Ultrasound apparatus and ultrasound image processing method

Abstract

This application relates to the field of medical technology, and in particular to an ultrasound device and an ultrasound image processing method. The method includes: emitting ultrasound waves to a detection object and receiving ultrasound echoes returned by the detection object to generate ultrasound data; responding to a first operation by a user to adjust rendering parameters, obtaining adjusted rendering parameters, which are used to perform volume rendering of the contour of the detection object; the rendering parameters include position parameters of the center pixel of at least one contour to be rendered and contour thickness parameters; the position parameters of the center pixel are used to determine the contour to be rendered corresponding to the detection object, and the contour thickness parameters are used to adjust the display effect of the contour; based on the rendering parameters before and after adjustment, performing volume rendering on the ultrasound data to obtain contour image data corresponding to the detection object; and displaying the contour image of the detection object according to the contour image data of the detection object.

Description

Technical Field

[0001] This application relates to the field of medical technology, and in particular to an ultrasound device and an ultrasound image processing method. Background Technology

[0002] Because ultrasound 3D imaging technology can clearly describe the surface structure information of organs or tissues, it is usually used as an auxiliary tool in prenatal screening of fetuses to examine the intracranial and skull structure, limb skeletal development, gastrointestinal lesions, and whether the reproductive organs are developing normally.

[0003] However, when generating corresponding ultrasound images using ultrasound 3D imaging technology, image artifacts can occur during the 3D rendering process, resulting in low-quality ultrasound images. Consequently, staff may be unable to accurately identify any abnormalities in the fetus based on these low-quality ultrasound images.

[0004] In other words, how to remove image artifacts and improve image quality during the generation of ultrasound images is an urgent problem to be solved. Summary of the Invention

[0005] This application provides an ultrasound device and an ultrasound image processing method for removing image artifacts in ultrasound images and improving the quality of ultrasound images.

[0006] In a first aspect, embodiments of this application provide an ultrasound device, comprising an ultrasound probe, a user interface, a processor, and a display screen; the ultrasound probe is used to emit ultrasound waves toward a detection object and receive ultrasound echoes returned by the detection object, generating ultrasound data; the user interface is used to respond to a user's first operation of adjusting rendering parameters to obtain the adjusted rendering parameters, the rendering parameters being used to perform volume rendering of the contour of the detection object; the rendering parameters include position parameters of the center pixel of at least one contour to be rendered and contour thickness parameters; the position parameters of the center pixel are used to determine the contour to be rendered corresponding to the detection object, and the contour thickness parameters are used to adjust the display effect of the contour; the processor is used to perform volume rendering of the ultrasound data based on the rendering parameters before and after adjustment, respectively, to obtain contour image data corresponding to the detection object; the display screen is used to display the contour image of the detection object according to the contour image data of the detection object.

[0007] In one possible implementation, when the processor performs volume rendering on the ultrasound data based on the rendering parameters before and after adjustment to obtain contour image data corresponding to the detected object, it specifically performs the following steps: filtering the ultrasound data to obtain multiple frames of volume data to be rendered for the detected object; performing volume rendering on each frame of volume data to be rendered at the sampling position corresponding to the volume data to be rendered based on the rendering parameters before adjustment to obtain the rendering result of the volume data to be rendered; fusing the rendering results corresponding to each of the multiple frames of volume data to be rendered into first contour image data; and performing volume rendering on the multiple frames of volume data to be rendered based on the rendering parameters after adjustment to obtain second contour image data corresponding to each of the multiple frames of volume data to be rendered; the resolution of the second contour image data is lower than that of the first contour image data.

[0008] In one possible implementation, the processor is further configured to: generate noise texture data corresponding to each of the volume data to be rendered; superimpose each of the volume data to be rendered with the corresponding noise texture data to obtain sampling position offset information corresponding to each of the volume data to be rendered; and determine the sampling position corresponding to each of the volume data to be rendered based on the reference sampling position and the sampling position offset information corresponding to each of the volume data to be rendered.

[0009] In one possible implementation, the user interface is further configured to: respond to a second operation by the user to adjust the three-dimensional space transformation parameters, and obtain the adjusted three-dimensional space transformation parameters; when the processor performs volume rendering at the sampling position corresponding to the volume data to be rendered based on the rendering parameters before adjustment, and obtains the rendering result of the volume data to be rendered, specifically configured to: determine the spatial position of each voxel included in the volume data to be rendered based on the adjusted three-dimensional space transformation parameters and the sampling position corresponding to the volume data to be rendered; determine the at least one rendering contour corresponding to the detection object based on the spatial position of each voxel included in the volume data to be rendered, and the position parameters of the center pixel of each of the at least one rendering contour before adjustment; for each rendering contour, determine the opacity of each voxel in the target area surrounded by the rendering contour based on the pixel value of each voxel in the target area surrounded by the rendering contour and the contour thickness parameter before adjustment corresponding to the rendering contour; and determine the rendering result corresponding to the volume data to be rendered based on the opacity of each voxel in the target area.

[0010] In one possible implementation, when the processor performs volume rendering on multiple frames of volume data to be rendered based on the adjusted rendering parameters, it specifically performs the following operations for each frame of volume data to be rendered: determining the spatial position of each voxel included in the volume data to be rendered based on the adjusted 3D spatial transformation parameters; determining the at least one contour to be rendered corresponding to the detection object based on the spatial position of each voxel included in the volume data to be rendered and the adjusted position parameter of at least one center pixel; determining the opacity of each voxel in the target area surrounded by the contour to be rendered based on the pixel value of each voxel in the target area surrounded by the contour to be rendered and the adjusted contour thickness parameter corresponding to the contour to be rendered; and determining the second contour image data corresponding to the volume data to be rendered based on the opacity of each voxel in the target area.

[0011] In one possible implementation, the user interface is further configured to respond to a third operation by the user to adjust the filtering parameters, thereby obtaining the adjusted filtering parameters; the filtering parameters include a filter kernel size and a filter factor; when the processor performs filtering processing on the ultrasound data to obtain multi-frame renderable data of the detected object, it is specifically configured to: generate a filter kernel function based on the adjusted filter kernel size and the adjusted filter factor; and perform filtering processing on the ultrasound data based on the filter kernel function to obtain multi-frame renderable data of the detected object.

[0012] In one possible implementation, when the processor filters the ultrasound data to obtain multi-frame renderable data of the detected object, it specifically performs the following operations: For the ultrasound data, it repeatedly performs the following operations until the number of iterations reaches a preset iteration threshold to obtain multi-frame renderable data of the detected object: Based on the ultrasound data, it determines the first image features of each of the multiple local ultrasound data included in the ultrasound data; the first image features are used to characterize the detection position of the detected object corresponding to the local ultrasound data; for each local ultrasound data, it performs the following operations: comparing the feature value of the first image feature of the local ultrasound data with the feature threshold corresponding to the first image feature to determine the data type of the local ultrasound data; if the data type characterizes the local ultrasound data as boundary data, it performs enhancement processing on the local ultrasound data; if the data type characterizes the local ultrasound data as tissue data, it performs smoothing processing on the local ultrasound data.

[0013] In one possible implementation, when the processor filters the ultrasound data to obtain multi-frame renderable data of the detected object, it specifically performs the following: for each sliding window of ultrasound data, it determines a second image feature of the ultrasound data in the sliding window based on the mean and variance of the pixel values ​​included in the ultrasound data in the sliding window; and determines the multi-frame renderable data of the detected object based on the second image feature of the ultrasound data in each sliding window.

[0014] Secondly, embodiments of this application provide an ultrasonic image processing method applied to an ultrasonic device. The method includes: emitting ultrasonic waves to a detection object and receiving ultrasonic echoes returned by the detection object to generate ultrasonic data; responding to a first operation by a user to adjust rendering parameters, obtaining adjusted rendering parameters, the rendering parameters being used to perform volume rendering on the contour of the detection object; the rendering parameters including position parameters of the center pixel of at least one contour to be rendered and contour thickness parameters; the position parameters of the center pixel being used to determine the contour to be rendered corresponding to the detection object, and the contour thickness parameters being used to adjust the display effect of the contour; performing volume rendering on the ultrasonic data based on the rendering parameters before and after adjustment to obtain contour image data corresponding to the detection object; and displaying the contour image of the detection object according to the contour image data of the detection object.

[0015] In one possible implementation, the step of performing volume rendering on the ultrasound data based on the rendering parameters before and after adjustment to obtain contour image data corresponding to the detected object includes: filtering the ultrasound data to obtain multiple frames of volume data to be rendered for the detected object; performing volume rendering on each frame of volume data to be rendered at the sampling position corresponding to the volume data to be rendered based on the rendering parameters before adjustment to obtain the rendering result of the volume data to be rendered; fusing the rendering results corresponding to each of the multiple frames of volume data to be rendered into first contour image data; and performing volume rendering on the multiple frames of volume data to be rendered based on the rendering parameters after adjustment to obtain second contour image data corresponding to each of the multiple frames of volume data to be rendered; the resolution of the second contour image data is lower than that of the first contour image data.

[0016] In one possible implementation, the method further includes: generating noise texture data corresponding to each of the volume data to be rendered; superimposing each of the volume data to be rendered with the corresponding noise texture data to obtain sampling position offset information corresponding to each of the volume data to be rendered; and determining the sampling position corresponding to each of the volume data to be rendered based on the reference sampling position and the sampling position offset information corresponding to each of the volume data to be rendered.

[0017] In one possible implementation, the method further includes: responding to a second operation by a user to adjust the three-dimensional space transformation parameters, and obtaining the adjusted three-dimensional space transformation parameters; the step of performing volume rendering at the sampling position corresponding to the volume data to be rendered based on the rendering parameters before adjustment, to obtain the rendering result of the volume data to be rendered, includes: determining the spatial position of each voxel included in the volume data to be rendered based on the adjusted three-dimensional space transformation parameters and the sampling position corresponding to the volume data to be rendered; determining the at least one rendering contour corresponding to the detection object based on the spatial position of each voxel included in the volume data to be rendered, and the position parameters of the center pixel of each of the at least one rendering contour before adjustment; for each rendering contour, determining the opacity of each voxel in the target area surrounded by the rendering contour based on the pixel value of each voxel in the target area surrounded by the rendering contour and the contour thickness parameter before adjustment corresponding to the rendering contour; and determining the rendering result corresponding to the volume data to be rendered based on the opacity of each voxel in the target area.

[0018] In one possible implementation, the step of performing volume rendering on multiple frames of volume data to be rendered based on the adjusted rendering parameters includes: for each frame of volume data to be rendered, performing the following operations: determining the spatial position of each voxel included in the volume data to be rendered based on the adjusted 3D space transformation parameters; determining the at least one contour to be rendered corresponding to the detection object based on the spatial position of each voxel included in the volume data to be rendered and the adjusted position parameter of at least one center pixel; for each contour to be rendered, determining the opacity of each voxel in the target area surrounded by the contour to be rendered based on the pixel value of each voxel in the target area surrounded by the contour to be rendered and the adjusted contour thickness parameter corresponding to the contour to be rendered; and determining the second contour image data corresponding to the volume data to be rendered based on the opacity of each voxel in the target area.

[0019] In one possible implementation, the method further includes: responding to a third operation by a user to adjust filtering parameters, and obtaining adjusted filtering parameters; the filtering parameters include a filter kernel size and a filter factor; the step of filtering the ultrasound data to obtain multi-frame renderable data of the detected object includes: generating a filter kernel function based on the adjusted filter kernel size and the adjusted filter factor; and filtering the ultrasound data based on the filter kernel function to obtain multi-frame renderable data of the detected object.

[0020] In one possible implementation, the step of filtering the ultrasound data to obtain multi-frame renderable data of the detected object includes: repeatedly performing the following operations on the ultrasound data until the number of iterations reaches a preset iteration threshold to obtain multi-frame renderable data of the detected object; based on the ultrasound data, determining the first image features of each of the multiple local ultrasound data included in the ultrasound data; the first image features are used to characterize the detection position of the detected object corresponding to the local ultrasound data; for each local ultrasound data, performing the following operations respectively: comparing the feature value of the first image feature of the local ultrasound data with the feature threshold corresponding to the first image feature to determine the data type of the local ultrasound data; if the data type characterizes the local ultrasound data as boundary data, then performing enhancement processing on the local ultrasound data; if the data type characterizes the local ultrasound data as tissue data, then performing smoothing processing on the local ultrasound data. In one possible implementation, the step of filtering the ultrasound data to obtain multi-frame renderable data of the detected object includes: for each sliding window of ultrasound data, determining a second image feature of the ultrasound data in the sliding window based on the mean and variance of the pixel values ​​included in the ultrasound data in the sliding window; and determining the multi-frame renderable data of the detected object based on the second image feature of the ultrasound data in each sliding window.

[0021] Thirdly, embodiments of this application provide an ultrasound image processing apparatus, comprising:

[0022] The transceiver unit is used to transmit ultrasonic waves to the object being detected and to receive the ultrasonic echoes returned by the object being detected, thereby generating ultrasonic data.

[0023] A parameter adjustment unit is used to respond to the user's first operation of adjusting rendering parameters and obtain the adjusted rendering parameters. The rendering parameters are used to perform volume rendering on the contour of the detected object. The rendering parameters include the position parameters of the center pixel of at least one contour to be rendered and the contour thickness parameters. The position parameters of the center pixel are used to determine the contour to be rendered corresponding to the detected object, and the contour thickness parameters are used to adjust the display effect of the contour.

[0024] A three-dimensional imaging unit is used to perform volume rendering on the ultrasound data based on the rendering parameters before and after adjustment, respectively, to obtain the contour image data corresponding to the detected object.

[0025] The display unit is used to display the contour image of the detected object based on the contour image data of the detected object.

[0026] In one possible implementation, when the three-dimensional imaging unit performs volume rendering on the ultrasound data based on the rendering parameters before and after adjustment to obtain the contour image data corresponding to the detected object, it specifically performs the following steps: filtering the ultrasound data to obtain multiple frames of volume data to be rendered for the detected object; performing volume rendering on each frame of volume data to be rendered at the sampling position corresponding to the volume data to be rendered based on the rendering parameters before adjustment to obtain the rendering result of the volume data to be rendered; fusing the rendering results corresponding to each of the multiple frames of volume data to be rendered into first contour image data; and performing volume rendering on the multiple frames of volume data to be rendered based on the rendering parameters after adjustment, and fusing the second contour image data corresponding to each of the multiple frames of volume data to be rendered into second contour image data; the resolution of the second contour image data is lower than that of the first contour image data; and performing image fusion on the first contour image data and the second contour image data to obtain the contour image data of the detected object.

[0027] In one possible implementation, the three-dimensional imaging unit is further configured to: generate noise texture data corresponding to each of the volume data to be rendered; superimpose each of the volume data to be rendered with the corresponding noise texture data to obtain sampling position offset information corresponding to each of the volume data to be rendered; and determine the sampling position corresponding to each of the volume data to be rendered based on the reference sampling position and the sampling position offset information corresponding to each of the volume data to be rendered.

[0028] In one possible implementation, the parameter adjustment unit is further configured to: respond to a second operation by the user to adjust the three-dimensional space transformation parameters, and obtain the adjusted three-dimensional space transformation parameters; when the three-dimensional imaging unit performs volume rendering at the sampling position corresponding to the volume data to be rendered based on the rendering parameters before adjustment, and obtains the rendering result of the volume data to be rendered, it is specifically configured to: determine the spatial position of each voxel included in the volume data to be rendered based on the adjusted three-dimensional space transformation parameters and the sampling position corresponding to the volume data to be rendered; determine the at least one rendering contour corresponding to the detection object based on the spatial position of each voxel included in the volume data to be rendered, and the position parameters of the center pixel points of at least one rendering contour before adjustment; for each rendering contour, determine the opacity of each voxel in the target area surrounded by the rendering contour based on the pixel values ​​of each voxel in the target area surrounded by the rendering contour and the contour thickness parameter before adjustment corresponding to the rendering contour; and determine the rendering result corresponding to the volume data to be rendered based on the opacity of each voxel in the target area.

[0029] In one possible implementation, when the 3D imaging unit performs volume rendering on multiple frames of volume data to be rendered based on the adjusted rendering parameters, it specifically performs the following operations for each frame of volume data to be rendered: determining the spatial position of each voxel included in the volume data to be rendered based on the adjusted 3D spatial transformation parameters; determining the at least one contour to be rendered corresponding to the detection object based on the spatial position of each voxel included in the volume data to be rendered and the adjusted position parameter of at least one center pixel; determining the opacity of each voxel in the target area surrounded by the contour to be rendered based on the pixel value of each voxel in the target area surrounded by the contour to be rendered and the adjusted contour thickness parameter corresponding to the contour to be rendered; and determining the second contour image data corresponding to the volume data to be rendered based on the opacity of each voxel in the target area.

[0030] In one possible implementation, the parameter adjustment unit is further configured to respond to a third operation by the user to adjust the filter parameters and obtain the adjusted filter parameters; the filter parameters include a filter kernel size and a filter factor; when the three-dimensional imaging unit performs filtering processing on the ultrasound data to obtain multi-frame renderable data of the detected object, it is specifically configured to: generate a filter kernel function based on the adjusted filter kernel size and the adjusted filter factor; and perform filtering processing on the ultrasound data based on the filter kernel function to obtain multi-frame renderable data of the detected object.

[0031] In one possible implementation, when the three-dimensional imaging unit filters the ultrasound data to obtain multi-frame renderable data of the detected object, it specifically performs the following operations: For the ultrasound data, it repeatedly performs the following operations until the number of iterations reaches a preset iteration threshold to obtain multi-frame renderable data of the detected object: Based on the ultrasound data, it determines the first image features of each of the multiple local ultrasound data included in the ultrasound data; the first image features are used to characterize the detection position of the detected object corresponding to the local ultrasound data; for each local ultrasound data, it performs the following operations: comparing the feature value of the first image feature of the local ultrasound data with the feature threshold corresponding to the first image feature to determine the data type of the local ultrasound data; if the data type characterizes the local ultrasound data as boundary data, it performs enhancement processing on the local ultrasound data; if the data type characterizes the local ultrasound data as tissue data, it performs smoothing processing on the local ultrasound data.

[0032] In one possible implementation, when the three-dimensional imaging unit filters the ultrasound data to obtain multi-frame renderable data of the detected object, it specifically performs the following: for each sliding window of ultrasound data, it determines a second image feature of the ultrasound data in the sliding window based on the mean and variance of the pixel values ​​included in the ultrasound data in the sliding window; and determines the multi-frame renderable data of the detected object based on the second image feature of the ultrasound data in each sliding window.

[0033] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method described in the second aspect.

[0034] Fifthly, this application provides a computer program product, including a computer program: when the computer program is executed by a processor, it implements the shear wave image generation method as described in any one of the first aspects above.

[0035] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects:

[0036] This application provides an ultrasound device and an ultrasound image processing method. The user interface of the ultrasound device can respond to a user's first operation to adjust rendering parameters, obtaining the adjusted rendering parameters. These rendering parameters are used to perform volume rendering of the contour of the object being detected. The processor of the ultrasound device can perform volume rendering of the ultrasound data based on the rendering parameters before and after adjustment, respectively, to obtain contour image data corresponding to the object being detected. This allows the display screen to display the contour image of the object being detected based on the contour image data.

[0037] In the ultrasound image processing method provided in this application embodiment, the method can respond to a user's first operation of adjusting rendering parameters to obtain the adjusted rendering parameters. Then, the contour image of the detected object is displayed based on the adjusted rendering parameters. In other words, the user can adjust the required contour image of the detected object by adjusting the rendering parameters according to their own needs, resulting in a more flexible generated contour image. Moreover, since the number of contours to be rendered can be adjusted by adjusting the position parameters of the center pixel, multiple contours to be rendered can be displayed in a single contour image, thereby improving the user's work efficiency. Furthermore, since the contour image data corresponding to the detected object after rendering is obtained by volume rendering the ultrasound data based on both the rendering parameters before and after adjustment, rather than solely based on the adjusted rendering parameters, image artifacts can be reduced, thereby improving image quality.

[0038] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 A hardware configuration block diagram of an ultrasound device provided in an embodiment of this application;

[0041] Figure 2 A schematic diagram of an ultrasonic device provided in an embodiment of this application;

[0042] Figure 3 This is a schematic diagram of the structure of an ultrasonic probe provided in an embodiment of this application;

[0043] Figure 4 An application scenario diagram of an ultrasonic device provided in an embodiment of this application;

[0044] Figure 5 A system architecture diagram of an ultrasound image processing system provided in this application embodiment;

[0045] Figure 6 An exemplary flowchart of an ultrasound image processing method provided in an embodiment of this application;

[0046] Figure 7 This is a schematic diagram of the structure of the three-dimensional imaging module provided in the embodiments of this application;

[0047] Figure 8 A schematic flowchart of the volume rendering method provided in the embodiments of this application;

[0048] Figure 9 This is a schematic diagram of a filtering method provided in an embodiment of this application;

[0049] Figure 10 An exemplary flowchart of a filtering processing method provided in an embodiment of this application;

[0050] Figure 11 This is one of the flowcharts illustrating a volume rendering method provided in an embodiment of this application;

[0051] Figure 12One of the flowcharts of the volume rendering method provided in the embodiments of this application;

[0052] Figure 13 A schematic diagram of the contour image provided in the embodiments of this application;

[0053] Figure 14 This is one of the flowcharts illustrating a volume rendering method provided in an embodiment of this application;

[0054] Figure 15 This is one of the flowcharts illustrating a volume rendering method provided in an embodiment of this application;

[0055] Figure 16 This is a schematic diagram of an optional volume rendering process provided in an embodiment of this application. Detailed Implementation

[0056] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. The described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0057] Furthermore, in the description of the embodiments of this application, unless otherwise stated, "and" means "or", for example, A / B can mean A or B; "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone.

[0058] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined with "first" and "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0059] like Figure 1 As shown, the embodiments of this application are in Figure 1 A schematic diagram of the hardware structure of the ultrasonic device 10 is shown.

[0060] by Figure 1 Taking the hardware structure of the ultrasonic device 10 shown as an example, the embodiment will be described in detail. It should be understood that... Figure 1 The hardware structure of the ultrasound device 10 shown is merely an example, and the ultrasound device 10 can have more than... Figure 1The more or fewer components shown can be combined into two or more components, or they can have different component configurations. The various components shown in the figure can be implemented in hardware, software, or a combination of hardware and software, including one or more signal processing and / or application-specific integrated circuits.

[0061] Figure 1 The diagram illustrates, for example, the hardware configuration block diagram of the ultrasonic device 10 in an embodiment of this application. Figure 1 As shown, the ultrasonic device 10 includes components such as an ultrasonic probe 110, a memory 120, a display 130, a control panel 140, a processor 150, an audio circuit 160, a communication interface 170, and a power supply 180.

[0062] The ultrasound probe 110 can be used to acquire ultrasound data. During the acquisition process, the ultrasound probe 110 can convert electrical signals into ultrasound signals, emit ultrasound waves to the patient's tissues, and receive ultrasound echoes reflected by the tissues, converting the ultrasound signals into electrical signals. These electrical signals are then sent to the processor 120 for processing, and the corresponding ultrasound images are displayed on the display 130. In this embodiment, the converted electrical signals are referred to as ultrasound data.

[0063] The memory 120 can be used to store software programs and data. The processor 150 executes various functions of the ultrasound device 10 and performs data processing by running the software programs or data stored in the memory 120. The memory 120 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. The memory 120 stores an operating system that enables the ultrasound device 10 to run. In this application, the memory 120 may store the operating system and various application programs, and may also store code that executes the methods described in the embodiments of this application.

[0064] The display 130 can be used to receive input digital or character information and generate signal inputs related to user settings and function control of the ultrasound device 10. Specifically, the display 130 may include a touch screen 131 disposed on the front of the ultrasound device 10, which can collect touch operations of the user on or near it, such as clicking buttons, dragging scroll boxes, etc.

[0065] The display 130 can also be used to display information input by the user or information provided to the user, as well as various ultrasound interfaces of the ultrasound device 10. Specifically, the display 130 may include at least one of a touch screen 131 and a display screen 132 disposed on the front of the ultrasound device 10. The display screen 132 may be configured as a liquid crystal display, a light-emitting diode, or the like.

[0066] The touchscreen 131 can be placed over the display screen 132, or the touchscreen 131 and the display screen 132 can be integrated to realize the input and output functions of the ultrasound device 10. After integration, it can be referred to as a touch display screen. In this application, the display screen 130 can display the application program and the corresponding operation steps. The touchscreen 131 can be an implementation of the user operation interface of this application embodiment. For example, the user can perform a first operation to adjust rendering parameters, a second operation to adjust three-dimensional space transformation parameters, a third operation to adjust filtering parameters, etc., through touch operation.

[0067] The control panel 140 is used to install human-computer interaction components, such as a combination of one or more of the following: a keyboard 141, a mouse 142, a scroll wheel 143, a trackball 144, and a display 145 for touch screen display. Specifically, when a user triggers an operation on the human-computer interaction component on the control panel, generating signal input related to user settings and function control of the ultrasound device 10, the processor 150 presents corresponding content on the display 130 based on the generated signal. The keyboard 141 includes multiple keys, and the user sends different numbers or characters corresponding to each key to the processor 150 by triggering different keys. The control panel 140 can also be an implementation of the user operation interface of this application embodiment; for example, the user can perform a first operation to adjust rendering parameters, a second operation to adjust three-dimensional space transformation parameters, and a third operation to adjust filtering parameters by triggering different keys.

[0068] The processor 150 is the control center of the ultrasound device 10. It connects various parts of the ultrasound device 10 via various interfaces and lines, and performs various functions and processes data by running or executing software programs stored in the memory 120 and calling data stored in the memory 120. In some embodiments, the processor 150 may include one or more processing units; the processor 150 may also integrate an application processor and a baseband processor, wherein the application processor mainly handles the operating system, ultrasound device interface, and applications, and the baseband processor mainly handles wireless communication. It is understood that the baseband processor may not be integrated into the processor 150. In this application, the processor 150 can run the operating system, applications, ultrasound device interface display and touch response, and the processing methods described in the embodiments of this application. Furthermore, the processor 150 is coupled to the display 130.

[0069] Audio circuit 160 provides an audio interface between the user and ultrasound device 10. Audio circuit 160 can connect to speaker 161 and microphone 162. Audio circuit 160 converts received audio data into electrical signals and transmits them to speaker 161, where speaker 161 converts them into sound signals for output. Ultrasound device 10 can also be equipped with volume buttons for adjusting the volume of the sound signal. On the other hand, microphone 162 converts collected sound signals into electrical signals, which are received by audio circuit 160, converted into audio data, and then output to other electronic devices or to memory 120 for further processing. In this application, microphone 162 can acquire sound from the environment in which ultrasound device 10 is located.

[0070] It should be noted that, in the embodiments of this application, when transmitting audio data to other electronic devices, wired or wireless transmission can be used. This application does not limit the transmission method, the number of devices, or the type of other devices. For example, other electronic devices can be ultrasound equipment, personal computers, mobile phones, tablets, laptops, e-book readers, intelligent voice interaction devices, smart home devices, in-vehicle terminals, and other computer devices with certain computing capabilities that run instant messaging software and websites or social networking software and websites.

[0071] The communication interface 170 is used for information exchange with other electronic devices. Specifically, the communication interface 170 may include one or more of the following: network port 171, WiFi module 172, Bluetooth module 173, 4G module 174, and USB 175. Using different communication interfaces 170 allows for the use of corresponding communication methods to exchange information with other electronic devices.

[0072] The power supply 180 supplies power to the various components in the ultrasonic device 10. The power supply 180 can be logically connected to the processor 150 through a power management system, thereby enabling the management of charging, discharging, and power consumption. The ultrasonic device 10 may also be equipped with a power button for turning the ultrasonic device on and off, as well as locking the screen.

[0073] Optionally, the hardware structure of the ultrasonic device 10 in this embodiment may further include a camera. In this embodiment, the camera is connected to a processor, and the camera can be used to capture still images or videos. An object generates an optical image through the lens and projects it onto a photosensitive element. The photosensitive element can be a charge-coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the light signal into an electrical signal, and then transmits the electrical signal to the processor 150 to convert it into a digital image signal.

[0074] Based on the hardware structure diagram of the ultrasonic device 10 described above, this application implements, for example... Figure 2 A schematic diagram of the ultrasonic equipment shown. Figure 2 As shown, the ultrasonic device 10 includes an ultrasonic probe 110, a display 130, a control panel 140, an ultrasonic main unit 210, a support device 220, and a caster control device 230.

[0075] The memory 120, processor 150, audio circuit 160, communication interface 170 and power supply 180 in the hardware structure of the ultrasound device 10 can be set on the ultrasound host 210 or in other locations of the ultrasound device 10. This application does not limit this.

[0076] In practice, the ultrasound probe 110 can be connected to the ultrasound host 210 via a cable. The ultrasound image data acquired by the ultrasound probe 110 is transmitted to the ultrasound host 210 via the cable. The ultrasound host 210 receives the ultrasound image data transmitted by the ultrasound probe and stores, processes and analyzes it.

[0077] In this embodiment, the display 130 and the control panel 140 can be connected to the support device 220, which supports the display 130 and the control panel 140 respectively. In this embodiment, the position and orientation of the display 130 and the control panel 140 can be adjusted by adjusting the support device 220.

[0078] It should be noted that the respective pose states of the display 130 and the control panel 140 include at least height and tilt angle, etc., which are not limited in this application.

[0079] Optional, Figure 2 The ultrasound device 10 may also include a camera. In this embodiment, the camera can be placed at any position on the ultrasound device 10, or it can be placed within the surrounding area of ​​the ultrasound device 10 to facilitate the acquisition of suitable images using the camera.

[0080] In practice, in this embodiment of the application, the user can move the ultrasonic device 10 by adjusting the caster control device 230.

[0081] In the embodiments of this application, such as Figure 3 The diagram shown is a schematic representation of the structure of an ultrasonic probe according to an embodiment of this application. The ultrasonic probe 110 includes an acoustic lens 1101, a matching layer 1102, a piezoelectric crystal 1103, a backing block 1104, and a housing 1105.

[0082] It should be noted that, for Figure 3 In the ultrasound probe 110, the side of the ultrasound probe that contacts the patient is designated as the front side of the ultrasound probe in this embodiment.

[0083] When using an ultrasound probe to scan a patient, the acoustic lens 1101 is located between the matching layer 1102 of the ultrasound probe and the patient's tissue. It can be used to converge the ultrasound beam and also serves as a protective layer for the ultrasound probe 110. Specifically, when the sound velocity of the lens material corresponding to the acoustic lens 1101 is greater than the sound velocity of the surrounding medium, the ultrasound beam converges.

[0084] Matching layer 1102 is one or more layers of acoustic material located in front of the piezoelectric crystal, used to achieve impedance matching between the high acoustic impedance piezoelectric oscillator and the low acoustic impedance human tissue, thereby improving the maximum transmission efficiency of acoustic energy. Exemplarily, in embodiments of this application, matching layer 1102 can be set to a quarter-wavelength thickness.

[0085] The piezoelectric chip 1103 is used to convert electrical signals into ultrasonic signals and to convert received ultrasonic echoes into electrical signals.

[0086] It should be noted that when mechanical pressure or vibration is applied to the piezoelectric wafer 1103, an electric charge is generated on its surface. This phenomenon of mechanical energy being converted into electrical energy is called the direct piezoelectric effect. When an alternating electric field is applied to the piezoelectric wafer 1103, causing deformation and corresponding mechanical vibration, this phenomenon of electrical energy being converted into mechanical energy is called the inverse piezoelectric effect. In this embodiment, ultrasonic waves are generated through the inverse piezoelectric effect and the echoes are received through the direct piezoelectric effect.

[0087] The backing block 1104 is a sound-absorbing material filled behind the piezoelectric crystal 1103. It is used to absorb backward ultrasound and play a damping role, generating short ultrasonic pulses and improving longitudinal resolution.

[0088] Based on such Figure 3 The ultrasound probe shown performs ultrasound scanning. In this embodiment, the front side of the ultrasound probe is placed on the patient's body surface or inserted into the body. The ultrasound probe emits ultrasound waves into the patient's body tissue to collect ultrasound image data. As the ultrasound probe moves, the ultrasound image data within the range of the ultrasound waves emitted by the probe is sent to the ultrasound host for processing. Based on the processed ultrasound image data, the corresponding ultrasound image is displayed on the monitor, allowing the user to obtain the state of lesions in the patient's body and the environment around the lesions. Figure 4 As shown, taking the placement of an ultrasound probe on the surface of a patient's body as an example, this application embodiment illustrates an application scenario of an ultrasound device.

[0089] Reference numbers and / or reference letters may be repeated in different examples in this application. Such repetition is for the purpose of simplification and clarity and does not in itself indicate the relationship between the various implementations and / or settings discussed.

[0090] See Figure 5 This is an architectural diagram of an ultrasonic image processing system for an application of an ultrasonic image processing method provided in this application embodiment. The ultrasonic image processing system 500 may include a probe 510, a transmitting module 520, a receiving module 530, a beamforming module 540, an image processing module 550, a three-dimensional imaging module 560, a display 570, and a user interaction module 580.

[0091] The probe 510 includes, but is not limited to, volumetric probes, intracavitary probes, linear array probes, and convex array probes. The probe 510 can be... Figure 1 The ultrasonic probe 110 shown includes a transmitting module 520, a receiving module 530, and a beamforming module 540, which can be modules in probe 510 used for data processing. The transmitting module 520 and the receiving module 530 are used to transmit and receive ultrasonic waves, respectively. The beamforming module 540 is used to synthesize the received ultrasonic waves to generate ultrasonic data.

[0092] Image processing module 550 is used to preprocess the ultrasound data generated by beamforming module 540. Three-dimensional imaging module 560 is used to further process the preprocessed ultrasound data to display a contour image of the detected object on display 570. Display 570 can be... Figure 1 The display 130 shown. The image processing module 550 and the three-dimensional imaging module 560 may be included in the display. Figure 1 In the processor shown, the user interaction module 580 is used to respond to user adjustments of various adjustable parameters and obtain the adjusted adjustable parameters. For example, adjustable parameters may include rendering parameters, three-dimensional space transformation parameters, filtering parameters, etc. The user interaction module 580 is the user operation interface described in the ultrasonic device provided in this application embodiment, which can be accessed through... Figure 1 The touchscreen 131 or control panel 140 shown is used for implementation. It should be noted that the types of adjustable parameters can be set according to actual conditions or experience, and are not limited to the examples above. This application does not limit this.

[0093] The following will describe the processing flow of each module included in the ultrasound image processing system 500, using an ultrasound image processing method provided in an embodiment of this application as an example:

[0094] See Figure 6 This is an exemplary flowchart of an ultrasound image processing method provided in an embodiment of this application. Figure 6 As shown, this method can be applied to Figure 5 The ultrasound image processing system shown includes the following steps S61-S64:

[0095] S61, emits ultrasonic waves to the object being tested, and receives the ultrasonic echoes returned by the object being tested, generating ultrasonic data.

[0096] The transmitting module emits ultrasound waves towards the object being detected, the receiving module receives the ultrasound echoes returned by the object, and the beamforming module performs beamforming on the received ultrasound echoes to obtain ultrasound data. The object being detected can refer to the part or tissue that needs to be imaged using ultrasound; for example, when performing fetal ultrasound imaging, the object being detected can refer to the fetus.

[0097] It should be noted that since the transmitting module can continuously transmit, the receiving module can continuously receive the ultrasonic echoes returned by the object being detected, thus obtaining ultrasonic data that can be ultrasonic data over a continuous period of time, i.e., multi-frame ultrasonic data.

[0098] The image processing module can preprocess the ultrasound data to obtain preprocessed ultrasound data, such as edge detection and normalization. The corresponding preprocessing methods can be found in the commonly used preprocessing methods in related technologies, which will not be elaborated here.

[0099] S62 responds to the user's first operation to adjust rendering parameters and obtains the adjusted rendering parameters.

[0100] The user interaction module 580 can respond to the user's first operation to adjust the rendering parameters and obtain the adjusted rendering parameters. The rendering parameters are used to perform volume rendering on the contour of the detected object. The rendering parameters include the position parameter of the center pixel of at least one contour to be rendered and the contour thickness parameter. The center pixel is the pixel located at the center of the contour to be rendered. The position parameter of the center pixel is used to determine the contour to be rendered corresponding to the detected object. The position parameter of the center pixel can include the center pixel value. The user can select the contour of interest as the contour to be rendered by inputting different center pixel values. The contour thickness parameter can be used to adjust the display effect of the contour's thickness.

[0101] In one example, when the object of detection is a fetus, the user can obtain a contour image of the fetal skull by adjusting the position parameter of the center pixel to the position of the fetal brain through the ultrasound image processing method provided in this application embodiment.

[0102] In another example, when a user needs to display multiple outline images of the fetus, they can determine multiple outlines to be rendered by inputting position parameters of multiple different center pixels, and adjust the display effect of each outline by inputting its respective outline thickness parameter, thereby obtaining a fetal outline image that can display multiple outlines. For example, the user can input the position parameter of the center pixel corresponding to the brain, and input the outline thickness parameter corresponding to the intracranial outline according to the display effect requirements; the user can also continue to input the position parameter of the center pixel corresponding to the gastrointestinal tract, and input the outline thickness parameter corresponding to the gastrointestinal outline according to the display effect requirements, thereby obtaining a fetal outline image that can simultaneously display the intracranial outline and the gastrointestinal outline through the ultrasound image processing method provided in this application embodiment.

[0103] S63, based on the rendering parameters before and after adjustment, performs volume rendering on the ultrasound data to obtain the contour image data corresponding to the object being detected.

[0104] The 3D imaging module 560 can be used to execute S63, see [link / reference]. Figure 7 This is a schematic diagram of the structure of the three-dimensional imaging module provided in the embodiments of this application, such as... Figure 7 As shown, Figure 5 The 3D imaging module 560 shown may also include a data preprocessing submodule 561, a 3D reconstruction submodule 562, a cropping submodule 563, a rendering submodule 564, and an image postprocessing submodule 565.

[0105] The following will combine Figure 7 Each submodule shown provides a detailed description of the volume rendering method provided in the application embodiments. See also... Figure 8 This is a flowchart illustrating the volume rendering method provided in this application embodiment. S63 can be... Figure 8 The process shown can be executed and can be applied to... Figure 7 The process includes S631-S634 in the various sub-modules of the 3D imaging module 560 shown:

[0106] S631 filters the ultrasound data to obtain multiple frames of data to be rendered from the object being tested.

[0107] In some embodiments, before executing S631, the user interaction module 580 can respond to the third operation of the user adjusting the filter parameters, obtain the adjusted filter parameters, and send them to the data preprocessing submodule 561. At this time, S631 can specifically be executed as follows: the data preprocessing submodule 561 receives the adjusted filter parameters obtained by the user interaction module 580, and generates a filter kernel function based on the adjusted filter kernel size and the adjusted filter factor. Based on the filter kernel function, the ultrasound data is filtered to obtain multi-frame data of the detected object to be rendered.

[0108] Optionally, the filtering kernel function is an m*m matrix with a sum of 1 within the matrix, where m is determined based on the adjusted size of the filtering kernel. After applying the filtering kernel function, the correspondence between the ultrasonic data I and the data I' to be rendered satisfies formula (1):

[0109]

[0110] Where w is the filtering kernel function, i and j are the index values ​​in the kernel function, and x and y are the coordinate index values ​​of the image pixels in the ultrasound data.

[0111] See Figure 9 This is a schematic diagram of a filtering method provided in an embodiment of this application, as shown below. Figure 9 As shown, the user can input the filter kernel size *m* and the filter factor *β* through the user interaction module 580. The user interaction module can then send the obtained filter kernel size *m* and filter factor *β* to the data preprocessing submodule. The data preprocessing submodule generates a corresponding filter kernel function *w* based on the received filter kernel size *m* and filter factor *β*, thereby filtering the ultrasound data using the filter kernel function to obtain the data to be rendered. It should be noted that... Figure 9 In this context, w(m, β) indicates that the filter kernel function w is generated by m and β, which is the same as w in formula (1).

[0112] In other embodiments, the filtering process may include smoothing filtering and enhancement filtering, see [link to relevant documentation]. Figure 10 An exemplary flowchart of a filtering processing method provided in an embodiment of this application is shown below. Figure 10 As shown, S631 can also be specifically executed as follows: For ultrasound data, repeat the following S6311-S6313 until the number of iterations reaches the preset iteration threshold, to obtain multi-frame data of the detected object to be rendered:

[0113] S6311, based on ultrasound data, determine the first image features of each of the multiple local ultrasound data included in the ultrasound data.

[0114] The first image feature is used to characterize the detection location of the object corresponding to the local ultrasound data. The first image feature includes, but is not limited to, gradient features, structural tensor, mean, standard deviation and variance. The calculation method of the corresponding first image feature can be found in the calculation method in the relevant technology in this field, and will not be repeated here.

[0115] The ultrasound data, including multiple local ultrasound data points, can be obtained by dividing the ultrasound data into a predetermined number of parts. For example, if the predetermined number is 4, the ultrasound data can be divided into four parts, each of which is a local ultrasound data point. It should be noted that the above method of dividing local ultrasound data is merely exemplary, and this application does not limit the method of dividing local ultrasound data.

[0116] S6312, for each local ultrasound data, perform the following operations respectively: compare the feature value of the first image feature of the local ultrasound data with the feature threshold corresponding to the first image feature to determine the data type of the local ultrasound data.

[0117] If the data type represents local ultrasound data as boundary data, then S6313A is executed to enhance the local ultrasound data; if the data type represents local ultrasound data as tissue data, then S6313B is executed to smooth the local ultrasound data.

[0118] It should be noted that the feature threshold corresponding to the first image feature can be set according to the actual situation or experience, and this application does not limit it.

[0119] For example, suppose the first image feature is a gradient feature. The gradient feature can include gradient magnitude and gradient direction. When the gradient magnitude is greater than the gradient magnitude threshold A1 and the gradient direction is perpendicular to the image boundary, the local ultrasound data can be considered as data describing the boundary. When the gradient magnitude is less than or equal to the gradient magnitude threshold A1 and the gradient direction changes significantly, the local ultrasound data can be considered as data describing the tissue.

[0120] S6313A, enhanced processing.

[0121] For specific methods of enhancement processing, please refer to image enhancement methods in related technologies, such as edge enhancement and contrast enhancement, which will not be elaborated here.

[0122] S6313B, smoothing process.

[0123] The smoothing methods can refer to the smoothing methods in related technologies, such as mean filtering, Gaussian filtering, etc., which will not be elaborated here.

[0124] In some other embodiments, S631 may further be specifically performed as follows: for each sub-ultrasound data in the sliding window, a second image feature of the sub-ultrasound data is determined based on the mean and variance of the pixel values ​​included in the sub-ultrasound data. Then, based on the ultrasound data and the second image feature of each sub-ultrasound data, multi-frame volume data to be rendered of the object to be detected is determined.

[0125] The second image feature may include a k and b k As shown in formulas (2) and (3):

[0126]

[0127] In the formula, μ k and These represent the guiding data I in the k-th sliding window w. k The mean and variance of the pixel values ​​for each pixel in the sliding window. ω is the number of pixels within the sliding window. This indicates that the ultrasound data p is in the sliding window w k The mean pixel value of each pixel in the data is ∈, which is an adjustable factor. In the embodiments of this application, the guiding data I can be equal to the ultrasound data p.

[0128]

[0129] Therefore, the relationship between the volume data to be rendered and the ultrasound data can satisfy formula (4):

[0130] q = a k p+b k Formula (4)

[0131] In the formula, q represents the volume data to be rendered.

[0132] In one possible implementation, to execute S631, any one of the three filtering methods described above can be executed, or at least two of the three filtering methods can be combined. For example, executing... Figure 10 The filtering process shown can be performed using a third filtering method when smoothing local ultrasound data describing tissue. This application does not limit the number of filtering algorithms used or the combination of algorithms.

[0133] Optionally, when applying any of the three filtering methods mentioned above, multi-scale ultrasound data can be input, and the output data corresponding to each scale in the multi-scale can be fused together. The fused output data can then be used as the data to be rendered. This application does not limit this.

[0134] In one implementation, to save computational load during subsequent real-time rendering, the data preprocessing submodule 561, after filtering the preprocessed ultrasound data output by the image processing module, can also perform parameter pre-calculation on the preprocessed ultrasound data and store the pre-calculated parameter values ​​in the texture for subsequent real-time rendering. The parameters pre-calculated refer to parameters that are not adjustable by the user and need to be calculated in the processor; for example, they may include the gradient value of each voxel.

[0135] In one embodiment, the gradient value of each voxel can be estimated using the central difference method. For each voxel, the gradient vector at that voxel can be estimated by sampling the function in the vicinity of that voxel and then using the differences between these sampled values.

[0136] Specifically, assuming there exists a three-dimensional function f(x,y,z), the gradient vector at voxel (x,y,z) can be estimated using the following formulas (5)-(7):

[0137]

[0138] Where Δx, Δy, and Δz are the step sizes of the voxel (x, y, z) in the x, y, and z axes, respectively.

[0139] Based on the above scheme, since the gradient value after filtering is smoother than the unfiltered gradient value, the various illumination values ​​calculated using the gradient will be more continuous and realistic.

[0140] It should be noted that other algorithms can also be used to calculate the gradient values ​​of voxels, such as convolution filtering, but this application does not limit this to any particular algorithm.

[0141] In one possible implementation, after filtering and parameter preprocessing, the preprocessed ultrasound data can be first input into the clipping submodule 562 to remove occluded parts, and then the clipped data can be input into the 3D reconstruction submodule 563 to convert the clipped data from the Cartesian coordinate system to the polar coordinate system, and the output reconstructed data can be used as the multi-frame rendering data of the detection object.

[0142] It should be noted that the trimming submodule 562 and the three-dimensional reconstruction submodule 563 are commonly used modules in ultrasonic equipment. The specific execution flow can be found in the execution methods in the relevant technologies, and will not be repeated here.

[0143] S632, for each frame of volume data to be rendered, based on the rendering parameters before adjustment, performs volume rendering at the sampling position corresponding to the volume data to be rendered, and obtains the rendering result of the volume data to be rendered.

[0144] In one possible implementation, to optimize the image quality of the rendered contour image, the sampling point positions can be offset by random dithering to remove wavy wood grain defects. Before executing S632, a noise texture generation algorithm can be used to generate noise texture data corresponding to each volume data to be rendered. Then, by superimposing each volume data to be rendered with its corresponding noise texture data, the sampling position offset information corresponding to each volume data to be rendered is obtained. Finally, based on the reference sampling position and the sampling position offset information corresponding to each volume data to be rendered, the sampling position corresponding to each volume data to be rendered is determined.

[0145] In one example, the noise texture data described above can be a two-dimensional Gaussian texture map of size n*n, where n is typically a power of 2, for example, 2^n. 5 =32, therefore n can be 32; 2 6 =64, therefore n can take the value 64, etc.

[0146] Optionally, when determining the sampling position offset information by random jitter, in addition to generating noise texture, the sampling position offset information can also be determined by generating random numbers. That is, the sampling position offset information is determined based on the generated random numbers. This application does not limit the method of determining the sampling position offset information by random jitter.

[0147] In one possible implementation, the volume rendering algorithm can be expressed in multiple rendering modes, including but not limited to contour rendering mode and realistic skin rendering mode. This application's embodiments use contour rendering as an example for illustration. See also... Figure 11 This is one of the flowcharts illustrating a volume rendering method provided in an embodiment of this application, such as... Figure 11 As shown, for each frame of volume data to be rendered, volume rendering is performed at the sampling positions corresponding to the volume data to be rendered based on the rendering parameters before adjustment. When obtaining the rendering result of the volume data to be rendered, S6321-S6324 can be executed for each frame of volume data to be rendered:

[0148] S6321, based on the adjusted three-dimensional space transformation parameters and the sampling positions corresponding to the volume data to be rendered, determines the spatial positions of each voxel included in the volume data to be rendered.

[0149] Before executing S6321, the user interaction module 580 can respond to the user's second operation of adjusting the three-dimensional space transformation parameters, obtain the adjusted three-dimensional space transformation parameters, and send the adjusted three-dimensional space transformation parameters to the rendering submodule 564. The three-dimensional space transformation parameters are used to transform the three-dimensional coordinate system of the volume data to be rendered, and may include parameters such as rotation and translation parameters, scaling factors, etc.

[0150] After receiving the adjusted rotation and translation parameters and scaling factor, the rendering submodule 564 can transform the three-dimensional coordinate system of the volume data to be rendered, and obtain the three-dimensional spatial coordinates of each voxel included in the volume data after rotation, translation and scaling based on the sampling position corresponding to the volume data to be rendered.

[0151] S6322, based on the spatial positions of each voxel included in the volume data to be rendered, and the position parameters of the center pixel of each of the at least one outline to be rendered before adjustment, determine at least one outline to be rendered corresponding to the detection object.

[0152] Based on the spatial positions of the voxels included in the volume data to be rendered determined by S6321, at least one outline to be rendered, centered on its respective center pixel, can be determined. The position parameter of the center pixel can be the center pixel value. It should be noted that the position parameter of the center pixel before adjustment can be the original parameter pre-configured in the rendering submodule.

[0153] S6323, for each outline to be rendered, determines the opacity of each voxel in the target area based on the pixel value of each voxel in the target area surrounded by the outline to be rendered and the outline thickness parameter before adjustment corresponding to the outline to be rendered.

[0154] To achieve the effect of highlighting the outline corresponding to the center pixel by mapping the pixels within a certain distance from the center pixel to gradually reduce the opacity of the target area surrounded by the outline, at least one outline to be rendered can be centered on its own center pixel. This can be done by converting the pixel values ​​of each voxel to opacity using a conversion function.

[0155] Specifically, when the conversion function is only related to one parameter, it can be set as a unary function. Taking the parameter as the pixel value as an example, the conversion function can be as shown in formula (8). Substitute the pixel value of each voxel as x into formula (8) to obtain the opacity of each voxel.

[0156]

[0157] In the formula, k is the contour thickness parameter; the smaller k is, the finer and thinner the contour; the larger k is, the coarser and thicker the contour. t For the center pixel value, a v This is the preset maximum opacity threshold.

[0158] It should be noted that when the transformation function is set as a unary function, the parameters of the transformation function can also be gradient values ​​and other related parameters. The parameters of the transformation function and the maximum opacity threshold can be set according to the actual situation, and this application does not limit them.

[0159] In one possible implementation, when the transformation function is related to two parameters, it can be set as a binary function. For example, if the transformation function is related to pixel value and gradient value, the transformation function can be as shown in formula (9).

[0160]

[0161] In the formula, g represents the gradient value of voxel x, which is obtained by the data preprocessing submodule 561 through parameter pre-calculation of the preprocessed ultrasound data.

[0162] Generally, with a selected center pixel value, the larger the gradient value of voxel x, the greater the opacity of voxel x, until it reaches near the set maximum opacity threshold. Since the opacity does not change abruptly near the center pixel, but rather there is a gradient area, the farther voxel x is from the center pixel, the smaller the corresponding opacity.

[0163] It should be noted that for each target area surrounded by the outline to be rendered, a corresponding formula (8) or formula (9) can be established to obtain the opacity of each voxel in the target area corresponding to at least one outline to be rendered.

[0164] S6324 determines the rendering result corresponding to the volume data to be rendered based on the opacity of each voxel in the target area.

[0165] In one possible implementation, before executing S6324, the user interaction module 580 can respond to the user's fourth operation of adjusting the color mapping parameters and obtain the adjusted color mapping parameters. The color mapping parameters may include light source position parameters, etc., which are not limited in this application.

[0166] After receiving the adjusted color mapping parameters, the rendering submodule 564 can perform lighting calculations based on these parameters to determine the color values ​​of each voxel in response to the light source. Then, based on the opacity and color values ​​of each voxel in the target area, it renders each voxel. After each voxel is rendered, it can composite the current voxel with previously rendered voxels or slices to determine the rendering result corresponding to the volume data to be rendered.

[0167] Optionally, when the volume rendering mode includes contour rendering mode and realistic skin rendering mode, the rendering result obtained from contour rendering mode and realistic skin rendering mode can be mixed to obtain the rendering result.

[0168] In one possible implementation, the blending method can be linear blending. Assuming that the opacity of a voxel x calculated by the realistic skin rendering mode is α1(x), and the opacity calculated by the outline rendering mode is α2(x), then the opacity α(x) of the blended voxel x is as shown in formula (10):

[0169] α(x)=k1*α1(x)+(1-k1)*α2(x) Formula (10)

[0170] In the formula, k1 is a scaling factor, and its value ranges from [0,1].

[0171] In another possible implementation, since the opacity calculated by the realistic skin rendering mode is usually much greater than that calculated by the outline rendering mode, the linear blending method usually reflects the opacity of the realistic skin rendering mode. To solve this problem, the rendering result can be obtained by non-linear blending.

[0172] Specifically, assuming that the opacity of a certain voxel x calculated by the realistic skin rendering mode is α1(x) and the opacity calculated by the outline rendering mode is α2(x), then the opacity of the voxel x after blending is as shown in formula (11):

[0173]

[0174] In the formula, n is preset according to the actual situation.

[0175] When the blended opacity is obtained by formula (10) or formula (11), each voxel is rendered based on the blended opacity and color value of each voxel in the target area. After each voxel is rendered, the current voxel can be combined with the previously rendered voxels or slices to determine the rendering result corresponding to the volume data to be rendered.

[0176] S633, the rendering results corresponding to the multiple frames of data to be rendered are merged into the first contour image data.

[0177] To further improve image quality, multiple frames of volume data can be rendered, and then the rendering results of each of the multiple frames of volume data can be merged into the first contour image data.

[0178] It should be noted that S62 can be executed before S634, that is, S62 can be executed after S633 or after S632. This application does not limit the execution order of each step.

[0179] In one example, S62 can be executed after S633. After obtaining the first contour image data, the display can show the contour image of the detected object based on the first contour image data. Then, the user adjusts the rendering parameters based on the displayed contour image. The user interaction module 580 responds to the user's first operation of adjusting the rendering parameters, obtains the adjusted rendering parameters, and sends the adjusted rendering parameters to the rendering submodule 564. At this time, the rendering submodule 564 can execute S634 to obtain the second contour image data rendered based on the adjusted rendering parameters.

[0180] Based on the above solution, since the outline image displayed after static rendering can reduce wood grain defects and has a higher image quality, users can select rendering parameters based on the high-quality image to obtain an outline image that better meets their needs.

[0181] S634, based on the adjusted rendering parameters, performs volume rendering on multiple frames of volume data to be rendered, and obtains the second contour image data corresponding to each of the multiple frames of volume data to be rendered.

[0182] Since volume rendering requires dynamically adjusted rendering parameters during S634 execution, the resolution of the second contour image data can be lower than that of the first contour image data. For example, the resolution of the first contour image data can be 900*600, and the resolution of the second contour image data can be 450*300. It should be understood that the resolutions of the first and second contour image data can be set based on experience or actual conditions, and will not be elaborated further here. The number of frames of the volume data to be rendered can be set by the user based on experience or actual conditions, such as 3 or 4 frames, etc., and this application does not limit this.

[0183] Users can adjust the rendering parameters multiple times, and each time the adjusted rendering parameters are obtained, the volume rendering process shown in S634 can be executed.

[0184] In one possible implementation, see [link to relevant documentation]. Figure 12 This is one of the flowcharts illustrating the volume rendering method provided in this application. When performing volume rendering on multiple frames of volume data based on adjusted rendering parameters, the method can execute the following steps for each frame of volume data: Figure 12 The process shown includes:

[0185] S6341, based on the adjusted 3D spatial transformation parameters, determines the spatial position of each voxel included in the volume data to be rendered.

[0186] For specific methods, please refer to [link / reference]. Figure 11 The relevant descriptions in S6321 of the method embodiment shown will not be repeated here.

[0187] S6342, based on the spatial positions of each voxel included in the volume data to be rendered and the adjusted position parameters of at least one center pixel, determine at least one outline to be rendered corresponding to the detected object.

[0188] For specific methods, please refer to [link / reference]. Figure 11 The relevant description in S6322 of the method embodiment shown can be achieved by replacing the position parameter of at least one center pixel before adjustment with the position parameter of at least one center pixel after adjustment, and will not be repeated here.

[0189] S6343, for each contour to be rendered, determines the opacity of each voxel in the target area based on the pixel value of each voxel in the target area surrounded by the contour and the adjusted contour thickness parameter corresponding to the contour to be rendered.

[0190] For specific methods, please refer to [link / reference]. Figure 11 The relevant description in S6323 of the method embodiment shown is that the position parameter of at least one center pixel before adjustment is replaced with the position parameter of at least one center pixel after adjustment, and the contour thickness parameter before adjustment is replaced with the contour thickness parameter after adjustment. Substituting into formula (8) or (9) will not be repeated here.

[0191] S6344, based on the opacity of each voxel in the target region, determines the second contour image data corresponding to the volume data to be rendered.

[0192] For specific methods, please refer to [link / reference]. Figure 11 The relevant descriptions in S6324 of the method embodiment shown will not be repeated here.

[0193] S64: Display the contour image of the detected object based on the contour image data of the detected object.

[0194] After obtaining the rendered contour image data of the detected object, the rendering submodule 564 can send the contour image data to the image post-processing submodule 565. The image post-processing submodule 565 can perform image post-processing such as color mapping transformation and image contrast enhancement on the contour image data, and send the post-processed contour image data to the display so that the display can display the contour image of the detected object.

[0195] In one example, when the detected object is a fetus, the rendering result and the second contour image data are obtained through non-linear blending. The scaling factor k1 takes the value [0.0, 0.2], and the center pixel value x t When the value of is 100 and the contour thickness k is 8, the fetal external contour and the fetal intracranial anterior fontanelle tissue, skull tissue, etc., can be rendered simultaneously. See [link to documentation]. Figure 13This is a schematic diagram of the contour image provided in the embodiments of this application, such as... Figure 13 As shown, the contour image data obtained by the ultrasonic image processing method provided in this application embodiment does not contain obvious wood grain defects. It can be seen that the method can achieve the technical effect of reducing image artifacts and improving the quality of ultrasonic three-dimensional imaging.

[0196] See Figure 14 This is one of the flowcharts illustrating a volume rendering method provided in an embodiment of this application, such as... Figure 14 As shown, this process, taking the static volume rendering of two frames of volume data to be rendered as an example, includes:

[0197] S1401, Obtain the data of the volume to be rendered.

[0198] After filtering and pre-calculating the parameters of the ultrasound data, two consecutive frames of data of the object to be rendered are obtained.

[0199] S1402, random jitter.

[0200] Apply a first noise texture to the first frame of volume data to be rendered, and determine the sampling position of the first frame of volume data to be rendered by random jittering; apply a second noise texture to the second frame of volume data to be rendered, and determine the sampling position of the first frame of volume data to be rendered by random jittering.

[0201] S1403, calculates three-dimensional spatial coordinates.

[0202] S1404 calculates opacity using a transformation function.

[0203] S1405, rendering and compositing.

[0204] S1406, Mixed rendering mode.

[0205] Executing S1402-S1406 on the first frame of data to be rendered yields the rendering result corresponding to the first frame of data to be rendered. Executing S1402-S1406 on the second frame of data to be rendered yields the rendering result corresponding to the second frame of data to be rendered. The rendering result is a high-resolution image.

[0206] S1407, rendering results are blended.

[0207] The obtained rendering results are merged into first contour image data so that the display shows the contour image based on the first contour image data.

[0208] It should be understood that the specific implementation methods of S1401-S1407 above can be found in [reference needed]. Figure 11 The relevant descriptions in the method embodiments shown will not be repeated here.

[0209] See Figure 15 This is one of the flowcharts illustrating a volume rendering method provided in an embodiment of this application, such as... Figure 15 As shown, this process, taking the dynamic volume rendering of three frames of volume data to be rendered as an example, includes:

[0210] S1501, Obtain the data of the volume to be rendered.

[0211] After filtering and pre-calculating the parameters of the ultrasound data, three consecutive frames of data of the object to be rendered are obtained.

[0212] S1502, calculates three-dimensional spatial coordinates.

[0213] S1503, obtain the adjusted rendering parameters.

[0214] S1504 calculates opacity using a transformation function.

[0215] Based on the adjusted rendering parameters, the opacity of the volume data in each of the three consecutive frames to be rendered is calculated.

[0216] Optionally, when calculating the opacity of each voxel in each frame of volume data to be rendered, it can be calculated based on the currently adjusted rendering parameters. That is, the adjusted rendering parameters corresponding to each frame of volume data to be rendered can be different. For example, when calculating the opacity of each voxel in the first frame of volume data to be rendered out of three consecutive frames, the user may adjust the outline thickness parameter to 7 through the user interaction module, and then calculate the opacity of each voxel using k=7; when calculating the opacity of each voxel in the second frame of volume data to be rendered out of three consecutive frames, the user may adjust the outline thickness parameter to 8 through the user interaction module, and then calculate the opacity of each voxel using k=8, and so on, which will not be elaborated further here.

[0217] S1505, rendering and compositing.

[0218] S1506, Mixed rendering mode.

[0219] S1507, Obtain the second contour image data.

[0220] Executing steps S1502-S1506 on the first frame of a three-frame renderable data yields the corresponding second contour image data. Executing steps S1502-S1506 on the second frame of a three-frame renderable data yields the corresponding second contour image data. Executing steps S1503-S1506 on the third frame of a three-frame renderable data yields the corresponding second contour image data. The second contour image data can be a low-resolution image.

[0221] It should be understood that the specific implementation methods of S1501-S1507 above can be found in [reference needed]. Figure 11 The relevant descriptions in the method embodiments shown will not be repeated here.

[0222] See Figure 16 This is a schematic diagram illustrating an optional volume rendering process provided in an embodiment of this application. Figure 16 As shown, before the user adjusts the rendering parameters, the rendering submodule 564 will use the following... Figure 14 The process shown performs a static volume rendering, that is, rendering the volume data 1 and volume data 2 to be rendered into two high-resolution images at different sampling positions: Rendering Result 1 and Rendering Result 2, and then merging them into a single frame of first contour image data. When the user starts adjusting the rendering parameters, the rendering submodule 564 will use the following... Figure 15 The process shown involves multiple dynamic renderings, i.e. Figure 16 Taking the rendering of 3 frames as an example, based on the adjusted rendering parameters, the data to be rendered, ...

[0223] Optionally, after the user completes the adjustment of the rendering parameters, a static rendering can be performed on the data 6 and 7 to be rendered according to the final rendering parameters to obtain rendering result 6 and rendering result 7, which are then merged into third contour image data. Then, the first contour image data, the second contour image data and the third contour image data are merged into the contour image data of the detected object, so that the display can display the contour image of the detected object according to the rendered contour image data of the detected object.

[0224] It should be noted that the data to be rendered, data 2 and data 3, may be continuous or discontinuous in time. Similarly, the data to be rendered, data 5 and data 6, may be continuous or discontinuous in time. This application does not impose any restrictions on this.

[0225] Based on the above scheme, this application embodiment employs a spatiotemporal supersampling method for volume rendering. Specifically, in the temporal domain, when dynamically adjusting rendering parameters, multiple frames of volume data to be rendered are rendered at low resolution. In the spatial domain, the rendering results of each of the multiple frames of data to be rendered are obtained through multiple different sampling positions, and these rendering results are then fused. Since after the user completes the adjustment of the rendering parameters, a second static rendering can be performed to fuse the rendering results obtained in the temporal and spatial domains, thereby achieving high-resolution display and effectively removing wood grain imperfections, improving the image quality of the outline image.

[0226] Based on the same inventive concept, the ultrasound image processing method described above in this application can also be implemented by an ultrasound image processing device. The effect of this ultrasound image processing device is similar to that of the aforementioned method, and will not be described again here.

[0227] Based on the same inventive concept as the above method embodiments, this application also provides an electronic device. The principle of the electronic device in solving the problem is similar to that of the method in the above embodiments. Therefore, the implementation of the electronic device can refer to the implementation of the above method, and the repeated parts will not be described again.

[0228] This application also provides a computer storage medium storing computer-executable instructions for implementing the xx method described in any embodiment of this application.

[0229] In the description of this application, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection. They can refer to a mechanical connection or an electrical connection. They can refer to a direct connection or an indirect connection through an intermediate medium, and they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in this invention can be understood according to the specific circumstances.

[0230] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0231] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0232] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0233] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0234] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. An ultrasonic device, characterized in that, The ultrasonic device includes an ultrasonic probe, a user interface, a processor, and a display screen; The ultrasonic probe is used to emit ultrasonic waves to the object being tested and to receive the ultrasonic echoes returned by the object being tested, thereby generating ultrasonic data. The user operation interface is used to respond to the user's first operation of adjusting rendering parameters and obtain the adjusted rendering parameters. The rendering parameters are used to perform volume rendering on the contour of the detected object. The rendering parameters include the position parameters of the center pixel of at least one contour to be rendered and the contour thickness parameters. The position parameters of the center pixel are used to determine the contour to be rendered corresponding to the detected object, and the contour thickness parameters are used to adjust the display effect of the contour. The processor is used to filter the ultrasound data to obtain multi-frame volume data of the detected object to be rendered; for each frame of volume data to be rendered, volume rendering is performed at the sampling position corresponding to the volume data to be rendered based on the rendering parameters before adjustment, to obtain the rendering result of the volume data to be rendered. The rendering results corresponding to the multiple frames of data to be rendered are merged into the first contour image data. Furthermore, based on the adjusted rendering parameters, volume rendering is performed on multiple frames of volume data to be rendered to obtain second contour image data corresponding to each of the multiple frames of volume data to be rendered; the resolution of the second contour image data is lower than that of the first contour image data; image fusion is performed on the first contour image data and the second contour image data to obtain the contour image data of the detected object. The display screen is used to display the contour image of the detected object based on the contour image data of the detected object.

2. The ultrasonic device according to claim 1, characterized in that, The processor is also used for: Generate noise texture data corresponding to each of the data to be rendered; Each of the data to be rendered is superimposed with the corresponding noise texture data to obtain the sampling position offset information corresponding to each of the data to be rendered. Based on the reference sampling position and the sampling position offset information corresponding to each of the data to be rendered, the sampling position corresponding to each of the data to be rendered is determined.

3. The ultrasonic device according to claim 1 or 2, characterized in that, The user operation interface is also used to: respond to a second operation by the user to adjust the three-dimensional space transformation parameters, and obtain the adjusted three-dimensional space transformation parameters; When the processor performs volume rendering at the sampling positions corresponding to the volume data to be rendered based on the rendering parameters before adjustment, and obtains the rendering result of the volume data to be rendered, it is specifically used for: Based on the adjusted three-dimensional space transformation parameters and the sampling positions corresponding to the volume data to be rendered, the spatial positions of each voxel included in the volume data to be rendered are determined. Based on the spatial positions of each voxel included in the volume data to be rendered, and the position parameters of the center pixel of each of the at least one outline to be rendered before adjustment, the at least one outline to be rendered corresponding to the detection object is determined. For each outline to be rendered, the opacity of each voxel in the target area surrounded by the outline to be rendered is determined based on the pixel value of each voxel in the target area and the outline thickness parameter before adjustment corresponding to the outline to be rendered. Based on the opacity of each voxel in the target region, the rendering result corresponding to the volume data to be rendered is determined.

4. The ultrasonic device according to claim 3, characterized in that, When the processor performs volume rendering on multiple frames of volume data based on the adjusted rendering parameters, it is specifically used for: For each frame of volume data to be rendered, perform the following operations: Based on the adjusted three-dimensional space transformation parameters, the spatial positions of each voxel included in the volume data to be rendered are determined; Based on the spatial positions of each voxel included in the volume data to be rendered and the adjusted position parameters of at least one center pixel, the at least one outline to be rendered corresponding to the detected object is determined. For each outline to be rendered, the opacity of each voxel in the target area surrounded by the outline to be rendered is determined based on the pixel value of each voxel in the target area and the adjusted outline thickness parameter corresponding to the outline to be rendered. Based on the opacity of each voxel in the target region, the second contour image data corresponding to the volume data to be rendered is determined.

5. The ultrasonic device according to claim 1 or 2, characterized in that, The user interface is also used to respond to a third user operation to adjust the filter parameters and obtain the adjusted filter parameters; the filter parameters include the filter kernel size and the filter factor. When the processor filters the ultrasound data to obtain multi-frame renderable data of the detected object, it is specifically used for: Based on the adjusted filter kernel size and the adjusted filter factor, a filter kernel function is generated; based on the filter kernel function, the ultrasound data is filtered to obtain multi-frame rendering data of the detected object.

6. The ultrasonic device according to claim 1 or 2, characterized in that, When the processor filters the ultrasound data to obtain multi-frame renderable data of the detected object, it is specifically used for: For the ultrasound data, repeat the following operations until the number of iterations reaches a preset iteration threshold to obtain multi-frame data of the detected object to be rendered: Based on the ultrasound data, a first image feature is determined for each of the multiple local ultrasound data included in the ultrasound data; the first image feature is used to characterize the detection location of the detection object corresponding to the local ultrasound data. For each local ultrasound data point, perform the following operations: The feature value of the first image feature of the local ultrasound data is compared with the feature threshold corresponding to the first image feature to determine the data type of the local ultrasound data. If the data type indicates that the local ultrasound data is data describing a boundary, then the local ultrasound data is enhanced. If the data type indicates that the local ultrasound data is data describing tissue, then the local ultrasound data is smoothed.

7. The ultrasonic device according to claim 1 or 2, characterized in that, When the processor filters the ultrasound data to obtain multi-frame renderable data of the detected object, it is specifically used for: For each sliding window of ultrasound data, a second image feature of the ultrasound data in the sliding window is determined based on the mean and variance of the pixel values ​​included in the ultrasound data in the sliding window. Based on the second image features of the ultrasound data in each of the sliding windows, multi-frame volume data to be rendered for the detected object are determined.

8. An ultrasound image processing method, characterized in that, Applied to ultrasonic equipment, the method includes: The system emits ultrasonic waves towards the object being detected and receives the ultrasonic echoes returned by the object, generating ultrasonic data. In response to the user's first operation to adjust the rendering parameters, the adjusted rendering parameters are obtained. The rendering parameters are used to perform volume rendering on the contour of the detected object. The rendering parameters include the position parameters of the center pixel of at least one contour to be rendered and the contour thickness parameters. The position parameters of the center pixel are used to determine the contour to be rendered corresponding to the detected object, and the contour thickness parameters are used to adjust the display effect of the contour. The ultrasound data is filtered to obtain multi-frame volume data of the detected object; for each frame of volume data, volume rendering is performed at the sampling position corresponding to the volume data based on the rendering parameters before adjustment to obtain the rendering result of the volume data; the rendering results corresponding to each of the multi-frame volume data are fused into first contour image data; and, based on the adjusted rendering parameters, volume rendering is performed on the multi-frame volume data respectively to obtain second contour image data corresponding to each of the multi-frame volume data; the resolution of the second contour image data is lower than that of the first contour image data; the first contour image data and the second contour image data are image fused to obtain the contour image data of the detected object. Based on the contour image data of the detected object, the contour image of the detected object is displayed.

9. An ultrasonic image processing device, characterized in that, The device includes: The transceiver unit is used to transmit ultrasonic waves to the object being detected and to receive the ultrasonic echoes returned by the object being detected, thereby generating ultrasonic data. A parameter adjustment unit is used to respond to the user's first operation of adjusting rendering parameters and obtain the adjusted rendering parameters. The rendering parameters are used to perform volume rendering on the contour of the detected object. The rendering parameters include the position parameters of the center pixel of at least one contour to be rendered and the contour thickness parameters. The position parameters of the center pixel are used to determine the contour to be rendered corresponding to the detected object, and the contour thickness parameters are used to adjust the display effect of the contour. A three-dimensional imaging unit is used to filter the ultrasound data to obtain multi-frame volume data of the detected object; for each frame of volume data, volume rendering is performed at the sampling position corresponding to the volume data based on the rendering parameters before adjustment to obtain the rendering result of the volume data; the rendering results corresponding to the multi-frame volume data are fused into first contour image data; and, based on the adjusted rendering parameters, volume rendering is performed on the multi-frame volume data to obtain second contour image data corresponding to each of the multi-frame volume data; the resolution of the second contour image data is lower than that of the first contour image data; image fusion is performed on the first contour image data and the second contour image data to obtain the contour image data of the detected object. The display unit is used to display the contour image of the detected object based on the contour image data of the detected object.

Images