Method and system for automatic region of interest frame placement and imaging setting selection during ultrasound imaging

Abstract

A system (100) and method (500) are provided for automatically selecting imaging settings based on first mode ultrasound image information and automatically placing a region of interest frame (420) on a first mode ultrasound image (304, 404) when entering a second ultrasound imaging mode. The method (500) includes acquiring (502) first ultrasound image information according to a first pattern, the first ultrasound image information including a first pattern ultrasound image (304, 404). The method (500) includes processing (504) the first mode ultrasound image (304, 404) to determine first mode information. The method (500) includes automatically selecting (506) a size and location of a region of interest frame (420) based on the first mode information. The method (500) includes acquiring (508) second ultrasound image information (430) according to a second pattern based on the region of interest frame (420). The method (500) includes presenting (510) the second ultrasound image information (430) and the region of interest frame (420) automatically placed on the first mode ultrasound image (304, 404) at a display system (134).

Description

Technical Field

[0001] Certain embodiments relate to ultrasound imaging. More specifically, certain embodiments relate to a method and system for automatically selecting imaging settings and automatically placing a region of interest box on a first-mode ultrasound image (e.g., a B-mode image) based on first-mode ultrasound image information when entering a second ultrasound imaging mode (e.g., Color Flow, Power Doppler, B-Flow Color, etc.). Background Art

[0002] Ultrasound imaging is a medical imaging technique used to image organs and soft tissues in the human body. Ultrasound imaging uses real-time, non-invasive, high-frequency sound waves to produce a series of two-dimensional (2D) images and / or three-dimensional (3D) images.

[0003] Standard ultrasound imaging views of the abdomen typically include multiple patient anatomical structures, such as the liver, kidneys, gallbladder, aorta, pancreas, spleen, and / or inferior vena cava. If the ultrasound operator activates color flow mode, power Doppler mode, B-flow color mode, etc., the region of interest box can be automatically positioned at the center of the B-mode image. However, for a particular standard view of the abdomen, the target anatomical structure may not always be located at the center of the image plane. In addition, due to the different hemodynamics of different anatomical structures, different imaging settings may be required to optimize the acquisition of ultrasound image data such as color flow mode, power Doppler mode, B-flow color mode, etc. for different anatomical structures. Therefore, the current process for positioning the region of interest box and selecting imaging settings to acquire ultrasound image data such as color flow mode, power Doppler mode, B-flow color mode, etc. for different anatomical structures is inefficient and may be difficult for inexperienced ultrasound operators.

[0004] Further limitations and disadvantages of conventional and traditional approaches will become apparent to those skilled in the art by comparing such systems with certain aspects of the present disclosure as set forth in the remainder of this application with reference to the accompanying figures. Summary of the Invention

[0005] There is provided a system and / or method for automatically selecting imaging settings based on first mode ultrasound image information and automatically placing a region of interest box on the first mode ultrasound image when entering a second mode ultrasound imaging mode, substantially as shown and / or described in conjunction with at least one of the accompanying drawings, as more fully set forth in the claims.

[0006] These and other advantages, aspects and novel features of the present disclosure, as well as details of illustrated embodiments thereof, will be more fully understood from the following description and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1is a block diagram of an exemplary ultrasound system operable to automatically select imaging settings based on first mode ultrasound image information and automatically place a region of interest box on the first mode ultrasound image upon entering a second mode ultrasound imaging mode, in accordance with various embodiments.

[0008] Figure 2 Screen shots of exemplary first mode ultrasound images with identified anatomical structures are shown in accordance with various embodiments.

[0009] Figure 3 Screen shot showing exemplary second ultrasound image information automatically placed within a region of interest box on a first modality ultrasound image in accordance with various embodiments.

[0010] Figure 4 is a flow chart illustrating exemplary steps that may be used to automatically select imaging settings based on first mode ultrasound image information and automatically place a region of interest box on the first mode ultrasound image when entering a second mode ultrasound imaging mode, according to various embodiments. DETAILED DESCRIPTION

[0011] Certain embodiments may be found in a method and system for automatically selecting imaging settings based on first-mode ultrasound image information and automatically placing a region of interest box on a first-mode ultrasound image (e.g., a B-mode image) upon entering a second ultrasound imaging mode (e.g., Color Flow, Power Doppler, B-Flow Color, etc.). For example, aspects of the present disclosure have the technical effect of automatically determining the size of a region of interest box centered on a target anatomical structure in the first-mode ultrasound image based on an analysis of the first-mode ultrasound image information and placing the region of interest box to determine the target anatomical structure and the location of the target anatomical structure. Furthermore, aspects of the present disclosure have the technical effect of automatically selecting imaging settings specific to the target anatomical structure for ultrasound image acquisition according to a second mode based on an analysis of the first-mode ultrasound image information to determine the target anatomical structure and the location of the target anatomical structure. Furthermore, aspects of the present disclosure have the technical effect of updating the region of interest box size (i.e., geometry), region of interest box position, and / or imaging settings in response to modifying the target anatomical structure by selecting a new target anatomical structure in a standard ultrasound image view or by repositioning the ultrasound probe to acquire a new standard ultrasound image view.

[0012] When reading in conjunction with the accompanying drawings, the following specific embodiments of the foregoing invention summary and certain embodiments will be better understood. With respect to the scope of the figures showing the functional blocks of each embodiment in the accompanying drawings, these functional blocks do not necessarily represent the division between the hardware circuits. Therefore, for example, one or more functional blocks (e.g., processors or memories) can be implemented in a single piece of hardware (e.g., a general-purpose signal processor or random access memory block, a hard disk, etc.) or multiple pieces of hardware. Similarly, a program can be an independent program, can be included in an operating system as a subroutine, can be a function in an installed software package, etc. It should be understood that each embodiment is not limited to the arrangements and tools shown in the accompanying drawings. It should also be understood that embodiments can be combined, or other embodiments can be utilized, and structural, logical and electrical changes can be made without departing from the scope of each embodiment. Therefore, the following detailed description should not be considered as restrictive, and the scope of this disclosure is limited by the appended claims and their equivalents.

[0013] As used herein, elements or steps listed in the singular and beginning with the word "a" or "an" should be understood not to exclude a plurality of said elements or steps, unless such exclusion is explicitly stated. Furthermore, references to "exemplary embodiments," "various embodiments," "certain embodiments," "representative embodiments," and the like are not intended to be interpreted as excluding the existence of additional embodiments that also include the features described. Furthermore, unless explicitly stated to the contrary, embodiments that "comprise," "include," or "have" an element or elements having a particular property may include additional elements that do not have that property.

[0014] In addition, as used herein, the term "image" refers broadly to both a visible image and the data representing the visible image. However, many embodiments generate (or are configured to generate) at least one visible image. In addition, as used herein, the phrase "image" is used to refer to an ultrasound mode, which can be one-dimensional (1D), two-dimensional (2D), three-dimensional (3D) or four-dimensional (4D), and includes a brightness mode (B mode or 2D mode), a motion mode (M mode), a color motion mode (CM mode), a color flow mode (CF mode), a pulsed wave (PW) Doppler, a continuous wave (CW) Doppler, a contrast-enhanced ultrasound (CEUS) and / or a sub-mode of a B mode and / or a CF mode, such as harmonic imaging, shear wave elastography (SWEI), strain elastography, tissue velocity imaging (TVI), power Doppler imaging (PDI), B flow color (BFC), microangiography (MVI), ultrasound-guided attenuation parameters (UGAP), etc.

[0015] Furthermore, as used herein, the term processor or processing unit refers to any type of processing unit that can perform the required computations required by various embodiments, such as a single-core or multi-core central processing unit (CPU), an accelerated processing unit (APU), a graphics processing unit (GPU), a digital signal processor (DSP), a field programmable gate array (FPGA), a system on a chip (SoC), an application-specific integrated circuit (ASIC), or a combination thereof.

[0016] It should be noted that various embodiments of generating or forming an image described herein may include a process for forming the image, which in some embodiments includes beamforming and in other embodiments does not include beamforming. For example, an image may be formed without beamforming, such as by multiplying a matrix of demodulated data by a coefficient matrix such that the product is an image, and wherein the process does not form any "beams." Additionally, image formation may be performed using a combination of channels that may originate from more than one transmit event (e.g., synthetic aperture techniques).

[0017] In various embodiments, ultrasound processing to form images, including ultrasound beamforming, such as receive beamforming, is performed, for example, in software, firmware, hardware, or a combination thereof. One specific implementation of an ultrasound system having a software beamformer architecture formed according to various embodiments is described in Figure 1 Shown in.

[0018] Figure 1 is a block diagram of an exemplary ultrasound system 100 operable to automatically select imaging settings based on first mode ultrasound image information and automatically place a region of interest box on the first mode ultrasound image when entering a second ultrasound imaging mode, according to various embodiments. Figure 1 , shows an ultrasound system 100 and a training system 200. The ultrasound system 100 includes a transmitter 102, an ultrasound probe 104, a transmit beamformer 110, a receiver 118, a receive beamformer 120, an A / D converter 122, an RF processor 124, an RF / IQ buffer 126, a user input device 130, a signal processor 132, an image buffer 136, a display system 134, and an archive 138.

[0019] The transmitter 102 may include suitable logic, circuitry, interfaces, and / or code operable to drive the ultrasound probe 104. The ultrasound probe 104 may include a two-dimensional (2D) array of piezoelectric elements. In various embodiments, the ultrasound probe 104 may be a matrix array transducer or any suitable transducer operable to acquire 2D and / or 3D (including 4D) ultrasound image data sets. The ultrasound probe 104 may include a set of transmit transducer elements 106 and a set of receive transducer elements 108, which are generally constructed of identical elements. In certain embodiments, the ultrasound probe 104 is operable to acquire ultrasound image data covering at least a majority of an anatomical structure, such as the abdomen, heart, fetus, lungs, blood vessels, or any suitable anatomical structure.

[0020] The transmit beamformer 110 may include suitable logic, circuitry, interfaces, and / or code operable to control the transmitter 102 to drive the set of transmit transducer elements 106 via the transmit sub-aperture beamformer 114 to transmit ultrasound transmit signals into a region of interest (e.g., a person, an animal, an underground cavity, a physical structure, etc.). The transmitted ultrasound signals may be backscattered from structures in the object of interest (such as blood cells or tissue) to generate echoes, which are received by the receive transducer elements 108.

[0021] The set of receive transducer elements 108 in the ultrasound probe 104 is operable to convert received echoes into analog signals, which are sub-aperture beamformed by the receive sub-aperture beamformer 116 and then transmitted to the receiver 118. The receiver 118 may comprise suitable logic, circuitry, interfaces, and / or code that may be operable to receive the signals from the receive sub-aperture beamformer 116. The analog signals may be transmitted to one or more A / D converters 122.

[0022] The plurality of A / D converters 122 may include suitable logic, circuitry, interfaces, and / or code operable to convert analog signals from the receiver 118 into corresponding digital signals. The plurality of A / D converters 122 are disposed between the receiver 118 and the RF processor 124. However, the present disclosure is not limited in this respect. Thus, in some embodiments, the plurality of A / D converters 122 may be integrated within the receiver 118.

[0023] The RF processor 124 may include suitable logic, circuitry, interfaces, and / or code operable to demodulate the digital signals output by the plurality of A / D converters 122. Depending on the embodiment, the RF processor 124 may include a complex demodulator (not shown) operable to demodulate the digital signals to form I / Q data pairs representing corresponding echo signals. The RF or I / Q signal data may then be transferred to an RF / IQ buffer 126. The RF / IQ buffer 126 may include suitable logic, circuitry, interfaces, and / or code operable to provide temporary storage of the RF or I / Q signal data generated by the RF processor 124.

[0024] The receive beamformer 120 may include suitable logic, circuitry, interfaces, and / or code operable to perform digital beamforming processing, for example, to sum delayed channel signals received from the RF processor 124 via the RF / IQ buffer 126 and output a beam-summed signal. The resulting processed information may be the beam-summed signal output from the receive beamformer 120 and transmitted to the signal processor 132. According to some embodiments, the receiver 118, the plurality of A / D converters 122, the RF processor 124, and the beamformer 120 may be integrated into a single beamformer, which may be a digital beamformer. In various embodiments, the ultrasound system 100 includes a plurality of receive beamformers 120.

[0025] The user input device 130 may be used to input patient data, image acquisition and scanning parameters, settings, configuration parameters, select protocols and / or templates, change scanning modes, select anatomical targets, etc. In an exemplary embodiment, the user input device 130 is operable to configure, manage, and / or control the operation of one or more components and / or modules of the ultrasound system 100. In this regard, the user input device 130 is operable to configure, manage, and / or control the operation of the transmitter 102, the ultrasound probe 104, the transmit beamformer 110, the receiver 118, the receive beamformer 120, the RF processor 124, the RF / IQ buffer 126, the user input device 130, the signal processor 132, the image buffer 136, the display system 134, and / or the archive 138. The user input device 130 may include one or more buttons, one or more rotary encoders, a touch screen, motion tracking, voice recognition, a mouse device, a keyboard, a camera, and / or any other device capable of receiving user commands. In certain embodiments, one or more of the user input devices 130 may be integrated into other components, such as the display system 134 or the ultrasound probe 104, for example. For example, the user input device 130 may include a touch screen display.

[0026] The signal processor 132 may include suitable logic, circuitry, interfaces, and / or code operable to process ultrasound scan data (i.e., the summed IQ signal) to generate an ultrasound image for presentation on the display system 134. The signal processor 132 may be operable to perform one or more processing operations based on a plurality of selectable ultrasound modalities on the acquired ultrasound scan data. In an exemplary embodiment, the signal processor 132 may be configured to perform display processing and / or control processing, among other things. The acquired ultrasound scan data may be processed in real time during a scanning session as echo signals are received. Additionally or alternatively, the ultrasound scan data may be temporarily stored in the RF / IQ buffer 126 during a scanning session and processed in a less-than-real-time manner in either online or offline operations. In various embodiments, the processed image data may be presented at the display system 134 and / or may be stored in an archive 138. The archive 138 may be a local archive, a picture archiving and communication system (PACS), or any other suitable device for storing images and related information.

[0027] The signal processor 132 may be one or more central processing units, graphics processing units, microprocessors, microcontrollers, and the like. For example, the signal processor 132 may be an integrated component or may be distributed across various locations. In an exemplary embodiment, the signal processor 132 may include a first mode processor 140, a view classification processor 150, an object identification processor 160, and a second mode processor 170, and may be capable of receiving input information from the user input device 130 and / or the archive 138, generating output that may be displayed by the display system 134, and manipulating the output in response to the input information from the user input device 130. The signal processor 132, the first mode processor 140, the view classification processor 150, the object identification processor 160, and the second mode processor 170 may be capable of executing, for example, any of the methods and / or instruction sets discussed herein according to various embodiments.

[0028] The ultrasound system 100 may be operable to continuously acquire ultrasound scan data at a frame rate appropriate for the imaging situation under consideration. Typical frame rates are in the range of 20 to 120, but may be lower or higher. The acquired ultrasound scan data may be displayed on the display system 134 at a display rate that is the same as the frame rate, or at a display rate that is slower or faster than the frame rate. An image buffer 136 is included to store processed frames of acquired ultrasound scan data that are not scheduled for immediate display. Preferably, the image buffer 136 has sufficient capacity to store at least several minutes' worth of ultrasound scan data frames. The frames of ultrasound scan data are stored in a manner that allows for easy retrieval based on their acquisition order or time. The image buffer 136 may be embodied as any known data storage medium.

[0029] The signal processor 132 may include a first mode processor 140 including suitable logic, circuitry, interfaces, and / or code operable to process the acquired and / or retrieved first mode ultrasound image dataset to generate an ultrasound image according to the first mode. By way of example, the first mode may be a 2D mode (e.g., B-mode, biplane mode, triplane mode, etc.), and the first mode processor 140 may be configured to process the received first mode ultrasound image dataset into a 2D image. The first mode image may be provided to a view classification processor 150, to an object identification processor 160, presented to a display system 134, and / or stored in an archive 138 or any suitable data storage medium.

[0030] The signal processor 132 may include a view classification processor 150 comprising suitable logic, circuitry, interfaces, and / or code operable to process the first mode ultrasound image generated by the first mode processor 140 to determine a standard view depicted in the first mode ultrasound image. For example, the view classification processor 150 may determine which of a plurality of standard views of the abdomen the first mode ultrasound image represents. In various embodiments, the standard view is associated with a target anatomical structure. Thus, the view classification processor 150 determines that the target anatomical structure is identified by the standard view. In an exemplary embodiment, processing of the first mode ultrasound image by the view classification processor 150 may be initiated in response to receiving a user selection to switch to a second mode (such as Color Flow, Power Doppler, B-Flow Color, etc.). In certain embodiments, the view classification processor 150 may continuously process received first mode ultrasound images to detect whether to move the ultrasound probe 104 to acquire a different standard view. Alternatively, after initial processing of the first mode ultrasound image, subsequent processing of the first mode ultrasound image may be triggered by a detected change in the target anatomical structure, as described in more detail below.

[0031] The view classification processor 150 may include an image analysis algorithm, an artificial intelligence algorithm, one or more deep neural networks (e.g., convolutional neural networks), and / or may utilize any suitable form of image analysis technology or machine learning processing functionality configured to automatically determine a standard view depicted in a first-mode ultrasound image (such as a standard abdominal view depicted in a B-mode image). In various embodiments, the view classification processor 150 may be implemented as a deep neural network, which may be comprised of, for example, an input layer, an output layer, and one or more hidden layers between the input and output layers. Each layer may be comprised of a plurality of processing nodes, which may be referred to as neurons. For example, the view classification processor 150 may include an input layer having a neuron for each pixel, or group of pixels, from the ultrasound image data. The output layer may have neurons corresponding to the classification of a standard view depicted in the ultrasound image data. Each neuron in each layer may perform a processing function and pass the processed ultrasound image information to one of the plurality of neurons in a downstream layer for further processing. The processing performed by the view classification processor 150 deep neural network (e.g., convolutional neural network) may classify a standard view depicted in the ultrasound image data with a high degree of probability. The view classification processor 150 may provide the classification of standard views depicted in the first modality ultrasound image to the object identification processor 160, provide the standard view classification to the second modality processor 170, present the standard view classification at the display system 134 and / or may store the standard view classification at the archive 138 and / or any suitable data storage medium.

[0032] The signal processor 132 may include an object identification processor 160 comprising suitable logic, circuitry, interfaces, and / or code operable to process the first mode ultrasound image generated by the first mode processor 140 to determine the location of anatomical structures depicted in the first mode ultrasound image. For example, the object identification processor 160 may determine the location of one or more of the liver, kidneys, gallbladder, aorta, pancreas, spleen, and / or inferior vena cava, as well as other anatomical structures, depicted in the first mode ultrasound image as a standard view of the abdomen. In various embodiments, the object identification processor 160 may receive a standard view classification from the view classification processor 150. The standard view identified by the view classification processor 150 is associated with the target anatomical structure. Thus, the object identification processor 160 may be configured to process the first mode ultrasound image to determine at least the location of the target anatomical structure. In an exemplary embodiment, processing of the first mode ultrasound image by the object identification processor 160 may be initiated in response to receiving a user selection to switch to a second mode (such as Color Flow, Power Doppler, B-Flow Color, etc.). In some embodiments, the object identification processor 160 can continuously process the received first mode ultrasound images to detect whether to move the ultrasound probe 104 to acquire a different standard view. Alternatively, after the initial processing of the first mode ultrasound images by the object identification processor 160, subsequent processing of the first mode ultrasound images can be triggered by detected changes in the target anatomical structure, as described in more detail below.

[0033] The object identification processor 160 may include image analysis algorithms, artificial intelligence algorithms, one or more deep neural networks (e.g., convolutional neural networks), and / or may utilize any suitable form of image analysis technology or machine learning processing functionality configured to automatically determine the location of one or more anatomical structures depicted in the first modality ultrasound image (such as the target anatomical structure associated with the identified standard view). In various embodiments, the object identification processor 160 may be provided as a deep neural network, which may be comprised of, for example, an input layer, an output layer, and one or more hidden layers between the input and output layers. In an exemplary embodiment, the deep neural network may be an object detection model that identifies regions within the first modality ultrasound image having specific anatomical structures. In a representative embodiment, the deep neural network may be an object segmentation model that identifies the boundaries of one or more anatomical structures in the first modality ultrasound image on a pixel-by-pixel basis. Each layer may be comprised of a plurality of processing nodes, which may be referred to as neurons. For example, the object identification processor 160 may include an input layer having a neuron for each pixel, or group of pixels, from the ultrasound image data. The output layer may have neurons corresponding to the location of at least one of the anatomical structures depicted in the ultrasound image data. Each neuron in each layer may perform a processing function and pass the processed ultrasound image information to one of the neurons in the downstream layer for further processing. The processing performed by the object identification processor 160 deep neural network (e.g., a convolutional neural network) may identify the location of the anatomical structure depicted in the ultrasound image data with a high probability. The object identification processor 160 may provide the identified object location to the second mode processor 170, present an identification of the object (i.e., anatomical structure) at the location on the first mode ultrasound image on the display system 134, and / or may store the identified object location in the archive 138 and / or any suitable data storage medium.

[0034] Figure 2 A screenshot 300 of an exemplary first mode ultrasound image 304 with identified anatomical structures 306, 308 310, 312 is shown in accordance with various embodiments. Figure 2 , the screenshot 300 includes an image display portion 302 having a first mode ultrasound image 304. The first mode ultrasound image 304 may be a B-mode image or any suitable image acquired according to the first mode and generated by the first mode processor 140. The first mode ultrasound image 304 may be processed by the view classification processor 150 of the signal processor 132 to classify the first mode ultrasound image 304 into a standard view depicted therein. Figure 2The standard view shown is a standard view of the abdomen of the inferior vena cava (IVC) 306, where the hepatic veins of the liver 308 drain into the IVC 306. In various embodiments, the view classification can be presented at the display system 134. For example, a list of standard views can be presented along with the probability that each standard view is the depicted standard view. The standard views identified by the view classification processor 150 are consistent with the target anatomical structure (which is in Figure 2 The first mode ultrasound image 304 may be processed by the object identification processor 160 of the signal processor 132 to identify the location of at least one anatomical structure 306, 308 shown in the first mode ultrasound image 304. For example, the object identification processor 160 may apply an object detection model to automatically identify a first region 310 of the first mode ultrasound image 304 having the IVC 306 and a second region 312 of the first mode ultrasound image 304 having the liver 308, as shown in FIG. Figure 2 Additionally and / or alternatively, the object identification processor 160 may apply the object segmentation model to automatically segment the anatomical structures 306 , 308 shown in the first mode ultrasound image 304 to identify boundaries of the anatomical structures 306 , 308 in the first mode ultrasound image 304 . Figure 2 The object detection and / or object segmentation shown in FIG. 3 identifies 310 , 312 the locations of anatomical structures 306 , 308 , including the target anatomical structure (ie , the target anatomical structure) shown in the first mode ultrasound image 304 . Figure 2 The first modality ultrasound image 304 with the identified regions 310, 312 of the anatomical structures 306, 308 may be provided to the second modality processor 170, presented at the display system 134 and / or stored at the archive 138 or any suitable data storage medium.

[0035] Refer again Figure 1 The signal processor 132 may include a second mode processor 170 including suitable logic components, circuitry, interfaces, and / or code that may be operable to automatically select a region of interest box geometry and second mode imaging settings to acquire second ultrasound image information according to the second mode via the ultrasound probe 104. For example, the second mode processor 170 may be configured to receive from the view classification processor 150 and the object identification processor 160, or retrieve from the archive 138 or any suitable data storage medium the target anatomical structure associated with the standard view and the location of the target anatomical structure in the first mode ultrasound image.

[0036] The second mode processor 170 can be configured to select a ROI box geometry, including the location of the ROI box in the first mode ultrasound image, the depth start of the ROI box, the depth end of the ROI box, the width of the ROI box, and the like. The ROI box geometry parameters can depend on the type of ultrasound probe 104. For example, the width of the ROI box can be a distance for a linear probe and an angle for a curved probe. The ROI box geometry automatically selected by the second mode processor 170 is based on the target anatomical structure associated with the standard view and the location of the target anatomical structure in the first mode ultrasound image. For example, the ROI box is centered on the target anatomical structure in the first mode ultrasound image and is sized based on the size and location of the target anatomical structure in the first mode ultrasound image.

[0037] The second mode processor 170 can be configured to automatically select second mode imaging settings based on the target anatomical structure associated with the standard view and the location of the target anatomical structure in the first mode ultrasound image identified by the view classification processor 150 and the object identification processor 160. The second mode imaging settings may include, for example, gain, frequency, line density / frame average (L / A), pulse repetition frequency (PRF), wall filter (WF), spatial filter / packet size (S / P), acoustic output, and / or any suitable imaging settings for the second mode, such as color flow, power Doppler, B-flow color, etc. The second mode imaging settings are selected based on the first mode information (i.e., view classification and object identification) provided by the view classification processor 150 and the object identification processor 160. For example, different target anatomical structures may correspond to different second mode imaging settings due to different hemodynamics of different anatomical structures. As another example, the location of the target anatomical structure in the first mode ultrasound image may influence the selection of various second mode imaging settings, such as the depth of the target anatomical structure in the first mode ultrasound image affecting the selected second mode frequency setting.

[0038] The ultrasound system 100 is configured to acquire second mode ultrasound information according to a second mode based on the geometry of the region of interest box and the second mode imaging settings automatically selected by the second mode processor 170. The second mode can be a color flow mode, a power Doppler mode, a B-flow color mode, or any suitable mode. The second mode processor 170 is configured to cause the display system 134 to present the region of interest box and the acquired second mode information within the region of interest box superimposed on the first mode ultrasound image. The second mode processor 170 can be configured to update the region of interest box geometry and the second mode imaging settings in response to the updated standard view classification and / or updated anatomical object position received from the view classification processor 150 and / or the object identification processor 160, respectively. For example, if the ultrasound operator moves the ultrasound probe 104 to a different standard view to acquire ultrasound image data on a different target anatomical structure, the second mode processor 170 can receive the updated standard view classification and / or object position identification. As another example, if the ultrasound operator selects a different target anatomical structure within the same standard view (such as switching from the IVC 306 target structure to the liver 308 as the target structure in the IVC abdomen standard view, such as Figure 2 , the second mode processor 170 may receive the updated standard view classification and / or object position identification. For example, the ultrasound operator may select a different target anatomical structure by navigating a cursor over different target anatomical structures in the displayed ultrasound image via the user input device 130 (e.g., a mouse device, a trackball, etc.) and providing a selection input (e.g., pressing a button), or by providing a touch input of different anatomical structures in the ultrasound image presented on the touch screen display 130, 134. As another example, the ultrasound operator may select a different target anatomical structure from a drop-down menu that lists anatomical structures depicted in the current standard view. As another example, the user input device 130 may include a button for switching to a different target anatomical structure associated with a standard view that is most similar to the determined standard view.

[0039] Figure 3 A screenshot 400 illustrates exemplary second ultrasound image information 430 automatically placed within a region of interest box 420 on a first mode ultrasound image 404 in accordance with various embodiments. Figure 3 , the screenshot 400 includes an image display portion 402 having a first mode ultrasound image 404. The first mode ultrasound image 404 may be a B-mode image or any suitable image acquired according to the first mode and generated by the first mode processor 140. Figure 2The second mode processor 170 may receive a standard view classification of the first mode ultrasound image 404 associated with the target anatomical structure from the view classification processor 150 and an object position of the anatomical structure from the object identification processor 160. For example, the second mode processor 170 may receive a classification as follows: the standard view is an abdominal standard view of the inferior vena cava (IVC), in which the hepatic veins of the liver 308 drain into the IVC, which identifies the target anatomical structure as the IVC, as described above with reference to Figure 2 The second mode processor 170 may receive the identified regions of the anatomical structure depicted in the first mode ultrasound image 404 from the object identification processor 160 that infers the object detection model (e.g., Figure 2 ), or the object identification processor 160 may receive the segmented boundaries of the anatomical structure depicted in the first mode ultrasound image 404 from the inferred object segmentation model. The view classification associated with the target anatomical structure and the position of the at least one anatomical structure depicted in the first mode ultrasound image defines the first mode information. The second mode processor 170 is configured to automatically select the region of interest box geometry (i.e., the region of interest box size and position) and automatically select the second mode imaging settings based on the first mode information. The ultrasound system 100 acquires the second mode ultrasound information 430 according to the second mode based on the region of interest box geometry and the second mode image settings. The second mode may be as follows: Figure 3 The second mode processor 170 is configured to cause the display system 134 to present a region of interest box 420 superimposed on the first mode ultrasound image 404, and the second mode ultrasound information 430 superimposed on the first mode ultrasound image 404 within the region of interest box 420. The second ultrasound image information 430 automatically placed within the region of interest box 420 on the first mode ultrasound image 404 can be presented on the display system 134 and / or stored in the archive 138 and / or any suitable data storage medium.

[0040] Refer again Figure 1As image data is acquired and images 304, 404 are generated by the first mode processor 140, the view classification processor 150 and the object identification processor 160 can continuously process the first mode ultrasound images 304, 404. Thus, if the ultrasound probe 104 is moved to a different position, the view classification processor 150 can detect a new standard view classification. For example, if the ultrasound probe 104 is moved to a different position, the object identification processor 160 can identify a new anatomical object position 310, 312. Additionally and / or alternatively, the signal processor 132 and / or the object identification processor 160 can continuously process the first mode image data within the region of interest box 420 to determine whether the target anatomical structure 306 has changed, such as due to movement of the ultrasound probe 104. In this regard, the signal processor 132 and / or the object identification processor 160 may include image analysis algorithms, artificial intelligence algorithms, one or more deep neural networks (e.g., convolutional neural networks), and / or may utilize any suitable form of image analysis technology or machine learning processing functionality configured to determine whether the target anatomical structure 306 within the region of interest box 420 has changed. A determination that the target anatomical structure 306 has changed may trigger the view classification processor 150 and the object identification processor 160 to process the entire first mode ultrasound image 304, 404 to determine an updated standard view and the location of the anatomical structure shown in the updated standard view. Optionally, only the first mode image data within the region of interest box 430 may be continuously processed to trigger processing of the entire first mode ultrasound image 304, 404, rather than continuously processing the entire first mode ultrasound image 304, 404, which reduces the use of computing resources, thereby improving the functionality of the ultrasound system 100.

[0041] The display system 134 may be any device capable of conveying visual information to a user. For example, the display system 134 may include a liquid crystal display, a light emitting diode display, and / or any suitable display or displays. The display system 134 may be operable to present the first mode ultrasound images 304, 404, the identified object regions 310, 312 and / or the segmented object boundaries, standard view classifications, imaging settings, a region of interest box 420, the second mode ultrasound image data 430, and / or any suitable information.

[0042] The archive 138 can be one or more computer-readable memories, such as a picture archiving and communication system (PACS), a server, a hard disk, a floppy disk, a CD, a CD-ROM, a DVD, a compact memory, a flash memory, a random access memory, a read-only memory, an electrically erasable and programmable read-only memory, and / or any other suitable memory, that is integrated with the ultrasound system 100 and / or communicatively coupled (e.g., via a network) to the ultrasound system 100. The archive 138 can include, for example, a database, a library, a collection of information, or other memory that is accessed by and / or integrated with the signal processor 132. For example, the archive 138 can store data temporarily or permanently. The archive 138 can store medical image data, data generated by the signal processor 132, and / or instructions readable by the signal processor 132, among other things. In various embodiments, for example, the archive 138 stores the first mode ultrasound images 304, 404, identified object regions 310, 312 and / or segmented object boundaries within the first mode ultrasound images 304, 404, standard view classifications, imaging settings, second mode ultrasound image data 430 within a region of interest box 420 superimposed on the first mode ultrasound images 304, 404, instructions for classifying standard views, instructions for identifying object regions, instructions for identifying object boundaries, instructions for selecting region of interest box geometry, and / or instructions for selecting second mode imaging settings.

[0043] The components of the ultrasound system 100 may be implemented in software, hardware, firmware, etc. The various components of the ultrasound system 100 may be communicatively connected. The components of the ultrasound system 100 may be implemented separately and / or integrated in various forms. For example, the display system 134 and the user input device 130 may be integrated into a touch screen display.

[0044] Still refer to Figure 1The training system 200 may include a training engine 210 and a training database 220. The training engine 210 may include suitable logic, circuitry, interfaces, and / or code operable to train neurons of a deep neural network (e.g., an artificial intelligence model) inferred (i.e., deployed) by the signal processor 132, the view classification processor 150, and / or the object identification processor 160. For example, the training engine 210 may apply the classified anatomical structures to train the view classification, object detection, and / or object segmentation networks inferred by the view classification processor 150 and / or the object identification processor 160 to automatically classify standard views, automatically detect regions 310, 312 having anatomical structures 306, 308, and / or automatically segment the anatomical structures 306, 308 in the first modality ultrasound images 304, 404. The classified anatomical structures may include manually classified standard views, manually detected object regions 310, 312, and / or manually segmented input images and ground truth binary images (i.e., masks) of anatomical structures 306, 308. The training engine 210 may be configured to optimize the view classification, object detection, and / or object segmentation networks by adjusting the weights of the view classification, object detection, and / or object segmentation networks to minimize a loss function between the input ground truth mask and the output predicted mask.

[0045] In various embodiments, the database of training images 220 may be a picture archiving and communication system (PACS) or any suitable data storage medium. In certain embodiments, the training engine 210 and / or the training image database 220 may be a remote system communicatively coupled to the ultrasound system 100 via a wired or wireless connection, such as Figure 1 Additionally and / or alternatively, components or all of the training system 200 may be integrated with the ultrasound system 100 in various forms.

[0046] Figure 4 5 is a flow chart 500 illustrating exemplary steps 502-524 that may be used to automatically select imaging settings based on the first mode ultrasound image information 310, 312 and automatically place a region of interest box 420 on the first mode ultrasound image 304, 404 when entering the second mode ultrasound imaging mode, according to various embodiments. Figure 4 , a flowchart 500 including exemplary steps 502 through 524 is shown. Certain embodiments may omit one or more steps, and / or perform steps in an order different from the order listed, and / or combine certain steps discussed below. For example, some steps may not be performed in certain embodiments. For another example, certain steps may be performed in a different chronological order than listed below, including simultaneously.

[0047] At step 502, the ultrasound probe 104 of the ultrasound system 100 may acquire first ultrasound image information according to a first mode to generate first mode ultrasound images 304, 404. For example, the ultrasound probe 104 in the ultrasound system 100 may be operable to perform an ultrasound scan of a region of interest, such as an abdominal region. The ultrasound scan may be performed according to a first mode, such as B-mode or any suitable image acquisition mode. The first ultrasound image data set may be received by the first mode processor 140 of the signal processor 132 and / or stored in the archive 138 or any suitable data storage medium from which the first mode processor 140 may retrieve the first ultrasound image information. The first mode processor 140 of the signal processor 132 of the ultrasound system 100 may be configured to process the acquired and / or retrieved first mode ultrasound image information to generate an ultrasound image according to the first mode. As an example, the first mode may be B-mode, and the first mode processor 140 may be configured to process the received first mode ultrasound image information into the B-mode images 304, 404.

[0048] At step 504, the signal processor 132 of the ultrasound system 100 may process the first mode ultrasound images 304, 404 to determine first mode information including a view classification and at least one object identification. For example, the view classification processor 150 of the signal processor 132 of the ultrasound system 100 may be configured to automatically determine a standard view depicted in the first mode ultrasound images 304, 404, such as a standard view of the abdomen depicted in a B-mode image. In various embodiments, the standard view is associated with the target anatomical structure. Thus, the standard view identified by the view classification processor 150 identifies the target anatomical structure. In a representative embodiment, the view classification processor 150 infers a view classification deep learning model or any suitable image analysis algorithm to classify the standard view depicted in the first mode ultrasound images 304, 404. The object identification processor 160 of the signal processor 132 of the ultrasound system 100 may be configured to process the first mode ultrasound images 304, 404 generated by the first mode processor 140 at step 502 to determine the anatomical structure locations 310, 312 depicted in the first mode ultrasound images 304, 404. The object identification processor 160 can determine the location of one or more of the liver, kidneys, gallbladder, aorta, pancreas, spleen, and / or inferior vena cava, as well as other anatomical structures, depicted in, for example, the first modality ultrasound image 304, 404, which is a standard view of the abdomen. In various embodiments, the object identification processor 160 can receive a standard view classification associated with the target anatomical structure 306 from the view classification processor 150. Accordingly, the object identification processor 160 can be configured to process the first modality ultrasound image 304, 404 to determine the location 310 of at least the target anatomical structure 306. In a representative embodiment, the object identification processor 160 infers an object detection deep learning model, an object segmentation deep learning model, or any suitable image analysis algorithm to identify regions 310, 312 or segmented boundaries of at least one anatomical structure 306, 308 depicted in the first modality ultrasound image 304, 404. In an exemplary embodiment, processing of the first mode ultrasound images 304, 404 by the view classification processor 150 and / or the object identification processor 160 may be initiated in response to receiving a user selection to switch to a second mode (such as Color Flow, Power Doppler, B-Flow Color, etc.).

[0049] At step 506, the signal processor 132 of the ultrasound system 100 may automatically select a region of interest box geometry and second mode imaging settings based on the first mode information determined at step 504. For example, the second mode processor 170 of the signal processor 132 may be configured to receive the target anatomical structure 306 associated with the standard view and the location of the target anatomical structure 310 in the first mode ultrasound image 304, 404 from the view classification processor 150 and the object identification processor 160, or retrieve the target anatomical structure 306 associated with the standard view and the location of the target anatomical structure 310 in the first mode ultrasound image 304, 404 from the archive 138 or any suitable data storage medium. The second mode processor 170 may be configured to select a region of interest box geometry, including the location of the region of interest box 420 in the first mode ultrasound image 304, 404, the depth start of the region of interest box, the depth end of the region of interest box 420, the width of the region of interest box 420, etc. The region of interest box geometry automatically selected by the second mode processor 170 is based on the target anatomical structure 306 associated with the standard view and the location 310 of the target anatomical structure 306 in the first mode ultrasound image 304, 404. For example, the position of the region of interest box 420 is centered on the target anatomical structure 306 in the first mode ultrasound image 304, 404 and is sized based on the size and position of the target anatomical structure 306 in the first mode ultrasound image 304, 404. The second mode processor 170 can be configured to automatically select second mode imaging settings based on the target anatomical structure 306 associated with the standard view and the position 310 of the target anatomical structure 306 in the first mode ultrasound image 304, 404 identified by the view classification processor 150 and the object identification processor 160. The second mode imaging settings may include, for example, gain, frequency, line density / frame average (L / A), pulse repetition frequency (PRF), wall filter (WF), spatial filter / packet size (S / P), acoustic output, and / or any suitable imaging settings for the second mode, such as color flow, power Doppler, B-flow color, etc. The selection of the second mode imaging settings is based on the first mode information (i.e., view classification and object identification) provided by the view classification processor 150 and the object identification processor 160.

[0050] At step 508, the ultrasound probe 104 of the ultrasound system 100 may acquire second ultrasound image information 430 according to the second mode within the region of interest box 420 and based on the second mode imaging settings. For example, the ultrasound probe 104 of the ultrasound system 100 may acquire the second mode ultrasound information according to the second mode based on the geometry of the region of interest box and the second mode imaging settings automatically selected by the second mode processor 170 at step 506. The second mode may be a color flow mode, a power Doppler mode, a B-flow color mode, or any suitable mode.

[0051] At step 510, the signal processor 132 may cause the display system 134 of the ultrasound system 100 to present the second ultrasound image information 430, wherein the region of interest box 420 is automatically placed on the first mode ultrasound image 304, 404. For example, the second mode processor 170 is configured to cause the display system 134 to present the region of interest box 420 superimposed on the first mode ultrasound image 304, 404 and the acquired second ultrasound image information 430 within the region of interest box 420.

[0052] At step 512, the signal processor 132 of the ultrasound system 100 may determine whether the target anatomical structure 306 has been modified. If the second mode ultrasound information 430 has been acquired for all desired target anatomical structures, the process proceeds to step 514. If the ultrasound operator desires to acquire the second mode ultrasound information 430 of additional target anatomical structures, the ultrasound operator may select a new target anatomical structure within the same standard view (i.e., without moving the ultrasound probe 104) at step 516, or may manipulate the ultrasound probe 104 to a different position to acquire a different standard view associated with the new target anatomical structure at step 522.

[0053] At step 514 , the process 500 ends when second mode ultrasound information has been acquired for all desired target anatomical structures.

[0054] At step 516, the ultrasound operator may select a new target anatomical structure in the same standard view (i.e., without moving the ultrasound probe 104). For example, the ultrasound operator may select a different target anatomical structure within the same standard view, such as switching from the IVC 306 target structure to the liver 308 as the target structure in the IVC abdomen standard view, as shown in FIG. Figure 2 As shown. As one example, the ultrasound operator may select a different target by navigating a cursor over different target anatomical structures in the displayed ultrasound image via a user input device 130 (e.g., a mouse device, a trackball, etc.) and providing a selection input (e.g., pressing a button), or providing a touch input of different anatomical structures in the ultrasound image presented on the touch screen display 130, 134. As another example, the ultrasound operator may select a different target anatomical structure from a drop-down menu that lists anatomical structures depicted in the current standard view. As another example, the user input device 130 may include a button for switching to a different target anatomical structure associated with a standard view that is most similar to the determined standard view.

[0055] At step 518, the signal processor 132 of the ultrasound system 100 performs object identification on the first mode ultrasound images 304, 404 to automatically update the region of interest box geometry and the second mode imaging settings. For example, the object identification processor 160 of the signal processor 132 may deploy an object detection deep learning model, an object segmentation deep learning model, or any suitable image analysis algorithm to identify the location of the new target anatomical structure (e.g., a region or a segmented boundary). The second mode processor 170 may be configured to update the region of interest box geometry and the second mode imaging settings in response to the updated anatomical object location received from the object identification processor 160.

[0056] At step 520 , the process returns to step 508 to acquire second ultrasound image information 430 according to the second mode within the region of interest box 420 and based on the second mode imaging settings updated at step 518 in response to the new target anatomy.

[0057] At step 522, the ultrasound operator may maneuver the ultrasound probe 104 to a different position to acquire a different standard view associated with the new target anatomical structure. In various embodiments, the view classification processor 150 and the object identification processor 160 may continuously process the first mode ultrasound images 304, 404 as image data is acquired and the images 304, 404 are generated by the first mode processor 140. Thus, if the ultrasound probe 104 is moved to a different position, the view classification processor 150 may detect a new standard view classification. For example, if the ultrasound probe 104 is moved to a different position, the object identification processor 160 may identify a new anatomical object position 310, 312. Additionally and / or alternatively, the signal processor 132 and / or the object identification processor 160 may continuously process the first mode image data within the region of interest box 420 to determine whether the target anatomical structure 306 has changed, such as due to movement of the ultrasound probe 104. In this regard, the signal processor 132 and / or the object identification processor 160 may include an image analysis algorithm, an artificial intelligence algorithm, one or more deep neural networks (e.g., a convolutional neural network), and / or may utilize any suitable form of image analysis technology or machine learning processing functionality configured to determine whether the target anatomical structure 306 within the region of interest box 420 has changed. A determination that the target anatomical structure 306 has changed may trigger the view classification processor 150 and the object identification processor 160 to process the entire first mode ultrasound image 304, 404 to determine an updated standard view and the location of the anatomical structure shown in the updated standard view.

[0058] At step 524 , the process returns to step 506 to automatically select a region of interest box geometry and second mode imaging settings based on the first mode information determined at step 522 in response to the ultrasound probe moving to acquire a different standard view of the new target anatomy.

[0059] Aspects of the present disclosure provide a method 500 and system 100 for automatically selecting imaging settings based on first mode ultrasound image information and automatically placing a region of interest box 420 on a first mode ultrasound image (e.g., B-mode image) 304, 404 when entering a second ultrasound imaging mode (e.g., Color Flow, Power Doppler, B-Flow Color, etc.). According to various embodiments, the method 500 may include acquiring 502 first ultrasound image information by an ultrasound probe 104 of the ultrasound system 100 according to a first mode. The first ultrasound image information includes the first mode ultrasound image 304, 404. The method 500 may include processing 504 the first mode ultrasound image 304, 404 by at least one processor 132, 150, 160 of the ultrasound system 100 to determine the first mode information. The method 500 may include automatically selecting 506 a size and position of the region of interest box 420 by the at least one processor 132, 170 based on the first mode information. The method 500 may include acquiring 508 second ultrasound image information 430 by the ultrasound probe 104 according to a second mode based on the region of interest box 420. The method 500 may include causing 510 , by the at least one processor 132 , 170 , the display system 134 to present the second ultrasound image information 430 and the region of interest box 420 automatically placed on the first mode ultrasound image 304 , 404 .

[0060] In an exemplary embodiment, the first mode is B-mode, and the second mode is one of a color flow mode, a power Doppler mode, or a B-flow color mode. In a representative embodiment, the first mode information includes an ultrasound standard view classification and at least one anatomical object identifier 310, 312. In various embodiments, the method 500 includes inferring 504, by the at least one processor 132, 150, an ultrasound view classification model to determine the ultrasound standard view classification. In certain embodiments, the method 500 includes inferring 504, by the at least one processor 132, 160, an object detection model or an object segmentation model to determine the at least one anatomical object identifier 310, 312. In an exemplary embodiment, the ultrasound standard view classification is associated with a target anatomical object 306. The at least one anatomical object identifier defines a location 310 of the target anatomical object 306. In a representative embodiment, the method includes automatically selecting 506, by the at least one processor 132, 170, a second mode imaging setting based on the first mode information. Second ultrasound image information 430 is acquired based on the second mode imaging setting.

[0061] Various embodiments provide a system 100 for automatically selecting imaging settings based on first-mode ultrasound image information and automatically placing a region of interest box 420 on a first-mode ultrasound image (e.g., B-mode image) 304, 404 when entering a second ultrasound imaging mode (e.g., Color Flow, Power Doppler, B-Flow Color, etc.). The ultrasound system 100 may include an ultrasound probe 104, a display system 134, and at least one processor 132, 140, 150, 160, 170. The ultrasound probe 104 is operable to acquire first ultrasound image information according to a first mode. The first ultrasound image information includes the first-mode ultrasound image 304, 404. The ultrasound probe 104 is operable to acquire second ultrasound image information 430 according to a second mode based on the region of interest box 420. The at least one processor 132, 150, 160 may be configured to process the first-mode ultrasound image 304, 404 to determine the first-mode information. The at least one processor 132, 150, 160 may be configured to automatically select the size and position of the region of interest box 420 based on the first-mode information. The display system 134 may be configured to present the second ultrasound image information 430 with a region of interest box 420 automatically placed on the first mode ultrasound image 304 , 404 .

[0062] In a representative embodiment, the first mode is B-mode, and the second mode is one of color flow mode, power Doppler mode, or B-flow color mode. In various embodiments, the first mode information includes an ultrasound standard view classification and at least one anatomical object identifier 310, 312. In certain embodiments, the ultrasound standard view classification is determined based on an inferred ultrasound view classification model. In an exemplary embodiment, the at least one anatomical object identifier 310, 312 is based on an inferred object detection model or an object segmentation model. In a representative embodiment, the ultrasound standard view classification is associated with the target anatomical object 306. The at least one anatomical object identifier defines the location 310 of the target anatomical object 306. In various embodiments, the second ultrasound image information 430 is acquired based on a second mode imaging setting. The at least one processor 132, 170 is configured to automatically select the second mode imaging setting based on the first mode information.

[0063] Certain embodiments provide a system 100 for automatically selecting imaging settings based on first-mode ultrasound image information and automatically placing a region of interest box 420 on a first-mode ultrasound image (e.g., B-mode image) 304, 404 when entering a second ultrasound imaging mode (e.g., Color Flow, Power Doppler, B-Flow Color, etc.). The ultrasound system 100 may include an ultrasound probe 104, a display system 134, and at least one processor 132, 140, 150, 160, 170. The ultrasound probe 104 is operable to acquire first ultrasound image information according to a first mode. The first ultrasound image information includes the first-mode ultrasound image 304, 404. The ultrasound probe 104 is operable to acquire second ultrasound image information 430 according to a second mode based on the region of interest box 420. The at least one processor 132, 150, 160 may be configured to process the first-mode ultrasound image 304, 404 to determine the first-mode information. The at least one processor 132, 170 can be configured to cause the display system 134 to present the second ultrasound image information 430, wherein a region of interest box 420 is automatically positioned over the first target anatomical object 306 in the first mode ultrasound image 304, 404 based on the first mode information. The at least one processor 132, 170 can be configured to change the first target anatomical object 306 to the second target anatomical object. The at least one processor 132, 170 can be configured to automatically adjust the size and position of the region of interest box 420 positioned over the second target anatomical object in the first mode ultrasound image 304, 404 based on the first mode information and in response to the change from the first target anatomical object 306 to the second target anatomical object. The display system 134 can be configured to present the second ultrasound image information 430, wherein the region of interest box 420 is automatically positioned over the first mode ultrasound image 304, 404.

[0064] In various embodiments, the first modality information includes an ultrasound standard view classification determined by an inferred ultrasound view classification model and at least one anatomical object identifier 310, 312 determined by an inferred object detection model or an object segmentation model. In certain embodiments, the second ultrasound image information 430 is acquired based on a second modality imaging setting. The at least one processor 132, 170 is configured to automatically select the second modality imaging setting based on the first modality information. In an exemplary embodiment, the at least one processor 132, 150, 160 is configured to continuously process the entire first modality ultrasound image 304, 404 to detect movement of the ultrasound probe 104 and determine updated first modality information based on the movement of the ultrasound probe 104. The updated first modality information includes a change from the first target anatomical object 306 to the second target anatomical object. In a representative embodiment, the at least one processor 132, 160 is configured to continuously process a portion of the first modality ultrasound image 304, 404 within the region of interest box 420 to determine that the first target anatomical object 306 has moved outside the region of interest box 420 due to movement of the ultrasound probe 104. The at least one processor 132, 150, 160 is configured to process the entirety of the first mode ultrasound image 304, 404 in response to determining that the first target anatomical object 306 has moved out of the region of interest box 420 due to movement of the ultrasound probe 104 to determine updated first mode information. The updated first mode information includes a change from the first target anatomical object 306 to a second target anatomical object. In various embodiments, the at least one processor 132, 150, 170 is configured to change the first target anatomical object 306 to the second target anatomical object in response to a user selecting the second target anatomical object in the first mode ultrasound image 304, 404.

[0065] As used herein, the term "circuit" refers to physical electronic components (i.e., hardware) and any software and / or firmware ("code") that can configure hardware, is executed by hardware, and / or is otherwise associated with hardware. For example, as used herein, when executing one or more first codes, a particular processor and memory may include a first "circuit," and when executing one or more second codes, a particular processor and memory may include a second "circuit." As used herein, "and / or" represents any one or more of the items in a list connected by "and / or." For example, "x and / or y" represents any element in a three-element set {(x), (y), (x, y)}. As another example, "x, y, and / or z" represents any element in a seven-element set {(x), (y), (z), (x, y), (x, z), (y, z), (x, y, z)}. As used herein, the term "exemplary" represents a non-limiting example, instance, or illustration. As used herein, the terms "for example" and "such as" introduce a list of one or more non-limiting examples, instances, or illustrations. As used herein, a circuit is “capable of operating” and / or “configured to” perform a function whenever the circuit includes the necessary hardware and code (if necessary) to perform the function, regardless of whether execution of the function is disabled or not enabled by some user-configurable setting.

[0066] Other embodiments may provide a computer-readable device and / or non-transitory computer-readable medium, and / or a machine-readable device and / or non-transitory machine-readable medium, on which the computer-readable device and / or non-transitory computer-readable medium and / or the machine-readable device and / or non-transitory machine-readable medium store machine code and / or a computer program having at least one code segment executable by a machine and / or computer, so that the machine and / or computer performs the steps described herein for automatically selecting imaging settings based on first mode ultrasound image information and automatically placing a region of interest box on a first mode ultrasound image (e.g., B-mode image) when entering a second ultrasound imaging mode (e.g., color flow, power Doppler, B-flow color, etc.).

[0067] Thus, the present disclosure may be implemented in hardware, software, or a combination of hardware and software. The present disclosure may be implemented in a centralized manner in at least one computer system, or in a distributed manner, with different elements distributed across several interconnected computer systems. Any type of computer system or other device suitable for executing the methods described herein is suitable.

[0068] The various embodiments may also be embedded in a computer program product, which comprises all the features enabling the implementation of the methods described herein and which, when loaded into a computer system, is capable of carrying out these methods. A computer program in this context is any expression of a set of instructions in any language, code or notation, which is intended to cause a system with information processing capabilities to perform certain functions either directly or after either or both of the following: a) conversion into another language, code or notation; b) reproduction in a different material form.

[0069] Although the present disclosure has been described with reference to certain embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the scope of the present disclosure. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the present disclosure without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the specific embodiments disclosed, but rather the present disclosure is intended to include all embodiments falling within the scope of the appended claims.

Claims

1. A method (500), comprising: Acquiring (502) first ultrasound image information according to a first mode by an ultrasound probe (104) of an ultrasound system (100), wherein the first ultrasound image information includes a first mode ultrasound image (304, 404); processing (504) the first mode ultrasound image (304, 404) by at least one processor (132, 150, 160) of the ultrasound system (100) to determine first mode information; automatically selecting (506) by the at least one processor (132, 170) a size and a position of a region of interest box (420) based on the first pattern information; The ultrasound probe (104) acquires (508) second ultrasound image information (430) according to a second mode based on the region of interest frame (420); as well as The at least one processor (132, 170) causes (510) a display system (134) to present the second ultrasound image information (430) and the region of interest box (420) automatically placed on the first mode ultrasound image (304, 404).

2. The method (500) of claim 1, wherein: The first mode is the B mode; and The second mode is one of a Color Flow mode, a Power Doppler mode, or a B-Flow Color mode.

3. The method (500) of claim 1, wherein the first modality information comprises an ultrasound standard view classification and at least one anatomical object identification (310, 312).

4. The method (500) of claim 3, comprising inferring (504), by the at least one processor (132, 150), an ultrasound view classification model to determine the ultrasound standard view classification.

5. The method (500) of claim 3, comprising inferring (504) by the at least one processor (132, 160) an object detection model or an object segmentation model to determine the at least one anatomical object identification (310, 312).

6. The method (500) of claim 3, wherein: The ultrasound standard view classification is associated with a target anatomical object (306); and The at least one anatomical object identification defines a location (310) of the target anatomical object (306).

7. The method (500) according to claim 1 includes automatically selecting (506) a second mode imaging setting by the at least one processor (132, 170) based on the first mode information, wherein the second ultrasound image information (430) is acquired based on the second mode imaging setting.

8. An ultrasound system (100), comprising: An ultrasound probe (104) operable to: acquiring first ultrasound image information according to a first mode, wherein the first ultrasound image information comprises a first mode ultrasound image (304, 404), and Acquiring second ultrasound image information (430) according to a second mode based on the region of interest frame (420); At least one processor (132, 140, 150, 160, 170), the at least one processor being configured to: processing the first mode ultrasound image (304, 404) to determine first mode information, and Automatically selecting the size and position of the region of interest box (420) based on the first mode information; and A display system (134) is configured to present the second ultrasound image information (430) and the region of interest box (420) automatically placed on the first mode ultrasound image (304, 404).

9. The system (100) of claim 8, wherein: The first mode is the B mode; and The second mode is one of a Color Flow mode, a Power Doppler mode, or a B-Flow Color mode.

10. The system (100) of claim 8, wherein the first modality information includes an ultrasound standard view classification and at least one anatomical object identification (310, 312).

11. The system (100) of claim 10, wherein the ultrasound standard view classification is determined based on an inferred ultrasound view classification model.

12. The system (100) of claim 10, wherein the at least one anatomical object identification (310, 312) is based on an inferred object detection model or an object segmentation model.

13. The system (100) of claim 10, wherein: The ultrasound standard view classification is associated with a target anatomical object (306); and The at least one anatomical object identification defines a location (310) of the target anatomical object (306).

14. The system (100) of claim 8, wherein: The second ultrasound image information (430) is acquired based on a second mode imaging setting; and The at least one processor (132, 170) is configured to automatically select the second mode imaging settings based on the first mode information.

15. An ultrasound system (100), comprising: An ultrasound probe (104) operable to: Acquiring first ultrasound image information according to a first mode, wherein the first ultrasound image information includes a first mode ultrasound image (304, 404); and Acquiring second ultrasound image information (430) according to a second mode based on the region of interest frame (420); At least one processor (132, 140, 150, 160, 170), the at least one processor being configured to: processing the first mode ultrasound image (304, 404) to determine first mode information; causing a display system (134) to present the second ultrasound image information (430), wherein a region of interest box (420) is automatically placed over a first target anatomical object (306) in the first mode ultrasound image (304, 404) based on the first mode information; changing the first target anatomical object (306) to a second target anatomical object; as well as automatically adjusting the size and position of the region of interest box (420) placed over the second target anatomical object in the first mode ultrasound image (304, 404) based on the first mode information and in response to a change from the first target anatomical object (306) to the second target anatomical object; and A display system (134) is configured to present the second ultrasound image information (430) and the region of interest box (420) automatically placed on the first mode ultrasound image (304, 404).

Images