Automatic steering of ultrasound imaging using artificial intelligence

Abstract

An ultrasound imaging system (100) includes a transducer configured to transmit and receive ultrasound signals in a three-dimensional volume. The ultrasound imaging system (100) includes processing circuitry (114) having a processor (116) coupled to a memory (118) device having instructions stored thereon that, when executed, cause the processing circuitry (114) to perform operations including receiving first image data (202) obtained by an ultrasound probe (106) from the three-dimensional volume, the first image data (202) corresponding to a first plane in the volume; identifying a desired view (208) based on the first image data (202); determining, by an artificial intelligence model, a deviation (210) from the first plane to the desired view (208) based on the first image data (202); automatically applying the deviation (210) to the ultrasound signals to receive second image data corresponding to a second plane based on the desired view (208); and displaying an output image based on the second image data on a display screen of the ultrasound imaging system (100).

Description

Technical Field

[0001] The embodiments of the subject matter disclosed herein relate to ultrasound imaging, and more specifically, to the use of artificial intelligence and ultrasound imaging to automatically redirect ultrasound signals. Background Technology

[0002] During medical imaging scans, technicians (such as ultrasound physicians) acquire multiple medical images of a patient to measure or detect various aspects of the anatomical features present within the images. Obtaining a standard view of the medical images is crucial for identifying anatomical features and diagnosing the patient. Obtaining a standard view can be challenging for technicians and requires manual adjustment of the probe until it is achieved. Summary of the Invention

[0003] The embodiment relates to an ultrasound imaging system. The ultrasound imaging system includes a transducer configured to transmit and receive ultrasound signals in a three-dimensional volume. The three-dimensional volume includes multiple planes. The ultrasound imaging system includes processing circuitry. The processing circuitry includes a processor coupled to a memory device storing instructions that, when executed, cause the processing circuitry to perform operations including: receiving first image data obtained by an ultrasound probe from the three-dimensional volume, the first image data corresponding to a first plane in the volume; identifying a desired view based on the first image data; determining, by an artificial intelligence model, a deviation from the first plane to the desired view based on the first image data; automatically applying the deviation to the ultrasound signals to receive second image data corresponding to a second plane based on the desired view; and displaying an output image based on the second image data on a display screen of the ultrasound imaging system.

[0004] Another embodiment relates to a medical imaging system. The medical imaging system includes an imaging unit configured to transmit and receive ultrasound signals in a three-dimensional volume to obtain first image data along a first plane. The medical imaging system includes control circuitry configured to determine, by an artificial intelligence model, a deviation from the first plane to a desired view based on the first image data. This deviation is automatically applied to the ultrasound signals to receive second image data corresponding to a second plane based on the desired view, such that the medical imaging system is configured to display an output image based on the second image data on a display screen of the medical imaging system.

[0005] Another embodiment relates to a method. The method includes receiving first image data obtained from a three-dimensional volume by an ultrasound probe via processing circuitry. The first image data corresponds to a first plane within the volume. The method includes identifying a desired view based on the first image data by the processing circuitry. The method includes determining a deviation from the first plane to the desired view by the processing circuitry and an artificial intelligence model based on the first image data. The method includes automatically applying the deviation to an ultrasound signal by the processing circuitry to receive second image data corresponding to a second plane along the desired view. The method displays an output image based on the second image data on a display screen of an ultrasound imaging system.

[0006] This overview is merely illustrative and is not intended to be limiting in any way. Other aspects, inventive features, and advantages of the apparatus or process described herein will become apparent from the detailed description set forth herein in conjunction with the accompanying drawings, wherein like reference numerals refer to like elements. Attached Figure Description

[0007] Figure 1 This is a block diagram of an ultrasound imaging system according to an example implementation.

[0008] Figure 2 This is based on the use of the example implementation plan. Figure 1 A flowchart of the artificial intelligence (AI) circuit of an ultrasound imaging system.

[0009] Figure 3 This is an example of an ultrasound imaging probe based on an example implementation.

[0010] Figure 4 This is another example of an ultrasound imaging probe based on an example implementation.

[0011] Figure 5 It is based on the example implementation plan. Figure 4 An example of the scanning volume of an ultrasound imaging probe.

[0012] Figure 6 This is an example of the use of the example implementation scheme. Figure 1 A flowchart of the ultrasound imaging method of an ultrasound imaging system.

[0013] Figure 7 This is a flowchart illustrating a method for using an artificial intelligence model according to an example implementation.

[0014] Figure 8A This is an example of ultrasound images acquired according to the example implementation scheme.

[0015] Figure 8B This is another example of ultrasound images acquired according to the example implementation scheme.

[0016] Figure 8C This is another example of ultrasound images acquired according to the example implementation scheme. Detailed Implementation

[0017] Referring generally to the accompanying drawings, a system and method for automatically navigating ultrasound signals using artificial intelligence and three-dimensional ultrasound imaging are disclosed. The system disclosed herein receives image data corresponding to a first plane and utilizes an artificial intelligence model to determine the deviation from the first plane to a desired view. The system and method automatically apply the deviation to the ultrasound signal to receive second image data corresponding to a second plane based on the desired view. An output image based on the second image data can be displayed on a display screen.

[0018] During an ultrasound scan, the ultrasound probe is typically positioned in a sagittal orientation (e.g., pointed towards the patient's head). However, obtaining a standard view for an ultrasound scan is often challenging, and images acquired in the first orientation may not be of sufficient quality to adequately visualize anatomical features and the patient's condition, necessitating probe adjustment to more closely align with the standard view. Visualizing ultrasound images in the appropriate standard view can be crucial for making appropriate diagnoses, assessing anatomical features, and searching for pathology. For example, in cardiac ultrasound, obtaining a standard (e.g., correctly aligned) apical four-chamber view of the patient's heart is essential for obtaining accurate measurements and making a correct diagnosis. Therefore, it is desirable to adjust the probe so that the resulting image data from the ultrasound beam from the probe is in the appropriate standard view. However, manually adjusting the ultrasound probe without assistance to achieve this is time-consuming and depends on the skill and expertise of the operator (e.g., ultrasound physician, technician, clinician, etc.), leading to inconsistencies due to operator efficiency and inconsistencies in obtaining consistent and high-quality ultrasound images.

[0019] The system and method described herein provide a technical solution for existing ultrasound imaging systems and employ a three-dimensional ultrasound probe. Using a three-dimensional ultrasound probe allows for the determination of a desired view (e.g., a standard view). Additionally, using a three-dimensional probe allows for the determination of deviations from the current image data to the desired view. Furthermore, as described herein, the scan volume from the three-dimensional imaging allows for the application of various electronic manipulation techniques to adjust the image data. The scan volume can be acquired from the three-dimensional probe, and the desired view can be searched within the three-dimensional volume.

[0020] Additionally, ultrasound systems can utilize artificial intelligence (AI)-powered guidance tools that assist in determining the desired view and / or identifying deviations. AI-guided tools may require or utilize less data compared to humans to analyze the current ultrasound images and generate outputs that allow for adjustments to the ultrasound images. With such AI-guided tools, the user is relieved of the responsibility of navigating the probe without assistance. Furthermore, when using AI systems, maximum image quality is only used or required when recording ultrasound image sequences for diagnostic purposes. Therefore, having fixed acquisition parameters can consume unnecessarily large amounts of energy transmission budget and waste the limited battery capacity of wireless probes. Technically and advantageously, the systems and methods described herein provide faster and more accurate ultrasound images, which improves productivity and diagnostic capabilities.

[0021] Before turning to the accompanying drawings, which detail certain exemplary embodiments, it should be understood that this disclosure is not limited to the details or methods set forth in the specification or illustrated in the drawings. It should also be understood that the terminology used herein is for descriptive purposes only and should not be construed as limiting.

[0022] refer to Figure 1 A schematic diagram of an ultrasound imaging system 100 is shown. The ultrasound imaging system 100 can be used in medical settings (e.g., hospitals, clinics, etc.), for example by an ultrasound physician, technician, or other clinician certified to collect ultrasound data from patients. Although the system and methods are described herein in the context of the ultrasound imaging system 100, it should be understood that the medical imaging parameter recommendation tool described herein can be implemented using any of a variety of medical imaging systems (e.g., medical resonance imaging, X-ray, computed tomography, positron emission tomography, etc.).

[0023] An example of a procedure performed using the ultrasound imaging system 100 could be echocardiography. An echocardiogram is performed to detect cardiac abnormalities in a patient by collecting and processing ultrasound data (e.g., using the ultrasound imaging system 100 described herein). During an echocardiogram, the sonographer follows a specific imaging protocol specific to the echocardiogram. This echocardiography-specific imaging protocol ensures that the heart is thoroughly captured by ultrasound data, and that the processing of the ultrasound data is focused on detecting cardiac abnormalities. The sonographer collects ultrasound data by navigating a probe (e.g., probe 106, as described below) above the patient's chest until a sufficient amount of ultrasound images has been collected. Using three-dimensional imaging, the three-dimensional volume of the ultrasound images can be obtained using the ultrasound imaging system 100. The sonographer can collect ultrasound images using ultrasound probes in sagittal, transverse, and coronal orientations. Referring to the Cartesian coordinate system described herein, transverse orientation refers to the XZ plane or the YZ plane. Sagittal orientation refers to the other of the XZ plane or the YZ plane. Coronal orientation refers to the XY plane. The collected images are stored in a central storage device (e.g., memory 118) and analyzed by the sonographer. The sonographer generates a set of measurements based on the images (e.g., 50 to 100 records), and these images and measurements are jointly reviewed by a cardiologist. The cardiologist provides any clinical findings / conclusions in the report submitted to the patient's medical record.

[0024] like Figure 1 As shown, the ultrasound imaging system 100 includes a transmit beamformer 102, a transmitter 104, a probe 106, a receiver 110, and a receive beamformer 112. The ultrasound imaging system 100 may also include a matching layer and a damping block. The matching layer improves ultrasound image quality by having acoustic impedance between the tissue to be imaged and the transducer material of the ultrasound imaging system 100. The damping block is configured to absorb ultrasound energy to improve ultrasound image quality.

[0025] Transmit beamformer 102 can be a hardware beamformer or a software beamformer. In embodiments where transmit beamformer 102 is a hardware beamformer, transmit beamformer 102 may include one or more of a graphics processing unit (GPU), a microprocessor, a central processing unit (CPU), a digital signal processor (DSP), or any other type of processor capable of performing logical operations. Transmit beamformer 102 may be configured to perform conventional beamforming techniques as well as techniques such as backtrack transmit beamforming (RTB). Alternatively, in embodiments where transmit beamformer 102 is a software beamformer, a processor (e.g., processor 116 as described below) may be configured to perform some or all of the functions associated with transmit beamformer 102.

[0026] The probe 106 may be a linear array probe, a curved array probe, a sector probe, or any other type of probe configured to acquire two-dimensional (2D) B-mode data, 2D color flow data, M-mode data, three-dimensional (3D) data, four-dimensional (4D) data, or any other type of ultrasound data. Alternatively or additionally, the probe 106 may be any type of probe including a matrix transducer array configured to acquire three-dimensional (3D) ultrasound data. In some embodiments, the probe 106 may include a positioning sensor configured to detect the positioning of the probe 106 relative to one or more reference locations. That is, when identifying the anatomical structure being imaged, the positioning sensor may continuously track the movement (e.g., rotation, translation, orientation, etc.) of the probe 106 relative to its position. For example, the anatomical structure being imaged may be identified as the left atrial appendage (LAA) at a first location of the probe 106. The positioning sensor may then track the movement of the probe 106 relative to the LAA to identify successive positions of the probe 106. In some implementations, the positioning sensor may transmit positioning data to be stored within the ultrasound imaging system 100 (e.g., in memory 118).

[0027] The probe 106 may include a transducer configured to transmit and receive ultrasonic signals. In some embodiments, such as Figure 1 As shown, probe 106 includes signal element 108. Signal element 108 may be arranged as a transducer array, and in some embodiments, as a 2D array. As described herein, a 2D array of signal element 108 may allow 3D ultrasound imaging (e.g., such that the transducers are configured to transmit and receive 3D ultrasound signals). Transmit beamformer 102 and transmitter 104 drive signal element 108 to transmit pulsed ultrasound signals into the body of a subject (e.g., a patient). For example, during an echocardiogram, an fluoroscopist or other clinician may navigate probe 106 above the patient's chest such that signal element 108 in probe 106 transmits pulsed ultrasound signals into the patient's chest cavity. The pulsed ultrasound signals are then backscattered from anatomical structures within the body, such as blood cells or muscle tissue, to produce an echo returning to signal element 108. That is, the signal element 108 may include: a transducer configured to transmit and receive ultrasound signals; a matching layer configured to have acoustic impedance between the tissue to be imaged and the material of the transducer (e.g., such that pulsed electronic signals can be backscattered from anatomical structures in the body and received by the signal element 108 as an echo); and a damping block configured to absorb ultrasound energy.

[0028] Additionally, in an ultrasound imaging system with an electronically steerable beam, the transmit beamformer 102 can be adjusted to shift the angle of the ultrasound beam, thereby shifting the transmitted ultrasound signal. For example, the transmit beamformer 102 can adjust the timing and phase shift of the ultrasound signal transmitted to the subject's body to change the angle of the ultrasound signal. In various embodiments, adjustment can be made without the operator having to move the transducer.

[0029] Receiver 110 receives the echo from probe 106 and converts the echo into an electrical signal. The electrical signal then passes through receiver beamformer 112, which generates ultrasound data based on the electrical signal. As described above with reference to transmit beamformer 102, receiver beamformer 112 can be a hardware beamformer or a software beamformer. In embodiments where receiver beamformer 112 is a hardware beamformer, receiver beamformer 112 may include one or more of a GPU, microprocessor, CPU, DSP, or any other type of processor capable of performing logical operations. Receiver beamformer 112 may be configured to perform conventional beamforming techniques as well as techniques such as backtrack transmit beamforming (RTB). Alternatively, in embodiments where receiver beamformer 112 is a software beamformer, a processor (e.g., processor 116 described below) may be configured to perform some or all of the functions associated with receiver beamformer 112.

[0030] Although the transmitting beamformer 102, transmitter 104, receiver 110 and receiving beamformer 112 are in Figure 1 While components of the ultrasound imaging system 100, which are shown as different from probe 106, are included, it should be understood that in some embodiments, probe 106 may include electronic circuitry configured to perform the functions of each of the transmit beamformer 102, transmitter 104, receiver 110, and / or receive beamformer 112. That is, all or part of the transmit beamformer 102, transmitter 104, receiver 110, and / or receive beamformer 112 may be located within probe 106.

[0031] Still referencing Figure 1 An ultrasound imaging system 100 is shown as including processing circuitry 114. As shown, processing circuitry 114 may include at least one processor 116, memory 118, image processing circuitry 120, artificial intelligence (AI) circuitry 122, and control circuitry 124. In this way, processing circuitry 114 may be configured or constructed to execute or implement the instructions, commands, and / or control processes described herein with respect to processor 116, memory 118, image processing circuitry 120, AI circuitry 122, and control circuitry 124. Although in Figure 1While shown separately from probe 106, it should be understood that processing circuitry 114 may be part of probe 106. For example, processing circuitry 114 may be housed in the handheld housing of probe 106 (e.g., in the case where probe 106 is a wireless probe).

[0032] Processor 116 may include a CPU, GPU, microprocessor, DSP, general-purpose single-chip or multi-chip processor, field-programmable gate array (FPGA), or any other type of processor capable of performing logical operations. A general-purpose processor may be a microprocessor or any conventional processor or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors incorporating a DSP core, or any other such configuration. In some embodiments, processor 116 may be shared by multiple circuits (e.g., the circuitry of processor 116 may include or otherwise share the same processor, and in some example embodiments, the processor may execute instructions stored or otherwise accessed via different regions of memory 118). Alternatively or additionally, processor 116 may be configured to perform or otherwise perform certain operations independently of one or more coprocessors. In some embodiments, two or more processors may be bus-coupled to enable independent, parallel, pipelined, or multi-threaded instruction execution. All such variations are intended to fall within the scope of this disclosure.

[0033] Processor 116 can be configured to control transmit beamformer 102, transmitter 104, receiver 110, and receive beamformer 112. Processor 116 can also communicate electronically with probe 106. For the purposes of this disclosure, the term "electronic communication" can be defined to include both wired and wireless communication.

[0034] In some embodiments, processor 116 may be configured to control probe 106 during data acquisition. That is, processor 116 can control data acquisition by controlling which signal element in signal elements 108 is active and by controlling the shape of the beam emitted from probe 106. For example, using a matrix configuration of signal elements 108, processor 116 may be configured to control the transmission direction of probe 106 such that data is acquired from the sagittal and / or lateral planes of probe 106. In another example, for 3D ultrasound imaging, processor 116 may be configured to automatically steer the ultrasound signal to acquire data along a plane within the volume. According to other embodiments, the transmission direction of probe 106 may be controlled by another component of the ultrasound imaging system 100 (e.g., control circuitry 124).

[0035] Alternatively or additionally, processor 116 may include a composite demodulator configured to demodulate radio frequency (RF) data acquired by probe 106 and generate raw data. According to other embodiments, demodulation of the RF data may be performed by another component of the ultrasound imaging system 100. Processor 116 may perform the processing operations described herein according to a variety of selectable ultrasound modes.

[0036] Depending on the operating mode of the ultrasound imaging system 100, the processor 116 can process ultrasound data acquired by the probe 106 to generate image data. For example, operating modes may include B-mode, color Doppler mode, M-mode, color M-mode, spectral Doppler, elastography, TVI, strain, strain rate, etc. Various modes among these operating modes can be configured to, for example, convert ultrasound data from beam space coordinates (e.g., received from the receiving beamformer 112) to display space coordinates (e.g., so that the ultrasound data can be displayed as image data). In some embodiments, the operating modes may allow video processing by the processor 116, enabling the real-time display of a series of images (e.g., processed ultrasound data) during a scan session / procedure performed on a patient. The operator of the ultrasound imaging system 100 (e.g., an ultrasound physician) can switch between various modes to acquire a variety of ultrasound data and perform a complete scan of the anatomical region of interest. For example, the operator can switch between modes using a user interface 130 (e.g., using physical controls, interface input representing physical controls, etc.).

[0037] When receiver 110 receives an echo signal from probe 106, processor 116 performs processing operations in real time. For the purposes of this disclosure, the term "real time" is defined as including procedures executed without any intentional delay. As an illustrative and non-limiting example, in some cases, ultrasound imaging system 100 may acquire images at a real-time volumetric rate of 7 to 20 volumes per second. However, it should be understood that the real-time volumetric rate may depend on the length of time taken to acquire each volume of data used for display. Thus, ultrasound imaging system 100 may be configured to acquire 2D data of an anatomical region at a faster rate than 3D data of the same anatomical region, since acquiring the volume of 3D data takes longer than acquiring the same volume of 2D data. Similarly, when ultrasound imaging system 100 acquires a relatively large amount of data, the real-time volumetric rate may be slower than a smaller amount of data. For example, during an abdominal scan, the real-time volumetric rate may be slower if the patient is an adult than if the patient is an infant, because the amount of data for an adult is larger than that for an infant (e.g., because the abdomen of an adult is larger than that of an infant). Therefore, some specific embodiments of the ultrasound imaging system 100 may have a real-time volume rate faster than 20 volumes / second, while other specific embodiments of the ultrasound imaging system 100 may have a real-time volume rate slower than 7 volumes / second.

[0038] In some embodiments, the ultrasound imaging system 100 may include multiple processors configured to perform the processing operations / functionality described in reference processor 116. For example, in such embodiments, a first processor among the multiple processors may be configured to demodulate and decimate RF signals, while a second processor among the multiple processors may be configured to further process the RF data before displaying an image representing the data. It should be understood that other embodiments may use different processor arrangements.

[0039] Processor 116 can also communicate electronically with display device 132, enabling processor 116 to process ultrasound data obtained from probe 106 and generate images for display on display device 132 (e.g., first ultrasound image 800a, second ultrasound image 800b, and third ultrasound image 800c, as referred to below). Figures 8A to 8C (As described).

[0040] like Figure 1 As shown, the processing circuitry 114 also includes a memory 118. The memory 118 may be configured to, for example, store processed data acquired by the ultrasound imaging system 100 (e.g., ultrasound data collected by probe 106, user input received by user interface 130, etc.). For example, the memory 118 may be a hospital picture archiving and communication system (PACS). The memory 118 (e.g., memory, memory cell, storage device, etc.) may include one or more devices (e.g., RAM, ROM, flash memory, hard disk storage, etc.) for storing data and / or computer code to perform or facilitate the processes, layers, and modules described in this application. The memory 118 may be or include tangible non-transient volatile memory or non-volatile memory. The memory 118 may also include database components, object code components, script components, or any other type of information structure for supporting the activities and information structures described in this application.

[0041] In various embodiments, the memory 118 may have different capacities (e.g., storage space) in the implementation of the ultrasound imaging system 100. For example, the memory 118 may be configured to store at least 60 minutes of ultrasound data value. Ultrasound data may be stored in the memory 118 such that the ultrasound data can be retrieved according to the order / time of data acquisition. That is, the ultrasound data may be stored together with a timestamp indicating the time when the ultrasound data was collected, and can be retrieved starting from the earliest time the ultrasound data was collected.

[0042] The processing circuitry 114 also includes an image processing circuitry 120, an AI circuitry 122, and a control circuitry 124. The image processing circuitry 120, the AI ​​circuitry 122, and the control circuitry 124 are all configured to facilitate the provision of recommended imaging parameters during ultrasound scanning, as described herein.

[0043] Image processing circuitry 120 is configured to receive image data acquired by the transducer of probe 106 during an ultrasound scan. Image data refers to ultrasound data collected by probe 106 when performing an ultrasound examination on a patient. For example, image data collected during echocardiography may include images of the patient's heart and specific structures therein (e.g., ventricles, atria, etc.). Image processing circuitry 120 may include multiple deep learning-based models configured to analyze the image data. For example, image processing circuitry may be configured to identify views of the image data it captures, anatomical structures captured by the image data, features, regions, etc., the presence of pathology in the image data, etc. Image processing circuitry 120 may be configured to identify anatomical structures using one or more algorithms (e.g., image processing algorithms such as edge detection, machine learning models, deep neural networks, etc.). In some embodiments, image processing circuitry 120 may identify anatomical features, such as bones, blood vessels, organs, etc., based on the shape, relative proximity, apparent depth, orientation, etc., of the features described in the image data. Then, based on the identified anatomical features, image processing circuitry 120 may be configured to determine the anatomical structures depicted in the image data. For example, because the lungs cannot be directly imaged (e.g., due to the lungs being filled with air and the acoustic impedance mismatch between the air and the transducer of probe 106), image processing circuitry 120 can determine that the lungs are being imaged based on the movement and / or orientation of the lungs relative to surrounding structures such as the pleura via a deep learning classification model trained to recognize the movement and / or orientation of the lungs and other anatomical structures. In some embodiments, image processing circuitry 120 can detect movement of structures in image data by comparing the position, shape, size, etc. of identified structures across a set of images (e.g., movie playback).

[0044] As described in more detail below, AI circuit 122 can be configured to base its operation on contextual information about the medical imaging procedure (e.g., from database 206, such as...). Figure 2 (As shown) to adjust or redirect the ultrasound signal. For example, during ultrasound performed using the ultrasound imaging system 100, the AI ​​circuit 122 can be configured to adjust the ultrasound signal to receive new image data based on determining whether the probe 106 is being navigated to a location that can capture diagnostic quality ultrasound images or has already been located to a location that can capture diagnostic quality ultrasound images.

[0045] The ultrasound imaging system 100 may also include an external database 128 and a user interface 130. The external database 128 refers to a database from which the processing circuitry 114 (e.g., AI circuitry 122) can retrieve information for providing recommended imaging parameters during ultrasound scanning. For example, the external database 128 may be a medical information database. A medical information database may store clinical guidelines, standard practices, medical literature, medical textbooks, published studies, previous case studies, etc. Depending on the specific implementation of the ultrasound imaging system 100 and / or the procedures performed therefrom, the AI ​​circuitry 122 may retrieve clinical guidelines, standard practices, medical literature, medical textbooks, published studies, and previous case studies relevant to the specific implementation and / or procedures. For example, if the ultrasound imaging system 100 is used in a hospital setting to perform a LAA closure procedure, the AI ​​circuitry 122 may retrieve clinical guidelines and standard practices relevant to the hospital setting and the LAA closure procedure. Continuing this example, the AI ​​circuitry 122 may also retrieve information from medical literature, medical textbooks, published studies, and previous case studies relevant to cardiac anatomy and the LAA closure procedure. In some cases, the information retrieved from external database 128 may include one or more algorithms for determining the desired view and the deviation from the current view to the desired view.

[0046] In some implementations, the image processing circuit 120 and / or control circuit 124 may be configured to apply one or more algorithms used by the AI ​​circuit 122 and / or retrieved from the external database 128. For example, see the following references. Figure 6 As described, the image processing circuit 120 may use one or more algorithms to evaluate anatomical features captured by the image data (e.g., using a segmentation model). In this way, the image processing circuit 120 and the control circuit 124 may be configured to determine the deviation from the plane corresponding to the image data to the desired view based on the analysis of the image data using the AI ​​circuit 122, so that this deviation can be used to adjust the ultrasound beam. The ultrasound beam refers to the transmitted ultrasound signal.

[0047] An ultrasound physician or other clinician can use the user interface 130 to control the operation of the ultrasound imaging system 100. For example, the ultrasound physician can use the user interface 130 to control the input of patient data, change scanning or display parameters, adjust the segmentation of anatomical features depicted in the ultrasound images, and / or select various other modes, operations, parameters, etc., of the ultrasound imaging system 100. In some embodiments, the user interface 130 may include off-the-shelf consumer electronics devices, such as smartphones, tablets, laptops, etc. For the purposes of this disclosure, the term "off-the-shelf consumer electronics device" is defined as an electronic device designed and developed for general consumer use rather than specifically designed for use in a medical setting. Alternatively, in other embodiments, the user interface 130 may be an electronic device designed and developed for use in a medical setting.

[0048] According to some embodiments, the user interface 130 may be physically separated from the rest of the ultrasound imaging system 100 (e.g., transmit beamformer 102, transmitter 104, probe 106, receiver 110, receive beamformer 112, processing circuitry 114, and / or external database 128). The user interface 130 may communicate with the processor 116 via wireless protocols such as Wi-Fi, Bluetooth, wireless local area network (WLAN), near-field communication, etc. According to some embodiments, the user interface 130 may communicate with the processor 116 via an application programming interface (API).

[0049] In some implementations, the user interface 130 may include one or more physical controls, such as buttons, sliders, knobs, mice, keyboards, trackballs, hard keys linked to specific actions, and soft keys configurable to control different functions. Figure 1 As shown, the user interface 130 may also include a display device 132. In some embodiments, the display device 132 may be configured to display a graphical user interface (GUI) based on instructions from the memory 118. The GUI may include user interface icons representing commands and instructions related to the operation of the ultrasound imaging system 100. The user interface icons of the GUI may be configured such that a user (e.g., an ultrasound physician, clinician, etc.) can select a specific user interface icon to activate a specific function controlled by the GUI. For example, various user interface icons may be used to represent windows, menus, buttons, cursors, scroll bars, etc. That is, the physical controls of the user interface 130 may be included as separate hardware components, as user interface icons displayed on the display device 132, or as a combination of hardware components and user interface icons.

[0050] In some embodiments, display device 132 may include a touch-sensitive display device or a touchscreen. According to such embodiments, the touchscreen may be configured to interact with a GUI displayed by display device 132, allowing a user (e.g., an ultrasound physician) to interact with the GUI via the touchscreen. The touchscreen may be a single-point touchscreen configured to detect a single contact point at a time, or a multi-point touchscreen configured to detect multiple contact points at a time. For embodiments where the touchscreen is a multi-point touchscreen, the touchscreen may be configured to detect multi-point gestures involving contact from two or more fingers of the user at a time. The touchscreen may be a resistive touchscreen, a capacitive touchscreen, or any other type of touchscreen configured to receive input from a stylus or one or more fingers of the user. According to some embodiments, the touchscreen may be an optical touchscreen that uses techniques such as infrared light or light of other frequencies to detect one or more contact points initiated by the user. In some embodiments, the touchscreen may be incorporated as part of display device 132 or may be separate from display device 132. User interface 130 may also include a proximity sensor configured to detect objects and / or gestures within a predetermined distance (e.g., five feet, six inches, ten centimeters, etc.) of the proximity sensor. In various implementations, the proximity sensor may be located on the display device 132 or as part of a touchscreen separate from the display device 132.

[0051] refer to Figure 2 The AI ​​circuitry 122 of the ultrasound imaging system 100 is shown in more detail. The AI ​​circuitry 122 is configured to determine a desired view 208 based on image data 202, as described in step 604 of reference method 600. The AI ​​circuitry 122 can be trained to identify the closest standard view (desired view 208) corresponding to image data acquired along a plane. For example, the AI ​​circuitry 122 can determine the desired view 208 using an image library comprising multiple historical ultrasound images. As described herein, the image library can be used to train the AI ​​circuitry 122. For example, the image library can assist the AI ​​circuitry 122 in processing image data 202 to determine the view of image data 202 and / or to determine the desired view 208.

[0052] AI circuitry 122 is further configured to determine a deviation 210 from the plane corresponding to image data 202 to the desired view. As described in step 606 of reference method 600, the deviation indicates the difference between the plane and the desired view in terms of linear movement, rotation, or tilt. It should be understood that the deviation can be expressed as any combination of values, angles, directions, etc. In some embodiments, the deviation is determined by comparing image data 202 and / or the plane with an image library comprising multiple historical ultrasound images. In some embodiments, the deviation is determined by a machine learning model.

[0053] AI circuitry 122 can provide feedback that guides a user (e.g., an ultrasound physician) to obtain a desired view or be close enough to it to automatically apply deviations to reach the desired view. In some embodiments, the feedback is based on clinical guidelines for obtaining ultrasound images used to determine a specific diagnosis. Therefore, because the received image data 202 used to determine deviations may not be in the desired view and may not be from the user's desired output, a degraded image of image data 202 may be generated or displayed while the user receives image data 202 and navigates the probe based on feedback generated by AI circuitry 122. For example, while probe 106 is navigated based on feedback generated by AI circuitry 122 to a location where deviations are applied to the ultrasound signal, the user may not rely on the displayed ultrasound image to determine whether an acceptable view has been achieved. Therefore, to reduce battery consumption of probe 106 and thus extend its battery life, the quality of the ultrasound image displayed on display device 132 while probe 106 is being navigated may be reduced via AI circuitry 122.

[0054] As shown in the figure, AI circuit 122 receives information about ultrasound imaging from database 206. Database 206 may provide contextual information to AI circuit 122. For example, database 206 may include an image library containing multiple historical ultrasound images. For example, ultrasound images may include standard views and non-standard views of anatomical structures. Additionally, database 206 may include multiple deviation values ​​and example applications of deviation to a plane. In some embodiments, database 206 may include indications of whether probe 106 is currently positioned to capture a desired view of the anatomical structure or whether probe 106 is currently being navigated (e.g., by a user or automatically) to obtain an image in the desired view. In other embodiments, as described with reference to method 600, database 206 may include contextual information for additional image data acquired from the same scan volume as image data 202 to provide additional information to determine deviations. In various embodiments, database 206 is part of external database 128.

[0055] Database 206 can be used as input to AI circuit 122. In some implementations, AI circuit 122 may include a Bayesian neural network. For example... Figure 2As shown, AI circuit 122 is configured to generate desired view 208 and deviation 210 based on information received from database 206. In some embodiments, AI circuit 122 may be trained using information about historical ultrasound scans performed by an expert sonographer (e.g., a sonographer with specific qualifications, a sonographer with many years of experience, etc.). For example, an expert sonographer may perform echocardiography or other ultrasounds (e.g., fetal ultrasound, etc.). Information about the echocardiography (e.g., imaging parameters used when probe 106 is navigated to the desired view, location of anatomical features in the desired view, AI scores of images during image capture in the desired view, etc.) may be stored as contextual information in database 206 (e.g., in memory 118).

[0056] refer to Figure 3 An illustration of an ultrasound imaging probe according to an example embodiment is shown. The ultrasound imaging probe 106 is configured for two-dimensional ultrasound imaging. Therefore, the ultrasound imaging probe 106 can send and receive ultrasound signals to provide image data along a scanning plane 302. The scanning plane 302 is finite, and the user can adjust the positioning of the ultrasound imaging probe by physically rotating, tilting, or translating it.

[0057] refer to Figure 4 An example of an ultrasound imaging probe according to an exemplary embodiment is shown. The ultrasound imaging probe 106 is configured for two-dimensional ultrasound imaging and three-dimensional ultrasound imaging. Figure 3 Compared to probe 106, probe 106 is capable of transmitting and receiving ultrasound signals within scanning volume 402. Compared to scanning plane 302, scanning volume 402 allows for electronic deflection of the ultrasound signal to receive multiple scanning planes. For example, the ultrasound signal can be tilted, rotated, or translated to receive scanning planes within scanning volume 402 (e.g., as...). Figure 5 The scanning plane 502 is shown.

[0058] refer to Figure 5 , showed Figure 4 An illustration of the scanning volume 402 of an ultrasound imaging probe. As depicted, the scanning volume 402 can be used to retrieve image data along multiple scanning planes 502. Because new image data is received from new locations within the scanning volume 402, the scanning planes within the scanning volume 402 can be electronically and automatically steered. Therefore, as described herein, the addition of artificial intelligence can assist in determining how the scanning planes should be steered to receive image data in a preferred or standard view. For probes configured for two-dimensional imaging only, the scanning planes cannot be electronically steered, and the user would have to manually adjust the probe to receive image data, which can be a tedious and unsuccessful process. Using a combination of a three-dimensional probe and artificial intelligence, the scanning planes can be automatically manipulated to achieve the desired view.

[0059] refer to Figure 6 A flowchart illustrating a method 600 for ultrasound imaging using an ultrasound imaging system is shown. In at least one embodiment, the ultrasound imaging system referred to in method 600 is the one described above. Figure 1 The ultrasound imaging system 100 is described, and the method 600 can be implemented by the ultrasound imaging system 100. In some embodiments, the method 600 can be implemented as a memory of the ultrasound imaging system 100 (such as...). Figure 1 Executable instructions in memory 118.

[0060] like Figure 6 As shown, at step 602, method 600 includes receiving first image data. As described herein, the transducer of ultrasound imaging system 100 is configured to transmit and receive ultrasound signals in a three-dimensional volume. The three-dimensional volume includes multiple planes in multiple views (e.g., lateral view, coronal view, sagittal view). The first image data can be received by extracting slices from the volume. Processing of the ultrasound signals allows for image construction. Processing the ultrasound signals may include converting echoes received from probe 106 into electrical signals, passing the electrical signals through receiving beamformer 112 for use as ultrasound data, and performing beamforming techniques to generate an image. At step 602, first image data is obtained from the three-dimensional volume by a probe (e.g., probe 106, three-dimensional probe). The first image data corresponds to a first plane in the volume. For example, the first plane may be along the lateral view. In various embodiments, image processing circuitry 120 applies processing techniques to the constructed image to further improve the quality of the constructed image (e.g., contrast adjustment, brightness adjustment, noise reduction, etc.).

[0061] like Figure 6 As shown, method 600 includes identifying a desired view based on first image data at step 604. The desired view may be a standard view for the type of imaging performed. For example, for lung ultrasound, the desired view for scanning the pleura may be a view in which the pleura is perpendicular to the ultrasound signal. The desired view may be a standard view known in practice. The identification of the desired view provides contextual information about what is expected to an artificial intelligence model (e.g., AI circuit 122), enabling the AI ​​model to assist in determining how to reach the desired view.

[0062] In various embodiments, method 600 includes identifying anatomical features based on first image data. In some embodiments, this may be performed by processing circuitry 114. For example, the first image data may be acquired during lung ultrasound, and therefore the first anatomical feature may include the pleura of the patient being imaged. However, it should be understood that although the ultrasound imaging system 100 cannot capture images of the lung cavities due to the air filling them, images of the lung cavities can be derived using surrounding anatomical structures / features (e.g., ribs, pleura, etc.) depicted in the image data. Identifying anatomical features may include segmentation, analysis, and mathematical modeling to appropriately identify the features. In various embodiments, the desired view is based on the localization of the anatomical features. For example, the localization of anatomical features in the first image data may assist in determining the desired localization of the anatomical features, thereby allowing the determination of the desired view. In various embodiments, anatomical features may assist in determining the desired view. Continuing with the previous lung ultrasound example, identifying the anatomical feature as the pleura may assist in determining the desired view.

[0063] In various implementations, artificial intelligence is used to identify the desired view. For example, identifying the desired view may be based on the output of an artificial intelligence model (e.g., AI circuit 122). The artificial intelligence model may be trained to recognize a standard view corresponding to image data. The artificial intelligence model can then use the first image data to generate an output corresponding to the desired view. The artificial intelligence model may use data from the first image data (e.g., location data, anatomical features, etc.) to generate the output.

[0064] In various implementations, patient history and / or data can be used to identify the desired view. For example, the desired view could be a view from a previous scan of the patient. This can be beneficial for various applications, such as lung imaging. When treating patients, it is important to properly visualize the B-line and pleura to monitor the patient's condition. By capturing the same view for each scan, making the desired view a view from a previous scan of the patient, consistent tracking of the patient can be ensured. In various implementations, artificial intelligence models can be used to determine the view from a previous scan of the patient.

[0065] like Figure 6 As shown, method 600 includes determining, at step 604, a deviation from a first plane to a desired view based on first image data. Step 604 utilizes an artificial intelligence model (e.g., AI circuit 122). The deviation includes information about how the first plane should be adjusted to reach the desired view. Determining the deviation may include determining the difference in at least one of angle (e.g., tilt), rotation, or lateral movement between the first plane and the desired view, such that the deviation is a combination of differences. For example, as referenced... Figure 7As described, the artificial intelligence model can determine, based on database 206, that the difference between the first plane and the desired view lies in the first degree of tilt and the second degree of rotation, such that the first plane must tilt by the first degree and rotate by the second degree to reach the desired view.

[0066] In various implementations, the artificial intelligence model can use additional information from the three-dimensional volume to determine the deviation. For example, the method may also include receiving third image data from the three-dimensional volume. The third image data is obtained from a third plane at an angle relative to a first plane. For example, the angle of the third plane relative to the first plane may be 90°. In various implementations, additional image data (e.g., fourth image data, fifth image data, multiple image data, etc.) is received from the volume. The additional image data is obtained from an additional plane at a second angle relative to the first plane (e.g., fourth plane, fifth plane, multiple planes, etc.). For example, the angle of the third plane relative to the first plane and the second angle of the fourth plane relative to the first plane may be 60°. The third image data and the additional image data can provide the artificial intelligence model with more information and context to determine the deviation. For example, the third plane can be compared with an additional plane at an angle relative to the desired view to assist in determining the deviation. Since the third image data does not need to be displayed, in various implementations, the image rate of the third image data does not necessarily need to be optimal for viewing. For example, the first image data can be received at a first image rate and the third image data can be received at a second image rate. In various implementations, the second image rate is lower than the first image rate.

[0067] like Figure 6 As shown, method 600 includes automatically applying a deviation to the ultrasound signal at step 608. In various embodiments, processing circuitry 114 can be used to apply the deviation to the ultrasound signal. Automatic application of the deviation may include automatic steering of the ultrasound signal (e.g., beam steering). For example, electronic rotation and tilting may be implemented to apply the deviation. Automatic steering of the ultrasound signal may include modifying the ultrasound signal to modify at least one of rotation or tilt of the imaging plane. Additionally, the transmitted beamformer 102 may be automatically adjusted to adjust the ultrasound beam, thereby modifying the ultrasound signal. As described herein, the use of three-dimensional imaging creates a scan volume in which the steering of the transmitted ultrasound signal (e.g., the ultrasound beam) can reach multiple planes.

[0068] Applying the deviation to the ultrasound signal allows the reception of second image data at step 610. The second image data corresponds to a second plane based on the desired view, such that the second image data is a standard view, a correctly aligned view, etc. In other words, the image generated from the second image data can improve the analysis (including measurement and diagnosis) of the ultrasound image. In various embodiments, the second image data is received at an image rate greater than the first image rate.

[0069] like Figure 6 As shown, method 600 includes displaying an output image based on the second image data at step 612. In some embodiments, the output image is displayed on a display device 132. In various embodiments, the output image includes an indication of deviation. For example, an operator of the ultrasound imaging system 100 can view the indication to see how to adjust the first image data and / or the ultrasound signal to receive the second image data. Advantageously, this can provide the operator with additional information about the first and second image data.

[0070] In various embodiments, the deviation may be greater than a deviation that can be automatically handled by the ultrasound imaging system 100. For example, an artificial intelligence model may determine that the deviation requires the operator to adjust the probe before the deviation can be automatically applied to the ultrasound signal. Therefore, the method may include providing feedback to the user (e.g., the operator) to manually adjust the probe positioning based on the deviation. In various embodiments, the feedback is provided on the display device 132. For example, the display device 132 may prompt the operator to tilt the probe 106 by X degrees along an axis in a first direction or by Y degrees along an axis in a second direction opposite to the first direction, such that the tilting of the probe 106 positions the probe at the location where the deviation is applied. Other movements of the probe 106 may be provided to the operator, including rotation, sliding, rocking, etc. In some embodiments, the user interface 130 may prompt the operator to adjust the probe 106 by providing an audio output. In various embodiments, the user interface 130 may provide real-time feedback as the operator adjusts the probe.

[0071] In various implementations, upon receiving the second image data, processing circuitry 114 and / or an artificial intelligence model can determine that the second image data is significantly different from a standard view. For example, the standard view could be a new standard view that can be determined by the artificial intelligence model, or the standard view could be a desired view. Therefore, method 600 can be iterative, and using the second image data and the standard view, method 600 can determine the deviation from a second plane of the second image data to the standard view, as described with reference to step 606. This deviation can then be applied to the ultrasound signal (e.g., step 608) to receive third image data along a third plane based on the standard view (e.g., step 610).

[0072] refer to Figure 7 The diagram illustrates a method 700 for determining the deviation from a first plane to a desired view. Method 700 utilizes an artificial intelligence model (e.g., AI circuit 122) and a database 206 to determine the deviation.

[0073] like Figure 7 As shown, method 700 includes receiving first image data and a desired view at step 702. The first image data and the desired view are received by an artificial intelligence model. (See reference...) Figure 2 As described in Method 600, the first image data and the desired view provide information to the artificial intelligence model for determining the bias.

[0074] like Figure 7 As shown, method 700 includes receiving contextual information by an artificial intelligence model at step 704. As described herein, contextual information can be provided to obtain more information about the image data and the desired view in order to determine discrepancies. Contextual information may include an image library comprising multiple historical ultrasound images. For example, ultrasound images may include standard views and non-standard views of anatomical structures. Contextual information is important for understanding the patient's condition and determining discrepancies or any anomalies in the image data because the image data can be compared with historical data. In various embodiments, contextual information includes patient information.

[0075] like Figure 7 As shown, method 700 includes determining, at step 706, a difference in at least one of angle, rotation, or lateral movement. As described herein with reference to step 606 of method 600, the difference includes information about how the first plane should be adjusted to reach the desired view. An artificial intelligence model may determine, based on database 206 and first image data, that the first plane differs from the desired view in terms of angle, rotation, and / or lateral movement. In various embodiments, the difference is determined using positioning information of the desired view and image data. In various embodiments, calculations may be determined for determining the difference along the direction of movement from the first plane to the desired view. For example, the first plane may differ from the desired view such that the first plane must be laterally moved and rotated by 10°.

[0076] like Figure 7 As shown, method 700 includes determining a deviation at step 708. The deviation can be a combination of differences. Continuing with the example discussed in step 706, the deviation of the first plane can be a lateral movement of magnitude X and a rotation of 10°.

[0077] refer to Figures 8A to 8C The diagram illustrates three-dimensional ultrasound images: a first ultrasound image 800a, a second ultrasound image 800b, and a third ultrasound image 800c. The ultrasound images are extracted from a three-dimensional volume obtained by transmitting and receiving ultrasound signals. The ultrasound images depict cardiac ultrasound. For cardiac ultrasound, it is important for the operator to find a standard view and orientation through translation, tilting, and rotation. As described herein, finding a standard view is crucial for accurate measurements and correct diagnosis. Figure 8AA first ultrasound image 800a shows an aligned apical four-chamber view of the heart. Second ultrasound images 800b and third ultrasound images 800c show incorrectly aligned apical four-chamber views (e.g., the probe has been tilted, causing the acquisition to be off-axis relative to the aligned view, or the 2D scan plane is correctly positioned in 3D space). Using method 600, as described herein, an artificial intelligence model and a three-dimensional ultrasound probe can be used to tilt and rotate the second ultrasound image 800b and third ultrasound image 800c to align them to the correct view of the first ultrasound image 800a.

[0078] The embodiments described herein have been illustrated with reference to the accompanying drawings. The drawings illustrate certain details of specific embodiments providing the systems, methods, and procedures described herein. However, the use of the drawings to describe the embodiments should not be construed as imposing any limitations that may exist in the drawings on the content of this disclosure.

[0079] It should be understood that no element of any claim herein may be applied under 35 USC. The provisions of 112(f) shall be interpreted unless the element is explicitly described using the phrase “parts for…”.

[0080] As used herein, terms of degree such as “about,” “approximately,” “substantially,” and similar terms are intended to have a broad meaning consistent with common and accepted usage by one of ordinary skill in the art to which the subject matter of this disclosure pertains. Those skilled in the art who read this disclosure will understand that these terms are intended to allow for the description of certain features described and claimed, without limiting the scope of these features to any precise numerical range provided. Therefore, these terms should be interpreted as indicating that non-substantial or irrelevant modifications or alterations to the described and claimed subject matter are considered to be within the scope of the disclosure set forth in the appended claims.

[0081] It should be noted that terms such as “exemplary,” “example,” and similar terms used herein to describe various implementations are intended to indicate that such implementations are possible examples, representations, or illustrations of possible implementations, and such terms are not intended to imply that such implementations are necessarily special or excellent examples.

[0082] As used herein, the term “coupling” and its variations refer to the direct or indirect engagement of two components with each other. Such engagement can be static (e.g., permanent or fixed) or movable (e.g., removable or releasable). Such engagement can be achieved by directly coupling the two components together, by coupling the two components together using a separate intermediate component and any additional intermediate components coupled to each other, or by coupling the two components together using an intermediate component integrally formed with one of the two components. If “coupling” or its variations are modified by an additional term (e.g., direct coupling), the general definition of “coupling” provided above will be modified by the common linguistic meaning of the additional term (e.g., “direct coupling” refers to the engagement of two components without any separate intermediate component), resulting in a narrower definition than the general definition of “coupling” provided above. Such coupling can be mechanical, electrical, or fluid.

[0083] As used herein, the term "or" is inclusive (not exclusive), and therefore, when used to connect lists of elements, the term "or" indicates one, some, or all of the elements in the list. Unless otherwise explicitly stated, conjunctions such as the phrase "at least one of X, Y, and Z" should be understood to mean that the elements can be X, Y, and Z; X and Y; X and Z; Y and Z; or X, Y, and Z (i.e., any element on its own or any combination of X, Y, and Z). Therefore, unless otherwise stated, such conjunctions generally do not imply that certain embodiments require at least one of X, at least one of Y, and at least one of Z to be present separately.

[0084] References to element positioning in this document (e.g., "top", "bottom", "above", "below") are used only to describe the orientation of the individual elements in the diagram. It should be noted that, according to other exemplary embodiments, the orientation of the various elements may differ, and such variations are intended to be covered by this disclosure.

[0085] As used herein, terms such as “engine” or “circuit” can include hardware and machine-readable media on which instructions for configuring hardware to perform the functions described herein are stored. An engine or circuit can be embodied as one or more circuit components, including but not limited to processing circuitry, network interfaces, peripherals, input devices, output devices, sensors, etc. In some embodiments, an engine or circuit can take the form of one or more analog circuits, electronic circuits (e.g., integrated circuits (ICs), discrete circuits, system-on-a-chip (SoC) circuits, etc.), telecommunications circuits, hybrid circuits, and any other type of circuit. In this respect, an engine or circuit can include any type of component for implementing or facilitating the implementation of the operations described herein. For example, an engine or circuit as described herein can include one or more transistors, logic gates (e.g., NAND, AND, NOR, OR, XOR, NOT, XNOR, etc.), resistors, multiplexers, registers, capacitors, inductors, diodes, wiring, etc.

[0086] An engine or circuit may be embodied as one or more processing circuits, which include one or more processors communicatively coupled to one or more memories or memory devices. In this respect, the one or more processors may execute instructions stored in memory or instructions otherwise accessible to the one or more processors. The one or more processors may be constructed in a manner sufficient to perform at least the operations described herein. In some embodiments, the one or more processors may be shared by multiple engines or circuits (e.g., engine A and engine B, or circuit A and circuit B may include or otherwise share the same processor, which in some example embodiments may execute instructions stored or otherwise accessed via different regions of memory).

[0087] Alternatively or additionally, one or more processors may be configured to perform or otherwise perform certain operations independently of one or more coprocessors. In other example embodiments, two or more processors may be bus-coupled to enable independent, parallel, pipelined, or multithreaded instruction execution. Each processor may be provided as one or more suitable processors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), or other suitable electronic data processing components configured to execute instructions provided by memory. One or more processors may take the form of a single-core processor, a multi-core processor (e.g., a dual-core processor, a triple-core processor, a quad-core processor, etc.), a microprocessor, etc. In some embodiments, one or more processors may be external to the device; for example, one or more processors may be remote processors (e.g., cloud-based processors). Alternatively or additionally, one or more processors may be internal to the device and / or local to the device. In this regard, a given engine or circuitry or its components may be deployed locally (e.g., as part of a local server, a local computing system, etc.) or remotely (e.g., as part of a remote server such as a cloud-based server). For this purpose, an engine or circuitry as described herein may include components distributed across one or more locations.

[0088] Example systems used to provide an overall system or part of the embodiments described herein may include one or more computers, including processing units, system memory, and a system bus coupling various system components, including the system memory, to the processing units. Each memory device may include a non-transitory volatile storage medium, a non-volatile storage medium (e.g., one or more volatile and / or non-volatile memories), etc. In some embodiments, the non-volatile medium may be in the form of ROM, flash memory (e.g., flash memory such as NAND, 3D NAND, NOR, 3D NOR, etc.), EEPROM, MRAM, magnetic storage devices, hard disks, optical disks, etc. In other embodiments, the volatile storage medium may be in the form of RAM, TRAM, ZRAM, etc. Combinations of the above are also included within the scope of machine-readable media. In this regard, machine-executable instructions include, for example, instructions and data that cause a general-purpose computer, a special-purpose computer, or a special-purpose processor to perform a function or a set of functions. According to the example implementation described herein, each respective memory device is operable to retain or otherwise store information related to operations performed by one or more associated circuits, including processor instructions and associated data (e.g., database components, object code components, script components, etc.).

[0089] Although the accompanying drawings may illustrate and the specification may describe a particular order and composition of method steps, the order of these steps may differ from the order depicted and described. For example, two or more steps may be performed simultaneously or partially simultaneously. Furthermore, some method steps performed as discrete steps may be combined, steps performed as combined steps may be divided into discrete steps, the order of certain processes may be reversed or otherwise altered, and the nature or number of discrete processes may be changed or varied. According to alternative embodiments, the order or sequence of any element or device may be changed or replaced. Therefore, all such modifications are intended to be included within the scope of this disclosure as defined in the appended claims. Such variations may depend, for example, on the chosen software and hardware system and the designer's choice. All such variations are within the scope of this disclosure. Similarly, software implementations of the described methods may be accomplished using standard programming techniques with rule-based logic and other logic to perform various connection steps, processing steps, comparison steps, and decision steps.

[0090] The foregoing description of embodiments has been given for purposes of illustration and description. It is not intended to be exhaustive or to limit the disclosure to the precise forms disclosed, and modifications and variations can be made, or may be derived from, the teachings described above. These embodiments were chosen and described to explain the principles of the disclosure and its practical application, thereby enabling those skilled in the art to utilize the various embodiments and make various modifications suitable for the intended particular purpose. Other substitutions, modifications, alterations, and omissions may be made to the design, operating conditions, and arrangement of the embodiments without departing from the scope of the disclosure as set forth in the appended claims.

Claims

1. An ultrasound imaging system (100), the ultrasound imaging system comprising: A transducer configured to transmit and receive ultrasonic signals in a three-dimensional volume comprising a plurality of planes; and Processing circuit (114) having a processor (116) coupled to a memory device (118) storing instructions that, when executed, cause the processing circuit (114) to perform operations including: Receive first image data (202) obtained from the three-dimensional volume by an ultrasound probe (106), the first image data (202) corresponding to a first plane in the volume; The desired view (208) is identified based on the first image data (202); The deviation (210) from the first plane to the desired view (208) is determined by an artificial intelligence model based on the first image data (202); The deviation (210) is automatically applied to the ultrasound signal to receive a second image corresponding to a second plane based on the desired view (208); and An output image based on the second image data is displayed on the display screen of the ultrasound imaging system (100).

2. The ultrasound imaging system (100) of claim 1, wherein the identification of the desired view (208) is based on the output from the artificial intelligence model.

3. The ultrasound imaging system (100) according to claim 1, wherein the probe (106) is a three-dimensional ultrasound matrix probe (106).

4. The ultrasound imaging system (100) according to claim 1, wherein automatically applying the deviation (210) to the ultrasound signal includes automatically redirecting the ultrasound signal.

5. The ultrasound imaging system (100) of claim 4, wherein automatically turning the ultrasound signal includes modifying the ultrasound signal to modify at least one of rotation or tilt of the imaging plane.

6. The ultrasound imaging system (100) of claim 1, wherein determining the deviation (210) includes determining the difference of at least one of angle, rotation or lateral movement between the first plane and the desired view (208).

7. The ultrasound imaging system (100) of claim 1, wherein the operation further comprises receiving third image data (202) obtained by the ultrasound probe (106) from the three-dimensional volume, the third image data (202) being obtained from a third plane at an angle relative to the first plane, the deviation (210) from the first plane to the desired view (208) being determined based on the first image data (202) and the third image data (202).

8. The ultrasound imaging system (100) according to claim 7, wherein the first image data (202) is received at a first image rate, and the third image data (202) is received at a second image rate lower than the first image rate.

9. The ultrasound imaging system (100) of claim 1, wherein the output image includes an indication of the deviation (210).

10. The ultrasound imaging system (100) of claim 1, wherein the operation further includes identifying anatomical features based on the first image data (202), and the desired view (208) is based on the location of the anatomical features.

11. The ultrasound imaging system (100) of claim 1, wherein the operation further includes providing feedback to the user to manually adjust the positioning of the ultrasound probe (106) based on the deviation (210).

12. A medical imaging system, the medical imaging system comprising: An imaging unit is configured to transmit and receive ultrasound signals in a three-dimensional volume to obtain first image data along a first plane (202). as well as Control circuit (124), the control circuit being configured to determine the deviation (210) from the first plane to the desired view (208) by an artificial intelligence model based on the first image data (202); The deviation (210) is automatically applied to the ultrasound signal to receive second image data corresponding to a second plane based on the desired view (208).

13. The medical imaging system of claim 12, wherein the identification of the desired view (208) is based on the output from the artificial intelligence model.

14. The medical imaging system of claim 12, wherein the medical imaging system includes an image processing circuit (120) configured to identify anatomical features based on the first image data (202), and the desired view (208) is based on the location of the anatomical features.

15. The medical imaging system of claim 12, wherein the imaging unit is configured to receive third image data (202) from the three-dimensional volume, the third image data (202) being obtained from a third plane at an angle relative to the first image data (202), and the deviation (210) from the first plane to the desired view (208) being determined based on the first image data (202) and the third image data (202).

Images