System for displaying data quality information for ultrasound imaging and sweep guidance information for ultrasound data acquisition

Abstract

Various systems (100) are provided for displaying data quality information for ultrasound imaging and sweep guidance information for ultrasound data acquisition. Ultrasound data of a region of interest of a subject may be acquired (710). An image of the region of interest of the subject may be generated (720). A region of the image generated using particular ones of the ultrasound data that includes a data quality less than a data quality threshold may be determined (730) using an artificial intelligence (AI) model (130). The image may be displayed (740) that includes a depiction of the region of the image generated using the particular ultrasound data. In addition, accurate registration in multiple locations of a large organ, such as the liver, is assisted by ultrasound sweep guidance at the location of interest identified in the preoperative imaging modality.

Description

Technical Field

[0001] This disclosure relates to systems and methods for ultrasound imaging. More specifically, this disclosure relates to a system and method for displaying data quality information for ultrasound imaging, and a system and method for displaying sweep guidance information for ultrasound data acquisition. Background Technology

[0002] The quality of ultrasound data can significantly impact the feasibility of applications or procedures utilizing ultrasound data. For example, an ultrasound imaging system can use acquired ultrasound data to generate and display ultrasound images. If the ultrasound data is of low quality, the ultrasound image may not accurately or fully depict the region of interest. As another example, an ultrasound imaging system can register ultrasound data with preoperative imaging data from another imaging modality. If the ultrasound data is of low quality, the ultrasound imaging system may not accurately or adequately register the ultrasound data with the preoperative imaging data. As yet another example, an ultrasound imaging system can track and display interventional devices during interventional procedures. If the ultrasound data is of low quality and image information (such as indications of needles in the image) is at least used as part of the tracking algorithm, the ultrasound imaging system may not accurately track or display the interventional device. As yet another example, an ultrasound imaging system can segment anatomical structures from ultrasound data and display a three-dimensional (3D) image of that anatomical structure. If the ultrasound data is of low quality, the ultrasound imaging system may not accurately or adequately segment the anatomical structure.

[0003] In the aforementioned situations, the reviewing entity (e.g., physician, sonographer, clinician, etc.) may find it difficult to decipher the displayed images or track the displayed interventional devices. These technical problems may be exacerbated when an ultrasound imaging system is used during an intraoperative procedure, as patient safety and procedural effectiveness may depend on the accuracy and robustness of the underlying ultrasound data.

[0004] In other situations, users may find it difficult to acquire ultrasound data of sufficient quality. For example, users may struggle to assess the specific location from which a scan is initiated, the specific orientation of the ultrasound probe used for the scan, the specific direction in which the ultrasound probe is moved during the scan, or the specific speed at which the ultrasound probe is moved during the scan. These technical problems may be exacerbated when acquiring ultrasound data for a specific region of interest. Therefore, if the ultrasound data is of low quality, the user may be required to perform an additional scan, which could introduce delays during the interventional procedure.

[0005] Registering intraoperative ultrasound data to preoperative data in a specific imaging modality is a challenging task. One problem is organ distortion from preoperative to surgical settings. This distortion can be caused by different patient positioning, CO2 insufflation in laparoscopic surgery, the patient's incision in open surgery, or the surgery itself. For large organs (such as the liver), registration requires accuracy at the locations of lesions seen in the preoperative imaging modality. For minimally invasive surgery, the ultrasound probe cannot move freely, and therefore it is useful to indicate to the user where and how to sweep to acquire sufficient ultrasound data at approximate locations of each lesion to perform accurate registration at that location. The algorithm that creates this visual instruction to the user is based on a coarse alignment between the preoperative data and the ultrasound as its input.

[0006] Coarse alignment can be established by keeping the tracking probe in a specific, well-defined position and orientation on the preoperative imaging modality. This coarse alignment can then be used as input to a sweep-guided algorithm.

[0007] If the quality or length of a particular original scan proves insufficient for the registration algorithm to function correctly, then visual indication of the sweep position is also useful. Summary of the Invention

[0008] This invention provides a more detailed description of concepts in specific embodiments. It should not be used to identify essential features of the claimed subject matter, nor should it be used to limit the scope of the claimed subject matter.

[0009] In one aspect, an apparatus may include a probe comprising: a transducer configured to transmit an ultrasonic signal toward a region of interest and receive an echo signal from the region of interest; a matching layer configured to have acoustic impedance between the region of interest to be imaged and a material of the transducer; and a damping block configured to absorb ultrasonic energy; a memory configured to store instructions; and one or more processors configured to execute the instructions to: acquire ultrasonic data of the region of interest of a subject; generate an image of the region of interest of the subject based on the ultrasonic data; determine, using an artificial intelligence (AI) model, regions of the image generated using specific ultrasonic data that include data quality less than a data quality threshold; and display the image, the image including a depiction of the region of the image generated using the specific ultrasonic data that includes data quality less than the data quality threshold.

[0010] In another aspect, a method may include: acquiring ultrasound data of a region of interest of a subject; generating an image of the region of interest of the subject based on the ultrasound data; using an artificial intelligence (AI) model to determine regions of the image generated using specific ultrasound data that have a data quality below a data quality threshold; and displaying the image, which includes a depiction of the region of the image generated using the specific ultrasound data that has a data quality below the data quality threshold.

[0011] On the other hand, a non-transitory computer-readable medium stores instructions that, when executed by one or more processors, cause the one or more processors to: acquire ultrasound data of a region of interest of a subject; generate an image of the region of interest of the subject based on the ultrasound data; use an artificial intelligence (AI) model to determine regions of the image generated using specific ultrasound data that include data quality less than a data quality threshold; and display the image, which includes a depiction of the region of the image generated using the specific ultrasound data that includes data quality less than the data quality threshold.

[0012] In another aspect of the invention, in order to perform registration between a preoperative imaging modality and live ultrasound, a method performs visual guidance that guides the user to position the ultrasound probe being tracked at a specific point and / or a specific orientation in space, or to perform an ultrasound sweep from a desired start position to a desired end position. Attached Figure Description

[0013] Figure 1 This is a diagram of an example system used to display data quality information for ultrasound imaging and sweep guidance information for ultrasound data acquisition.

[0014] Figure 2 yes Figure 1 A diagram illustrating example components of one or more systems.

[0015] Figure 3 This is a diagram of an example ultrasound imaging system.

[0016] Figure 4 This is a diagram of an example tracking system.

[0017] Figure 5 This is a diagram of the preoperative imaging system.

[0018] Figure 6 This is a diagram illustrating an example process for training an AI model.

[0019] Figure 7 This is a flowchart of an example process for displaying data quality information in association with ultrasound images.

[0020] Figure 8 This is a diagram illustrating an example process for displaying data quality information used in ultrasound imaging.

[0021] Figure 9A and Figure 9B This is a diagram of an example ultrasound image that displays data quality information.

[0022] Figure 10 This is a flowchart of an example process for displaying data quality information in association with an image.

[0023] Figure 11 This is an example 3D image illustrating data quality information.

[0024] Figure 12 This is a flowchart illustrating an example process for displaying sweep guidance information used in ultrasound data acquisition.

[0025] Figure 13 It is a diagram of sweep guidance information that includes visual indicators used to guide the orientation and speed of the ultrasound probe during ultrasound data acquisition.

[0026] Figure 14 It is a diagram of sweeping guidance information that includes visual indicators used to guide the positioning of the ultrasound probe during ultrasound data acquisition.

[0027] Figure 15 It is a diagram that includes sweep guidance information with visual indicators used to guide the movement of the ultrasound probe to reacquire ultrasound data corresponding to a region of data quality below a data quality threshold that corresponds to a 3D image generated using ultrasound data.

[0028] Figure 16 It is a diagram that includes sweeping guidance information, including visual indicators for guiding the positioning and orientation of the ultrasound probe.

[0029] Figure 17 It is a diagram that includes sweeping guidance information, including visual indicators used to guide the positioning and orientation of the ultrasound probe to acquire ultrasound data.

[0030] Figure 18 It is a diagram that includes sweeping guidance information, including visual indicators used to guide the positioning of the ultrasound probe to acquire ultrasound data.

[0031] Figure 19 It is a diagram that includes sweeping guidance information, including visual indicators used to guide the positioning and orientation of the ultrasound probe to acquire ultrasound data.

[0032] Figure 20 It is a diagram that includes sweeping guidance information, including visual indicators used to guide the positioning and orientation of the ultrasound probe to acquire ultrasound data. Detailed Implementation

[0033] Figure 1 This is a diagram illustrating an example system used to display data quality information for ultrasound imaging and sweep guidance information for ultrasound data acquisition. For example... Figure 1 As shown, system 100 may include ultrasound imaging system 110, artificial intelligence (AI) model 130, tracking system 150, preoperative imaging system 170 and network 190.

[0034] The ultrasound imaging system 110 can be configured to acquire ultrasound data and generate medical images based on the ultrasound data. For example, the ultrasound imaging system 110 can be a two-dimensional (2D) ultrasound system, a 3D ultrasound system, a four-dimensional (4D) ultrasound system, or a Doppler ultrasound system, etc. According to one embodiment, the medical image can be an ultrasound image. According to another embodiment, the medical image can be a 3D image of an anatomical structure generated using ultrasound data. The anatomical structure can be a blood vessel, tissue, or organ, etc.

[0035] AI model 130 can be configured to receive ultrasound data and determine the data quality of the ultrasound data. For example, AI model 130 can be a decision tree (e.g., a classification tree or regression tree), a linear regression model, a neural network (e.g., a deep neural network (DNN), a convolutional neural network (CNN), or a recurrent neural network (RNN)), a logistic regression model, or a support vector machine, etc.

[0036] The tracking system 150 can be configured to acquire tracking data corresponding to the tracked device. For example, the tracking system 150 can be an electromagnetic tracking system, an optical tracking system, an acoustic tracking system, or an inertial tracking system. The tracked device can be an ultrasound probe or an interventional device (e.g., a catheter or a needle).

[0037] The preoperative imaging system 170 can be configured to acquire preoperative imaging data. For example, the preoperative imaging system 170 can be a computed tomography (CT) system, a magnetic resonance imaging (MRI) system, an ultrasound system, an X-ray system, or a positron emission tomography (PET) device.

[0038] Network 190 can be configured to allow communication between ultrasound imaging system 110, tracking system 150, and preoperative imaging system 170. For example, network 190 can be a local area network (LAN), wide area network (WAN), metropolitan area network (MAN), cellular network, private network, ad hoc network, intranet, Internet, or fiber optic network, and / or a combination of these or other types of networks.

[0039] The number and arrangement of systems in system 100 are provided as examples. During implementation, system 100 may include additional systems, fewer systems, different systems, or systems related to... Figure 1 The systems shown are arranged differently. Additionally or alternatively, a group of systems of system 100 (e.g., one or more systems) may be integrated into a single system and / or perform one or more functions described as being performed by another system or another group of systems of system 100.

[0040] Figure 2 This is a diagram illustrating example components of system 200. System 200 may correspond to ultrasound imaging system 110, intraoperative imaging system 130, tracking system 150, and / or preoperative imaging system 170. Figure 2 As shown, system 200 may include bus 210, processor 220, memory 230, storage component 240, input component 250, output component 260 and communication interface 270.

[0041] Bus 210 includes components that allow communication between components of system 200. Processor 220 may be implemented using hardware, firmware, or a combination of hardware and software. Processor 180 may be a central processing unit (CPU), graphics processing unit (GPU), accelerated processing unit (APU), microprocessor, microcontroller, digital signal processor (DSP), field-programmable gate array (FPGA), application-specific integrated circuit (ASIC), or another type of processing component.

[0042] Processor 180 may include one or more processors capable of being programmed to perform functions. Processor 180 may include one or more processors 180 configured to perform the operations described herein. For example, a single processor 180 may be configured to perform all the operations described herein. Alternatively, multiple processors 180 may be collectively configured to perform all the operations described herein, and each of the multiple processors 180 may be configured to perform a subgroup of operations described herein. For example, a first processor 180 may perform a first subgroup of operations described herein, a second processor 180 may be configured to perform a second subgroup of operations described herein, and so on.

[0043] The memory 230 may include random access memory (RAM), read-only memory (ROM), and / or another type of dynamic or static storage device (e.g., flash memory, magnetic memory, and / or optical memory) that stores information and / or instructions for use by the processor 180.

[0044] Storage component 240 may store information and / or software related to the operation and use of system 200. For example, storage component 240 may include hard disks (e.g., magnetic disks, optical disks, magneto-optical disks, and / or solid-state disks), compact discs (CDs), digital versatile discs (DVDs), floppy disks, cassettes, magnetic tapes, and / or other types of non-transitory computer-readable media and corresponding drives.

[0045] Input component 250 may include components that allow system 200 to receive information such as via user input (e.g., touchscreen display, keyboard, keypad, mouse, buttons, switches, camera, and / or microphone). Additionally or alternatively, input component 250 may include sensors for sensing information (e.g., a Global Positioning System (GPS) component, accelerometer, gyroscope, and / or actuator). Output component 260 may include components that provide output information from system 200 (e.g., a display, a speaker for outputting sound at an output sound level, and / or one or more light-emitting diodes (LEDs)).

[0046] Communication interface 270 may include transceiver-like components (e.g., a transceiver and / or separate receiver and transmitter) that enable system 200 to communicate with other systems, such as via wired, wireless, or a combination of wired and wireless connections. Communication interface 270 may permit system 200 to receive information from and / or provide information to another system. For example, communication interface 270 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, a Wi-Fi interface, or a cellular network interface, etc.

[0047] System 200 can execute one or more processes described herein. System 200 can execute these processes based on software instructions stored in a non-transitory computer-readable medium such as memory 230 and / or storage component 240, executed by processor 180. Computer-readable medium may be defined herein as a non-transitory memory device. A memory device may include memory space within a single physical storage device or memory space distributed across multiple physical storage devices.

[0048] Software instructions can be read from another computer-readable medium or from another system into memory 230 and / or storage component 240 via communication interface 270. When executed, the software instructions stored in memory 230 and / or storage component 240 cause processor 180 to perform one or more processes described herein. Additionally or alternatively, hardwired circuitry may be used in place of or in combination with software instructions to perform one or more processes described herein. Therefore, the specific implementations described herein are not limited to any particular combination of hardware circuitry and software.

[0049] Figure 2 The number and arrangement of components shown are provided as an example. In implementation, system 200 may include additional components, fewer components, different components, or components related to... Figure 2 The components shown are arranged differently. Additionally or alternatively, a set of components of system 200 (e.g., one or more components) may perform one or more functions described as being performed by another set of components of system 200.

[0050] Figure 3 This is a diagram illustrating an example ultrasound imaging system. For example... Figure 3 As shown, the ultrasound imaging system 110 may include an ultrasound probe 111, a transmit beamformer 112, a transmitter 113, an element 114, a receiver 115, a receive beamformer 116, a user input device 117, a processor 118, a display 119, a memory 120, and a communication interface 121. The aforementioned components may be connected via wired or wireless connections.

[0051] The ultrasound probe 111 can be configured to acquire ultrasound data. For example, the ultrasound probe 111 can be a linear probe, a phased array probe, a curved linear probe coupled to a positioning and tracking system, a mechanically manipulated linear array transducer, a phased array transducer, a curved linear array transducer, an electronically manipulated 2D transducer array, an electronic 3D (e3D) probe, an electronic 4D (e4D) probe, or a low-profile wearable patch version of any of the aforementioned probes. According to one embodiment, the ultrasound probe 111 can be configured to generate ultrasound signals, emit ultrasound signals toward the region of interest (ROI) of the subject, receive echo ultrasound signals backscattered from the RIO of the subject, generate ultrasound data based on the echo ultrasound signals, and output ultrasound data. The RIO can be any region of the subject's anatomical structure. The subject can be a human, animal, or phantom, etc.

[0052] According to one embodiment, the ultrasonic probe 111 may include: a transducer configured to transmit an ultrasonic signal toward a region of interest and receive an echo signal from the region of interest; a matching layer configured to have acoustic impedance between the region of interest to be imaged and the material of the transducer; and a damping block configured to absorb ultrasonic energy.

[0053] Transmit beamformer 112 can be configured to apply a delay time to the electrical signal provided to element 114 to focus the corresponding ultrasonic signal at the region of interest. Transmitter 113 can be configured to send an electrical signal to element 114 to drive element 114 to emit an ultrasonic signal toward the region of interest. Element 114 can be configured to receive the electrical signal from transmitter 113, convert the electrical signal into an ultrasonic signal, and emit the ultrasonic signal toward the region of interest. Element 114 can be configured to receive the echo ultrasonic signal backscattered from the region of interest, convert the echo ultrasonic signal into an electrical signal, and provide the electrical signal to receiver 115. Receiver 115 can be configured to receive the electrical signal from element 114 and provide the electrical signal to receiver beamformer 116. Receiver beamformer 116 can apply a delay time to the electrical signal received from element 114.

[0054] User input device 117 may be configured to receive user input and provide the user input to processor 118. For example, user input device 117 may be a touch screen display, keyboard, keypad, mouse, button, switch, or microphone, etc. Additionally or alternatively, user input device 117 may be configured to sense information. For example, user input device 117 may sense information from an electromagnetic positioning system, inertial measurement system, accelerometer, gyroscope, or actuator, etc.

[0055] Processor 118 may be configured to perform the operations described herein. For example, processor 118 may be a CPU, GPU, APU, microprocessor, microcontroller, DSP, FPGA, or ASIC, etc. Processor 118 may be implemented using hardware, firmware, or a combination of hardware and software. Processor 118 may include one or more processors 118 configured to perform the operations described herein. For example, a single processor 118 may be configured to perform all the operations described herein. Alternatively, multiple processors 118 may be collectively configured to perform all the operations described herein, and each of the multiple processors 118 may be configured to perform a subgroup of operations described herein. For example, a first processor 118 may perform a first subgroup of operations described herein, a second processor 118 may be configured to perform a second subgroup of operations described herein, and so on.

[0056] Processor 118 can be configured to control ultrasound probe 111 to acquire ultrasound data. Processor 118 can be configured to control which elements in element 114 are active and to control the shape of the beam emitted from ultrasound probe 111. Processor 118 can generate ultrasound images for display. For example, processor 118 can generate B-mode images, color Doppler images, M-mode images, or color M-mode images, etc. Ultrasound images can be 3D images, 2D images, single-plane images, dual-plane images, tri-plane images, or multi-plane images, etc. Ultrasound images can correspond to various anatomical planes (e.g., sagittal, coronal, and transverse) of the region of interest.

[0057] Display 119 can be configured to display information. For example, display 119 can be a monitor, LED display, cathode ray tube, projector display, touch screen, tablet computer, or mobile phone. Display 119 can display ultrasound images based on ultrasound data in real time. For example, display 119 can display ultrasound images within one second, two seconds, five seconds, etc., of ultrasound data acquired by ultrasound probe 111.

[0058] Memory 120 may be configured to store information and / or instructions for use by processor 118. Memory 120 may be a non-transitory computer-readable medium. For example, memory 120 may be RAM, ROM, flash memory, magnetic memory, or optical memory, etc. Memory 120 may be configured to store instructions that, when executed by processor 118, cause processor 118 to perform the operations described herein.

[0059] The communication interface 121 may be configured to enable the processor 118 to communicate with other systems, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. For example, the communication interface 121 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, an RF interface, a USB interface, a Wi-Fi interface, or a cellular network interface, etc.

[0060] Figure 3 The number and arrangement of components in the ultrasound imaging system 110 shown are provided as an example. In practice, the ultrasound imaging system 110 may include additional components, fewer components, different components, or components related to... Figure 3 The components shown are arranged differently. Additionally or alternatively, a set of components (e.g., one or more components) of the ultrasound imaging system 110 may perform one or more functions described as being performed by another set of components of the intraoperative imaging system 130.

[0061] Figure 4 This is a diagram of the example tracking system 150. For example... Figure 4As shown, the tracking system 150 can be an electromagnetic tracking system and may include a transmitter 151, a receiver 152, a user input device 153, a processor 154, a display 155, a memory 156, and a communication interface 157.

[0062] Transmitter 151 can be configured to generate a magnetic field. Receiver 152 can be configured to output a signal in response to the magnetic field generated by transmitter 151. Processor 154 can receive the output signal from receiver 152 and acquire tracking data identifying the positioning and / or orientation of receiver 152. Receiver 152 can be attached to, integrated with, or disposed within a tracked device. For example, according to one embodiment, receiver 152 can be attached to ultrasound probe 111 to track the positioning and / or orientation of ultrasound probe 111. Alternatively, receiver 152 can be attached to a barcode scanner or another handheld device to track the positioning and / or orientation of the barcode scanner or other handheld device. Alternatively, receiver 152 can be attached to an interventional device to track the positioning and / or orientation of the interventional device. The interventional device can be a catheter or needle, etc.

[0063] User input device 153 may be configured to receive user input and provide the user input to processor 154. For example, user input device 153 may be a touch screen display, keyboard, keypad, mouse, button, switch, or microphone, etc. Additionally or alternatively, user input device 153 may be configured to sense information. For example, user input device 153 may sense information from an electromagnetic positioning system, inertial measurement system, accelerometer, gyroscope, or actuator, etc.

[0064] Processor 154 may be configured to perform the operations described herein. For example, processor 154 may be a CPU, GPU, APU, microprocessor, microcontroller, DSP, FPGA, or ASIC, etc. Processor 154 may be implemented using hardware, firmware, or a combination of hardware and software. Processor 154 may include one or more processors 154 configured to perform the operations described herein. For example, a single processor 154 may be configured to perform all the operations described herein. Alternatively, multiple processors 154 may be collectively configured to perform all the operations described herein, and each of the multiple processors 154 may be configured to perform a subgroup of operations described herein. For example, a first processor 154 may perform a first subgroup of operations described herein, a second processor 154 may be configured to perform a second subgroup of operations described herein, and so on.

[0065] Processor 154 can be configured to control transmitter 151 to acquire tracking data. Processor 154 can be configured to control the excitation of transmitter 151 to generate a magnetic field. Processor 154 can acquire tracking data based on controlling transmitter 151.

[0066] Display 155 can be configured to display information. For example, display 155 can be a monitor, LED display, cathode ray tube, projector display, touch screen, tablet computer, or mobile phone. Display 155 can display tracking data in real time. For example, display 155 can display tracking data within one second, two seconds, five seconds, etc., of the currently acquired tracking data.

[0067] Memory 156 may be configured to store information and / or instructions for use by processor 154. Memory 156 may be a non-transitory computer-readable medium. For example, memory 156 may be RAM, ROM, flash memory, magnetic memory, or optical memory, etc. Memory 156 may be configured to store instructions that, when executed by processor 154, cause processor 154 to perform the operations described herein.

[0068] The communication interface 157 can be configured to enable the processor 154 to communicate with other systems, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. For example, the communication interface 157 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, an RF interface, a USB interface, a Wi-Fi interface, or a cellular network interface, etc.

[0069] Figure 4 The number and arrangement of components in the tracking system 150 shown are provided as an example. In implementation, the tracking system 150 may include additional components, fewer components, different components, or components related to... Figure 4 The components shown are arranged differently. Additionally or alternatively, a set of components (e.g., one or more components) of the tracking system 150 may perform one or more functions described as being performed by another set of components of the tracking system 150.

[0070] although Figure 4 Tracking system 150 is described as an electromagnetic tracking system, but it should be understood that the embodiments described herein are applicable to other types of tracking systems, such as optical tracking systems, acoustic tracking systems, or ultrasonic tracking systems.

[0071] Figure 5 This is an illustration of the preoperative imaging system 170. (See image below.) Figure 5As shown, the preoperative imaging system 170 may be a CT imaging system and may include a gantry 171, a rotating frame 172, an X-ray source 173, an X-ray detector 174, a patient table 175, a processor 176, a memory 177, a display 178, a user input device 179, a communication interface 180, a picture archiving and communication system (PACS) 181, and a server 182.

[0072] A gantry 171 can be configured to support a rotating frame 172, an X-ray source 173, and an X-ray detector 174. The rotating frame 172 can be configured to rotate the X-ray source 173 and the X-ray detector 174 around a subject positioned on a patient table 175. The X-ray source 173 can be configured to emit X-ray radiation in the form of an X-ray beam toward the subject and the X-ray detector 174. The X-ray detector 174 can be configured to detect the X-ray radiation emitted by the X-ray source 173 and attenuated by the subject. The patient table 175 can be configured to support the subject during scanning. During scanning, the gantry 171 can rotate the rotating frame 172 around the subject to change the angle at which the X-ray beam emitted by the X-ray source 173 intersects with the subject. The X-ray detector 174 can acquire projection data by detecting the radiation from the X-ray beam.

[0073] Processor 176 may be configured to control the operation of preoperative imaging system 170. For example, processor 176 may be a CPU, GPU, APU, microprocessor, microcontroller, DSP, FPGA, or ASIC. Processor 176 may be implemented using hardware, firmware, or a combination of hardware and software. Processor 176 may include one or more processors 176 configured to perform the operations described herein. For example, a single processor 176 may be configured to perform all the operations described herein. Alternatively, multiple processors 176 may be collectively configured to perform all the operations described herein, and each of the multiple processors 176 may be configured to perform a subgroup of operations described herein. For example, a first processor 176 may perform a first subgroup of operations described herein, a second processor 176 may be configured to perform a second subgroup of operations described herein, and so on.

[0074] Processor 176 can be configured to control the movement of gantry 171, rotating frame 172, X-ray source 173, X-ray detector 174, and patient table 175. Processor 176 can receive projection data generated during scanning and use the projection data to generate medical images.

[0075] Memory 177 may be configured to store information and / or instructions for use by processor 176. Memory 177 may be a non-transitory computer-readable medium. For example, memory 177 may be RAM, ROM, flash memory, magnetic memory, or optical memory, etc. Memory 177 may be configured to store instructions that, when executed by processor 176, cause processor 176 to perform the operations described herein.

[0076] Display 178 can be configured to display information. For example, display 178 can be a monitor, a light-emitting diode (LED) display, a cathode ray tube, a projector display, a touch screen, a tablet computer, or a mobile phone. Display 178 can display medical images in real time. For example, display 178 can display medical images within one second, two seconds, or five seconds while medical images are being generated or scanning is being completed.

[0077] User input device 179 may be configured to receive user input and provide the user input to processor 176. For example, user input device 179 may be a touchscreen display, keyboard, keypad, mouse, button, switch, or microphone, etc. Additionally or alternatively, user input device 179 may be configured to sense information. For example, user input device 179 may sense information from an electromagnetic positioning system, inertial measurement system, accelerometer, gyroscope, or actuator, etc.

[0078] Communication interface 180 may be configured to enable processor 176 to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. For example, communication interface 180 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, a Wi-Fi interface, or a cellular network interface. PACS 181 may be configured to communicate with external systems and / or networks to allow users at various locations to access medical images. Server 182 may be configured to store one or more models as described herein. For example, server 182 may be a local server, a cloud server, or a virtual machine.

[0079] Figure 6 This is a diagram illustrating example process 600 used to train an AI model. For example... Figure 6 As shown, process 600 may include a training phase 602 and a deployment phase 608.

[0080] During the training phase, the training device can receive and process training data to generate a trained AI model 130 for determining the data quality of ultrasound data. The training data may include multiple training datasets, each comprising ultrasound data and corresponding data quality. The training data may be generated, received, or otherwise obtained from internal and / or external resources.

[0081] Typically, AI model 130 may include a set of variables (e.g., nodes, neurons, or filters) tuned (e.g., weighted or biased) to different values ​​through the application of training data. According to one embodiment, the training process may employ supervised, unsupervised, semi-supervised, and / or reinforcement learning processes to train AI model 130. According to one embodiment, a portion of the training data may be retained during training and / or used to validate the trained AI model 130.

[0082] For a supervised learning process, training data may include labels or scores that can facilitate the training process by providing ground truth values. For example, labels or scores may indicate the data quality corresponding to ultrasound data. Training can continue by feeding the training dataset into AI model 130. AI model 130 may have variables set to initial values ​​(e.g., randomly, based on Gaussian noise, or based on pre-trained values, etc.). AI model 130 can generate outputs. The outputs can be compared with corresponding labels or scores (e.g., ground truth values) and then backpropagated through AI model 130 to adjust the values ​​of the variables. This process can be repeated for multiple samples, at least until the determined loss or error is below a predefined threshold. According to one embodiment, some of the training data may be retained and used for further validation or testing of the trained AI model 130.

[0083] For unsupervised learning processes, training data may not include pre-assigned labels or scores to aid the learning process. Instead, unsupervised learning processes may include clustering or classification to identify patterns naturally present in the training data. As an example, training data can be clustered into groups based on identified similarities and / or patterns. K-means clustering or K-nearest neighbors can also be used, and these can be supervised or unsupervised. A combination of K-nearest neighbors and unsupervised clustering techniques can also be used. For semi-supervised learning, a combination of training data with pre-assigned labels or scores and training data without pre-assigned labels or scores can be used to train an AI model130.

[0084] After being trained, the trained AI model 130 can be stored and subsequently applied by the ultrasound imaging system 110 during deployment phase 608. For example, during deployment phase 608, the trained AI model 130, executed by the ultrasound imaging system 110, can receive ultrasound data and determine the data quality of the ultrasound data.

[0085] Figure 7 This is a flowchart of an example process 700 for displaying data quality information associated with an ultrasound image. For example, an ultrasound imaging system 110 may perform the operation of process 700. However, in other embodiments, one or more other systems may perform one or more operations of process 700.

[0086] like Figure 7 As shown, process 700 may include: acquiring ultrasound data (operation 710). For example, ultrasound imaging system 110 may acquire ultrasound data of a region of interest in a subject. The region of interest may be an anatomical structure of the subject. The subject may be a human, animal, or phantom, etc.

[0087] like Figure 7 As further shown, process 700 may include generating an ultrasound image based on ultrasound data (operation 720). For example, ultrasound imaging system 110 may generate an ultrasound image based on ultrasound data. The ultrasound image may be a 2D ultrasound image or a 3D ultrasound image, etc.

[0088] like Figure 7 As further shown, process 700 may include: using an AI model to determine regions of the ultrasound image that contain data quality below a data quality threshold (operation 730). For example, ultrasound imaging system 110 may use AI model 130 to determine regions of the ultrasound image that contain data quality below a data quality threshold.

[0089] As used herein, "data quality" can refer to a measure of the suitability of ultrasound data for a particular purpose. For example, the data quality of ultrasound data can identify the accuracy, completeness, comprehensiveness, consistency, timeliness, uniqueness, or validity of the ultrasound data. A data quality threshold can be a threshold that, if met, indicates that the ultrasound data is accurate, complete, comprehensive, consistent, timely, unique, or valid. Furthermore, a data quality threshold can be a threshold that, if not met, indicates that the ultrasound data is inaccurate, incomplete, inconsistent, untimely, or invalid. As used herein, "met" can mean greater than, greater than or equal to, less than, or less than or equal to.

[0090] Ultrasound imaging system 110 can determine the data quality of ultrasound data. According to one embodiment, ultrasound imaging system 110 can determine the data quality of ultrasound data based on signal quality metrics. For example, signal quality metrics may be signal-to-noise ratio (SNR), mean square error (MSE), or bit error rate (BER). According to one embodiment, ultrasound imaging system 110 can determine the data quality of ultrasound data based on image quality attributes. For example, image quality attributes may be sharpness, noise, contrast, distortion, or artifact levels. According to one embodiment, ultrasound imaging system 110 can use AI model 130 to determine the data quality of ultrasound data. For example, ultrasound imaging system 110 can input ultrasound images into AI model 130 and determine the data quality of the ultrasound images based on the output of AI model 130. AI model 130 can be trained using training data including known ultrasound images and known data quality.

[0091] The ultrasound imaging system 110 can identify regions of an ultrasound image that have data quality below a data quality threshold. For example, the ultrasound imaging system 110 can determine the corresponding data quality of each portion of the ultrasound image and compare the corresponding data quality with the data quality threshold. A portion of the ultrasound image can be a pixel or a group of pixels, etc. Furthermore, the ultrasound imaging system 110 can identify regions of the ultrasound image that include portions of the ultrasound image with data quality that does not meet the data quality threshold.

[0092] like Figure 7 Further, process 700 may include: displaying an ultrasound image, the ultrasound image including a depiction of a region of the ultrasound image with data quality less than a data quality threshold (operation 740). For example... Figure 7 As shown, it may also be desirable to depict the entire scanned area. For example, ultrasound imaging system 110 may display an ultrasound image that includes a depiction of a region of the ultrasound image with data quality less than a data quality threshold.

[0093] According to one embodiment, the ultrasound imaging system 110 can display an ultrasound image including a depiction of a region visually representing the ultrasound image, comprising a data quality below a data quality threshold. As an example, the ultrasound imaging system 110 may use visual indicators (e.g., lines, boxes, colors, or patterns) to depict the region. As another example, the ultrasound imaging system 110 may depict the region by removing it or by replacing it. According to one embodiment, the ultrasound imaging system 110 may display a notification indicating that the region comprises a data quality below a data quality threshold.

[0094] Figure 8 This is a diagram 800 illustrating an example process for displaying data quality information used in ultrasound imaging. (See diagram 800.) Figure 8 As shown, the ultrasound imaging system 110 can input an ultrasound image 810 into an AI model 130 and generate an ultrasound image 820 based on the output of the AI ​​model 130, which includes depictions of regions 830 and 840, both of which have data quality below a data quality threshold.

[0095] Figure 9A and Figure 9B This is a diagram 900 showing an example ultrasound image displaying data quality information. For example... Figure 9A As shown, the ultrasound image 910 may include: region 920, which includes data quality less than a data quality threshold; and region 930, which includes data quality greater than the data quality threshold. Furthermore, the ultrasound image 910 may include a visual indicator 940 that depicts the region 910 containing data quality less than the data quality threshold. Figure 9BAs shown, the ultrasound image 950 may include: region 960, which includes data quality less than a data quality threshold; and region 970, which includes data quality greater than the data quality threshold. Furthermore, the ultrasound image 950 may include a visual indicator 980 that depicts region 960, which includes data quality less than the data quality threshold.

[0096] Figure 10 This is a flowchart of an example process 1000 for displaying data quality information associated with a 3D image. For example, an ultrasound imaging system 110 may perform the operation of process 1000. However, in other embodiments, one or more other systems may perform one or more operations of process 1000.

[0097] like Figure 10 As shown, process 1000 may include: acquiring ultrasound data (operation 1010). For example, ultrasound imaging system 110 may acquire ultrasound data of a region of interest in a subject. The region of interest may be an anatomical structure of the subject. The subject may be a human, animal, or phantom, etc.

[0098] like Figure 10 As further shown, process 1000 may include generating an image based on ultrasound data. For example, ultrasound imaging system 110 may generate an image based on ultrasound data. The image may be a 2D image or a 3D image, etc. The image may be an image of a region of interest. The image may include anatomical structures within the region of interest. For example, the anatomical structures may be blood vessels or tissues, etc. Ultrasound imaging system 110 may use ultrasound data to segment the anatomical structures and generate an image based on the segmented anatomical structures.

[0099] like Figure 10 As further shown, process 1000 may include: using an artificial intelligence (AI) model to determine regions of data quality in an image generated from ultrasound data that are below a data quality threshold (operation 1030). For example, ultrasound imaging system 110 may use AI model 130 to determine regions of data quality in a 3D image generated from ultrasound data that are below a data quality threshold.

[0100] Ultrasound imaging system 110 can determine the data quality of ultrasound data used to generate images. According to one embodiment, ultrasound imaging system 110 can determine the data quality of ultrasound data based on signal quality metrics. For example, signal quality metrics may be SNR or MSE, etc. According to one embodiment, ultrasound imaging system 110 can determine the data quality of ultrasound data based on image quality attributes. For example, image quality attributes may be sharpness, noise, contrast, distortion, or artifact levels, etc. According to one embodiment, ultrasound imaging system 110 can use AI model 130 to determine the data quality of ultrasound data. For example, ultrasound imaging system 110 can input ultrasound images into AI model 130 and determine the data quality of the ultrasound images based on the output of AI model 130.

[0101] The ultrasound imaging system 110 can determine regions in an image generated using ultrasound data that have a data quality below a data quality threshold. For example, the ultrasound imaging system 110 can determine the corresponding data quality of the ultrasound data used to generate the image and compare the corresponding data quality with a data quality threshold. Furthermore, the ultrasound imaging system 110 can determine regions in an image generated using ultrasound data that have a data quality that does not meet a data quality threshold.

[0102] like Figure 10 As further shown, process 1000 may include: displaying an image that includes a depiction of regions of the image generated using ultrasound data that have a data quality below a data quality threshold. For example, ultrasound imaging system 110 may display an image that includes a depiction of regions of the image generated using ultrasound data that have a data quality below a data quality threshold.

[0103] According to one embodiment, the ultrasound imaging system 110 can display an image including a depiction of regions with data quality below a data quality threshold that visually represent the image generated using ultrasound data. As an example, the ultrasound imaging system 110 may use visual indicators (e.g., lines, boxes, colors, or patterns) to depict the regions. As another example, the ultrasound imaging system 110 may depict regions by removing or replacing them. According to one embodiment, the ultrasound imaging system 110 may display a notification identifying regions generated using ultrasound data that have data quality below a data quality threshold.

[0104] Figure 11 This is an example 3D image 1110 displaying data quality information. For example... Figure 11 As shown, the 3D image 1110 may include anatomical structures 1120 segmented using ultrasound data. Furthermore, as shown, the 3D image 1110 may include regions 1130 and 1140 generated using ultrasound data, which has a data quality below a data quality threshold.

[0105] Figure 12 This is a flowchart illustrating an example process 1200 for displaying sweep guidance information for ultrasound data acquisition. For example, an ultrasound imaging system 110 may perform the operation of process 1200. However, in other embodiments, one or more other systems may perform one or more operations of process 1200.

[0106] like Figure 12 As shown, process 1200 may include: displaying sweep guidance information (operation 1210). For example, ultrasound imaging system 110 may display sweep guidance information. Sweep guidance information may be information that guides the operator of ultrasound imaging system 110 to acquire ultrasound data.

[0107] According to one embodiment, the sweep guidance information may include a visual indicator guiding the positioning of the ultrasound probe 111 relative to the subject. For example, the visual indicator may guide the operator to place the ultrasound probe 111 at a specific location relative to the subject. Additionally or alternatively, the sweep guidance information may include a visual indicator guiding the orientation of the ultrasound probe 111 relative to the subject. For example, the visual indicator may guide the operator to orient the ultrasound probe 111 at a specific orientation relative to the subject. Additionally or alternatively, the sweep guidance information may include a visual indicator guiding the speed of the ultrasound probe 111. For example, the visual indicator may guide the operator to move the ultrasound probe 111 at a specific speed. Additionally or alternatively, the sweep guidance information may include a visual indicator guiding the direction of movement of the ultrasound probe 111. For example, the visual indicator may guide the operator to move the ultrasound probe 111 along a specific trajectory relative to the subject.

[0108] According to one embodiment, the sweep guidance information may include a visual indicator displaying the amount of ultrasound data acquired relative to the region of interest. For example, the visual indicator may display the total amount of ultrasound data to be acquired and the actual amount of ultrasound data acquired. When additional ultrasound data is acquired, the ultrasound imaging system 110 may update the actual amount of acquired ultrasound data.

[0109] According to one embodiment, the sweep guidance information may include a visual indicator displaying a 3D image generated based on the ultrasound data. Furthermore, the ultrasound imaging system 110 may update the 3D image as additional ultrasound data is acquired.

[0110] According to one embodiment, the ultrasound imaging system 110 can generate sweep guidance information based on tracking data acquired from the tracking system 150. For example, the ultrasound imaging system 110 can acquire tracking data from the tracking system 150 to determine the positioning, orientation, velocity, and / or direction of movement of the ultrasound probe 111 relative to one or more references, and generate sweep guidance information based on the positioning, orientation, velocity, and / or direction of movement of the ultrasound probe 111 relative to one or more references. The one or more references may include the subject, the subject's region of interest, anatomical features of the subject, or the imaging location, etc.

[0111] Additionally or alternatively, the ultrasound imaging system 110 may generate sweep guidance information based on preoperative imaging data acquired from the preoperative imaging system 170. For example, the ultrasound imaging system 110 may register ultrasound data acquired by the ultrasound probe 111 with the preoperative imaging data to determine the positioning, orientation, velocity, and / or direction of movement of the ultrasound probe 111 relative to the preoperative imaging data, and generate sweep guidance information based on the positioning, orientation, velocity, and / or direction of movement of the ultrasound.

[0112] According to the implementation scheme, the ultrasound imaging system 110 can use information from guided ultrasound sweeps to locally realign ultrasound data with preoperative data for more accurate registration.

[0113] According to one embodiment, the ultrasound imaging system 110 can compare acquired ultrasound data with preoperative imaging data and determine whether ultrasound data corresponding to the entire dataset of preoperative imaging data has been acquired. For example, if the preoperative imaging data falls within a region of interest, the ultrasound imaging system 110 can determine whether ultrasound data for the entire region of interest has been acquired. The ultrasound imaging system 110 can generate sweep guidance based on the comparison to guide the operator of the ultrasound imaging system 110 to acquire missing ultrasound data corresponding to the acquired preoperative imaging data.

[0114] According to one embodiment, the ultrasound imaging system 110 can determine the data quality of the acquired ultrasound data and generate sweep guidance information based on the data quality. For example, if the data quality is less than a data quality threshold, the ultrasound imaging system 110 can generate sweep guidance information that guides the operator of the ultrasound imaging system 110 to acquire ultrasound data with higher data quality. For example, the sweep guidance information can guide the operator to reposition and / or reorient the ultrasound probe 111, move the ultrasound probe 111 more slowly, or move the ultrasound probe 111 to reacquire ultrasound data in a specific area, etc.

[0115] like Figure 12As further shown, process 1200 may include: acquiring ultrasound data based on displayed sweep guidance information (operation 1220). For example, ultrasound imaging system 110 may acquire ultrasound data based on displayed sweep guidance information. Process 1200 may return to operation 1210. That is, ultrasound imaging system 110 may display updated sweep guidance information based on the acquired ultrasound data.

[0116] According to one embodiment, the ultrasound imaging system 110 may display information identifying the ultrasound data to be acquired. For example, the ultrasound imaging system 110 may determine that the ultrasound probe 111 is positioned at a specific location and / or oriented in a specific orientation, and display information guiding the operator of the ultrasound imaging system 110 to acquire ultrasound data. Alternatively, the ultrasound imaging system 110 may determine that the ultrasound probe 111 is positioned at a specific location and / or oriented in a specific orientation, and automatically acquire ultrasound data based on the ultrasound probe 111 being positioned at a specific location and / or oriented in a specific orientation.

[0117] Figure 13 This is a diagram 1300 illustrating sweep guidance information, including visual indicators for guiding the orientation and velocity of the ultrasound probe 111 during ultrasound data acquisition. As indicated by reference numerals 1302, 1304, and 1306, the ultrasound imaging system 110 can display sweep guidance information as the operator of the ultrasound imaging system 110 moves the ultrasound probe 111 relative to the subject. The visual indicators may include a virtual probe 1308 and a sphere 1310. The ultrasound imaging system 110 can adjust the positioning and / or orientation of the virtual probe 1308 relative to the sphere 1310 based on the movement of the ultrasound probe 111. If the positioning, orientation, and / or velocity of the ultrasound probe 111 relative to the subject is suitable for ultrasound data acquisition, the ultrasound imaging system 110 can display the virtual probe 1308 within the sphere 1310. Alternatively, if the positioning, orientation, and / or velocity of the ultrasound probe 111 relative to the subject is not suitable for ultrasound data acquisition, the ultrasound imaging system 110 may partially or completely display a virtual probe 1308 outside the sphere 1310, depending on the degree to which the positioning, orientation, and / or velocity of the ultrasound probe 111 relative to the subject is unsuitable for ultrasound data acquisition.

[0118] Figure 14A diagram 1400 includes sweep guidance information including visual indicators for positioning the ultrasound probe 111 during ultrasound data acquisition. The visual indicators may include an acquisition volume 1410 corresponding to a region of interest for which ultrasound data is to be acquired. The acquisition volume 1410 may include: a via acquisition area 1420 depicting the area of ​​the acquisition volume 1410 for which ultrasound data has already been acquired; and an unacquired area 1430 depicting the area of ​​the acquisition volume 1410 for which ultrasound data has not yet been acquired. As the operator moves the ultrasound probe 111 to acquire ultrasound data, the ultrasound imaging system 110 can update the display of the acquisition volume 1410 by adding to the via acquisition area 1420.

[0119] Figure 15 A diagram 1500 includes sweep guidance information with a visual indicator used to guide the movement of the ultrasound probe 111 to reacquire ultrasound data corresponding to regions with data quality below a data quality threshold in a 3D image generated using ultrasound data. The visual indicator may include a 3D image 1510 displaying segmented anatomical features 1520 and regions 1530 and 1540 generated using ultrasound data with data quality below the data quality threshold. Furthermore, the visual indicator may include a current virtual probe position 1550 and a destination virtual probe position 1560. The destination position 1560 may be the positioning of the ultrasound probe 111 relative to the subject, allowing reacquisition of ultrasound data corresponding to regions 1530 and 1540.

[0120] Figure 16 A diagram 1600 includes sweep guidance information, including visual indicators for guiding the positioning and orientation of the ultrasound probe 111 to acquire ultrasound data. The visual indicators may include a 3D image 1610 of the region of interest and include a region 1620 depicting the area where ultrasound data acquisition should occur. According to one embodiment, the ultrasound imaging system 110 may register preoperative imaging data from a preoperative imaging system 170 with ultrasound data from an ultrasound probe 111 tracked by a tracking system 150. Anatomical structures (e.g., blood vessels) in the preoperative imaging data may have been previously segmented. Similarly, the ultrasound imaging system 110 may segment anatomical structures in the ultrasound data. Due to differences in organ positioning during preoperative scanning and during surgery, anatomical structures may not accurately match in the two imaging modalities. In this case, the ultrasound imaging system 110 may display sweep guidance information to ensure or improve the likelihood that the user sweeps an area suitable for accurate alignment between the two modalities. According to one embodiment, the sweep guidance information may guide the user to perform a scan such that the area of ​​acoustic action includes at least one vascular bifurcation near a predefined target lesion.

[0121] Figure 17 It is a diagram including sweeping guidance information of a visual indicator for guiding the positioning and orientation of the ultrasound probe to acquire ultrasound data. The visual indicator may include a 3D image 1710 of the region of interest and a region 1720 depicting the area where ultrasound data acquisition should occur. Region 1720 may be transparent or translucent.

[0122] Figure 18 This is an illustration of sweep guidance information including visual indicators for guiding the positioning of the ultrasound probe to acquire ultrasound data. The visual indicators may include a 3D image 1810 and a location identifier 1820 for positioning the ultrasound probe 111 relative to the region of interest. According to one embodiment, the ultrasound imaging system 110 can register preoperative imaging data from a preoperative imaging system 170 and ultrasound data from the ultrasound probe 111 tracked by a tracking system 150. Anatomical structures (e.g., blood vessels) in the preoperative imaging data may have been previously segmented. Similarly, the ultrasound imaging system 110 can segment anatomical structures in the ultrasound data. According to one embodiment, the tracking system 150 can track patient orientation in ultrasound space with reasonable accuracy, but the positioning of the ultrasound probe 111 relative to the preoperative imaging data may not be known with reasonable accuracy. In this case, the ultrasound imaging system 110 can display sweep guidance information to guide the user to position the ultrasound probe 111 at a specific anatomical point on the scanning surface, enabling the ultrasound data to be registered to the preoperative data with reasonable accuracy for subsequent processing. The approximate orientation and approximate positioning obtained through the tracking system 150 and the positioning process via the ultrasonic probe 111 enable subsequent accurate registration of the two imaging modalities.

[0123] Figure 19 It is a diagram including sweep guidance information of visual indicators for guiding the positioning and orientation of the ultrasound probe to acquire ultrasound data. The visual indicators may include a 3D image 1910 and a position identifier 1920 for positioning the ultrasound probe 111 relative to the region of interest and / or moving the ultrasound probe 111 relative to the region of interest.

[0124] According to one embodiment, ultrasound imaging system 110 can register preoperative imaging data from preoperative imaging system 170 and ultrasound data from ultrasound probe 111 tracked by tracking system 150. Anatomical structures (e.g., blood vessels) in the preoperative imaging data may have been previously segmented. Similarly, ultrasound imaging system 110 can segment anatomical structures in the ultrasound data. According to one embodiment, tracking system 150 may be unavailable, making it impossible to know the patient orientation with reasonable accuracy in the ultrasound imaging space. Furthermore, the positioning of ultrasound probe 111 relative to the preoperative imaging data may not be known with reasonable accuracy. In this case, ultrasound imaging system 110 can display sweep guidance information to guide the user to position ultrasound probe 111 at a specific anatomical point on the scanning surface with a specific orientation (e.g., directly pointing up and down without rolling or yaw), enabling the ultrasound data to be registered to the preoperative imaging data with reasonable accuracy for subsequent processing. The approximate orientation and positioning obtained through this process enable subsequent accurate registration of the two imaging modalities.

[0125] Figure 20 It is a diagram that includes sweeping guidance information, including visual indicators used to guide the positioning and orientation of the ultrasound probe for acquiring ultrasound data. For example... Figure 20 As shown, the ultrasound imaging system 110 can display 3D images 2010, 2020, 2030 and 2040 of the relevant area for which ultrasound data is to be acquired.

[0126] The embodiments shown in the accompanying drawings and described above are merely exemplary embodiments and are not intended to limit the scope of the appended claims, including any equivalents included within the scope of the claims. Various modifications are possible and will be apparent to those skilled in the art. Any combination of non-mutually exclusive features described herein is intended to be within the scope of the invention. That is, features of the described embodiments may be combined with any suitable aspect described above, and optional features of any aspect may be combined with any other suitable aspect. Similarly, features listed in dependent claims may be combined with non-mutually exclusive features of other dependent claims, particularly where the dependent claims are subordinate to the same independent claim. In some jurisdictions that claim a single claim dependency, such dependencies may have been used in practice, but this should not be construed as meaning that features in dependent claims are mutually exclusive.

Claims

1. A device (110), the device comprising: Probe (111), the probe comprising: A transducer configured to transmit an ultrasonic signal toward a region of interest and receive an echo signal from the region of interest; A matching layer, configured to have acoustic impedance between the region of interest to be imaged and the material of the transducer; and A damping block configured to absorb ultrasonic energy; Memory (120), the memory being configured to store instructions; and One or more processors (118), said one or more processors being configured to execute the instructions to: (710) Acquire ultrasound data of the region of interest of the subject; (720) An image of the region of interest of the subject is generated based on the ultrasound data; The artificial intelligence (AI) model (130) is used to determine (730) the regions of the image generated using specific ultrasound data from the ultrasound data that include data quality below a data quality threshold; and Display (740) the image, the image including a depiction of the region of the image generated using the specific ultrasound data in the ultrasound data, including the data quality being less than the data quality threshold.

2. The device (110) according to claim 1, wherein the one or more processors (118) are further configured to: The ultrasound data is used to segment anatomical features within the region of interest. The image includes the anatomical features.

3. The device (110) according to claim 1, wherein the one or more processors (118) are further configured to: The display includes sweep guidance information including visual indicators that guide the operator to place the ultrasound probe (111) at a specific location relative to the subject.

4. The device (110) according to claim 1, wherein the one or more processors (118) are further configured to: The display includes sweep guidance information including visual indicators that guide the operator to orient the ultrasound probe (111) relative to the subject.

5. The device (110) according to claim 1, wherein the one or more processors (118) are further configured to: The display includes sweep guidance information including visual indicators that guide the operator of the ultrasound probe (111) to move the ultrasound probe at a specific speed.

6. The device (110) according to claim 1, wherein the one or more processors (118) are further configured to: Display sweep guidance information including visual indicators that guide the operator to move the ultrasound probe (111) relative to the subject along a specific trajectory.

7. The device (110) according to claim 1, wherein the one or more processors (118) are further configured to: The display includes sweep guidance information including visual indicators that show the amount of ultrasound data acquired relative to the region of interest.

8. A method (700), the method comprising: (710) Acquire ultrasound data of the region of interest of the subject; (720) An image of the region of interest of the subject is generated based on the ultrasound data; The artificial intelligence (AI) model (130) is used to determine (730) regions of data quality (less than a data quality threshold) in the image generated using specific ultrasound data from the ultrasound data; and Display (740) the image, the image including a depiction of the region of the image generated using the specific ultrasound data in the ultrasound data, including the data quality being less than the data quality threshold.

9. The method (700) according to claim 8, further comprising: The ultrasound data is used to segment anatomical features within the region of interest. The image includes the anatomical features.

10. The method (700) according to claim 8, further comprising: The display includes sweep guidance information including visual indicators that guide the operator to place the ultrasound probe (111) at a specific location relative to the subject.

11. The method (700) according to claim 8, further comprising: The display includes sweep guidance information including visual indicators that guide the operator to orient the ultrasound probe (111) relative to the subject.

12. The method (700) according to claim 8, further comprising: The display includes sweep guidance information including visual indicators that guide the operator of the ultrasound probe (111) to move the ultrasound probe at a specific speed.

13. The method (700) according to claim 8, further comprising: Display sweep guidance information including visual indicators that guide the operator to move the ultrasound probe (111) relative to the subject along a specific trajectory.

14. The method (700) according to claim 8, further comprising: The display includes sweep guidance information including visual indicators that show the amount of ultrasound data acquired relative to the region of interest.

15. A non-transitory computer-readable medium (120) storing instructions that, when executed by one or more processors (118), cause the one or more processors (118) to: (710) Acquire ultrasound data of the region of interest of the subject; (720) An image of the region of interest of the subject is generated based on the ultrasound data; The artificial intelligence (AI) model (130) is used to determine (730) the regions of the image generated using specific ultrasound data from the ultrasound data that include data quality below a data quality threshold; and Display (740) the image, the image including a depiction of the region of the image generated using the specific ultrasound data in the ultrasound data, including the data quality being less than the data quality threshold.

Images