuitable for measurement.

36. The ultrasonic diagnostic program according to claim 34 or 35.

42. a measurement process for making the measurement item in the observation area measurable even if the specified measurement item is estimated to be unmeasurable by the estimation process; causing the computer to execute 36. The ultrasonic diagnostic program according to claim 34 or 35.

43. An ultrasonic probe transmits and receives ultrasonic waves to and from the subject, generating ultrasound image data based on a received signal obtained from the observation region; Estimate potential measurement items that are measurable or non-measurable; Displaying the measurement item candidates; A method for displaying information in an ultrasound diagnostic device.

44. An ultrasonic probe transmits and receives ultrasonic waves to and from the subject, generating ultrasound image data based on a received signal obtained from the observation region; Specify the measurement item, Estimating whether the specified measurement item is measurable; The information on whether or not the measurement is possible is displayed on a display unit. A method for displaying information in an ultrasound diagnostic device.

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