System and method for automated optic sheath measurement based on three-dimensional ultrasound data

Abstract

An ultrasound imaging system (100) and method (200) are provided for determining measurements of an optic nerve sheath. The ultrasound imaging system (100) and method (200) may include controlling (210) an ultrasound probe (102) to acquire three-dimensional (3D) ultrasound data of the optic nerve sheath. The ultrasound imaging system (100) and method (200) may include determining (220) the measurement of the optic nerve sheath based on the 3D ultrasound data. The ultrasound imaging system (100) and method (200) may include controlling (230) a display (118) to display information related to the measurement of the optic nerve sheath.

Description

Background Art

[0001] A person may experience increased intracranial pressure (ICP) due to a primary injury such as head trauma, underlying health problems, etc. In addition, increased ICP may aggravate secondary injuries such as ischemia, cerebral edema, hypoxia, etc., which manifest after the primary injury. Due to increased ICP, the size of the optic nerve sheath may increase. Therefore, an enlargement of the optic nerve sheath can indicate an increased ICP. Summary of the invention

[0002] This summary introduces concepts that are described in more detail in the detailed description. 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.

[0003] In one aspect, an ultrasound imaging system may include an ultrasound probe, a display, and one or more processors configured to control the ultrasound probe to acquire three-dimensional (3D) ultrasound data of an optic nerve sheath, determine measurement results of the optic nerve sheath based on the 3D ultrasound data, and control the display to display information related to the measurement results of the optic nerve sheath.

[0004] In another aspect, a method may include: controlling an ultrasound probe to acquire three-dimensional (3D) ultrasound data of an optic nerve sheath; determining a measurement result of the optic nerve sheath based on the 3D ultrasound data; and controlling the display to display information related to the measurement result of the optic nerve sheath.

[0005] On the other hand, an ultrasound imaging system may include: a memory configured to store instructions; and one or more processors configured to execute the instructions to control an ultrasound probe to acquire three-dimensional (3D) ultrasound data of an optic nerve sheath, determine measurement results of the optic nerve sheath based on the 3D ultrasound data, and control a display to display information related to the measurement results of the optic nerve sheath.

[0006] Some embodiments of the present disclosure provide an improved ultrasound imaging system that improves the accuracy, efficiency, speed, and reliability of ultrasound data acquisition and optic nerve sheath measurement, provides improvements in the technical field of ultrasound imaging, and provides improvements in patient safety and treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 is a diagram of an ultrasound imaging system according to one embodiment.

[0008] Figure 2 is a flow chart of an exemplary process for determining measurements of the optic nerve sheath, according to one embodiment.

[0009] Figure 3 is a diagram showing a preview ultrasound image in real time according to an embodiment.

[0010] Figure 4 is a flow chart of an exemplary process for generating scan guidance information according to one embodiment.

[0011] Figure 5 is a diagram showing scan guide information according to one embodiment.

[0012] Figure 6 is a flow chart of an exemplary process for controlling an ultrasound probe to automatically acquire 3D ultrasound data based on a scan quality metric according to one embodiment.

[0013] Figure 7 is a flow chart of an exemplary process for determining measurements of the optic nerve sheath based on 3D ultrasound data, according to one embodiment.

[0014] Figure 8 is a diagram of a major axis measurement plane according to one embodiment.

[0015] Fig. 9 is a diagram of a minor axis measurement plane according to one embodiment.

[0016] Fig.10 is a graph of measurement results of the optic nerve sheath according to one embodiment.

[0017] Fig.11 is a flow chart of an exemplary process for determining measurements of an optic nerve sheath at a measurement location at a predetermined distance from an anatomical landmark based on 3D ultrasound data, according to one embodiment.

[0018] FIG. 12A to FIG. 12C is a diagram of an ultrasound image used to determine measurements of the optic nerve sheath based on 3D ultrasound data, according to one embodiment.

[0019] Fig.13 is a flow chart of an exemplary process for determining measurements of the optic nerve sheath using multiple measurements based on 3D ultrasound data, according to one embodiment.

[0020] Fig.14A and Fig. 14B is a diagram of an ultrasound image used to determine measurements of the optic nerve sheath based on 3D ultrasound data, according to one embodiment.

[0021] Fig.15 is a flow chart of an exemplary process for determining measurements of the optic nerve sheath based on 3D ultrasound data using AI model inference, according to one embodiment.

[0022] Fig.16is a diagram of a display of information related to measurements of the optic nerve sheath according to one embodiment.

[0023] Fig.17 is a diagram of an exemplary process for training AI model inference according to one embodiment. DETAILED DESCRIPTION

[0024] Embodiments of the present disclosure will now be described by way of example with reference to the accompanying drawings.

[0025] Ultrasound imaging systems and methods can use two-dimensional (2D) ultrasound imaging to help medical personnel determine measurements of the optic nerve sheath. In this way, ultrasound imaging systems and methods that utilize 2D ultrasound data may provide relatively rapid and non-invasive ICP assessments through measurements of the optic nerve sheath. However, ultrasound imaging systems and methods may involve optimal alignment of the ultrasound probe relative to the anatomical planes of the optic nerve sheath in order to obtain a 2D ultrasound image that accurately reflects the true measurements of the optic nerve sheath.

[0026] Therefore, ultrasound imaging systems and methods utilizing 2D ultrasound data may involve a skilled operator spending a sufficiently long time and imaging resources to position the ultrasound probe when acquiring the 2D ultrasound data. Therefore, ultrasound imaging systems and methods utilizing 2D ultrasound data may not be optimally effective for implementation at the point of medical care, at the point of injury, or during transportation to the treatment location in a medical vehicle. In addition, ultrasound imaging systems and methods utilizing 2D data may involve a skilled examiner evaluating the 2D ultrasound image to determine the measurement results of the optic nerve sheath. If the ultrasound probe is not aligned relative to the optic nerve sheath during image acquisition, the 2D ultrasound image may result in optic nerve sheath measurements with less than optimal accuracy, reliability, etc. In addition, if the anatomical structure of the optic nerve sheath is tilted, curved, etc., the 2D ultrasound image may not accurately reflect the true size of the optic nerve sheath, and may result in inaccurate optic nerve sheath measurements.

[0027] The ability of medical personnel to accurately identify elevated ICP and routinely monitor changes in ICP is valuable. In addition, the ability to quickly and effectively identify elevated ICP in resource-constrained environments may be valuable. For example, medical personnel may desire to determine ICP at the point of medical care, at the point of injury, or during transportation in a medical vehicle in order to accurately determine the appropriate treatment location. As another example, medical personnel may desire to identify elevated ICP in a large number of casualties at the site of a mass casualty event in order to triage the victims.

[0028] Some embodiments of the present disclosure provide an improved ultrasound imaging system that improves the accuracy, efficiency, speed, and reliability of ultrasound data acquisition and optic nerve sheath measurement, provides improvements in the technical field of ultrasound imaging, and provides improvements in patient safety and treatment. For example, some embodiments of the present disclosure provide an ultrasound imaging system that can acquire 3D ultrasound data of the optic nerve sheath and use the 3D ultrasound data to determine the measurement results of the optic nerve sheath. In addition, some embodiments of the present disclosure provide an ultrasound imaging system that can use an artificial intelligence (AI) model for scanning guidance, segmentation, measurement, and / or diagnosis. In this way, some embodiments of the present disclosure provide an ultrasound imaging system that improves the speed and efficiency of acquiring accurate ultrasound data reflecting the true anatomical structure of the optic nerve sheath, reduces the sensitivity of the alignment of the ultrasound probe relative to the optic nerve sheath, reduces the need for skilled operators of the ultrasound probe, improves the accuracy of optic nerve sheath measurement, and allows optic nerve sheath measurement in various time-limited and resource-limited environments.

[0029] Figure 1 is a diagram of an ultrasound imaging system 100 according to one embodiment. Figure 1 As shown, the ultrasound imaging system 100 may include an ultrasound probe 102, a transmit beamformer 104, a transmitter 106, an element 108, a receiver 110, a receive beamformer 112, a user input device 114, a processor 116, a display 118, a memory 120, a scan guidance AI model inference 122, a segmentation AI model inference 124, a measurement AI model inference 126, a diagnosis AI model inference 128, a communication interface 130, a server 132, and a network 134. The aforementioned devices may be connected via a wired or wireless connection.

[0030] The ultrasound probe 102 may be configured to acquire 3D ultrasound data. For example, the ultrasound probe 102 may be a linear probe, a phased array probe, a curved linear probe coupled to a position 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, a thin wearable patch version of any of the foregoing probes, and the like. According to one embodiment, the ultrasound probe 102 may be configured to transmit an ultrasound signal suitable for ophthalmic imaging. The ultrasound probe 102 may be configured to generate an ultrasound signal, transmit the ultrasound signal toward a target location of the subject, receive an echo ultrasound signal backscattered from the target location of the subject, generate 3D ultrasound data based on the echo ultrasound signal, and output the 3D ultrasound data. The target location may be an optic nerve sheath, an optic nerve, a retina, and the like. The subject may be a human, an animal, a phantom, and the like.

[0031] The transmit beamformer 104 may be configured to apply a delay time to an electrical signal provided to the element 108 to focus the corresponding ultrasonic signal at the target location. The transmitter 106 may be configured to transmit an electrical signal to the element 108 to drive the element 108 to transmit the ultrasonic signal toward the target location. The element 108 may be configured to receive the electrical signal from the transmitter 106, convert the electrical signal into an ultrasonic signal, and transmit the ultrasonic signal toward the target location. The element 108 may be configured to receive an echo ultrasonic signal backscattered by the target location, convert the echo ultrasonic signal into an electrical signal, and provide the electrical signal to the receiver 110. The receiver 110 may be configured to receive the electrical signal from the element 108 and provide the electrical signal to the receive beamformer 112. The receive beamformer 112 may apply a delay time to the electrical signal received from the element 108.

[0032] The user input device 114 may be configured to receive user input and provide the user input to the processor 116. For example, the user input device 114 may be a touch screen display, a keyboard, a keypad, a mouse, a button, a switch, a microphone, etc. Additionally or alternatively, the user input device 114 may be configured to sense information. For example, the user input device 114 may sense information from an electromagnetic positioning system, an inertial measurement system, an accelerometer, a gyroscope, an actuator, etc.

[0033] The processor 116 may be configured to perform operations as described herein. For example, the processor 116 may be a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), a microprocessor, a microcontroller, a digital signal processor (DSP), a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), etc. The processor 116 may be implemented in hardware, firmware, or a combination of hardware and software. The processor 116 may include one or more processors 116 configured to perform the operations described herein. For example, a single processor 116 may be configured to perform all operations described herein. Alternatively, a plurality of processors 116 may be collectively configured to perform all operations described herein, and each of the plurality of processors 116 may be configured to perform a subset of the operations described herein. For example, a first processor 116 may perform a first subset of the operations described herein, a second processor 116 may be configured to perform a second subset of the operations described herein, and so on.

[0034] The processor 116 may be configured to control the ultrasound probe 102 to acquire 3D ultrasound data. The processor 116 may be configured to control which elements of the elements 108 are active and to control the shape of the beam emitted from the ultrasound probe 102. The processor 116 may generate an ultrasound image for display. For example, the processor 116 may generate a B-mode image, a color Doppler image, an M-mode image, a color M-mode image, etc.

[0035] The display 118 may be configured to display information. For example, the display 118 may be a monitor, a light emitting diode (LED) display, a cathode ray tube, a projector display, a touch screen, a tablet computer, a mobile phone, etc. The display 118 may display an ultrasound image based on 3D ultrasound data in real time. For example, the display 118 may display an ultrasound image within one second, two seconds, five seconds, etc. of the 3D ultrasound data acquired by the ultrasound probe 102.

[0036] The memory 120 may be configured to store information and / or instructions for use by the processor 116. The memory 120 may be a non-transitory computer-readable medium. For example, the memory 120 may be a random access memory (RAM), a read-only memory (ROM), a flash memory, a magnetic memory, an optical memory, etc. The memory 120 may be configured to store instructions that, when executed by the processor 116, cause the processor 116 to perform the operations described herein.

[0037] The memory 120 may store one or more AI model inferences. For example, the memory 120 may store a scan guidance AI model inference 122 that may be configured to determine a scan quality metric, a segmentation AI model 124 that may be configured to segment the optic nerve sheath three-dimensionally based on 3D ultrasound data, a measurement AI model inference 126 that may be configured to determine measurements of the optic nerve sheath, and / or a diagnosis AI model inference 128 that may be configured to determine a diagnosis of the subject based on measurements of the subject's optic nerve sheath.

[0038] The communication interface 130 may be configured to enable the processor 116 to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of a wired connection and a wireless connection. For example, the communication interface 130 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 wireless fidelity (Wi-Fi) interface, a cellular network interface, etc.

[0039] The server 132 may be configured to provide information to the processor 116 and / or the memory 120 via the communication interface 130. For example, the server 132 may be a server, a cloud server, a virtual machine, etc.

[0040] The network 134 may be a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a cellular network, a private network, an ad hoc network, an intranet, the Internet, a fiber-based network, etc., and / or combinations of these or other types of networks.

[0041] Figure 1 The number and arrangement of devices of the ultrasound imaging system 100 shown are provided as examples. In implementation, the ultrasound imaging system 100 may include additional devices, fewer devices, different devices, or different Figure 1 Additionally or alternatively, one or more devices (eg, one or more devices) of the ultrasound imaging system 100 may perform one or more functions described as being performed by another set of devices of the ultrasound imaging system 100 .

[0042] Figure 2 is a flow chart of an exemplary process 200 for determining optic nerve sheath measurements according to one embodiment. The ultrasound imaging system 100 may be configured to perform the operations of the process 200 .

[0043] like Figure 2 As shown, process 200 may include controlling an ultrasound probe to acquire three-dimensional (3D) ultrasound data of an optic nerve sheath (operation 210). The 3D ultrasound data may correspond to the ocular anatomical structure of the subject. That is, the 3D ultrasound data may include the optic nerve, the optic nerve sheath, the lens, the iris, the cornea, the retina, the macula, the optic disc, the vitreous body, the choroid, etc. The processor 116 may generate an ultrasound image based on the 3D ultrasound data. The ultrasound image may be a 3D image, a 2D image, a single plane image, a dual plane image, a triplane image, a multiplane image, etc. The ultrasound image may correspond to various anatomical planes (e.g., sagittal, coronal, and transverse) of the ocular anatomical structure. In addition, the ultrasound image may correspond to a long axis plane of the ocular anatomical structure or a short axis plane of the ocular anatomical structure. The long axis plane of the ocular anatomical structure may be a plane in which the optic nerve sheath is substantially tubular. The short axis plane of the ocular anatomical structure may be a plane in which the optic nerve sheath is substantially circular or substantially elliptical.

[0044] According to one embodiment, and in order to assist the operator of the ultrasound probe 102 in acquiring 3D ultrasound data, the processor 116 may control the display 118 to display a preview ultrasound image in real time. Figure 3 FIG. 300 is a diagram showing a preview ultrasound image in real time according to one embodiment. Figure 3As shown, the acquired 3D ultrasound data can be represented as a volume 310. The processor 116 can generate various preview ultrasound images corresponding to various planes of the ocular anatomical structure based on the 3D ultrasound data. For example, as shown, the preview ultrasound image 320 can correspond to the transverse plane and the long axis plane of the ocular anatomical structure. The processor 116 can control the display 118 to display the biplane preview ultrasound image 330 and the preview ultrasound image 340 corresponding to various anatomical planes of the ocular anatomical structure and the long axis plane and the short axis plane of the ocular anatomical structure in real time. For example, the processor 116 can control the display 118 to display the preview ultrasound image, such as a single plane image, a biplane image, a three-plane image, a multi-plane image, a curved surface image, a 3D rendering, etc. in real time.

[0045] According to another embodiment, and also to assist the operator of the ultrasound probe 102 in acquiring 3D ultrasound data, the processor 116 can generate scan guidance information and control the display 118 to display the scan guidance information to assist or guide the operator in positioning the ultrasound probe 102 to acquire 3D ultrasound data for determining the measurement results of the optic nerve sheath.

[0046] Figure 4 is a flow chart of an exemplary process 400 for generating scan guidance information according to one embodiment. The ultrasound imaging system 100 may be configured to perform the operations of the process 400 .

[0047] like Figure 4 As shown, the process 400 may include controlling the ultrasound probe to acquire positioning ultrasound data (operation 410). The positioning ultrasound data may be ultrasound data used by the processor 116 to generate scanning guidance information. According to one embodiment, the processor 116 may control the display 118 to display an ultrasound image corresponding to the positioning ultrasound data in real time. According to another embodiment, the processor 116 may prohibit controlling the display 118 to display an ultrasound image corresponding to the positioning ultrasound data. For example, the processor 116 may generate scanning guidance information using the positioning ultrasound data, and the processor 116 may control the display 118 to scan the guidance information, and may not control the display 118 to display an ultrasound image corresponding to the positioning ultrasound data.

[0048] like Figure 4 As further shown, process 400 may include determining a scan quality metric based on the localized ultrasound data (operation 420). The scan quality metric may indicate the quality of the 3D ultrasound data used to determine the optic nerve sheath measurement. For example, 3D ultrasound data with a low scan quality metric may result in an inaccurate or less accurate optic nerve sheath measurement, while 3D ultrasound data with a high scan quality metric may result in an accurate or more accurate optic nerve sheath measurement.

[0049] According to one embodiment, the processor 116 may determine a scan quality metric based on one or more image quality attributes of the localized ultrasound data. The image quality attributes may be spatial resolution, contrast resolution, probe motion parameters, noise parameters, artifact parameters, etc. According to another embodiment, the processor 116 may determine a scan quality metric based on the degree of alignment between the anatomical structure of the eye anatomical structure of the subject and the alignment reference. The anatomical structure may be the centerline of the optic nerve, the optic nerve, the optic nerve sheath, a landmark of the retina, etc. The alignment reference may be the focus of the ultrasound beam, the centerline of the acquisition volume for 3D ultrasound data, etc. According to another embodiment, the processor 116 may determine a scan quality metric based on the scan guidance AI model inference 122. For example, the processor 116 may input the localized ultrasound data into the scan guidance AI model inference 122, and determine the scan quality metric based on the output of the scan guidance AI model inference 122.

[0050] like Figure 4 As further shown, process 400 may include generating scan guidance information based on the scan quality metric (operation 430), and controlling a display to display the scan guidance information (operation 440). The scan guidance information may be information that assists an operator in positioning the ultrasound probe 102 relative to the subject. For example, the scan guidance information may indicate whether the position of the ultrasound probe 102 is appropriate or optimal for acquiring 3D ultrasound data for determining measurements of the optic nerve sheath. An operator of the ultrasound probe 102 may use the scan guidance information to position the ultrasound probe 102 relative to the subject. For example, if the scan guidance information indicates that an improved or optimal position of the ultrasound probe 102 can be achieved by moving the ultrasound probe 102 from the current position, the operator may reposition the ultrasound probe 102 from the current position toward the improved or optimal position.

[0051] According to one embodiment, the scan guidance information may include an ultrasound image. Figure 5 is a diagram of a display 500 of scanning guidance information according to one embodiment. Figure 5 As shown, the scan guidance information may include a diagram 518 indicating where to position the ultrasound probe 102 on the subject for the current examination. Figure 5 As shown, the scan guidance information may include ultrasound image 502. In addition, the scan guidance information may include identification of anatomical structures. Figure 5 As shown, the scan guidance information may include an identification 504 of the lens, an identification 506 of the optic nerve, and an identification 508 of the retina. Additionally or alternatively, the scan guidance information may include an indication of a measurement location at which the processor 116 is configured to use the 3D ultrasound data to determine a measurement result of the optic nerve sheath. For example, Figure 5As shown, the scan guidance information may include an indicator 510 of a measurement location at which the processor 116 is configured to use the 3D ultrasound data to determine the measurement result of the optic nerve sheath. Additionally or alternatively, the scan guidance information may include an indicator of an anatomical structure. For example, Figure 5 As shown, the scanning guidance information may include an indicator mark 512 of the center line of the optic nerve. Additionally or alternatively, the scanning guidance information may include an indicator mark of an alignment reference object. For example, Figure 5 As shown, the scan guidance information may include an indicator 514 for a centerline of an acquisition volume of the 3D ultrasound data 502 .

[0052] According to one embodiment, the scanning guidance information may be a preview ultrasound image. For example, the processor 116 may generate a preview ultrasound image based on the positioning ultrasound data, and control the display 118 to display the preview ultrasound image in real time. The preview ultrasound image may be a single-plane image, a dual-plane image, a tri-plane image, a multi-plane image, a curved surface image, a 3D rendering, etc.

[0053] According to one embodiment, the scanning guidance information may be an indicator of image quality. For example, the indicator may be a discrete value of image quality (e.g., 90%, 50%, 7, 10, etc.), an indication of image quality (e.g., a variable number of bars, variable brightness, variable state, etc.), etc. For example, and as Figure 5 As shown, the scanning guidance information may include an indication mark 516 of image quality represented in the form of a bar.

[0054] According to one embodiment, the scanning guidance information may be an indicator of the alignment level between the anatomical structure and the alignment reference. For example, the indicator may be a discrete value of the alignment level (e.g., 90%, 50%, 7, 10, etc.), a representation of the alignment level (e.g., a variable number of bars, variable brightness, variable state, etc.), etc. For example, and as Figure 5 As shown, the scan guide information may include an indication 518 of the alignment level as a representation in the form of a bar.

[0055] According to one embodiment, the scanning guidance information may be an indicator of the direction in which the ultrasound probe 102 is moved to obtain improved or optimal 3D ultrasound data in order to determine the measurement result of the optic nerve sheath. For example, the indicator may indicate whether to move the ultrasound probe 102 vertically, horizontally, tilt the ultrasound probe 102, rotate the ultrasound probe 102, etc. For example, and as Figure 5 As shown, the scan guidance information may include an indicator 518 indicating that the ultrasound probe 102 should be moved horizontally toward the center of the subject in order to achieve a position that provides improved or optimal acquisition of 3D ultrasound data for determining measurements of the optic nerve sheath.

[0056] The processor 116 can control the display 118 to display the scanning guidance information, generate updated scanning guidance information based on the updated positioning ultrasound data when the operator moves the ultrasound probe 102 based on the scanning guidance information to acquire updated positioning ultrasound data, and control the display 118 to display the updated scanning guidance information. In this way, the operator of the ultrasound probe 102 can detect whether the position of the ultrasound probe 102 is suitable for acquiring 3D ultrasound data in order to determine the measurement results of the optic nerve sheath, and can move the ultrasound probe 102 to an improved or optimal position based on the scanning guidance information indicating the existence of an improved or optimal position. Although Figure 4 Exemplary operations of process 400 are shown, but in some embodiments, process 400 may include additional operations, fewer operations, different operations, or different operations. Figure 4 Those operations depicted are operations of different arrangements. Additionally or alternatively, two or more of the operations of process 400 may be performed in parallel.

[0057] See also Figure 2 , and according to one embodiment, the processor 116 can control the ultrasound probe 102 to acquire 3D ultrasound data for determining the measurement results of the optic nerve sheath based on the user input. For example, an operator of the ultrasound probe 102 can interact with the user input device 114 to provide the user input to the processor 116, and the processor 116 can control the ultrasound probe 102 to acquire 3D ultrasound data based on the user input.

[0058] According to another embodiment, the processor 116 can control the ultrasound probe 102 to automatically acquire 3D ultrasound data for determining the measurement results of the optic nerve sheath. For example, the processor 116 can control the ultrasound probe 102 to automatically acquire 3D ultrasound data without receiving user input to acquire 3D ultrasound data.

[0059] Figure 6 is a flow chart of an exemplary process 600 for controlling an ultrasound probe to automatically acquire 3D ultrasound data based on a scan quality metric according to one embodiment. The ultrasound imaging system 100 may be configured to perform the operations of the process 600 .

[0060] like Figure 6 As shown, the process 600 may include controlling the ultrasound probe to acquire positioning ultrasound data (operation 610), and determining a scan quality metric based on the positioning ultrasound data (operation 620). For example, the processor 116 may control the ultrasound probe 102 to combine with the above Figure 4 The positioning ultrasound data is acquired in a manner similar to the manner described in operation 410 and may be combined with the above Figure 4The scan quality metric is determined based on the localized ultrasound data in a manner similar to that described in operation 420 .

[0061] like Figure 6 As further shown, process 600 may include determining whether the scan quality metric satisfies a threshold value (operation 630). The threshold value may indicate a scan quality metric resulting in 3D ultrasound data that is suitable for providing accurate or optimal measurements of the optic nerve sheath. Processor 116 may compare the scan quality metric to the threshold value and determine whether the scan quality metric satisfies the threshold value based on the scan quality metric being greater than or equal to the threshold value.

[0062] like Figure 6 As further shown, if the scan quality metric does not meet the threshold (operation 630-No), process 600 may return to operation 610. Figure 6 As further shown, if the scan quality metric satisfies the threshold value (operation 630-yes), the process 600 may include controlling the ultrasound probe to automatically acquire 3D ultrasound data (operation 640). For example, the processor 116 may control the ultrasound probe 102 to automatically acquire 3D ultrasound data for determining the measurement result of the optic nerve sheath based on the scan quality metric satisfying the threshold value.

[0063] like Figure 6 As further shown, the process 600 may include controlling the display to display information instructing the operator to maintain the position of the ultrasound probe (operation 650). For example, the processor 116 may control the display 118 to display information instructing the operator to maintain the position of the ultrasound probe 102 while the ultrasound probe 102 acquires 3D ultrasound data. For example, the information may instruct the operator to keep the ultrasound probe 102 still.

[0064] although Figure 6 Exemplary operations of process 600 are shown, but in some embodiments, process 600 may include additional operations, fewer operations, different operations, or operations that are different from those of process 600. Figure 6 Those operations depicted are operations of a different arrangement. Additionally or alternatively, two or more of the operations of process 600 may be performed in parallel.

[0065] refer to Figure 2 , the ultrasound probe 102 may acquire 3D ultrasound data. For example, an operator of the ultrasound probe 102 may position the ultrasound probe 102 relative to the subject, and the processor 116 may control the ultrasound probe 102 to acquire 3D ultrasound data based on user input or automatically.

[0066] like Figure 2As further shown, process 200 may include determining a measurement of the optic nerve sheath based on the 3D ultrasound data (operation 220). The measurement may be a diameter of the optic nerve sheath, a radius of the optic nerve sheath, a cross-sectional area of ​​the optic nerve sheath, a volume of a longitudinal segment of the optic nerve sheath, etc. The measurement of the optic nerve sheath may correspond to an outer boundary of the optic nerve sheath. Alternatively, the measurement of the optic nerve sheath may correspond to an inner boundary. Alternatively, the measurement may correspond to a center of the optic nerve sheath.

[0067] Figure 7 is a flow chart of an exemplary process 700 for determining measurements of the optic nerve sheath based on 3D ultrasound data, according to one embodiment. The ultrasound imaging system 100 may be configured to perform the operations of the process 700 .

[0068] like Figure 7 As shown, process 700 may include determining a 3D path of the optic nerve based on the 3D ultrasound data (operation 710). The 3D path of the optic nerve may identify the position and curvature of the optic nerve. Processor 116 may determine the 3D path of the optic nerve using image analysis techniques associated with the 3D ultrasound data.

[0069] According to one embodiment, the processor 116 may determine the centerline of the optic nerve based on the 3D path of the optic nerve. The processor 116 may determine the centerline using image analysis techniques associated with 3D ultrasound data. According to one embodiment, the processor 116 may control the ultrasound probe 102 to acquire 3D B-mode ultrasound data, and determine the centerline of the optic nerve based on the 3D B-mode ultrasound data. According to one embodiment, the processor 116 may control the ultrasound probe 102 to acquire 3D color flow Doppler ultrasound data, and determine the centerline of the optic nerve based on the 3D color flow Doppler ultrasound data. Techniques for determining the 3D path of the optic nerve may include region growing segmentation, eigenanalysis for identifying tubular structures, and the like.

[0070] like Figure 7 As further shown, process 700 may include determining a measurement position along the 3D path (operation 720). The measurement position may be a position along the 3D path of the optic nerve at which the processor 116 is configured to determine the measurement result of the optic nerve sheath. The measurement position may be a position located at a predetermined distance from the anatomical structure. For example, the measurement position may be 3 millimeters (mm) from the retina, 4 mm from the retina, 5 mm from the retina, etc. The measurement position may be predetermined based on clinical guidelines, may be input by an operator, may be selected at will, etc. The processor 116 may determine the measurement position based on determining the position of the anatomical structure and based on determining the position along the 3D path at a predetermined distance from the anatomical structure. For example, the processor 116 may determine the measurement position as a position located at a predetermined distance from the anatomical structure along the 3D path.

[0071] like Figure 7 As further shown, process 700 may include segmenting the optic nerve sheath of the optic nerve three-dimensionally based on the 3D ultrasound data (operation 730). For example, processor 116 may obtain a three-dimensionally segmented optic nerve sheath based on segmenting the optic nerve sheath three-dimensionally. Processor 116 may segment a portion of the optic nerve sheath three-dimensionally. For example, processor 116 may segment the outer boundary of the optic nerve sheath three-dimensionally. Additionally or alternatively, processor 116 may segment the inner boundary of the optic nerve sheath three-dimensionally. Additionally or alternatively, processor 116 may segment any other portion of the optic nerve sheath.

[0072] According to one embodiment, the processor 116 may use a segmentation technique associated with the 3D ultrasound data to segment the optic nerve sheath in three dimensions. The segmentation technique may include edge detection, region-based segmentation, clustering-based segmentation, surface models deformed to edges, neural network-based segmentation, etc. According to one embodiment, the processor 116 may generate a plurality of ultrasound images based on the 3D ultrasound data, and use the ultrasound images to segment the optic nerve sheath in three dimensions.

[0073] According to another embodiment, the processor 116 may segment the optic nerve sheath three-dimensionally using the segmentation AI model inference 124. For example, the processor 116 may input the 3D ultrasound data into the segmentation AI model inference 124, and obtain the three-dimensionally segmented optic nerve sheath based on the output of the segmentation AI model inference 124. In this case, the segmentation AI model inference 124 may be configured to segment the optic nerve sheath three-dimensionally directly from the 3D ultrasound data.

[0074] According to another embodiment, the processor 116 can use a structural model to segment the optic nerve sheath in three dimensions. The structural model can be cylindrical, a curved cylinder with a smoothly varying radius, an elliptical cylinder, etc. The processor 116 can use image analysis techniques and a structural model to segment the optic nerve sheath in three dimensions. By using the structural model, the processor 116 can adjust or adjust the optic nerve sheath in the ultrasound image. For example, the processor 116 can generate an ultrasound image in which the optic nerve sheath appears to be substantially straight despite the physical optic nerve sheath being curved. The processor 116 can align each plane relative to the center of the optic nerve. That is, the intersection of the planes can be the center of the optic nerve. For another example, the processor 116 can control the display 118 to display a preview ultrasound image along the 3D path of the optic nerve. In this case, due to the curvature of the optic nerve, a single plane image may not display the entire optic nerve. In this way, by controlling the display 118 to display an ultrasound preview image corresponding to a curved plane, the processor 116 can facilitate the acquisition of a more accurate ultrasound image for determining the measurement results of the optic nerve sheath.

[0075] According to another embodiment, the processor 116 may use the 2D ultrasound image to segment the optic nerve sheath.For example, the processor 116 may generate a 2D ultrasound image based on the 3D ultrasound data, and use the 2D ultrasound image to segment the optic nerve sheath.

[0076] like Figure 7 As further shown, process 700 may include determining a measurement plane based on the 3D ultrasound data (operation 740). The measurement plane may be a plane of the 3D ultrasound data, wherein processor 116 is configured to determine the measurement results of the optic nerve sheath. For example, the measurement plane may be an anatomical plane of the eye anatomy, and may be a long axis plane of the eye anatomy or a short axis plane of the eye anatomy.

[0077] The processor 116 may determine the measurement plane based on the 3D path of the optic nerve. For example, the processor 116 may determine the measurement plane based on the centerline of the optic nerve, the curvature of the optic nerve, etc. According to one embodiment, the processor 116 may determine a long axis measurement plane coplanar with the centerline of the optic nerve. Figure 8 is a diagram 800 of a long axis measurement plane according to one embodiment. Figure 8 As shown, the processor 116 can determine a first measurement plane 810, a second measurement plane 820, and a third measurement plane 830 that are each coplanar with the centerline 840 of the optic nerve. In this way, the processor 116 can determine a more accurate measurement result of the optic nerve sheath because the measurement plane is provided at the centerline of the optic nerve. According to another embodiment, the processor 116 can determine a short axis measurement plane orthogonal to the centerline of the optic nerve. In addition, the processor 116 can determine the short axis measurement plane located at the measurement position. That is, the measurement plane can be located at a predetermined distance from the anatomical structure. Fig. 9 FIG. 900 is a diagram of a short axis measurement plane according to one embodiment. Fig. 9 As shown, the processor 116 can determine a measurement plane 910 that is orthogonal to the centerline 920 of the optic nerve. In this manner, the processor 116 can determine a more accurate measurement of the optic nerve sheath because the measurement plane is provided orthogonal to the optic nerve sheath.

[0078] like Figure 7 As further shown, process 700 may include determining a measurement result of the optic nerve sheath at a measurement position in the measurement plane based on the three-dimensional segmentation of the optic nerve sheath (operation 750). For example, processor 116 may determine a measurement result of the optic nerve sheath at a measurement position in the measurement plane based on the three-dimensional segmented optic nerve sheath.

[0079] According to one embodiment, the processor 116 may determine measurements of the optic nerve sheath in the long axis plane. For example, the processor 116 may determine measurements of the optic nerve sheath orthogonal to the centerline of the optic nerve at a measurement location in the long axis plane. The processor 116 may determine a distance between two portions of the optic nerve sheath and determine a diameter, radius, area, volume, etc. of the optic nerve sheath based on the distance. Fig.10 FIG1000 is a graph of measurements of the optic nerve sheath according to one embodiment. Fig.10 As shown, the processor 116 can determine the diameter of the optic nerve sheath in the long axis plane 1010 by measuring the distance 1020 between the outer boundaries of the optic nerve sheath.

[0080] According to another embodiment, the processor 116 can determine the measurements of the optic nerve sheath in the short axis plane. For example, the processor 116 can determine the measurements of the optic nerve sheath in the short axis plane that is orthogonal to the centerline of the optic nerve. In this case, the short axis plane can correspond to the measurement location. The processor 116 can determine the distance between two parts of the optic nerve sheath, and based on the distance, determine the diameter, radius, area, volume, etc. of the optic nerve sheath. Additionally or alternatively, the processor 116 can use a structural model (e.g., a circle, an ellipse, etc.) to determine the measurements of the optic nerve sheath. For example, the processor 116 can fit a structural model to correspond to the optic nerve sheath, and determine the measurements of the optic nerve sheath based on the measurements of the structural model. Fig.10 As shown, the processor 116 can determine the area of ​​the optic nerve sheath in the short axis plane 1030 by fitting a geometric model 1040 to the optic nerve sheath. Figure 7 Exemplary operations of process 700 are shown, but in some embodiments, process 700 may include additional operations, fewer operations, different operations, or operations that are different from those of process 700. Figure 7 Those operations depicted are operations of different arrangements. Additionally or alternatively, two or more of the operations of process 700 may be performed in parallel.

[0081] Fig.11 is a flow chart of an exemplary process 1100 for determining measurements of an optic nerve sheath based on 3D ultrasound data, according to one embodiment. The ultrasound imaging system 100 may be configured to perform the operations of the process 1100 . FIG. 12A to FIG. 12C is a diagram 1100 of an ultrasound image used to determine measurements of the optic nerve sheath based on 3D ultrasound data, according to one embodiment.

[0082] like Fig.11 As shown, process 1100 may include determining the location of a hypoechoic sphere based on 3D ultrasound data (operation 1110). Fig. 12AAs shown, the processor 116 may determine the position of a hypoechoic sphere 1202 in a transverse plane 1204 of the ultrasound data and determine the position of a hypoechoic sphere 1206 in a sagittal plane 1208 of the 3D ultrasound data. The hypoechoic sphere 1202 may correspond to the vitreous body of the ocular anatomy.

[0083] like Fig.11 As further shown, process 1100 may include segmenting the retinal border at the posterior portion of the hypoechoic sphere (operation 1120). Fig. 12A As shown, the processor 116 may segment the retinal boundary 1210 at the posterior portion of the hypoechoic sphere 1202 , and may segment the retinal boundary 1212 at the posterior portion of the hypoechoic sphere 1206 .

[0084] like Fig.11 As further shown, process 1100 may include determining a 3D path of the optic nerve based on the 3D ultrasound data (operation 1130). Fig. 12B As shown, processor 116 may determine a 3D path 1214 of the optic nerve based on the ultrasound data, and may determine a 3D path 1216 of the optic nerve based on the ultrasound data.

[0085] like Fig.11 As further shown, process 1100 may include determining a location of an anatomical landmark corresponding to an intersection between the 3D path of the optic nerve and a boundary of the retina (operation 1140). Fig. 12B As shown, processor 116 can determine the position of anatomical landmark 1218 corresponding to the intersection between 3D path 1214 of the optic nerve and retinal boundary 1210, and can determine the position of anatomical landmark 1220 corresponding to the intersection between 3D path 1216 of the optic nerve and retinal boundary 1212.

[0086] like Fig.11 As further shown, process 1100 may include segmenting the optic nerve sheath in three dimensions based on the 3D ultrasound data (operation 1150). Fig. 12C As shown, the processor 116 may three-dimensionally segment the optic nerve sheath based on the 3D ultrasound data to obtain a three-dimensionally segmented optic nerve sheath 1222 and a three-dimensionally segmented optic nerve sheath 1224 .

[0087] like Fig.11 As further shown, process 1100 may include determining a measurement location along the 3D path that is a predetermined distance from an anatomical landmark (operation 1160). Fig. 12CAs shown, processor 116 may determine a measurement location 1226 along 3D path 1214 that is a predetermined distance from anatomical landmark 1218 , and may determine a measurement location 1228 along 3D path 1216 that is a predetermined distance from anatomical landmark 1220 .

[0088] like Fig.11 As further shown, process 1100 may include determining a measurement plane based on the 3D ultrasound data (operation 1170). Fig. 12C As shown, the processor 116 can determine a measurement plane 1230 corresponding to the transverse plane 1204 and can determine a measurement plane 1232 corresponding to the sagittal plane 1208 based on the ultrasound data.

[0089] like Fig.11 As further shown, process 1100 may include determining a measurement result of the optic nerve sheath at a measurement location in a measurement plane based on segmenting the optic nerve sheath in three dimensions (operation 1180). Fig. 12C As shown, the processor 116 can determine a measurement result 1234 of the optic nerve sheath at a measurement position 1226 in a measurement plane 1230 based on the three-dimensionally segmented optic nerve sheath 1222, and can determine a measurement result 1236 of the optic nerve sheath at a measurement position 1228 in the measurement plane 1232 based on the three-dimensionally segmented optic nerve sheath 1224.

[0090] although Fig.11 Exemplary operations of process 1100 are shown, but in some embodiments, process 1100 may include additional operations, fewer operations, different operations, or operations that are different from those of process 1100. Fig.11 Those operations depicted are operations of different arrangements. Additionally or alternatively, two or more of the operations of process 1100 may be performed in parallel.

[0091] Fig.13 is a flow chart of an exemplary process 1300 for determining measurements of an optic nerve sheath based on 3D ultrasound data, according to one embodiment. The ultrasound imaging system 100 may be configured to perform the operations of the process 1300 . Fig.14A and Fig. 14B is a diagram 1400 of an ultrasound image used to determine measurements of the optic nerve sheath based on 3D ultrasound data, according to one embodiment.

[0092] like Fig.13 As shown, process 1300 may include determining a plurality of measurement planes based on the 3D ultrasound data (operation 1310). For example, processor 116 may be combined with the above Figure 7 The plurality of measurement planes are determined in a manner similar to that described in operation 740. Fig.14AAs shown, the processor 116 may determine a measurement plane 802, a measurement plane 804, and a measurement plane 806, each corresponding to a long axis plane of the 3D ultrasound data. Fig. 14B As shown, the processor 116 may determine a measurement plane 808 corresponding to a short-axis plane of the 3D ultrasound data.

[0093] like Fig.13 As further shown, process 1300 may include determining a plurality of measurements of the optic nerve sheath based on the plurality of measurement planes (operation 1320). Figure 7 Determine multiple measurements of the optic nerve sheath in a manner similar to that described in operation 750. Fig.14A As shown, processor 116 may determine measurement results 810 in measurement plane 802, measurement results 812 in measurement plane 804, and measurement results 814 in measurement plane 806. Fig. 14B As shown, processor 116 may determine measurement 816 , measurement 818 , and measurement 820 in measurement plane 808 .

[0094] like Fig.13 As further shown, process 1300 may include determining a measurement result of the optic nerve sheath based on the plurality of measurement results (operation 1330). The measurement result may be an average measurement result of the plurality of measurement results, a measurement result with a maximum value, a measurement result with a minimum value, a measurement result with an intermediate value, etc.

[0095] According to one embodiment, the processor 116 may apply a corresponding weight value to each of the plurality of measurements and determine the measurement of the optic nerve sheath based on applying the corresponding weight value. The processor 116 may determine the weight value for the measurement based on a scan quality metric of the underlying 3D ultrasound data used to determine the measurement. Additionally or alternatively, the processor 116 may determine the weight value based on the quality of the three-dimensionally segmented optic nerve sheath. Additionally or alternatively, the processor 116 may determine the weight value based on a predetermined weight value to apply to various corresponding measurement planes.

[0096] According to one embodiment, the processor 116 may determine the measurement result based on multiple measurement results of multiple measurement planes corresponding to the same axis view of the optic nerve sheath. For example, the processor 116 may determine the measurement result based on multiple measurement results in multiple measurement planes corresponding to the long axis view of the optic nerve sheath. For another example, the processor 116 may determine the measurement result based on multiple measurement results in multiple measurement planes corresponding to the short axis view of the optic nerve sheath. According to another embodiment, the processor 116 may determine the measurement result based on multiple measurement results of multiple measurement planes corresponding to different axis views of the optic nerve sheath. For example, the processor 116 may determine the measurement result based on the measurement results in the measurement plane corresponding to the long axis view of the optic nerve sheath and the measurement results in the measurement plane corresponding to the short axis view of the optic nerve sheath.

[0097] although Fig.13 Exemplary operations of process 1300 are shown, but in some embodiments, process 1300 may include additional operations, fewer operations, different operations, or operations that are different from those of process 1300. Fig.13 Those operations depicted are operations of different arrangements. Additionally or alternatively, two or more of the operations of process 1300 may be performed in parallel.

[0098] Fig.15 is a flow chart of an exemplary process 1500 for determining measurements of the optic nerve sheath based on 3D ultrasound data, according to one embodiment. The ultrasound imaging system 100 may be configured to perform the operations of the process 1500 .

[0099] like Fig.15 As shown, process 1500 may include inputting 3D ultrasound data into an AI model inference (operation 1510), and determining measurements of the optic nerve sheath based on the output of the AI ​​model inference (operation 1520). For example, the processor 116 may input the 3D ultrasound data into the measurement AI model inference 126, and determine measurements of the optic nerve sheath based on the output of the measurement AI model inference 126. The measurement AI model inference 126 may be configured to determine measurements of the optic nerve sheath directly from the 3D ultrasound data. That is, the measurement AI model inference 126 may be configured to determine measurements of the optic nerve sheath without performing any preliminary operations (such as segmentation). Although Fig.15 Exemplary operations of process 1500 are shown, but in some embodiments, process 1500 may include additional operations, fewer operations, different operations, or operations that are different from those of process 1500. Fig.15 Those operations depicted are operations of different arrangements. Additionally or alternatively, two or more of the operations of process 1500 may be performed in parallel.

[0100] like Figure 2As shown, process 200 may include controlling a display to display information related to the measurement results of the optic nerve sheath (operation 230). Fig.16 is a diagram 1600 of a display of information related to measurements of the optic nerve sheath, according to one embodiment.

[0101] According to one embodiment, the information related to the measurement result of the optic nerve sheath may be the measurement result of the optic nerve sheath. For example, the information related to the measurement result may be a specific value (e.g., an average value, a maximum value, etc.) of the measurement result of the optic nerve sheath, a plurality of values ​​for a plurality of measurement planes, etc. Fig.16 As shown, the display 118 may display measurement results 1610 of the optic nerve sheath.

[0102] According to another embodiment, the information related to the measurement result of the optic nerve sheath can be an ultrasound image associated with the measurement result. For example, the ultrasound image can correspond to the measurement plane in which the measurement result is determined. The processor 116 can perform image processing on the ultrasound image to enhance contrast, enhance resolution, reduce speckle, etc. The operator of the ultrasound imaging system 100 can provide user input for selecting a specific ultrasound image to be displayed via the user input device 114. Based on the user input, the processor 116 can control the display 118 to display a specific ultrasound image. According to one embodiment, the ultrasound image may include an indicator. For example, the indicator can be an indicator of an anatomical structure, an indicator of a measurement position, etc. Additionally or alternatively, the ultrasound image may include a three-dimensionally segmented optic nerve sheath. The operator of the ultrasound imaging system 100 can provide user input for modifying the segmentation of the optic nerve sheath via the user input device 114. For example, the user input can include a point in the specific ultrasound image corresponding to the correction of the optic nerve sheath segmentation at the position. Based on the user input, the processor 116 can determine the updated measurement result of the optic nerve sheath based on the modified segmentation, and control the display 118 to display the updated measurement result of the optic nerve sheath.

[0103] According to another embodiment, the information associated with the measurement of the optic nerve sheath can be an indicator of a change in the size of the optic nerve sheath from a previous measurement. For example, the indicator of the change in the size of the optic nerve sheath can be a specific value by which the size of the optic nerve sheath has changed (e.g., +0.5 millimeters (mm), -0.1 mm, etc.). Additionally or alternatively, the indicator of the change in the size of the optic nerve sheath can be an indicator that identifies whether the size has increased, decreased, or remained substantially constant. For example, if Fig.16As shown, the display 118 may display an indicator 1620 indicating that the size of the optic nerve sheath has increased. The processor 116 may determine the change in the size of the optic nerve sheath using a plurality of measurements of the optic nerve sheath. For example, the processor 116 may determine the change in the size of the optic nerve sheath by using a most recently determined measurement, by using a most recently determined measurement and a reference measurement, etc. The reference measurement may be a measurement of the optic nerve sheath of the subject in a normal state.

[0104] According to another embodiment, the information related to the measurement results of the optic nerve sheath can be a diagnosis of the subject. For example, the diagnosis can be a diagnosis of a primary injury to the subject, a diagnosis of a secondary injury to the subject, a diagnosis of an elevated ICP level, etc. The diagnosis can indicate the severity of the injury. For example, the diagnosis can indicate "normal", "severe", "mild", etc. For example, and as Fig.16 As shown, the display 118 may display a diagnosis 1630 indicating that the subject's injury is severe. According to one embodiment, the processor 116 may input the measurement results of the optic nerve sheath into the diagnostic AI model inference 128, and determine the diagnosis of the subject based on the output of the diagnostic AI model inference 128. According to another embodiment, the processor 116 may determine the diagnosis of the subject based on demographic information, vital signs, body posture, measurement results of the optic nerve sheath, and multiple thresholds. The thresholds may correspond to the level of change in the severity of the injury.

[0105] Fig.17 is a diagram of an exemplary process 1700 for training AI model inference according to one embodiment. The ultrasound imaging system 100 may be configured to perform the operations of process 1700 to train AI model inference. The AI ​​model inference may be scan guidance AI model inference 122, segmentation AI model inference 124, measurement AI model inference 126, and / or diagnosis AI model inference 128. According to one embodiment, the server 132 may train the AI ​​model inference and provide the trained AI model inference to the memory 120.

[0106] Training data 1710 may include one or more of level inputs 1720 and known results 1730 related to the AI ​​model inference to be trained. Level input 1720 may come from any applicable source, including text, images, data, values, comparisons, level outputs, etc. Known results 1730 may be included for AI model inferences generated based on supervised or semi-supervised training. Unsupervised AI models may be trained without using known results 1730. Known results 1730 may include known or expected outputs for future inputs of similar or the same category as level input 1720 that does not have a corresponding known output.

[0107] The training data 1710 and the training algorithm 1750 may be provided to a training component 1760, which may apply the training data 1710 to the training algorithm 1750 to generate an AI model inference. According to one embodiment, a comparison result 1740 may be provided to the training component 1760, which compares the previous output of the corresponding AI model inference to apply the previous result to retrain the AI ​​model inference. The comparison result 1740 may be used by the training component 1760 to update the corresponding AI model inference. The training algorithm 1750 may utilize an AI network and / or model, including but not limited to a deep learning network (e.g., a deep neural network (DNN), a convolutional neural network (CNN), a fully convolutional network (FCN), a recursive neural network (RCN), etc.), a probabilistic model (e.g., a Bayesian network, a graphical model, etc.), a classifier (e.g., K nearest neighbors, naive Bayes, etc.), a discriminative model (e.g., a decision forest, a maximum margin method, etc.), a model specifically discussed in the present disclosure, etc.

[0108] The AI ​​model inference used herein may be trained and / or used by adjusting one or more weights and / or one or more layers of the AI ​​model inference. For example, during training, a given weight may be adjusted (e.g., increased, decreased, removed, etc.) based on training data or input data. Similarly, layers may be updated, added, or removed based on training data and / or input data. The resulting output may be adjusted based on the adjusted weights and / or layers.

[0109] In accordance with the foregoing, some embodiments of the present disclosure provide an ultrasound imaging system 100 that improves the accuracy, efficiency, speed, and reliability of ultrasound data acquisition and optic nerve sheath measurement, and provides improvements in the technical field of ultrasound imaging. For example, some embodiments of the present disclosure provide an ultrasound imaging system 100 that can acquire 3D ultrasound data of the optic nerve sheath and use the 3D ultrasound data to determine the measurement results of the optic nerve sheath. In addition, some embodiments of the present disclosure provide an ultrasound imaging system 100 that can utilize scanning-guided AI model inference 122, segmentation AI model inference 124, measurement AI model inference 126, and / or diagnosis AI model inference 128. In this way, some embodiments of the present disclosure provide an ultrasound imaging system 100 that improves the speed and efficiency of acquiring accurate ultrasound data reflecting the true anatomical structure of the optic nerve sheath, reduces the sensitivity of the alignment of the ultrasound probe relative to the optic nerve sheath, reduces the need for skilled operators of the ultrasound probe, improves the accuracy of optic nerve sheath measurement, and allows optic nerve sheath measurement in a variety of time-limited and resource-limited environments.

[0110] The embodiments of the present disclosure shown in the drawings and described above are exemplary embodiments only 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. It is intended that any combination of non-mutually exclusive features described herein is within the scope of the invention. That is, the features of the embodiments may be combined with any appropriate aspect described above, and the optional features of any one aspect may be combined with any other appropriate aspect. Similarly, the features listed in the dependent claims may be combined with non-mutually exclusive features of other dependent claims, particularly where the dependent claims are dependent on the same independent claim. In some jurisdictions that require single claim dependencies, these dependencies may have been used as a practice, but this should not be taken to mean that the features in the dependent claims are mutually exclusive.

Claims

1. An ultrasound imaging system (100), comprising: Ultrasonic probe (102); Display (118); and One or more processors (116), the one or more processors configured to: controlling (210) the ultrasound probe (102) to acquire three-dimensional (3D) ultrasound data of the optic nerve sheath; determining (220) measurements of the optic nerve sheath based on the 3D ultrasound data; and The display (118) is controlled (230) to display information related to the measurement result of the optic nerve sheath.

2. The ultrasound imaging system (100) of claim 1, wherein the one or more processors (116) are further configured to: Controlling (410) the ultrasound probe (102) to acquire positioning ultrasound data; determining (420) a scan quality metric associated with the optic nerve sheath based on the localized ultrasound data; and The display (118) is controlled (440) to display scan guidance information that guides an operator of the ultrasound probe (102) to position the ultrasound probe (102) relative to the optic nerve sheath based on the scan quality metric.

3. The ultrasound imaging system (100) of claim 1, wherein the one or more processors (116) are further configured to: controlling (610) the ultrasound probe (102) to acquire positioning ultrasound data; and determining (620) a scan quality metric associated with the optic nerve sheath based on the localized ultrasound data, Wherein, when controlling (210) the ultrasound probe (102) to acquire the 3D ultrasound data of the optic nerve sheath, the processor (116) is configured to automatically control (640) the ultrasound probe (102) to acquire the 3D ultrasound data of the optic nerve sheath based on the scan quality metric.

4. The ultrasound imaging system (100) of claim 1, wherein the one or more processors (116) are further configured to: controlling (410) the ultrasound probe (102) to acquire positioning ultrasound data; and The display (118) is controlled (440) to display a preview ultrasound image in real time relative to the acquisition of the localized ultrasound data, wherein the preview ultrasound image is a bi-plane ultrasound image or a multi-plane ultrasound image.

5. The ultrasound imaging system (100) of claim 1, wherein the one or more processors (116) are further configured to: controlling (410) the ultrasound probe (102) to acquire positioning ultrasound data; and The display is controlled (440) to display a preview ultrasound image based on the localization ultrasound data, the preview ultrasound image being a curved surface image along the 3D path of the optic nerve.

6. The ultrasound imaging system (100) of claim 1, wherein the one or more processors (116) are further configured to: three-dimensionally segmenting (730) the optic nerve sheath based on the 3D ultrasound data; and The display (118) is controlled (230) to display the three-dimensionally segmented optic nerve sheath in the long-axis plane.

7. The ultrasound imaging system (100) of claim 1, wherein the one or more processors (116) are further configured to: three-dimensionally segmenting (730) the optic nerve sheath based on the 3D ultrasound data; and The display (118) is controlled (230) to display the three-dimensionally segmented optic nerve sheath in the short-axis plane.

8. The ultrasound imaging system (100) of claim 1, wherein the information related to the measurement results of the optic nerve sheath includes the measurement results of the optic nerve sheath.

9. The ultrasound imaging system (100) of claim 1, wherein the information related to the measurement results of the optic nerve sheath includes an indicator of changes in the size of the optic nerve sheath.

10. The ultrasound imaging system (100) of claim 1, wherein the information related to the measurements of the optic nerve sheath includes a diagnosis of a severity of damage associated with the optic nerve sheath.

11. A method (200), comprising: controlling (210) the ultrasound probe (102) to acquire three-dimensional (3D) ultrasound data of the optic nerve sheath; determining (220) measurements of the optic nerve sheath based on the 3D ultrasound data; and The display (118) is controlled (230) to display information related to the measurement results of the optic nerve sheath.

12. The method (200) of claim 11, further comprising: Controlling (410) the ultrasound probe (102) to acquire positioning ultrasound data; determining (420) a scan quality metric associated with the optic nerve sheath based on the localized ultrasound data; as well as The display (118) is controlled (440) to display scan guidance information that guides an operator of the ultrasound probe (102) to position the ultrasound probe (102) relative to the optic nerve sheath based on the scan quality metric.

13. The method (200) of claim 11, further comprising: Controlling (610) the ultrasound probe (102) to acquire positioning ultrasound data; as well as determining (620) a scan quality metric associated with the optic nerve sheath based on the localized ultrasound data, Wherein controlling (210) the ultrasound probe (102) to acquire the 3D ultrasound data of the optic nerve sheath includes automatically controlling (640) the ultrasound probe (102) to acquire the 3D ultrasound data of the optic nerve sheath based on the scan quality metric.

14. The method (200) of claim 11, further comprising: Controlling (410) the ultrasound probe (102) to acquire positioning ultrasound data; as well as The display (118) is controlled (440) to display a preview ultrasound image in real time relative to the acquisition of the localized ultrasound data, wherein the preview ultrasound image is a bi-plane ultrasound image or a multi-plane ultrasound image.

15. An ultrasound imaging system (100), comprising: a memory (120) configured to store instructions; and One or more processors (116) configured to execute the instructions to: controlling (210) the ultrasound probe (102) to acquire three-dimensional (3D) ultrasound data of the optic nerve sheath; determining (220) measurements of the optic nerve sheath based on the 3D ultrasound data; and The display (118) is controlled (230) to display information related to the measurement results of the optic nerve sheath.

Images