B ultrasonic image data processing method and operation platform thereof

Abstract

The invention provides a B ultrasonic image data processing method and an operation platform thereof. The method comprises the following steps: acquiring a navigation mode triggering instruction through a triggering key on a B-ultrasonic probe, uploading the navigation mode triggering instruction to a processor, so that the processor responds to the navigation mode triggering instruction, generating a navigation vector according to B-ultrasonic image data of a target area of a to-be-detected object, and then sending the navigation vector to the B-ultrasonic probe; the processor generates B-ultrasonic navigation image data according to the navigation vector and the B-ultrasonic image data, and the B-ultrasonic navigation image data is displayed through the display, so that the B-ultrasonic probe is guided to move according to a navigation path, and the problem that a local area is missed to be observed due to random movement of the probe or human negligence in traditional examination is solved; and the completeness and efficiency of B ultrasonic image observation are effectively improved.

Description

Technical Field

[0001] This application relates to data processing technologies, and particularly to a B-ultrasound image data processing method and its operating platform. Background Art

[0002] In the field of medical imaging, as a non-invasive, painless, and non-radiative imaging examination method, B-ultrasound has been widely used in clinical medicine due to its advantages such as portability, high resolution, and high sensitivity. However, with the continuous progress of medical technologies and the increasing requirements of patients for the quality of medical services, some problems have gradually emerged in traditional B-ultrasound examination methods.

[0003] During the traditional B-ultrasound examination process, doctors mainly rely on manually operating the B-ultrasound probe to obtain image data of the target area. This method not only requires doctors to have rich experience and skilled operation skills, but also is prone to missing the observation of images due to human factors, thus affecting the accuracy and efficiency of diagnosis. Especially when examining complex structures or minor lesions, doctors need to continuously adjust the position and angle of the probe to obtain comprehensive and clear image information. This process not only takes time and effort, but also is prone to missing some areas that need to be observed due to the random movement of the probe. Summary of the Invention

[0005] This application provides a B-ultrasound image data processing method and its operating platform to avoid the problem of missing the observation of local areas caused by the random movement of the probe or human negligence in traditional examinations, and effectively improve the integrity and efficiency of B-ultrasound image observation.

[0006] In a first aspect, this application provides a B-ultrasound image data processing method, which is applied to a B-ultrasound device operating platform. The B-ultrasound device operating platform includes a B-ultrasound probe, a processor, and a display. The processor is communicatively connected to the B-ultrasound probe and the display respectively; the method includes: Obtain a navigation mode trigger instruction through a trigger button on the B-ultrasound probe, and upload the navigation mode trigger instruction to the processor; The processor responds to the navigation mode trigger instruction, and generates a navigation vector based on the B-ultrasound image data of the target area of the object to be detected. The navigation vector is at least used to guide the movement direction of the B-ultrasound probe; The processor generates B-ultrasound navigation image data based on the navigation vector and the B-ultrasound image data, and displays the B-ultrasound navigation image data through the display.

[0007] In the above solution, through the trigger button on the B-ultrasound probe, the user can easily start the navigation mode and quickly upload the trigger instruction to the processor. The processor can immediately respond to this instruction and get ready for the subsequent image processing and activation of the navigation function. This function simplifies the user operation and improves the inspection efficiency, enabling the B-ultrasound device to enter the navigation state more quickly and providing instant image guidance for doctors. The processor generates a navigation vector based on the B-ultrasound image data of the target area of the object to be detected. This navigation vector not only clearly indicates the relationship between the current position and the target position of the B-ultrasound probe but also details the movement path of the probe, thus effectively guiding the moving direction of the probe. The introduction of the navigation vector enables the B-ultrasound probe to move along the navigation path, avoiding the problem of missed observations caused by random movement of the probe or human negligence in traditional inspections and significantly improving the integrity and efficiency of image acquisition. After obtaining the navigation vector, the processor further combines it with the B-ultrasound image data to generate B-ultrasound navigation image data. The generation and display of the B-ultrasound navigation image data provide intuitive and comprehensive image information for the user, effectively reducing the workload of B-ultrasound operation and improving the integrity of B-ultrasound observation. At the same time, the introduction of the navigation identifier enables the user to more clearly understand the movement path and target position of the probe, thus improving the integrity and efficiency of the inspection.

[0008] Optionally, the processor generates the B-ultrasound navigation image data according to the navigation vector and the B-ultrasound image data, including: The processor generates a first B-ultrasound display image and a second B-ultrasound display image. The B-ultrasound navigation image data includes the first B-ultrasound display image and the second B-ultrasound display image. Among them, the first B-ultrasound display image is a local B-ultrasound image of the target area, and the second B-ultrasound display image is a two-dimensional simulation image corresponding to the object to be detected or an overall two-dimensional simulation image of the target area; The processor superimposes the navigation identifier corresponding to the navigation vector on the second B-ultrasound display image to generate a second processed display image; The processor generates the B-ultrasound navigation image data according to the first B-ultrasound display image and the second processed display image.

[0009] In the above solution, after receiving the navigation mode trigger instruction, the processor first generates a first B-ultrasound display image, that is, a local B-ultrasound image of the target area. At the same time, a second B-ultrasound display image is generated in parallel, which is a two-dimensional simulation image corresponding to the object to be detected or an overall two-dimensional simulation image of the target area. This way of generating two images in parallel not only retains the local details of the target area but also provides the overall anatomical structure information of the object to be detected. When the doctor views the navigation image, local and overall image information can be obtained simultaneously, which helps to more comprehensively understand the condition and improve the accuracy of diagnosis. After generating the second B-ultrasound display image, the processor will superimpose a navigation identifier corresponding to the navigation vector, such as an arrow, a line, etc., on this image to generate a second processed display image.

[0010] Optionally, generating the navigation vector according to the B-ultrasound image data of the target area of the object to be detected includes: The processor determines the characteristic observation area of the target area according to the B-ultrasound image data sequence, where the B-ultrasound image data sequence includes B-ultrasound image data obtained by the B-ultrasound probe at different regional positions of the object to be detected; The processor determines the current visual feature point according to the B-ultrasound image data obtained by the B-ultrasound probe at the current moment, and determines the target visual feature point according to the characteristic observation area; The processor determines the navigation vector according to the current visual feature point and the target visual feature point, and the navigation vector is a vector used to indicate from the current visual feature point to the target visual feature point.

[0011] In the above solution, the processor determines the characteristic observation area of the target area according to the B-ultrasound image data sequence, that is, the B-ultrasound image data obtained by the B-ultrasound probe at different regional positions of the object to be detected. This process involves comparative analysis of the B-ultrasound image data at different display magnifications, extracting the overall outer contour and the local outer contour sequence of the target area, and then generating a spliced outer contour and a reference outer contour. Finally, the characteristic observation area is determined through a Boolean difference operation. The accurate determination of the characteristic observation area provides an accurate data basis for subsequent visual feature point matching and navigation vector calculation. It ensures that the navigation vector can guide according to the key features of the target area, thereby improving the accuracy and effectiveness of navigation.

[0012] Optionally, the processor determining the characteristic observation area of the target area according to the B-ultrasound image data sequence includes: At the first display magnification, obtain the scaled B-ultrasound image data of the target area, and the scaled B-ultrasound image data includes the overall outer contour of the target area; The processor extracts the overall outer contour of the target area according to the scaled B-ultrasound image data; At a second display magnification, obtain the B-ultrasound image data sequence of the target area, where each B-ultrasound image data in the B-ultrasound image data sequence only includes the local outer contour of the target area, so as to generate a local outer contour sequence, where the second display magnification is greater than the first display magnification; The processor generates a spliced outer contour according to the local outer contour sequence, and the spliced outer contour is the outer contour formed after splicing the local outer contour sequence; The processor determines a reference outer contour according to the magnification ratio between the first display magnification and the second display magnification and the overall outer contour, and according to the reference outer contour and the spliced outer contour; The processor determines the feature observation area according to the reference outer contour and the spliced outer contour.

[0013] In the above solution, the processor obtains the scaled B-ultrasound image data of the target area at the first display magnification, and this data includes the overall outer contour of the target area. Subsequently, at the second display magnification (and the second display magnification is greater than the first display magnification), the B-ultrasound image data sequence of the target area is obtained, and each data only includes the local outer contour of the target area, so as to generate a local outer contour sequence. By obtaining image data at different display magnifications, the processor can comprehensively capture the overall and local information of the target area. This multi-magnification data acquisition method not only retains the overall structural information of the target area but also provides rich local details, providing comprehensive data support for the subsequent determination of the feature observation area.

[0014] Optionally, the processor determines the feature observation area according to the reference outer contour and the spliced outer contour, including: The feature observation area is the area obtained by performing a Boolean difference between the reference area enclosed by the reference outer contour and the spliced area enclosed by the spliced outer contour.

[0015] In the above solution, the determination of the feature observation region is based on the Boolean difference operation between the reference outer contour and the spliced outer contour. In this application, the Boolean difference operation is performed between the reference region enclosed by the reference outer contour and the spliced region enclosed by the spliced outer contour, and the result obtained is the feature observation region. The application of the Boolean difference operation makes the determination of the feature observation region accurate and efficient. By calculating the difference part between the two outer contours, the processor can accurately identify the parts in the target region that may be missed during observation. Among them, the reference outer contour is extracted from the scaled B-ultrasound image data at the first display magnification, which reflects the overall shape and approximate range of the target region. During the determination process of the feature observation region, the reference outer contour serves as a stable morphological benchmark, providing a reference for the comparison and analysis of the spliced outer contour. The determination of the reference outer contour takes into account the magnification ratio between the first display magnification and the second display magnification, as well as the shape and size of the overall outer contour. By comprehensively considering these factors, the processor can generate a reference outer contour that not only conforms to the actual morphological changes but also is convenient for calculation. The stability and accuracy of the reference outer contour ensure the reliability and consistency of the determination of the feature observation region. It provides a reliable benchmark for the comparison and analysis of the spliced outer contour, making the determination of the feature observation region more accurate and credible. Moreover, the spliced outer contour is generated based on the B-ultrasound image data sequence at the second display magnification, which reflects the morphological changes and detailed features of the target region at different local positions. By comparing and analyzing it with the reference outer contour, the processor can accurately identify the feature observation region in the target region.

[0016] Optionally, when the second B-ultrasound display image is the overall two-dimensional simulation image of the target region, the overall two-dimensional simulation image is a two-dimensional simulation image generated according to the overall outer contour.

[0017] In the above solution, the processor obtains the scaled B-ultrasound image data of the target region at the first display magnification and extracts the overall outer contour of the target region from it. The extraction of the overall outer contour provides a morphological basis for the subsequent generation of the two-dimensional simulation image. It ensures that the simulation image can reflect the overall shape and structural features of the target region, providing an important morphological basis for subsequent diagnosis. Based on the extracted overall outer contour, the processor generates the overall two-dimensional simulation image of the target region.

[0018] Optionally, the processor determines the current visual feature point according to the B-ultrasound image data obtained by the B-ultrasound probe at the current moment, and determines the target visual feature point according to the feature observation region, including: The processor determines the current observation feature region according to the local outer contour and the image boundary of the target region in the B-ultrasound image data acquired by the B-ultrasound probe at the current moment, maps the current observation feature region to the overall two-dimensional simulation image to determine the current observation mapping region, and determines the center-of-gravity position of the current observation mapping region as the current visual feature point; The processor maps the feature observation region to the overall two-dimensional simulation image to determine the feature observation mapping region, and determines the center-of-gravity position of the feature observation mapping region as the target visual feature point.

[0019] In the above solution, by extracting the local outer contour and the image boundary of the target region in the B-ultrasound image data acquired by the B-ultrasound probe at the current moment, the system can accurately define the current observation feature region. This step ensures that the selected local image region contains the target structure and has a clear boundary, providing an accurate basis for subsequent positioning operations. Mapping the current observation feature region to the overall two-dimensional simulation image and calculating its center-of-gravity position as the current visual feature point further improves the positioning accuracy. The selection of the center-of-gravity position as the feature point effectively avoids positioning deviations caused by the complexity of the local image and ensures the stability of the navigation process. The feature observation region is used as the target region for navigation, and the center-of-gravity position after its mapping to the overall two-dimensional simulation image is determined as the target visual feature point. This process not only considers the overall shape of the target region but also ensures the uniqueness and accuracy of the target point through center-of-gravity calculation, providing an accurate target direction for the generation of the navigation vector.

[0020] In a second aspect, the present application provides a B-ultrasound device operation platform, including: a B-ultrasound probe, a processor, and a display, where the processor is communicatively connected to the B-ultrasound probe and the display respectively; Obtain a navigation mode trigger instruction through a trigger button on the B-ultrasound probe and upload the navigation mode trigger instruction to the processor; The processor responds to the navigation mode trigger instruction and generates a navigation vector according to the B-ultrasound image data of the target region of the object to be detected, where the navigation vector is at least used to guide the movement direction of the B-ultrasound probe; The processor generates B-ultrasound navigation image data according to the navigation vector and the B-ultrasound image data, and displays the B-ultrasound navigation image data through the display.

[0021] Optionally, the processor generates B-ultrasound navigation image data according to the navigation vector and the B-ultrasound image data, including: The processor generates a first B-ultrasound display image and a second B-ultrasound display image. The B-ultrasound navigation image data includes the first B-ultrasound display image and the second B-ultrasound display image. Among them, the first B-ultrasound display image is a local B-ultrasound image of the target area, and the second B-ultrasound display image is a two-dimensional simulation image corresponding to the object to be detected or an overall two-dimensional simulation image of the target area; The processor superimposes a navigation identifier corresponding to the navigation vector on the second B-ultrasound display image to generate a second processed display image; The processor generates the B-ultrasound navigation image data according to the first B-ultrasound display image and the second processed display image.

[0022] Optionally, generating the navigation vector according to the B-ultrasound image data of the target area of the object to be detected includes: The processor determines a characteristic observation area of the target area according to a sequence of B-ultrasound image data, where the sequence of B-ultrasound image data includes B-ultrasound image data obtained by the B-ultrasound probe at different area positions of the object to be detected; The processor determines a current visual feature point according to the B-ultrasound image data obtained by the B-ultrasound probe at the current moment, and determines a target visual feature point according to the characteristic observation area; The processor determines the navigation vector according to the current visual feature point and the target visual feature point, and the navigation vector is a vector used to indicate from the current visual feature point to the target visual feature point.

[0023] Optionally, the processor determining the characteristic observation area of the target area according to the sequence of B-ultrasound image data includes: At a first display magnification, scaled B-ultrasound image data of the target area is acquired, and the scaled B-ultrasound image data includes the overall outer contour of the target area; The processor extracts the overall outer contour of the target area according to the scaled B-ultrasound image data; At a second display magnification, the sequence of B-ultrasound image data of the target area is acquired, and each B-ultrasound image data in the sequence of B-ultrasound image data only includes a local outer contour of the target area to generate a local outer contour sequence, where the second display magnification is greater than the first display magnification; The processor generates a spliced outer contour according to the local outer contour sequence, and the spliced outer contour is an outer contour formed after splicing the local outer contour sequence; The processor determines a reference outer contour according to a magnification ratio between the first display magnification and the second display magnification and the overall outer contour, and according to the reference outer contour and the spliced outer contour; The processor determines the feature observation area according to the reference outer contour and the spliced outer contour.

[0024] Optionally, the processor determines the feature observation area according to the reference outer contour and the spliced outer contour, including: The feature observation area is the area obtained by performing a Boolean difference between the reference area enclosed by the reference outer contour and the spliced area enclosed by the spliced outer contour.

[0025] Optionally, when the second B-ultrasound display image is the overall two-dimensional simulation image of the target area, the overall two-dimensional simulation image is a two-dimensional simulation image generated according to the overall outer contour.

[0026] Optionally, the processor determines the current visual feature point according to the B-ultrasound image data acquired by the B-ultrasound probe at the current moment, and determines the target visual feature point according to the feature observation area, including: The processor determines the current observation feature area according to the local outer contour and the image boundary of the target area in the B-ultrasound image data acquired by the B-ultrasound probe at the current moment, maps the current observation feature area to the overall two-dimensional simulation image to determine the current observation mapping area, and determines the center-of-gravity position of the current observation mapping area as the current visual feature point; The processor maps the feature observation area to the overall two-dimensional simulation image to determine the feature observation mapping area, and determines the center-of-gravity position of the feature observation mapping area as the target visual feature point.

[0027] In a third aspect, the present application provides an electronic device, including: A processor; and, A memory for storing executable instructions of the processor; Wherein, the processor is configured to execute any possible method described in the first aspect by executing the executable instructions.

[0028] In a fourth aspect, the present application provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, they are used to implement any possible method described in the first aspect.

[0029] The B-ultrasound image data processing method and its operation platform provided by this application obtain a navigation mode trigger instruction through a trigger button on the B-ultrasound probe, and upload the navigation mode trigger instruction to the processor, so that the processor responds to the navigation mode trigger instruction and generates a navigation vector according to the B-ultrasound image data of the target area of the object to be detected. Then, the processor generates B-ultrasound navigation image data according to the navigation vector and the B-ultrasound image data, and displays the B-ultrasound navigation image data through a display, thereby guiding the movement of the B-ultrasound probe along the navigation path, avoiding the problem of missing observation of local areas caused by random movement of the probe or human negligence in traditional examinations, and effectively improving the integrity and efficiency of B-ultrasound image observation. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The accompanying drawings herein are incorporated into and constitute a part of this specification, showing embodiments consistent with this application, and are used together with the specification to explain the principles of this application.

[0032] Figure 1 is a schematic flowchart of a B-ultrasound image data processing method shown according to an exemplary embodiment of this application; Figure 2 is a schematic flowchart of a B-ultrasound image data processing method shown according to another exemplary embodiment of this application; Figure 3 is a schematic structural diagram of a B-ultrasound device operation platform shown according to an exemplary embodiment of this application; Figure 4 is a schematic structural diagram of an electronic device shown according to an exemplary embodiment of this application.

[0033] Through the above accompanying drawings, specific embodiments of this application have been shown, and there will be more detailed descriptions hereinafter. These drawings and textual descriptions are not intended to limit the scope of the concept of this application in any way, but to illustrate the concept of this application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0035] Here, the exemplary embodiments will be described in detail, and the examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. On the contrary, they are merely examples of devices and methods consistent with some aspects of this application as detailed in the appended claims.

[0036] Figure 1 is a schematic flowchart of a B-ultrasound image data processing method shown according to an exemplary embodiment of this application. As Figure 1As shown in the figure, the B-ultrasound image data processing method provided in this embodiment includes: S101. Obtain a navigation mode trigger instruction through a trigger button on the B-ultrasound probe.

[0037] In this step, obtain a navigation mode trigger instruction through a trigger button on the B-ultrasound probe, and upload the navigation mode trigger instruction to the processor. Specifically, when a doctor needs to perform navigation-assisted examination, press the trigger button on the B-ultrasound probe. The signal of the trigger button is transmitted to the processor through the circuit inside the probe. After receiving the trigger instruction, the processor is ready to enter the navigation mode.

[0038] It should be noted that the above navigation mode can be triggered after the doctor performs a B-ultrasound examination on the target area of the patient to determine whether there is an area that has been missed. If the processor determines that there is an area that has been missed, the navigation mode is started. If it is determined that there is no area that has been missed, it can be prompted that the examination has been completed. It can be seen that the main purpose of this navigation mode is to assist the doctor to avoid inaccurate B-ultrasound diagnosis caused by missed observations by humans.

[0039] S102. The processor responds to the navigation mode trigger instruction and generates a navigation vector according to the B-ultrasound image data of the target area of the object to be detected.

[0040] In this step, the processor responds to the navigation mode trigger instruction and generates a navigation vector according to the B-ultrasound image data of the target area of the object to be detected. The navigation vector is at least used to guide the movement direction of the B-ultrasound probe.

[0041] Specifically, the processor first determines the characteristic observation area of the target area according to the B-ultrasound image data sequence. This includes obtaining the scaled B-ultrasound image data of the target area at the first display magnification and extracting the overall outer contour; then obtaining the local outer contour sequence at the second display magnification and generating a spliced outer contour; finally, determining the reference outer contour according to the magnification ratio and the overall outer contour, and determining the characteristic observation area through Boolean difference operation. Then, the processor determines the current visual feature point according to the B-ultrasound image data obtained by the B-ultrasound probe at the current moment, and determines the target visual feature point according to the characteristic observation area. This includes extracting the current observation characteristic area and mapping it to the overall two-dimensional simulation image to determine the current visual feature point, and determining the target visual feature point after mapping the characteristic observation area. Finally, the processor determines the navigation vector according to the current visual feature point and the target visual feature point. This vector is used to indicate the direction and distance from the current visual feature point to the target visual feature point.

[0042] S103. The processor generates B-ultrasound navigation image data according to the navigation vector and the B-ultrasound image data, and displays the B-ultrasound navigation image data through a display.

[0043] Specifically, the processor first generates a first B-ultrasound display image and a second B-ultrasound display image. The first B-ultrasound display image is a local B-ultrasound image of the target area, and the second B-ultrasound display image is a two-dimensional simulation image corresponding to the object to be detected or an overall two-dimensional simulation image of the target area.

[0044] The processor superimposes a navigation identifier (such as an arrow, a line, etc.) corresponding to the navigation vector on the second B-ultrasound display image to generate a second processed display image. The processor generates final B-ultrasound navigation image data based on the first B-ultrasound display image and the second processed display image, and displays it through a display. During the display process, the processor can also adjust the image in terms of color, brightness, contrast, etc. as needed to ensure the clarity and readability of the navigation image data.

[0045] In this embodiment, a navigation mode trigger instruction is obtained through a trigger button on the B-ultrasound probe and uploaded to the processor, so that the processor responds to the navigation mode trigger instruction, generates a navigation vector based on the B-ultrasound image data of the target area of the object to be detected, and then the processor generates B-ultrasound navigation image data based on the navigation vector and the B-ultrasound image data, and displays the B-ultrasound navigation image data through a display, thereby guiding the movement of the B-ultrasound probe along the navigation path, avoiding the problem of missing observation of local areas caused by random movement of the probe or human negligence in traditional examinations, and effectively improving the integrity and efficiency of B-ultrasound image observation.

[0046] Figure 2 It is a schematic flowchart of a B-ultrasound image data processing method shown by another exemplary embodiment of the present application. As Figure 2 shown, the B-ultrasound image data processing method provided in this embodiment includes: S201. Obtain a navigation mode trigger instruction through a trigger button on the B-ultrasound probe.

[0047] In this step, a navigation mode trigger instruction is obtained through a trigger button on the B-ultrasound probe and uploaded to the processor. Specifically, when a doctor needs to perform navigation-assisted examination, the trigger button on the B-ultrasound probe is pressed. The signal of the trigger button is transmitted to the processor through the circuit inside the probe. After receiving the trigger instruction, the processor is ready to enter the navigation mode.

[0048] S202. The processor determines a characteristic observation area of the target area according to the B-ultrasound image data sequence.

[0049] In this step, the processor determines a characteristic observation area of the target area according to the B-ultrasound image data sequence, where the B-ultrasound image data sequence includes B-ultrasound image data obtained by the B-ultrasound probe at different regional positions of the object to be detected.

[0050] In a possible implementation, it may be to obtain the scaled B-ultrasound image data of the target area at the first display magnification, and the scaled B-ultrasound image data includes the overall outer contour of the target area.

[0051] The processor extracts the overall outer contour of the target area according to the scaled B-ultrasound image data.

[0052] At the second display magnification, obtain a sequence of B-ultrasound image data of the target area. Each B-ultrasound image data in the B-ultrasound image data sequence only includes the local outer contour of the target area to generate a local outer contour sequence, where the second display magnification is greater than the first display magnification.

[0053] The processor generates a spliced outer contour according to the local outer contour sequence. The spliced outer contour is the outer contour formed after splicing the local outer contour sequence.

[0054] The processor determines a reference outer contour according to the magnification ratio between the first display magnification and the second display magnification and the overall outer contour, and according to the reference outer contour and the spliced outer contour.

[0055] The processor determines a feature observation area according to the reference outer contour and the spliced outer contour.

[0056] In the above solution, the processor acquires the scaled B-mode ultrasound image data of the target area at the first display magnification, and this data contains the overall outer contour of the target area. Subsequently, at the second display magnification (and the second display magnification is greater than the first display magnification), the processor acquires a sequence of B-mode ultrasound image data of the target area, and each data only contains the local outer contour of the target area, thereby generating a sequence of local outer contours. By acquiring image data at different display magnifications, the processor can comprehensively capture the overall and local information of the target area. This multi-magnification data acquisition method not only retains the overall structural information of the target area but also provides rich local details, providing comprehensive data support for the subsequent determination of the feature observation area. The processor extracts the overall outer contour of the target area based on the scaled B-mode ultrasound image data and generates a spliced outer contour according to the sequence of local outer contours. The spliced outer contour is the outer contour formed by splicing each local outer contour in the sequence of local outer contours. During the outer contour extraction process, the processor can utilize image edge detection techniques, such as Sobel, Prewitt, etc. operators, to accurately identify the edge information in the image. When splicing the outer contours, image registration and fusion techniques will be adopted to ensure that the spliced outer contour can accurately reflect the complete shape of the target area. The extraction and splicing of the outer contour provide the processor with the complete shape information of the target area. This complete shape information not only helps the processor more accurately identify the key features of the target area but also provides an important morphological basis for the subsequent determination of the feature observation area. Then, the processor determines the reference outer contour according to the magnification ratio between the first display magnification and the second display magnification and the overall outer contour. The reference outer contour is an important benchmark for calculating the feature observation area, and it reflects the morphological change relationship of the target area at different display magnifications. When determining the reference outer contour, the processor will consider the proportional relationship between the first display magnification and the second display magnification, as well as the shape and size of the overall outer contour. By comprehensively considering these factors, the processor can generate a reference outer contour that not only conforms to the actual morphological changes but is also convenient for calculation. The determination of the reference outer contour provides the processor with a benchmark for calculating the feature observation area. By comparing the differences between the reference outer contour and the spliced outer contour, the processor can accurately identify the feature observation area of the target area, providing important support for the subsequent navigation vector calculation and probe guidance. Finally, the processor determines the feature observation area according to the reference outer contour and the spliced outer contour. The feature observation area is the part of the target area that has not been focused on or examined, and it may contain the key features and pathological change information of the target area. During the calculation of the feature observation area, the processor will adopt mathematical methods such as Boolean difference operation to process the reference outer contour and the spliced outer contour, thereby obtaining the feature observation area. In addition, the processor will also appropriately adjust and optimize the feature observation area according to the actual inspection requirements and operation habits.The calculation of the feature observation area realizes the navigation and efficient inspection of the target area. By focusing on and inspecting the feature observation area, doctors can quickly locate the areas that may be overlooked during the inspection process, thereby improving the integrity and efficiency of the observation.

[0057] Furthermore, the above-mentioned feature observation area is the area after the Boolean difference between the reference area enclosed by the reference outer contour and the splicing area enclosed by the splicing outer contour.

[0058] In the above solution, the determination of the feature observation region is based on the Boolean difference operation between the reference outer contour and the spliced outer contour. In this application, the reference region enclosed by the reference outer contour and the spliced region enclosed by the spliced outer contour are subjected to a Boolean difference operation, and the result obtained is the feature observation region. The application of the Boolean difference operation makes the determination of the feature observation region accurate and efficient. By calculating the difference part between the two outer contours, the processor can accurately identify the parts that may be missed in the observation of the target region. Among them, the reference outer contour is extracted according to the scaled B-ultrasound image data at the first display magnification, which reflects the overall shape and approximate range of the target region. During the determination of the feature observation region, the reference outer contour serves as a stable morphological benchmark, providing a reference for the comparison and analysis of the spliced outer contour. The determination of the reference outer contour takes into account the magnification ratio between the first display magnification and the second display magnification, as well as the shape and size of the overall outer contour. By comprehensively considering these factors, the processor can generate a reference outer contour that not only conforms to the actual morphological changes but also is convenient for calculation. The stability and accuracy of the reference outer contour ensure the reliability and consistency of the determination of the feature observation region. It provides a reliable benchmark for the comparison and analysis of the spliced outer contour, making the determination of the feature observation region more accurate and credible. Moreover, the spliced outer contour is generated according to the B-ultrasound image data sequence at the second display magnification, which reflects the morphological changes and detailed features of the target region at different local positions. By comparing and analyzing with the reference outer contour, the processor can accurately identify the feature observation region in the target region. The generation of the spliced outer contour involves the extraction and splicing process of local outer contours. The processor will use image edge detection technology to accurately identify the edge information in the image and splice the local outer contours into a complete shape through advanced image registration and fusion technology. The rich detailed and morphological change information of the spliced outer contour provides an important basis for the determination of the feature observation region. By comparing and analyzing with the reference outer contour, the processor can more accurately identify the regions that may be missed in the observation of the target region, providing a more reliable basis for the doctor's diagnosis. Through the Boolean difference operation between the reference outer contour and the spliced outer contour, the processor can accurately define the feature observation region. This region contains the regions that may be missed in the observation of the target region and is an important object for the doctor to conduct supplementary observations. The determination of the feature observation region realizes the navigation and inspection of the target region, thereby improving the integrity and efficiency of the observation.

[0059] Moreover, when the second B-ultrasound display image is the overall two-dimensional simulation image of the target region, the overall two-dimensional simulation image is the two-dimensional simulation image generated according to the overall outer contour.

[0060] In the above solution, the processor obtains the scaled B-ultrasound image data of the target area at the first display magnification and extracts the overall outer contour of the target area from it. The extraction of the overall outer contour provides a morphological basis for the subsequent generation of two-dimensional simulation images. It ensures that the simulation image can reflect the overall shape and structural characteristics of the target area and provides an important morphological basis for subsequent diagnosis. Based on the extracted overall outer contour, the processor generates the overall two-dimensional simulation image of the target area. This simulation image not only retains the overall shape of the target area but also enhances the visual effect and readability of the image through the adjustment of visual elements such as color and brightness. During the process of generating the two-dimensional simulation image, the processor can also adopt image rendering and visualization techniques to generate the image color and brightness distribution that conforms to visual habits according to the shape and size of the overall outer contour. In addition, in the B-ultrasound navigation image data, the overall two-dimensional simulation image is usually combined with the local B-ultrasound display image. The local B-ultrasound display image provides the detailed local enlarged structure of the target area, while the overall two-dimensional simulation image provides a macroscopic view of the overall shape and position. The combination of the overall two-dimensional simulation image and the local B-ultrasound display image provides comprehensive and intuitive diagnostic information for doctors. Doctors can not only observe the detailed structure of the target area through the local B-ultrasound display image but also understand the overall shape and positional relationship of the target area through the overall two-dimensional simulation image, thus making a more accurate diagnosis.

[0061] In addition, the processor determines the current observed feature area according to the local outer contour and the image boundary of the target area in the B-ultrasound image data obtained by the B-ultrasound probe at the current moment, maps the current observed feature area to the overall two-dimensional simulation image to determine the current observed mapping area, and determines the centroid position of the current observed mapping area as the current visual feature point. The processor maps the feature observation area to the overall two-dimensional simulation image to determine the feature observation mapping area and determines the centroid position of the feature observation mapping area as the target visual feature point.

[0062] In the above solution, by extracting the local outer contour and the image boundary of the target area from the B-ultrasound image data obtained by the B-ultrasound probe at the current moment, the system can accurately define the current observation feature area. This step ensures that the selected local image area contains the target structure and has a clear boundary, providing an accurate basis for subsequent positioning operations. Mapping the current observation feature area to the overall two-dimensional simulation image and calculating its centroid position as the current visual feature point further improves the accuracy of positioning. The selection of the centroid position as the feature point effectively avoids positioning errors caused by the complexity of the local image and ensures the stability of the navigation process. The feature observation area, as the target area of navigation, the centroid position after mapping it to the overall two-dimensional simulation image is determined as the target visual feature point. This process not only considers the overall shape of the target area but also ensures the uniqueness and accuracy of the target point through centroid calculation, providing an accurate target direction for the generation of the navigation vector. Then, when generating the B-ultrasound navigation image data, the processor superimposes the navigation vector containing the current visual feature point and the target visual feature point onto the second B-ultrasound display image (i.e., the overall two-dimensional simulation image). This process not only makes the navigation information more intuitive but also enhances the readability of the image through visual elements such as colors and lines, facilitating doctors to quickly understand and apply the navigation information. Through the navigation guidance, doctors can find the target area faster and perform supplementary examinations, which not only shortens the overall examination time, improves the examination efficiency, but also ensures the integrity of the examination.

[0063] In another possible implementation, it can be to obtain the scaled B-ultrasound image data of the target area at the first display magnification, and the scaled B-ultrasound image data includes the overall outer contour of the target area.

[0064] The processor extracts the overall outer contour of the target area according to the scaled B-ultrasound image data and generates a reference area according to the overall outer contour.

[0065] At the second display magnification, obtain a sequence of B-ultrasound image data of the target area, and each B-ultrasound image data in the sequence of B-ultrasound image data only includes the local outer contour of the target area to generate a local outer contour sequence, where the second display magnification is greater than the first display magnification.

[0066] The processor determines the observation feature area according to each local outer contour in the local outer contour sequence and the corresponding image boundary, and determines the centroid position of the observation feature area as the visual feature point to form a sequence of visual feature points corresponding to the local outer contour sequence.

[0067] The processor generates a visual trajectory contour according to the sequence of visual feature points and generates a visual coverage area according to the visual trajectory contour, where the visual trajectory contour is a closed contour formed based on the outermost visual feature points in the sequence of visual feature points.

[0068] The processor determines the feature observation area based on the reference area and the visual coverage area.

[0069] In the above solution, it is possible to obtain the scaled B-ultrasound image data of the target area at the first display magnification, and this data contains the overall outer contour of the target area. This step ensures that the overall structural information of the target area is completely retained. Obtain the B-ultrasound image data sequence of the target area at the second display magnification (and the second display magnification is greater than the first display magnification), and each data only contains the local outer contour of the target area, thereby generating a local outer contour sequence. This step provides the local detail information of the target area, making the subsequent determination of the feature observation area more accurate.

[0070] By fusing the overall outer contour information at the first display magnification and the local outer contour information at the second display magnification, it is possible to comprehensively capture the overall and local features of the target area, providing comprehensive data support for the subsequent determination of the feature observation area. Extract the overall outer contour of the target area according to the scaled B-ultrasound image data, and generate a reference area based on the overall outer contour. The reference area serves as the basis for the subsequent determination of the feature observation area, providing the approximate range and morphological benchmark of the target area. Determine the observation feature area according to each local outer contour in the local outer contour sequence and the corresponding image boundary, and calculate the centroid position of the observation feature area as the visual feature point. This step accurately defines the observation feature area and determines the key visual feature points by extracting and analyzing the local image features. Generate a visual trajectory contour according to the visual feature point sequence, and this contour is a closed contour formed based on the outermost visual feature points in the visual feature point sequence. The visual trajectory contour reflects the line-of-sight movement trajectory during the inspection process, providing important dynamic information for the subsequent determination of the feature observation area. Generate a visual coverage area according to the visual trajectory contour, and this area covers the area that has been observed by the B-ultrasound probe during the inspection process. By comparing the reference area and the visual coverage area, the unobserved feature observation area can be defined. Finally, determine the feature observation area through a Boolean difference operation, that is, the difference part between the reference area and the visual coverage area. This step realizes the accurate identification of the unobserved part in the target area, providing important support for the subsequent navigation vector calculation and probe guidance. Through the accurate determination of the feature observation area, the present invention can help doctors quickly locate the unobserved part in the target area, thereby avoiding inspection omissions and improving the integrity of the inspection.

[0071] The navigation vector is generated based on the feature observation area, which can accurately indicate the movement direction of the B-ultrasound probe, helping doctors complete the examination task more efficiently and improving the examination efficiency. At the same time, the B-ultrasound navigation image data contains local and overall image information as well as accurate navigation marks, providing doctors with intuitive and comprehensive image information, which helps doctors judge the condition more accurately and improve the accuracy of diagnosis.

[0072] Further, the processor determines that the area determined after performing a Boolean difference operation on the reference area and the visual coverage area is the feature observation area.

[0073] Prior to this, the processor has extracted the overall outer contour of the target area based on the scaled B-ultrasound image data and generated a reference area, which represents the morphological range of the target area in an ideal state. At the same time, the processor has also generated a visual coverage area based on the local outer contour sequence and the corresponding visual feature point sequence, which reflects the possible activity range of the target area in the B-ultrasound image data sequence.

[0074] The precise positioning of these two areas provides a basis for the subsequent determination of the feature observation area. Through the Boolean difference operation, the processor determines the difference part between the reference area and the visual coverage area as the feature observation area. This area not only reflects the overall morphology of the target area but also contains the dynamic change information of the target area in the B-ultrasound image data sequence. The precise definition of the feature observation area helps doctors understand the performance of the target area in the B-ultrasound image more accurately, thereby making a more accurate diagnosis. In medical diagnosis, any tiny detail may have an important impact on the diagnosis result. Therefore, improving the precision of the feature observation area is of great significance for improving the accuracy and reliability of B-ultrasound examinations.

[0075] Further, after generating the visual coverage area based on the visual trajectory contour, the processor can also generate a visual expansion area based on the visual coverage area. The visual expansion area is an expansion area formed by expanding a preset size outward from the visual coverage area on the basis of the visual coverage area.

[0076] Correspondingly, the above-mentioned processor determines the feature observation area based on the reference area and the visual coverage area, including: the processor determines that the area determined after performing a Boolean difference operation on the reference area with respect to the visual expansion area is the feature observation area.

[0077] In the above solution, after generating the visual coverage area, the processor further expands it outward by a preset size to form a visual expansion area. When determining the feature observation area, the processor uses the Boolean difference operation, but the objects of this operation are the reference area and the visual expansion area, rather than the original visual coverage area. By performing the Boolean difference operation with the visual expansion area, the processor can more accurately define the feature observation area. This area not only contains the overall morphological information of the target area but also takes into account the visual expansion factor, thereby improving the accuracy and reliability of the feature observation area. It should be noted that the above-mentioned outward expansion by a preset size can be set personalized by the doctor.

[0078] Compared with the feature observation area determined only based on the visual coverage area, the feature observation area obtained by performing the Boolean difference operation using the visual expansion area is more accurate and comprehensive. This area not only covers the main observation range of the target area but also includes its potential visual expansion area. The accurate definition of the feature observation area has an important impact on the diagnostic accuracy of B-ultrasound examinations. By improving the accuracy and comprehensiveness of the feature observation area, doctors can more accurately understand the performance of the target area in B-ultrasound images and thus make more accurate diagnoses.

[0079] In another possible implementation, it can be that at the first display magnification, the scaled B-ultrasound image data of the target area is obtained, and the scaled B-ultrasound image data includes the overall outer contour of the target area.

[0080] The processor extracts the overall outer contour of the target area based on the scaled B-ultrasound image data and generates a reference area according to the overall outer contour.

[0081] At the second display magnification, a sequence of B-ultrasound image data of the target area is obtained. Each B-ultrasound image data in the sequence of B-ultrasound image data only includes the local outer contour of the target area to generate a local outer contour sequence, where the second display magnification is greater than the first display magnification.

[0082] The processor determines the observation feature area based on each local outer contour in the local outer contour sequence and the corresponding image boundary, and determines the centroid position of the observation feature area as the visual feature point to form a sequence of visual feature points corresponding to the local outer contour sequence.

[0083] The processor determines the effective visual range based on each visual feature point in the sequence of visual feature points to generate a sequence of effective visual ranges corresponding to the sequence of visual feature points, where the effective visual range is a circular range with the visual feature as the geometric center.

[0084] The processor generates an effective visual coverage area based on the sequence of effective visual ranges, where the range after performing the Boolean union operation on all the effective visual ranges in the sequence of effective visual ranges is the effective visual coverage area.

[0085] The processor determines that the area determined after performing the Boolean difference operation between the reference area and the effective visual coverage area is the feature observation area.

[0086] In the above solution, at the first display magnification, the processor obtains the scaled B-ultrasound image data of the target area. This step effectively reduces the complexity of the image, enabling the overall outer contour of the target area to be clearly presented. Through this step, the processor can accurately extract the overall outer contour of the target area, providing a global reference basis for the subsequent determination of the feature observation area. Based on the extracted overall outer contour, the processor generates a reference area. The reference area, as the approximate range of the target area, provides a benchmark for subsequent local detail analysis and determination of the feature observation area.

[0087] At the second display magnification, the processor obtains a sequence of B-ultrasound image data of the target area, and each piece of data only contains the local outer contour of the target area. Since the second display magnification is higher than the first display magnification, it can capture the local details of the target area more precisely. These local outer contour information are organized into a local outer contour sequence, providing rich data support for subsequent feature analysis.

[0088] The processor determines the observation feature areas according to each local outer contour in the local outer contour sequence and the corresponding image boundaries, and calculates the centroid position of each observation feature area as the visual feature point. The construction of the visual feature point sequence enables the processor to track the dynamic change trajectory of the target area in the B-ultrasound image data sequence.

[0089] The processor determines the effective visual range according to each visual feature point in the visual feature point sequence. The effective visual range is defined as a circular range with the visual feature point as the geometric center. This setting fully considers the shape and size change characteristics of the target area in the B-ultrasound image, and also conforms to the visual field habit of human vision, enabling the effective visual range to accurately cover the possible activity range of the target area.

[0090] By performing the Boolean union operation on all the effective visual ranges, the processor generates the effective visual coverage area. The effective visual coverage area comprehensively reflects the activity trajectory and range of the target area in the B-ultrasound image data sequence, providing key information for the subsequent determination of the feature observation area. The processor determines the difference part between the reference area and the effective visual coverage area as the feature observation area through the Boolean difference operation. This step fully considers the overall shape and local dynamic change information of the target area, making the definition of the feature observation area more accurate and comprehensive. The accurate definition of the feature observation area helps to improve the accuracy and efficiency of B-ultrasound examination, providing a more reliable diagnostic basis for doctors.

[0091] In addition, for the above solution, it is worth noting that the effective visual coverage area generated by the above processor based on the effective visual range sequence may cover the boundary position of the target area while ignoring the intermediate position. It can be understood that when a doctor performs a B-ultrasound examination, from the perspective of effective visual coverage, there are some areas in the middle of the target area that are not carefully observed or are missed.

[0092] S203. The processor determines the current visual feature points according to the B-ultrasound image data obtained by the B-ultrasound probe at the current moment, and determines the target visual feature points according to the feature observation area.

[0093] Specifically, the processor obtains in real time the B-ultrasound image data obtained by the B-ultrasound probe at the current moment. These data reflect the shape and position information of the target area from the current perspective. The processor processes the current B-ultrasound image data and uses image processing techniques (such as feature extraction, edge detection, etc.) to determine the current visual feature points. The current visual feature points are the main feature points of the target area from the current perspective and are used to indicate the specific position of the target area in the current image. According to the previously determined feature observation area, the processor determines the target visual feature points within the feature observation area. The target visual feature points are the ideal observation points of the target area within the feature observation area and are used to indicate the main observation direction and target position of the target area. For example, the above target visual feature points can be the centroid position of the area formed by the detected contour after edge detection.

[0094] S204. The processor determines the navigation vector according to the current visual feature points and the target visual feature points.

[0095] In this step, the processor determines the navigation vector according to the current visual feature points and the target visual feature points. The navigation vector is a vector used to indicate the vector from the current visual feature points to the target visual feature points.

[0096] Specifically, the processor calculates the navigation vector according to the position information of the current visual feature points and the target visual feature points. The navigation vector is a vector used to indicate the direction and distance from the current visual feature points to the target visual feature points. It helps the doctor or operator understand how to move the B-ultrasound probe from the current position to the target position in order to more accurately observe and analyze the target area. Once the navigation vector is calculated, it can be applied to the operation of the B-ultrasound device. The doctor or operator can adjust the position and angle of the B-ultrasound probe according to the indication of the navigation vector in order to more accurately obtain the B-ultrasound image data of the target area.

[0097] In the actual operation process, the processor can obtain new B-ultrasound image data in real time and update the current visual feature points and the navigation vector according to these data. This real-time update and adjustment mechanism ensures the accuracy and reliability of the navigation vector and improves the efficiency and accuracy of B-ultrasound examinations.

[0098] S205. The processor generates a first B-ultrasound display image and a second B-ultrasound display image.

[0099] In this step, the processor generates a first B-ultrasound display image and a second B-ultrasound display image. The B-ultrasound navigation image data includes the first B-ultrasound display image and the second B-ultrasound display image. Among them, the first B-ultrasound display image is a local B-ultrasound image of the target area, and the second B-ultrasound display image is a two-dimensional simulation image corresponding to the object to be detected or an overall two-dimensional simulation image of the target area.

[0100] Specifically, the processor first generates a local B-ultrasound image of the target area, that is, the first B-ultrasound display image, according to the B-ultrasound image data. This image is a local image of the target area from the current perspective of the B-ultrasound probe, showing the detailed structure and morphology of the target area. The processor can use image processing techniques (such as image enhancement, denoising, etc.) to process the original B-ultrasound image data to improve the clarity and contrast of the image, so as to generate a more accurate first B-ultrasound display image.

[0101] Then, the processor generates a two-dimensional simulation image corresponding to the object to be detected or an overall two-dimensional simulation image of the target area, that is, the second B-ultrasound display image. This image provides an overall view of the object to be detected, helping doctors or operators understand the positional relationship of the target area in the overall structure. For the two-dimensional simulation image, the processor may use three-dimensional reconstruction techniques to convert the B-ultrasound image data into a two-dimensional view, or generate a simulation image according to known anatomical structure information. And for the above three-dimensional reconstruction techniques, it can be any one of the existing three-dimensional reconstruction techniques, which is not specifically limited in this embodiment. It is worth noting that the above overall two-dimensional simulation image is a simulation image that reflects the main features when needed, rather than an accurate image. Because its purpose is to be used for navigation, rather than for doctors to make a diagnosis. Therefore, in the process of generation, the generation efficiency can be mainly considered, and then the generation accuracy.

[0102] S206. The processor superimposes a navigation identifier corresponding to the navigation vector on the second B-ultrasound display image to generate a second processed display image.

[0103] Specifically, the processor determines the position and direction of the navigation vector in the second B-ultrasound display image according to the previously generated navigation vector. The navigation vector indicates the direction and distance from the current visual feature point to the target visual feature point, which is an important basis for guiding doctors or operators to adjust the position of the B-ultrasound probe.

[0104] Based on the position and orientation information of the navigation vector, the processor generates corresponding navigation marks in the second B-ultrasound display image. The navigation marks may be an arrow, a line segment, or other graphical elements, which are used to intuitively represent the direction and distance of the navigation vector. Attributes such as the color, size, and shape of the navigation marks can be adjusted as needed to ensure that they are clearly visible in the second B-ultrasound display image.

[0105] The processor superimposes the generated navigation marks on the second B-ultrasound display image to form a second processed display image. This step ensures the combination of the navigation vector with the overall view of the object to be detected, providing more intuitive and comprehensive guiding information for doctors or operators.

[0106] S207. The processor generates B-ultrasound navigation image data based on the first B-ultrasound display image and the second processed display image.

[0107] Specifically, the processor merges the first B-ultrasound display image and the second processed display image to generate B-ultrasound navigation image data. This step combines the local B-ultrasound image of the target area with the overall view of the object to be detected, providing comprehensive diagnostic information for doctors or operators.

[0108] After generating the B-ultrasound navigation image data, the processor may perform further optimization processing on it, such as adjusting parameters such as the contrast and brightness of the image to improve the visual effect of the image.

[0109] Finally, the processor outputs the optimized B-ultrasound navigation image data to the display device for doctors or operators to view and analyze.

[0110] Figure 3 It is a schematic structural diagram of a B-ultrasound device operation platform shown according to an exemplary embodiment of the present application. As Figure 3 shown, the B-ultrasound device operation platform 300 provided in this embodiment includes: a B-ultrasound probe 310, a processor 320, and a display 330. The processor 320 is communicatively connected to the B-ultrasound probe 310 and the display 330 respectively; Obtain a navigation mode trigger instruction through the trigger button on the B-ultrasound probe 310 and upload the navigation mode trigger instruction to the processor 320; The processor 320 responds to the navigation mode trigger instruction and generates a navigation vector based on the B-ultrasound image data of the target area of the object to be detected. The navigation vector is at least used to guide the movement direction of the B-ultrasound probe 310; The processor 320 generates B-ultrasound navigation image data based on the navigation vector and the B-ultrasound image data, and displays the B-ultrasound navigation image data through the display 330.

[0111] Optionally, the processor 320 generates B-ultrasound navigation image data based on the navigation vector and the B-ultrasound image data, including: The processor 320 generates a first B-ultrasound display image and a second B-ultrasound display image. The B-ultrasound navigation image data includes the first B-ultrasound display image and the second B-ultrasound display image. Among them, the first B-ultrasound display image is a local B-ultrasound image of the target area, and the second B-ultrasound display image is a two-dimensional simulation image corresponding to the object to be detected or an overall two-dimensional simulation image of the target area; The processor 320 superimposes a navigation identifier corresponding to the navigation vector on the second B-ultrasound display image to generate a second processed display image; The processor 320 generates the B-ultrasound navigation image data based on the first B-ultrasound display image and the second processed display image.

[0112] Optionally, generating a navigation vector based on the B-ultrasound image data of the target area of the object to be detected includes: The processor 320 determines a characteristic observation area of the target area according to a sequence of B-ultrasound image data, where the sequence of B-ultrasound image data includes B-ultrasound image data obtained by the B-ultrasound probe 310 at different area positions of the object to be detected; The processor 320 determines a current visual feature point according to the B-ultrasound image data obtained by the B-ultrasound probe 310 at the current moment, and determines a target visual feature point according to the characteristic observation area; The processor 320 determines the navigation vector according to the current visual feature point and the target visual feature point. The navigation vector is a vector used to indicate the direction from the current visual feature point to the target visual feature point.

[0113] Optionally, the processor 320 determines the characteristic observation area of the target area according to the sequence of B-ultrasound image data, including: At a first display magnification, scaled B-ultrasound image data of the target area is obtained, and the scaled B-ultrasound image data includes the overall outer contour of the target area; The processor 320 extracts the overall outer contour of the target area according to the scaled B-ultrasound image data; At a second display magnification, the sequence of B-ultrasound image data of the target area is obtained. Each B-ultrasound image data in the sequence of B-ultrasound image data only includes a local outer contour of the target area to generate a local outer contour sequence, where the second display magnification is greater than the first display magnification; The processor 320 generates a spliced outer contour according to the local outer contour sequence. The spliced outer contour is an outer contour formed after splicing the local outer contour sequence. The processor 320 determines a reference outer contour according to the magnification ratio between the first display magnification and the second display magnification and the overall outer contour, and according to the reference outer contour and the spliced outer contour; The processor 320 determines the feature observation area according to the reference outer contour and the spliced outer contour.

[0114] Optionally, the processor 320 determines the feature observation area according to the reference outer contour and the spliced outer contour, including: The feature observation area is the area after performing a Boolean difference between the reference area enclosed by the reference outer contour and the spliced area enclosed by the spliced outer contour.

[0115] Optionally, when the second B-ultrasound display image is the overall two-dimensional simulation image of the target area, the overall two-dimensional simulation image is a two-dimensional simulation image generated according to the overall outer contour.

[0116] Optionally, the processor 320 determines a current visual feature point according to the B-ultrasound image data acquired by the B-ultrasound probe 310 at the current moment, and determines a target visual feature point according to the feature observation area, including: The processor 320 determines a current observation feature area according to the local outer contour and the image boundary of the target area in the B-ultrasound image data acquired by the B-ultrasound probe 310 at the current moment, maps the current observation feature area to the overall two-dimensional simulation image to determine a current observation mapping area, and determines the centroid position of the current observation mapping area as the current visual feature point; The processor 320 maps the feature observation area to the overall two-dimensional simulation image to determine a feature observation mapping area, and determines the centroid position of the feature observation mapping area as the target visual feature point.

[0117] Figure 4 It is a schematic structural diagram of an electronic device shown according to an exemplary embodiment of the present application. As Figure 4 shown, an electronic device 400 provided in this embodiment includes: a processor 401 and a memory 402; wherein: The memory 402 is used to store a computer program, and this memory can also be a flash (flash memory).

[0118] The processor 401 is used to execute the execution instructions stored in the memory to implement each step in the above method. Specifically, reference can be made to the relevant descriptions in the foregoing method embodiments.

[0119] Optionally, the memory 402 can be either independent or integrated with the processor 401.

[0120] When the memory 402 is a device independent of the processor 401, the electronic device 400 may further include: A bus 403 for connecting the memory 402 and the processor 401.

[0121] This embodiment also provides a readable storage medium. A computer program is stored in the readable storage medium. When at least one processor of the electronic device executes the computer program, the electronic device executes the methods provided by the above various embodiments.

[0122] This embodiment also provides a program product. The program product includes a computer program which is stored in a readable storage medium. At least one processor of the electronic device can read the computer program from the readable storage medium, and the execution of the computer program by at least one processor causes the electronic device to implement the methods provided by the above various embodiments.

[0123] Those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include common general knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and embodiments are to be considered as exemplary only, and the true scope and spirit of the present application are pointed out by the claims.

[0124] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A method for processing B-ultrasound image data, characterized in that: Applied to a B-ultrasound device operating platform, the B-ultrasound device operating platform includes a B-ultrasound probe, a processor and a display, the processor is respectively connected to the B-ultrasound probe and the display for communication; the method includes: Acquire a navigation mode trigger instruction through a trigger button on the B-ultrasound probe, and upload the navigation mode trigger instruction to the processor; The processor responds to the navigation mode trigger instruction and generates a navigation vector according to the B-ultrasound image data of the target area of ​​the object to be detected, wherein the navigation vector is at least used to guide the movement direction of the B-ultrasound probe; The processor generates B-ultrasound navigation image data according to the navigation vector and the B-ultrasound image data, and displays the B-ultrasound navigation image data through the display.

2. The method for processing B-ultrasound image data according to claim 1, characterized in that: The processor generates B-ultrasound navigation image data according to the navigation vector and the B-ultrasound image data, including: The processor generates a first B-ultrasound display image and a second B-ultrasound display image, and the B-ultrasound navigation image data includes the first B-ultrasound display image and the second B-ultrasound display image, wherein the first B-ultrasound display image is a local B-ultrasound image of the target area, and the second B-ultrasound display image is a two-dimensional simulation image corresponding to the object to be detected or an overall two-dimensional simulation image of the target area; The processor superimposes the navigation mark corresponding to the navigation vector on the second B-ultrasound display image to generate a second processed display image; The processor generates the B-ultrasound navigation image data according to the first B-ultrasound display image and the second processed display image.

3. The method for processing B-ultrasound image data according to claim 2, characterized in that: The step of generating a navigation vector according to the B-ultrasound image data of the target area of ​​the object to be detected comprises: The processor determines the characteristic observation area of ​​the target area according to the B-ultrasound image data sequence, wherein the B-ultrasound image data sequence includes the B-ultrasound image data acquired by the B-ultrasound probe at different regional positions of the object to be detected; The processor determines the current visual feature point according to the B-ultrasound image data acquired by the B-ultrasound probe at the current moment, and determines the target visual feature point according to the characteristic observation area; The processor determines the navigation vector according to the current visual feature point and the target visual feature point, where the navigation vector is a vector indicating a distance from the current visual feature point to the target visual feature point.

4. The method for processing B-ultrasound image data according to claim 3, characterized in that: The processor determines the characteristic observation area of ​​the target area according to the B-ultrasound image data sequence, including: Under a first display magnification, obtaining zoomed B-ultrasound image data of the target area, wherein the zoomed B-ultrasound image data includes an overall outer contour of the target area; The processor extracts the overall outer contour of the target area according to the scaled B-ultrasound image data; Under a second display magnification, acquiring the B-ultrasound image data sequence of the target area, each B-ultrasound image data in the B-ultrasound image data sequence only includes a local outer contour of the target area, so as to generate a local outer contour sequence, wherein the second display magnification is greater than the first display magnification; The processor generates a spliced ​​outer contour according to the local outer contour sequence, wherein the spliced ​​outer contour is an outer contour formed after the local outer contour sequence is spliced; The processor determines a reference outer contour according to a ratio between the first display magnification and the second display magnification and the overall outer contour, and determines a reference outer contour according to the reference outer contour and the spliced ​​outer contour; The processor determines the feature observation area according to the reference outer contour and the spliced ​​outer contour.

5. The method for processing B-ultrasound image data according to claim 4, characterized in that: The processor determines the feature observation area according to the reference outer contour and the spliced ​​outer contour, including: The feature observation area is an area obtained by performing Boolean difference between a reference area enclosed by the reference outer contour and a spliced ​​area enclosed by the spliced ​​outer contour.

6. The method for processing B-ultrasound image data according to claim 4 or 5, characterized in that: When the second B-ultrasound display image is the overall two-dimensional simulated image of the target area, the overall two-dimensional simulated image is a two-dimensional simulated image generated according to the overall outer contour.

7. The method for processing B-ultrasound image data according to claim 6, characterized in that: The processor determines the current visual feature point according to the B-ultrasound image data acquired by the B-ultrasound probe at the current moment, and determines the target visual feature point according to the characteristic observation area, including: The processor determines the current observed feature area according to the local outer contour and image boundary of the target area in the B-ultrasound image data acquired by the B-ultrasound probe at the current moment, and maps the current observed feature area to the overall two-dimensional simulated image to determine the current observed mapping area, and determines the center of gravity position of the current observed mapping area as the current visual feature point; The processor maps the feature observation area into the overall two-dimensional simulated image to determine the feature observation mapping area, and determines the center of gravity position of the feature observation mapping area as the target visual feature point.

8. A B-ultrasound equipment operating platform, characterized in that: include: A B-ultrasound probe, a processor and a display, wherein the processor is communicatively connected to the B-ultrasound probe and the display respectively; Acquire a navigation mode trigger instruction through a trigger button on the B-ultrasound probe, and upload the navigation mode trigger instruction to the processor; The processor responds to the navigation mode trigger instruction and generates a navigation vector according to the B-ultrasound image data of the target area of ​​the object to be detected, wherein the navigation vector is at least used to guide the movement direction of the B-ultrasound probe; The processor generates B-ultrasound navigation image data according to the navigation vector and the B-ultrasound image data, and displays the B-ultrasound navigation image data through the display.

9. An electronic device, characterized in that: include: processor; as well as, A memory, configured to store executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 7 by executing the executable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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