Parameter detection method, ultrasonic device and storage medium

Abstract

This invention relates to the field of ultrasound equipment technology, specifically to a parameter detection method, an ultrasound device, and a storage medium. The method includes: acquiring multiple ultrasound images; comparing the ultrasound images with a target IVC (Intracytoplasmic Voice Capacitor) cross-sectional image to determine and display the image quality of the ultrasound images, thereby obtaining a target ultrasound image that meets preset quality conditions; determining the position of sampling lines based on the type and characteristics of the target ultrasound images to determine the region of interest (ROI); and determining IVC parameters based on the characteristics of the ROI image. This method ensures the accuracy of the determined sampling lines, does not rely on user experience, and further guarantees the accuracy of the ROI image. Then, the ultrasound device determines the IVC parameters based on the characteristics of the ROI image, thus ensuring the accuracy of the determined IVC parameters.

Description

Technical Field

[0001] This invention relates to the field of ultrasonic equipment technology, specifically to a parameter detection method, ultrasonic equipment, and storage medium. Background Technology

[0002] With the development of science and technology, ultrasound examinations are increasingly being used by clinicians to measure the inferior vena cava (IVC). Inferior vena cava parameters are a means of assessing patient volume overload using bedside ultrasound, clinically determining whether there is sufficient blood supply to the end organs and assisting physicians in making decisions.

[0003] In existing technologies, to measure IVC, clinicians must use one hand to hold the ultrasound probe while using the other hand to perform the IVC measurement on the ultrasound device, or perform the measurement offline.

[0004] Therefore, ultrasound IVC measurement is affected not only by probe movement but also by the movement of IVC with respiration. Conventional methods are complicated and cumbersome, and M-line positioning involves certain subjective factors, which leads to inaccurate IVC parameters. Summary of the Invention

[0005] In view of this, embodiments of the present invention provide a parameter detection method, an ultrasound device, and a storage medium to solve the problem of inaccurate IVC parameters.

[0006] According to a first aspect, embodiments of the present invention provide a parameter detection method, the method comprising:

[0007] Acquire multiple ultrasound images; the types of ultrasound images include IVC transverse and IVC longitudinal sections;

[0008] The ultrasound image is compared with the target IVC cross-sectional image to determine and display the image quality of the ultrasound image, so as to obtain a target ultrasound image that meets the preset quality conditions.

[0009] Based on the type and characteristics of the target ultrasound image, the location of the sampling line is determined to identify the region of interest.

[0010] IVC parameters are determined based on the characteristics of the region of interest in the image.

[0011] The parameter detection method provided in this invention acquires multiple ultrasound images, including IVC transverse and longitudinal sections, enabling parameter detection on both IVC transverse and longitudinal ultrasound images. Then, the ultrasound images are compared with a target IVC section image to determine and display the image quality, ensuring the target ultrasound image's quality and preventing inaccurate IVC parameters due to poor target image quality. Furthermore, based on the type and characteristics of the target ultrasound image, the location of sampling lines is determined to identify the region of interest (ROI), ensuring the accuracy of the determined sampling lines and eliminating reliance on user experience, further guaranteeing the accuracy of the ROI image. Finally, the ultrasound device determines the IVC parameters based on the characteristics of the ROI image, ensuring the accuracy of the determined IVC parameters.

[0012] In conjunction with the first aspect, in the first embodiment of the first aspect, comparing an ultrasound image with a target IVC cross-sectional image to determine and display the image quality of the ultrasound image includes:

[0013] Quality identification of ultrasound images;

[0014] Based on the quality identification results, the ultrasound image is compared with the target IVC cross-sectional image to determine and display the image quality of the ultrasound image on the ultrasound interface.

[0015] The parameter detection method provided in this invention performs quality identification on ultrasound images, compares the ultrasound images with the target IVC cross-sectional images based on the quality identification results, determines and displays the image quality of the ultrasound images, thereby ensuring the accuracy of the displayed ultrasound image quality.

[0016] In conjunction with the first embodiment of the first aspect, in the second embodiment of the first aspect, the ultrasound interface includes a quality display area, and displaying the image quality of the ultrasound image on the ultrasound interface includes:

[0017] The quality of the ultrasound image is compared with the threshold of each quality level to determine the corresponding quality level of the ultrasound image.

[0018] The quality display area shows the corresponding indicator for the quality level.

[0019] The parameter detection method provided in this invention determines the quality level of the ultrasound image by comparing the quality of the ultrasound image with thresholds for each quality level, and displays the corresponding identifier of the quality level in the quality display area, so that users can quickly obtain the quality of the ultrasound image.

[0020] In conjunction with the second embodiment of the first aspect, in the third embodiment of the first aspect, the quality display area includes a quality progress bar, and displays an indicator corresponding to the quality level in the quality display area, including:

[0021] The actual progress of the quality progress bar is determined based on the quality level.

[0022] The actual progress of the quality progress bar is displayed in the quality display area.

[0023] The parameter detection method provided in this invention determines the actual progress of a quality progress bar based on the quality level of the ultrasound image and displays the actual progress of the quality progress bar in the quality display area. This allows users to quickly and intuitively determine the quality level of the current ultrasound image based on the actual progress of the quality progress bar.

[0024] In conjunction with the third embodiment of the first aspect, the fourth embodiment of the first aspect further includes displaying an identifier corresponding to the quality level in the quality display area, and further includes:

[0025] The first fill indicator of the quality progress bar is determined based on the quality level;

[0026] The first fill indicator is overlaid with the actual progress in the quality display area.

[0027] The parameter detection method provided in this embodiment of the invention determines the first fill indicator of the quality progress bar based on the quality level; the first fill indicator and the actual progress are superimposed and displayed in the quality display area, so that the user can quickly and intuitively determine the quality level of the current ultrasound image based on the actual progress of the quality progress bar and the first fill indicator of the quality progress bar.

[0028] In conjunction with the second embodiment of the first aspect, in the fifth embodiment of the first aspect, the ultrasound interface includes an ultrasound image display area, and the image quality of displaying ultrasound images on the ultrasound interface further includes:

[0029] Obtain the ultrasound image contour corresponding to the ultrasound image;

[0030] The second fill identifier corresponding to the ultrasound image contour is determined based on the quality level;

[0031] A second fill identifier is displayed in the ultrasound image display area based on the ultrasound image contour.

[0032] The parameter detection method provided in this invention obtains the ultrasound image contour corresponding to the ultrasound image; then, it determines a second fill identifier corresponding to the ultrasound image contour based on the quality level; and displays the second fill identifier in the ultrasound image display area based on the ultrasound image contour. This allows users to intuitively and quickly determine the image quality of the ultrasound image based on the ultrasound image contour corresponding to it.

[0033] In conjunction with the first aspect, in the sixth embodiment of the first aspect, determining the location of the sampling line based on the type and characteristics of the target ultrasound image to determine the region of interest includes:

[0034] Based on the type and characteristics of the target ultrasound image, the sampling points are determined;

[0035] Based on the location of the sampling points and the location information of the IVC in the target ultrasound image, the location of the sampling line is determined to identify the region of interest in the image.

[0036] The parameter detection method provided in this invention determines sampling points based on the type and features of the target ultrasound image. Then, based on the location of the sampling points and the location information of the IVC (Intravascular Coefficient) in the target ultrasound image, it determines the location of the sampling line to identify the region of interest. This ensures the accuracy of the determined sampling point locations and further guarantees the accuracy of the determined sampling line locations.

[0037] In conjunction with the sixth embodiment of the first aspect, in the seventh embodiment of the first aspect, the method further includes:

[0038] When the image quality near the sampling point meets the preset requirements, the region of interest is determined based on the location of the sampling point;

[0039] Perform quality inspection on the region of interest to determine the image quality of the region of interest, and display the image quality of the region of interest.

[0040] The parameter detection method provided in this invention determines the region of interest (ROI) based on the location of the sampling point when the image quality near the sampling point meets preset requirements, thus ensuring the accuracy of the determined ROI. Then, quality detection is performed on the ROI to determine and display its image quality. This allows users to obtain the image quality of the ROI while ensuring that the image quality meets user needs. Furthermore, it guarantees the accuracy of the IVC parameters determined based on the characteristics of the ROI image.

[0041] In conjunction with the seventh embodiment of the first aspect, the eighth embodiment of the first aspect further includes:

[0042] When the image quality near the sampling point does not meet the preset requirements, the system responds to the adjustment command for the sampling point to determine the position of the adjusted sampling point.

[0043] Based on the adjusted sampling point locations, determine the region of interest;

[0044] The system identifies the quality of regions of interest and issues a warning message when the quality of a region of interest does not meet preset requirements.

[0045] The parameter detection method provided in this embodiment of the invention, when the image quality near a sampling point does not meet preset requirements, responds to an adjustment command for the sampling point to determine the position of the adjusted sampling point, thereby ensuring the accuracy of the adjusted sampling point position. Then, based on the position of the adjusted sampling point, the region of interest (ROI) is determined, thereby ensuring the accuracy of the ROI. The quality of the ROI is then identified, and a prompt message is issued when the quality of the ROI does not meet preset requirements. This ensures the quality of the ROI and avoids inaccurate IVC parameters due to poor ROI quality.

[0046] In conjunction with the first aspect, in the ninth embodiment of the first aspect, determining the IVC parameters based on the features of the image of the region of interest includes:

[0047] Based on the type of target ultrasound image corresponding to the region of interest, the region of interest is preprocessed to obtain the target image at the sampling line position corresponding to the region of interest;

[0048] Based on the ultrasound images of each target, adaptive interpolation processing is performed on each target image;

[0049] Based on the target images after adaptive interpolation, generate M-maps and display them;

[0050] Based on the M-chart, determine the IVC parameters, generate a parameter trend chart based on the IVC parameters, and display the parameter trend chart.

[0051] The parameter detection method provided in this invention preprocesses the region of interest (ROI) according to the type of the target ultrasound image corresponding to the ROI, obtaining the target image at the sampling line position corresponding to the ROI, thus ensuring higher quality for each target image. Based on each target ultrasound image, adaptive interpolation is performed on each target image, and an M-map is generated and displayed based on the adaptively interpolated target images. This ensures that the generated M-map is more accurate and allows users to clearly and accurately obtain the M-map. Then, based on the M-map, IVC parameters are determined, and a parameter trend graph is generated and displayed based on the IVC parameters. This ensures the accuracy of the determined IVC parameters. Furthermore, the parameter trend graph generated and displayed based on the IVC parameters better characterizes the features of the IVC parameters, allowing users to more clearly understand their characteristics.

[0052] In conjunction with the ninth embodiment of the first aspect, in the tenth embodiment of the first aspect, before performing adaptive interpolation processing on each target ultrasound image based on each target ultrasound image, the method further includes:

[0053] Obtain the diameter of the IVC in each target image;

[0054] Compare the diameter of the IVC in the target image with a preset diameter range;

[0055] When the diameter of the IVC in the target image is within the preset diameter range, adaptive interpolation processing is performed on each target ultrasound image based on each target ultrasound image.

[0056] When the diameter of the IVC in the target image is not within the preset diameter range, an error message is output and the corresponding region of interest in the target image is adjusted.

[0057] The parameter detection method provided in this invention compares the diameter of the IVC in the target image with a preset diameter range to re-detect the sampling line position corresponding to each region of interest. When the diameter of the IVC in the target image is within the preset diameter range, it indicates that the sampling line position is accurate. Based on each target ultrasound image, adaptive interpolation processing is performed on each target image to ensure the accuracy of the generated map. When the diameter of the IVC in the target image is not within the preset diameter range, it indicates that the sampling line position is inaccurate. An error message is output, and the corresponding region of interest in the target image is adjusted, thereby further ensuring the accuracy of the sampling line position.

[0058] According to a second aspect, embodiments of the present invention provide an ultrasound device, including: a human-machine interface device and at least one probe interface, wherein the at least one probe interface is used for communicatively connecting at least one probe to the human-machine interface device, and the human-machine interface device is used for...

[0059] Acquire multiple ultrasound images; the types of ultrasound images include IVC transverse and IVC longitudinal sections;

[0060] The ultrasound image is compared with the target IVC cross-sectional image to determine and display the image quality of the ultrasound image, so as to obtain a target ultrasound image that meets the preset quality conditions.

[0061] Based on the type and characteristics of the target ultrasound image, the location of the sampling line is determined to identify the region of interest.

[0062] IVC parameters are determined based on the characteristics of the region of interest in the image.

[0063] The ultrasound device provided in this invention acquires multiple ultrasound images, including IVC transverse and longitudinal sections, enabling parameter detection for both IVC transverse and longitudinal ultrasound images. Then, the ultrasound images are compared with a target IVC section image to determine and display the image quality, ensuring the target ultrasound image's quality and preventing inaccurate IVC parameters due to poor target image quality. Furthermore, based on the type and characteristics of the target ultrasound image, the location of sampling lines is determined to identify the region of interest (ROI), ensuring the accuracy of the determined sampling lines and eliminating reliance on user experience, further guaranteeing the accuracy of the ROI image. Finally, the ultrasound device determines the IVC parameters based on the characteristics of the ROI image, ensuring the accuracy of the determined IVC parameters.

[0064] According to a third aspect, embodiments of the present invention provide a computer-readable storage medium storing computer instructions for causing a computer to perform the parameter detection method of the first aspect or any embodiment of the first aspect. Attached Figure Description

[0065] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0066] Figure 1 This is a schematic diagram of the structure of an ultrasonic device according to an embodiment of the present invention;

[0067] Figure 2 This is a schematic diagram of the host structure according to an embodiment of the present invention;

[0068] Figure 3 This is a schematic diagram of a parameter detection method according to an embodiment of the present invention;

[0069] Figure 4 This is a schematic diagram of a parameter detection method according to an embodiment of the present invention;

[0070] Figure 5a - Figure 5c This is a schematic diagram of ultrasound image quality display according to an embodiment of the present invention;

[0071] Figure 6 This is a schematic diagram of ultrasound image quality display according to an embodiment of the present invention;

[0072] Figure 7This is a schematic diagram of a parameter detection method according to an embodiment of the present invention;

[0073] Figure 8a - Figure 8c This is a schematic diagram showing the image quality of the region of interest according to an embodiment of the present invention;

[0074] Figure 9 This is a schematic diagram showing the image quality of the region of interest according to an embodiment of the present invention;

[0075] Figure 10 This is a schematic diagram of a parameter detection method according to an embodiment of the present invention;

[0076] Figure 11a This is a schematic diagram of a longitudinal section of an ultrasound image according to an embodiment of the present invention;

[0077] Figure 11b This is a schematic diagram of a cross-sectional type of an ultrasound image according to an embodiment of the present invention;

[0078] Figure 12 This is a schematic diagram of ultrasound images and M-maps according to an embodiment of the present invention;

[0079] Figure 13a - Figure 13c This is a schematic diagram illustrating the determination of IVC parameters according to an embodiment of the present invention;

[0080] Figure 14 This is a schematic diagram illustrating the output of error messages according to an embodiment of the present invention;

[0081] Figure 15 This is a schematic diagram of a parameter detection method according to an embodiment of the present invention;

[0082] Figure 16 This is a structural block diagram of a parameter detection device according to an embodiment of the present invention. Detailed Implementation

[0083] This invention provides an ultrasonic device, such as... Figure 1 As shown, the ultrasound device includes a human-computer interaction device 101 and at least one probe interface 102. The probe interface is used to connect the ultrasound probe to the human-computer interaction device 101. The type and number of probe interfaces provided on the ultrasound device can be set according to actual needs, and no limitation is made here.

[0084] Specifically, the human-computer interaction device 101 can receive the area to be scanned input by the user, then activate the corresponding IVC measurement model based on the received area, select the appropriate probe based on the area, and then guide the user to find the location of the IVC through voice, text, or images. The area to be scanned may include, but is not limited to, the bladder, abdomen, heart, etc.

[0085] The human-computer interaction device 101 includes a display. When performing an ultrasound scan on the area to be scanned, an ultrasound image in B-mode is first displayed on the display. This ultrasound image can be either a transverse or longitudinal section of the intravascular coagulation (IVC). The human-computer interaction device 101 detects the section type corresponding to the ultrasound image. Once the section type is determined, the human-computer interaction device 101 acquires multiple ultrasound images and checks whether each ultrasound image meets quality standards. Optionally, the human-computer interaction device 101 can acquire image attribute information for each ultrasound image and then compare this information with the image attribute information of the target IVC section image to determine and display the image quality of each ultrasound image. The image attribute information includes, but is not limited to, image brightness and image sharpness. Optionally, the human-computer interaction device 101 can also input each ultrasound image into a quality recognition model. The quality recognition model compares each ultrasound image with the target IVC section image to determine and display the image quality of each ultrasound image.

[0086] After determining the image quality of each ultrasound image, the human-computer interaction device 101 can use a display to show the image quality corresponding to each ultrasound image in the form of text, outline markings, or color images.

[0087] If the image quality level of each ultrasound image exceeds a certain threshold, then each ultrasound image is designated as a target ultrasound image. Based on the characteristics of each target ultrasound image, the human-machine interface device 101 determines sampling points, and then determines sampling lines based on the positions of these sampling points. If the determined sampling points do not meet preset requirements, the human-machine interface device 101 can also receive user-inputted sampling point adjustment commands, and then adjust the positions of the sampling points according to these commands to obtain the region of interest (ROI), and display the image quality corresponding to the ROI. If the ROI quality meets preset requirements, the IVC parameters are determined based on the characteristics of the ROI image, and a parameter trend graph is generated and displayed based on the IVC parameters.

[0088] The ultrasound device provided in this invention acquires multiple ultrasound images, including IVC transverse and longitudinal sections, enabling parameter detection for both IVC transverse and longitudinal ultrasound images. Each ultrasound image is then compared to a target IVC section image to determine and display its image quality, ensuring the target ultrasound image's quality and preventing inaccurate IVC parameters due to poor target image quality. Furthermore, based on the type and characteristics of the target ultrasound image, the location of sampling lines is determined to identify the region of interest (ROI), ensuring the accuracy of the determined sampling lines and eliminating reliance on user experience, further guaranteeing the accuracy of the ROI image. Finally, the ultrasound device determines the IVC parameters based on the characteristics of the ROI image, ensuring the accuracy of the determined IVC parameters.

[0089] In some optional embodiments of this example, the ultrasonic device may also have other functions, which are described in detail in the parameter detection method section below.

[0090] In some optional implementations of this embodiment, please refer to Figure 2 , Figure 2 This is a schematic diagram of the structure of a human-computer interaction device according to an optional embodiment of the present invention, such as... Figure 2 As shown, the human-computer interaction device may include: a display ( Figure 2 The system comprises at least one processor 201 (not shown), such as a CPU (Central Processing Unit), at least one communication interface 203, a memory 204, and at least one communication bus 202. The communication bus 202 is used to establish communication between these components. The communication interface 203 may include a display screen or a keyboard; optionally, the communication interface 203 may also include a standard wired interface or a wireless interface. The memory 204 may be high-speed RAM (Random Access Memory) or non-volatile memory, such as at least one disk drive. Optionally, the memory 204 may also be at least one storage device located remotely from the aforementioned processor 201. The memory 204 stores application programs, and the processor 201 calls the program code stored in the memory 204 to execute the following steps of the ultrasonic scanning display method and sends the corresponding content to the display device for display.

[0091] The communication bus 202 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The communication bus 202 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 2 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0092] The memory 204 may include volatile memory, such as random-access memory (RAM); the memory may also include non-volatile memory, such as flash memory, hard disk drive (HDD) or solid-state drive (SSD); the memory 204 may also include a combination of the above types of memory.

[0093] The processor 201 can be a central processing unit (CPU), a network processor (NP), or a combination of CPU and NP.

[0094] The processor 201 may further include a hardware chip. This hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0095] Optionally, the memory 204 is also used to store program instructions. The processor 201 can invoke the program instructions to implement the parameter detection method as shown in any embodiment of this application.

[0096] According to an embodiment of the present invention, a parameter detection method embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0097] This embodiment provides a parameter detection method that can be used in the aforementioned ultrasonic equipment. Figure 3 This is a flowchart of a parameter detection method according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps:

[0098] S11, acquire multiple ultrasound images.

[0099] The types of ultrasound images include IVC transverse section and IVC longitudinal section.

[0100] Specifically, the ultrasound device can receive the area to be scanned input by the user, then activate the corresponding IVC measurement model based on the received area, select the appropriate probe according to the area, and guide the user to find the location of the IVC through voice, text, or images. The area to be scanned can include, but is not limited to, the bladder, abdomen, and heart.

[0101] When an ultrasound device performs an ultrasound scan on the area to be scanned, it first displays an ultrasound image in B-mode on the display. This ultrasound image can be either a transverse or longitudinal section of the intravascular coagulation (IVC). The ultrasound device then detects the section type corresponding to the ultrasound image. If the section type matches the characteristics of the area to be scanned, the ultrasound device scans the area and acquires multiple ultrasound images.

[0102] S12, compare the ultrasound image with the target IVC section image, determine and display the image quality of the ultrasound image, so as to obtain a target ultrasound image that meets the preset quality conditions.

[0103] Optionally, the ultrasound device can acquire image attribute information of the ultrasound image, and then compare the image attribute information of the ultrasound image with the image attribute information of the target IVC cross-section image to determine and display the image quality of the ultrasound image. The image attribute information includes, but is not limited to, information such as image brightness and image sharpness, thereby obtaining a target ultrasound image that meets the preset quality conditions.

[0104] Optionally, the ultrasound equipment can also input ultrasound images into a quality recognition model. The quality recognition model compares each ultrasound image with the target IVC cross-sectional image to determine and display the image quality of each ultrasound image, thereby obtaining a target ultrasound image that meets the preset quality conditions.

[0105] Optionally, the ultrasound device can input multiple acquired ultrasound images into the quality recognition model, or input one frame of the acquired ultrasound images into the quality recognition model; or input any number of frames of the acquired ultrasound images into the quality recognition model.

[0106] S13, based on the type and characteristics of the target ultrasound image, determine the location of the sampling line to identify the region of interest in the image.

[0107] Specifically, the ultrasound equipment determines the location of the sampling line based on the location of the IVC in the target ultrasound image. Then, the ultrasound equipment segments the target ultrasound image according to the location of the sampling line, thereby determining the region of interest.

[0108] S14. Determine the IVC parameters based on the characteristics of the image of the region of interest.

[0109] Specifically, ultrasound equipment can obtain basic parameters such as the upper and lower boundaries of the IVC, the maximum and minimum diameter of the IVC within the period, the sampling line envelope, and the period segmentation line based on the image features of the region of interest. Based on these basic parameters, IVC parameters such as the variability and collapse rate of the IVC within the period can be calculated.

[0110] The specifics of this step will be described in detail below.

[0111] The parameter detection method provided in this invention acquires multiple ultrasound images, including IVC transverse and longitudinal sections, enabling parameter detection on both IVC transverse and longitudinal ultrasound images. Each ultrasound image is then compared to a target IVC section image to determine and display its image quality, ensuring the target ultrasound image's quality and preventing inaccurate IVC parameters due to poor target image quality. Furthermore, based on the type and characteristics of the target ultrasound image, the location of sampling lines is determined to identify the region of interest (ROI), ensuring the accuracy of the determined sampling lines and eliminating reliance on user experience, further guaranteeing the accuracy of the ROI image. Finally, the ultrasound device determines the IVC parameters based on the characteristics of the ROI image, ensuring the accuracy of the determined IVC parameters.

[0112] This embodiment provides a parameter detection method that can be used in the aforementioned ultrasonic equipment. Figure 4 This is a flowchart of a parameter detection method according to an embodiment of the present invention, such as... Figure 4 As shown, the process includes the following steps:

[0113] S21, acquire multiple ultrasound images.

[0114] The types of ultrasound images include IVC transverse section and IVC longitudinal section.

[0115] Please see details Figure 3 S11 of the illustrated embodiment will not be described again here.

[0116] S22, compare the ultrasound image with the target IVC section image, determine and display the image quality of the ultrasound image, so as to obtain a target ultrasound image that meets the preset quality conditions.

[0117] The above S22 includes:

[0118] S221, quality identification of ultrasound images.

[0119] Specifically, the ultrasound equipment can train a quality recognition network based on multiple ultrasound images and the corresponding label information of the multiple ultrasound images to obtain a quality recognition model, and then perform quality recognition on the ultrasound images based on the quality recognition model.

[0120] The quality identification model can be generated based on traditional identification algorithms or deep learning algorithms. Traditional algorithms may include, but are not limited to, feature descriptor operators + Adaboost algorithm, histogram of oriented gradients (HOR) features + SVM algorithm, and DPM algorithm. Deep learning algorithms include DNN (Deep Neural Networks), CNN (Convolutional Neural Networks), and RNN (Recurrent Neural Networks). When the quality identification model is a CNN, it can be a V-Net model, U-Net model, FastCNN model, or Generative Adversarial Nets model. This application does not specifically limit the type of quality identification model.

[0121] Optionally, the ultrasound device can also receive quality identification models sent by other devices.

[0122] S222: Based on the quality identification results, compare the ultrasound image with the target IVC cross-sectional image to determine and display the image quality of the ultrasound image on the ultrasound interface.

[0123] Specifically, the ultrasound equipment inputs ultrasound images into a quality recognition model, which compares the features of the ultrasound images with the features of the target IVC cross-sectional image. For example, a longitudinal section of the target ultrasound image contains features such as the middle hepatic vein, the right atrial opening, and the diaphragm. Then, based on the comparison results, the quality recognition result of each ultrasound image is determined.

[0124] Then, the ultrasound equipment compares each ultrasound image with the target IVC cross-sectional image to determine and display the image quality of each ultrasound image on the ultrasound interface.

[0125] In one optional embodiment of this application, the ultrasound interface includes a quality display area, and the "displaying the image quality of each ultrasound image on the ultrasound interface" in S222 above may include the following:

[0126] (1) Compare the quality of the ultrasound image with the threshold of each quality level to determine the corresponding quality level of the ultrasound image.

[0127] Specifically, the ultrasound equipment can receive threshold values ​​for various quality levels input by the user, as well as threshold values ​​for various quality levels sent by other devices. The ultrasound equipment compares the quality of the ultrasound image with the threshold values ​​for each quality level to determine the corresponding quality level of the ultrasound image.

[0128] For example, suppose the quality level thresholds include a first threshold and a second threshold, where the first threshold can be 0.5 and the second threshold can be 0.8. The first threshold and the second threshold can also be other values, and this application does not specifically limit the values ​​of the first threshold and the second threshold.

[0129] When the quality of an ultrasound image is less than the first threshold of the quality level, the quality of the ultrasound image is level one; when the quality of an ultrasound image is greater than or equal to the first threshold of the quality level but less than the second threshold of the quality level, the quality of the ultrasound image is level two; when the quality of an ultrasound image is greater than or equal to the second threshold of the quality level, the quality of the ultrasound image is level three, wherein the quality of level three is greater than that of level two, and the quality of level two is greater than that of level one.

[0130] (2) Display the corresponding quality level identifier in the quality display area.

[0131] Specifically, the ultrasound equipment can display a corresponding indicator in the quality display area based on the quality level of the ultrasound image.

[0132] The identifier can be text, numbers, letters, or any image. This application does not specifically limit the identifier corresponding to the quality level.

[0133] For example, assuming the identifier is a number, when the quality of the ultrasound image is level one, the quality display area displays 1; when the quality of the ultrasound image is level two, the quality display area displays 2; and when the quality of the ultrasound image is level three, the quality display area displays 3.

[0134] In an optional embodiment of this application, the quality display area includes a quality progress bar, and step (2) above, "displaying the identifier corresponding to the quality level in the quality display area," may include:

[0135] (21) Determine the actual progress of the quality progress bar based on the quality level.

[0136] (22) Display the actual progress of the quality progress bar in the quality display area.

[0137] Specifically, the ultrasound equipment determines the actual progress of the quality progress bar corresponding to the quality level of the ultrasound image based on the quality level of the ultrasound image.

[0138] It should be noted that the actual progress of the quality progress bar can be directly proportional to or inversely proportional to the quality level of the ultrasound image.

[0139] In one alternative implementation, the quality progress bar corresponding to the quality level of the ultrasound image can be filled with a color. The ultrasound device can display the quality level of the ultrasound image using the actual progress of the quality progress bar in the quality display area. For example, the quality progress bar can be filled with black or gray; this application embodiment does not specifically limit the color used to fill the quality progress bar.

[0140] Let's take the example of the progress bar's actual progress being directly proportional to the ultrasound image's quality level. For instance, when the ultrasound image's quality level is three, the progress bar displayed in the quality display area is five-sixths complete; when the quality level is two, it's two-thirds complete; and when the quality level is one, it's one-third complete. It should be noted that three represents the best image quality, two represents moderate quality, and three represents the worst image quality.

[0141] In one alternative implementation, the ultrasound device can also fill a quality progress bar with different colors according to the different quality levels of the ultrasound image. The user can then determine the quality level of the ultrasound image based on the color of the quality progress bar.

[0142] For example, the quality progress bar can be filled with green, yellow, or red. Assuming the ultrasound image quality level is three, the quality progress bar can be filled with green; the quality level is two, with yellow; and the quality level is one, with red. It should be noted that three represents the best image quality, two represents moderate quality, and three represents the worst image quality.

[0143] In another optional embodiment of this application, step (2) above, "displaying the identifier corresponding to the quality level in the quality display area," further includes:

[0144] (23) Determine the first fill identifier of the quality progress bar based on the quality level.

[0145] (24) Overlay the first fill indicator with the actual progress in the quality display area.

[0146] Specifically, the ultrasound equipment determines the first fill indicator of the quality progress bar based on the quality level of the ultrasound image. Then, the first fill indicator of the quality progress bar is superimposed on the actual progress in the quality display area.

[0147] The first fill indicator of the quality progress bar can be a color indicator or an image indicator. The image indicator can be a circle, square, triangle, etc.

[0148] For example, taking the first fill indicator of the quality progress bar as a color indicator: When the ultrasound image quality level is three, the first fill indicator of the quality progress bar is determined to be green. The first fill indicator and the actual progress are superimposed on the quality display area; for example, the actual progress of the quality progress bar corresponding to the ultrasound image is five-sixths and the fill color is green. When the ultrasound image quality level is two, the first fill indicator of the quality progress bar is determined to be yellow. The first fill indicator and the actual progress are superimposed on the quality display area; that is, the actual progress of the quality progress bar corresponding to the ultrasound image is two-thirds and the fill color is yellow. When the ultrasound image quality level is one, the first fill indicator of the quality progress bar is determined to be red. The first fill indicator and the actual progress are superimposed on the quality display area; that is, the actual progress of the quality progress bar corresponding to the ultrasound image is one-third and the fill color is red.

[0149] In another optional embodiment of this application, the ultrasound interface includes an ultrasound image display area, and the "image quality of displaying each ultrasound image on the ultrasound interface" in S222 above may further include the following:

[0150] (3) Obtain the ultrasound image contour corresponding to the ultrasound image.

[0151] (4) Determine the second fill identifier corresponding to the ultrasound image contour based on the quality level.

[0152] (5) Display a second fill mark in the ultrasound image display area based on the ultrasound image contour.

[0153] Specifically, the ultrasound equipment can use a contour recognition algorithm to identify the ultrasound image contours corresponding to each ultrasound image. Then, a second fill identifier corresponding to each ultrasound image contour is determined based on the quality level.

[0154] The second fill identifier can be a color fill identifier or other fill identifiers.

[0155] For example, suppose the second fill identifier can be a color fill identifier. When the quality level of the ultrasound image is level 1, the ultrasound image outline is red; when the quality level of the ultrasound image is level 2, the ultrasound image outline is yellow; and when the quality level of the ultrasound image is level 3, the ultrasound image outline is green. For example, as shown in Figure 5. Figure 5a In ultrasound images, the outline is red, indicating that the image quality level is Level 1. Figure 5b In mid-tone ultrasound images, a yellow outline indicates that the image quality level is level two. Figure 5c In ultrasound images, a green outline indicates that the image quality level is level three.

[0156] In another alternative implementation, the ultrasound equipment can also output the image quality of each ultrasound device in text form. For example... Figure 6 As shown, Figure 6 In the "Quality Tip: XX" message, the "XX" can be displayed in colors such as red, yellow, and green, or it can display text such as "Poor", "Average", or "Good".

[0157] S23, based on the type and characteristics of the target ultrasound image, determine the location of the sampling line to identify the region of interest in the image.

[0158] Please see details Figure 3 S13 of the illustrated embodiment will not be described again here.

[0159] S24. Determine the IVC parameters based on the characteristics of the image of the region of interest.

[0160] Please see details Figure 3 S14 of the illustrated embodiment will not be described again here.

[0161] The parameter detection method provided in this invention identifies the quality of each ultrasound image, compares each ultrasound image with the target IVC cross-sectional image based on the quality identification results, and determines the image quality of each ultrasound image, thereby ensuring the accuracy of the displayed image quality. By comparing the quality of the ultrasound image with thresholds for each quality level, the corresponding quality level of the ultrasound image is determined, and the corresponding indicator for the quality level is displayed in the quality display area, allowing users to quickly obtain the quality of each ultrasound image.

[0162] Optionally, the actual progress of the quality progress bar can be determined based on the quality level of the ultrasound image, and displayed in the quality display area. This allows users to quickly and intuitively determine the quality level of the current ultrasound image based on the actual progress of the quality progress bar.

[0163] Optionally, the ultrasound equipment can also determine the first fill indicator of the quality progress bar based on the quality level; the first fill indicator and the actual progress are superimposed on the quality display area, so that the user can quickly and intuitively determine the quality level of the current ultrasound image based on the actual progress of the quality progress bar and the first fill indicator of the quality progress bar.

[0164] Optionally, the ultrasound device can also acquire the ultrasound image contours corresponding to each ultrasound image; then, determine a second fill identifier corresponding to each ultrasound image contour based on the quality level; and display the second fill identifier in the ultrasound image display area based on the ultrasound image contours. This allows users to intuitively and quickly determine the image quality of each ultrasound image based on the ultrasound image contours corresponding to the ultrasound image contours.

[0165] This embodiment provides a parameter detection method that can be used in the aforementioned ultrasonic equipment. Figure 7 This is a flowchart of a parameter detection method according to an embodiment of the present invention, such as... Figure 7 As shown, the process includes the following steps:

[0166] S31, acquire multiple ultrasound images.

[0167] The types of ultrasound images include IVC transverse section and IVC longitudinal section.

[0168] Please see details Figure 4 S21 of the illustrated embodiment will not be described again here.

[0169] S32, compare the ultrasound image with the target IVC section image, determine and display the image quality of the ultrasound image, so as to obtain a target ultrasound image that meets the preset quality conditions.

[0170] Please see details Figure 4 S22 of the illustrated embodiment will not be described again here.

[0171] S33, based on the type and characteristics of the target ultrasound image, determines the location of the sampling line to identify the region of interest in the image.

[0172] In some optional implementations of this embodiment, S33 may include:

[0173] S331, Based on the type and characteristics of the target ultrasound image, determine the sampling points.

[0174] Specifically, the ultrasound equipment can first identify the type of the target ultrasound image, determining whether it is an IVC transverse ultrasound image or an IVC longitudinal ultrasound image. Then, based on the type of the target ultrasound image, the features of the target ultrasound image are extracted using a sampling point detection model, and sampling points are determined based on the extracted features.

[0175] The sampling point detection model can be a model generated based on traditional recognition algorithms or a model generated based on deep learning algorithms. Traditional algorithms may include, but are not limited to, feature descriptor operators + Adaboost algorithm, histogram of oriented gradients features + SVM algorithm, DPM algorithm, etc. Deep learning algorithms include DNN (Deep Neural Networks), CNN (Convolutional Neural Networks), RNN (Recurrent Neural Networks), etc. When the quality recognition model is a CNN, it can be a V-Net model, U-Net model, FastCNN model, CenterNet model, Generative Adversarial Nets model, etc. This application does not specifically limit the type of sampling point detection model.

[0176] For example, when the target ultrasound image is a transverse IVC section, the sampling point is located about 2 cm from the right atrium entrance of the inferior vena cava, perpendicular to the intima of the inferior vena cava; when the target ultrasound image is a longitudinal IVC section, the sampling point is scanned below the xiphoid process. The measurement position is found in the longitudinal section, and then rotated 90 degrees to ensure that it is the same as the measurement position in the transverse section.

[0177] S332, based on the location of the sampling point and the location information of the IVC in the target ultrasound image, determine the location of the sampling line in order to determine the image of the region of interest.

[0178] Specifically, after determining the location of the sampling point, the ultrasound equipment determines the location of the sampling line based on the location of the sampling point and the location information of the IVC in the target ultrasound image. The sampling line is perpendicular to the upper and lower walls of the IVC.

[0179] Sampling points are determined based on the type and characteristics of the target ultrasound image. Then, based on the location of the sampling points and the location information of the IVC (Intravascular Coagulation) in the target ultrasound image, the location of the sampling line is determined to define the region of interest. This ensures the accuracy of the determined sampling point locations, and further guarantees the accuracy of the determined sampling line locations.

[0180] In some optional embodiments of this example, S332 may further include the following:

[0181] (1) When the image quality near the sampling point meets the preset requirements, the region of interest is determined according to the location of the sampling point.

[0182] (2) Perform quality detection on the region of interest, determine the image quality of the region of interest, and display the image quality of the region of interest.

[0183] (3) When the image quality near the sampling point does not meet the preset requirements, the position of the adjusted sampling point is determined in response to the adjustment command of the sampling point.

[0184] (4) Determine the region of interest based on the adjusted sampling point locations;

[0185] (5) Identify the quality of the region of interest and issue a prompt message when the quality of the region of interest does not meet the preset requirements.

[0186] Specifically, the ultrasound equipment can acquire images of the vicinity of the sampling point based on the location of the sampling point in each target ultrasound image, and detect whether the image quality of the vicinity of the sampling point meets preset requirements. These preset requirements may include, but are not limited to, the sampling point being located inside the lumen and the surrounding images being clear.

[0187] When the image quality near the sampling point meets the preset requirements, the ultrasound equipment determines the position of the sampling line based on the location of the sampling point, thereby determining the region of interest. The ultrasound equipment checks whether the target ultrasound image corresponding to the sampling point is the first frame ultrasound image and whether the sampling point is a reset sampling point. If not, the ultrasound equipment inputs the region of interest into the detection model to determine the quality of the region of interest.

[0188] The detection model may be the same as or different from the quality detection model in the above embodiments. The embodiments of this application do not specifically limit the detection model.

[0189] The ultrasound equipment inputs the region of interest (ROI) into the detection model, which then performs feature recognition on the ROI and outputs the image quality of the ROI. The ultrasound equipment can then compare the image quality of the ROI with thresholds for various image quality levels to determine the image quality of each ROI.

[0190] For example, suppose the image quality level thresholds include a first threshold and a second threshold. When the image quality of the region of interest (ROI) is less than the first threshold, the image quality of the ROI is level one; when the image quality of the ROI is greater than or equal to the first threshold but less than the second threshold, the image quality of the ROI is level two; when the image quality of the ROI is greater than or equal to the second threshold, the image quality of the ROI is level three, wherein level three image quality is greater than level two image quality, which is greater than level one image quality.

[0191] For example, when the quality level of the region of interest is level 1, the sampling line in the region of interest is red; when the quality level of the region of interest is level 2, the sampling line in the region of interest is yellow; and when the quality level of the region of interest is level 3, the sampling line in the region of interest is green. For example, as shown in Figure 8. Figure 8a In the region of interest, the sampling line is red, indicating that the image quality level of the region of interest is Level 1. Figure 8b Yellow sampling lines in the region of interest indicate that the image quality level of the region of interest is level 2. Figure 8c A green sampling line in the region of interest indicates that the image quality level of the region of interest is level three.

[0192] In another alternative implementation, the ultrasound device can also output the image quality of each region of interest in text form. For example... Figure 9 As shown, Figure 9 In the "Quality Tip: XX" message, the "XX" can be displayed in colors such as red, yellow, and green, or it can display text such as "Poor", "Average", or "Good".

[0193] When the image quality of the region of interest is greater than a preset quality threshold, the region of interest is determined as the region of interest template, which can ensure the quality of other regions of interest.

[0194] When the image quality near the sampling point does not meet preset requirements, the ultrasound equipment responds to the user's input adjustment command for the sampling point. The position of the sampling point is adjusted according to the command, and the region of interest (ROI) is determined based on the adjusted position. The ultrasound equipment then re-evaluates the image quality of the ROI and issues a prompt message if the image quality of the ROI does not meet preset requirements.

[0195] The preset requirements may include, but are not limited to, an image quality in the region of interest exceeding a preset quality threshold, and the sampling point in the region of interest being located within the lumen. The ultrasound device may output prompts in text, voice, or image format. This application does not specifically limit the manner in which the ultrasound device outputs prompts.

[0196] S34, determine the IVC parameters based on the characteristics of the image of the region of interest.

[0197] Please see details Figure 4 S24 of the illustrated embodiment will not be described again here.

[0198] The parameter detection method provided in this invention determines sampling points based on the type and features of the target ultrasound image. Then, based on the location of the sampling points and the location information of the IVC (Intravascular Coefficient) in the target ultrasound image, it determines the location of the sampling line to identify the region of interest. This ensures the accuracy of the determined sampling point locations and further guarantees the accuracy of the determined sampling line locations.

[0199] This embodiment provides a parameter detection method that can be used in the aforementioned ultrasonic equipment. Figure 10 This is a flowchart of a parameter detection method according to an embodiment of the present invention, such as... Figure 10 As shown, the process includes the following steps:

[0200] S41, acquire multiple ultrasound images.

[0201] The types of ultrasound images include IVC transverse section and IVC longitudinal section.

[0202] Please see details Figure 7 S31 of the illustrated embodiment will not be described again here.

[0203] S42, compare the ultrasound image with the target IVC section image, determine and display the image quality of the ultrasound image, so as to obtain a target ultrasound image that meets the preset quality conditions.

[0204] Please see details Figure 7 S32 of the illustrated embodiment will not be described again here.

[0205] S43, based on the type and characteristics of the target ultrasound image, determine the location of the sampling line to identify the region of interest in the image.

[0206] Please see details Figure 7 S33 of the illustrated embodiment will not be described again here.

[0207] S44, determine the IVC parameters based on the characteristics of the image of the region of interest.

[0208] Specifically, S44 may include:

[0209] S441, based on the type of the target ultrasound image corresponding to the region of interest, preprocess the region of interest to obtain the target image at the sampling line position corresponding to the region of interest.

[0210] Specifically, ultrasound equipment can perform data preprocessing on each region of interest. The data preprocessing methods used include, but are not limited to, normalization, adaptive histogram equalization, standardization, adaptive histogram equalization algorithm, and gamma correction.

[0211] Ultrasonic equipment can also utilize image segmentation algorithms to segment the regions of interest (ROIs) after data preprocessing, obtaining target images at the sampling line positions corresponding to each ROI. This results in smaller target image areas, faster processing speeds, and more accurate inclusion of IVC regions. Image segmentation algorithms can include, but are not limited to, deep learning-based U-Net segmentation algorithms, Otsu's method, and watershed methods.

[0212] After segmenting the region of interest and obtaining the target image corresponding to the sampling line position of each region of interest, the ultrasound equipment can also perform post-processing on each target image according to the cross-sectional type of the target ultrasound image corresponding to each target image.

[0213] For example, if the cross-section type of the target ultrasound image corresponding to each target image is IVC longitudinal section, the ultrasound equipment uses morphological operations to remove small regions, uses Gaussian filtering to smooth the edges, uses the edge gray value change to obtain the upper and lower edges of IVC, uses curve fitting to obtain the midline slope, uses point-slope method to find the linear expression of the sampling line required for the M-mode, the tangent of the upper and lower edges and the blood vessel diameter, etc., to generate the M-map. For example, Figure 11(a) shows a longitudinal section schematic diagram.

[0214] If the cross-section type of the target ultrasound image corresponding to each target image is IVC transverse, the ultrasound equipment generates the M-map by using morphological operations to remove small regions, smoothing edges using Gaussian filtering, fitting ellipses using the least squares method, and using the point-slope method to calculate the linear expression of the sampling lines required for the M-mode, the envelope, the tangents of the upper and lower edges, and the blood vessel diameter. For example, Figure 11(b) shows a schematic diagram of the transverse section.

[0215] S442 performs adaptive interpolation processing on each target ultrasound image based on each target ultrasound image.

[0216] Specifically, after post-processing the target image, the ultrasound equipment can also perform adaptive interpolation. Specifically, the ultrasound equipment first needs to adaptively calculate the number of interpolations required for the target image based on the frame rate of the ultrasound images and the frame rate of the target image; that is, the number of interpolations required to generate the target image between two adjacent ultrasound images. The calculation expression is as follows:

[0217] Num_Inter(i)=(T B *i-floor(T B *(i-1) / TAM )*T AM ) / T AM

[0218] Where T B T represents the time of each frame of ultrasound image. AM The time for the region of interest in each frame.

[0219] To improve temporal resolution, the algorithm employs the Lanczos method for interpolation. This method is commonly used to increase the sampling rate of digital signals and for multivariate interpolation. The effect of each input sample on the interpolation is defined by the filter's reconstruction kernel, called the Lanczos kernel. It is the normalized sinc function sinc(x) shown in the figure below, composed of a Lanczos window or a sinc window, which is a horizontal stretch of the center lobe of sinc(x / a) in the range -≤x≤a.

[0220]

[0221] Lanczos is used here for interpolation, but it is not the only option; other interpolation algorithms can be used depending on the specific circumstances.

[0222] S443 generates and displays an M-map based on each target image after adaptive interpolation.

[0223] Specifically, the ultrasound equipment generates an M-map based on the cross-section type corresponding to each target image after adaptive interpolation processing, and displays the M-map in the ultrasound image display area.

[0224] like Figure 12 The image shown is the generated M-map and ultrasound image. Figure 12 The upper part is the ultrasound image, and the lower part is the M-image.

[0225] S444: Based on the M diagram, determine the IVC parameters, generate a parameter trend chart based on the IVC parameters, and display the parameter trend chart.

[0226] Specifically, the ultrasound equipment obtains the positions of the upper and lower boundaries of the IVC based on the M-map. It divides the cycle into intervals, statistically analyzes the maximum and minimum IVC diameters for each interval, and then calculates IVC parameters such as variability and collapse rate. A parameter trend chart is generated and presented to the user in different formats, such as numerical values ​​or line graphs. For example, Figure 13 shows the specific images, where Figure 13(a) shows the IVC parameters changing over time or number of cycles; Figure 13(b) shows the IVC parameters changing over time or number of cycles with a reference line, where the reference line is a preset reference value. Taking bladder volume as an example, when the bladder volume differs from the reference value by more than a certain threshold, these parameters can be highlighted (normally represented by green hollow or solid, yellow when greater than the threshold but still acceptable, and red when greater than the threshold and unacceptable; the types and number of colors are not limited to these), so that users can intuitively obtain IVC parameters that differ significantly from the actual values. Furthermore, IVC parameters can be one or more of the following: IVC respiratory variability, IVC collapse index, or IVC expansion index. If there are multiple IVC parameters, multiple corresponding analytical curves can be generated, or multiple parameters can be placed in a single line graph, as shown in Figure 13(c). Figure 13(c) shows multiple IVC parameters in a single line graph (dashed lines or dotted lines represent different types of parameters, which can be represented in different ways). When the user moves the cursor to the curve, specific information at that location can be displayed, such as "IVC parameter: XX". The displayed information is not limited to this; any method of displaying information in line form is within the scope of protection.

[0227] In addition, the ultrasound equipment also provides a reset function for users. The reset function varies depending on how frequently the user switches observation points:

[0228] a) Switch observation point once: Provide the maximum and minimum values, variability, and interval identifier of the previous interval. Reset at the switch point, wait n frames, output a black line during the wait, then output a new M-graph, and continue to calculate the variability in the statistical period, where n is a positive integer greater than 1.

[0229] b) Multiple observation point switching within a period: Each switch waits for k frames, where k is a positive integer greater than 1, and a black line is output during the waiting period. No interval statistics are performed during multiple switching processes. From the user's last click until the interval's termination position is found, the interval is marked, and the maximum and minimum values ​​and variability are given. The period value within a period can be obtained through methods such as a given value, a value calculated by the algorithm based on the maximum and minimum values, or a value provided by the built-in ECG monitoring device of the ultrasound system to provide an accurate period.

[0230] This part of the algorithm is implemented on two objects: ultrasound images and target images. The anatomical M-map of the ultrasound image is output as the result, and the anatomical M-map of the target image is input for the next step of the calculation.

[0231] The parameter detection method provided in this invention preprocesses each region of interest (ROI) according to the type of the target ultrasound image corresponding to each ROI, obtaining the target image at the sampling line position corresponding to each ROI, thus ensuring higher quality for each target image. Based on each target ultrasound image, adaptive interpolation processing is performed on each target image, and an M-map is generated and displayed based on the adaptively interpolated target images. This ensures that the generated M-map is more accurate and allows users to clearly and accurately obtain the M-map. Then, based on the M-map, IVC parameters are determined, and a parameter trend graph is generated and displayed based on the IVC parameters. This ensures the accuracy of the determined IVC parameters. Furthermore, the parameter trend graph generated and displayed based on the IVC parameters better characterizes the features of the IVC parameters, allowing users to more clearly understand their characteristics.

[0232] In one optional embodiment of this application, the following steps may be included before S443:

[0233] (1) Obtain the diameter of IVC in each target image.

[0234] (2) Compare the diameter of the IVC in the target image with the preset diameter range.

[0235] (3) When the diameter of the IVC in the target image is within the preset diameter range, adaptive interpolation processing is performed on each target ultrasound image based on each target ultrasound image.

[0236] (4) When the diameter of the IVC in the target image is not within the preset diameter range, output an error message and adjust the corresponding region of interest in the target image.

[0237] Specifically, the ultrasound equipment identifies each target image and obtains the diameter of the intracellular container (IVC) in each target image. Then, the ultrasound equipment compares the diameter of the IVC in the target image with a preset diameter range. It determines whether the diameter of the IVC in the target image is within the preset diameter range. If the diameter of the IVC in the target image is within the preset diameter range, it indicates that the sampling point corresponding to the target image is accurate. The ultrasound equipment then generates an M-map by performing adaptive interpolation processing on each target image. If the diameter of the IVC in the target image is not within the preset diameter range, the ultrasound equipment determines that the sampling point corresponding to the target image is incorrect. The ultrasound equipment outputs an error message and adjusts the sampling point in the corresponding region of interest (ROI) of the target image, thereby adjusting the ROI.

[0238] Optionally, the ultrasound device can also receive the user's adjustment results for the sampling points corresponding to the region of interest. The ultrasound device can output error information in the form of text, voice, or image. This application does not specifically limit the method by which the ultrasound device outputs error information. Figure 14 As shown, the error message is output in text format. Figure 14 The white sampling points in the image can be user-selected points or sampling points selected by the ultrasound equipment.

[0239] The parameter detection method provided in this invention compares the diameter of the IVC in the target image with a preset diameter range to re-detect the sampling line position corresponding to each region of interest. When the diameter of the IVC in the target image is within the preset diameter range, it indicates that the sampling line position is accurate. Based on each target ultrasound image, adaptive interpolation processing is performed on each target image to ensure the accuracy of the generated map. When the diameter of the IVC in the target image is not within the preset diameter range, it indicates that the sampling line position is inaccurate. An error message is output, and the corresponding region of interest in the target image is adjusted, thereby further ensuring the accuracy of the sampling line position.

[0240] As a specific implementation of this embodiment, the parameter detection method mainly includes four aspects: (1) ultrasound image quality assessment; (2) sampling point quality assessment; (3) region of interest quality assessment; and (4) IVC parameter determination. Based on this, as follows Figure 15 As shown, the parameter detection method includes:

[0241] S1, acquire multiple ultrasound images.

[0242] S2 determines whether the quality of each ultrasound image meets the requirements. If the image quality meets the requirements, proceed to S3; otherwise, proceed to S1.

[0243] S3. Based on the characteristics of the ultrasound image, determine the sampling point.

[0244] S4 determines whether the location of the sampling point meets the requirements. If the location of the sampling point meets the requirements, execute S5; otherwise, execute S3.

[0245] S5, based on the location of the sampling points, determines the M-line to identify the region of interest.

[0246] S6: Determine if the image quality of the region of interest meets the requirements. If the image quality of the region of interest meets the requirements, execute S7; otherwise, execute S3.

[0247] S7. Determine the IVC parameters based on the characteristics of the image of the region of interest.

[0248] For details on the specific implementation of S1-S7, please refer to the detailed description of the corresponding steps in the parameter detection method above, which will not be repeated here.

[0249] This embodiment also provides a parameter detection device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0250] This embodiment provides a parameter detection device, such as... Figure 16 As shown, it includes:

[0251] The acquisition module 51 is used to acquire multiple ultrasound images; the types of ultrasound images include IVC transverse section type and IVC longitudinal section type;

[0252] The first determining module 52 is used to compare the ultrasound image with the target IVC section image, determine and display the image quality of the ultrasound image, so as to obtain a target ultrasound image that meets the preset quality conditions.

[0253] The second determining module 53 is used to determine the position of the sampling line based on the type and characteristics of the target ultrasound image, so as to determine the image of the region of interest;

[0254] The third determining module 54 is used to determine the IVC parameters based on the features of the image of the region of interest.

[0255] The ultrasonic scanning device in this embodiment is presented in the form of a functional unit. Here, a unit refers to an ASIC circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0256] Further functional descriptions of the above modules are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0257] This invention also provides a non-transitory computer storage medium storing computer-executable instructions that can execute the parameter detection method in any of the above method embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium may also include combinations of the above types of memory.

[0258] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A parameter detection method, characterized in that, The method includes: Multiple ultrasound images are acquired; the types of ultrasound images include IVC transverse sections and IVC longitudinal sections; The ultrasound image is compared with the target IVC cross-sectional image to determine and display the image quality of the ultrasound image, so as to obtain a target ultrasound image that meets the preset quality conditions. Based on the type and characteristics of the target ultrasound image, the location of the sampling line is determined to identify the region of interest. The IVC parameters are determined based on the features of the image of the region of interest. The step of determining the location of the sampling line based on the type and characteristics of the target ultrasound image to determine the region of interest includes: Based on the type and characteristics of the target ultrasound image, the sampling points are determined; Based on the location of the sampling point and the location information of the IVC in the target ultrasound image, the location of the sampling line is determined to determine the image of the region of interest; When the image quality near the sampling point meets the preset requirements, the region of interest is determined based on the location of the sampling point; The region of interest is subjected to quality detection to determine the image quality of the region of interest, and the image quality of the region of interest is displayed.

2. The method according to claim 1, characterized in that, The ultrasound image quality is displayed on an ultrasound interface, the ultrasound interface including a quality display area, comprising: The quality of the ultrasound image is compared with the threshold of each quality level to determine the quality level corresponding to each ultrasound image; The quality display area displays the identifier corresponding to the quality level.

3. The method according to claim 2, characterized in that, The quality display area includes a quality progress bar, and displaying the identifier corresponding to the quality level in the quality display area includes: The actual progress of the quality progress bar is determined based on the quality level. The actual progress of the quality progress bar is displayed in the quality display area.

4. The method according to claim 3, characterized in that, The step of displaying the identifier corresponding to the quality level in the quality display area further includes: The first fill indicator of the quality progress bar is determined based on the quality level; The first filling indicator and the actual progress are overlaid and displayed in the quality display area.

5. The method according to claim 2, characterized in that, The ultrasound image quality is displayed on an ultrasound interface, which includes an ultrasound image display area and further includes: Obtain the ultrasound image contour corresponding to the ultrasound image; Based on the quality level, a second fill identifier corresponding to the ultrasound image contour is determined; The second fill identifier is displayed in the ultrasound image display area based on the ultrasound image outline.

6. The method according to claim 1, characterized in that, The method further includes: When the image quality near the sampling point does not meet the preset requirements, the location of the adjusted sampling point is determined in response to the adjustment command of the sampling point. The region of interest is determined based on the location of the adjusted sampling points; The quality of the region of interest is identified, and a prompt message is issued when the quality of the region of interest does not meet the preset requirements.

7. The method according to claim 1, characterized in that, The step of determining the IVC parameters based on the features of the image of the region of interest includes: Based on the type of the target ultrasound image corresponding to the region of interest, the region of interest is preprocessed to obtain the target image at the sampling line position corresponding to the region of interest; Based on each of the target ultrasound images, adaptive interpolation processing is performed on each of the target images; Based on the target images after adaptive interpolation, an M-map is generated and displayed; Based on the M-chart, the IVC parameters are determined, a parameter trend chart is generated based on the IVC parameters, and the parameter trend chart is displayed.

8. The method according to claim 7, characterized in that, Before performing adaptive interpolation processing on each of the target ultrasound images, the method further includes: Obtain the diameter of the IVC in each of the target images; The diameter of the IVC in the target image is compared with a preset diameter range; When the diameter of the IVC in the target image is within the preset diameter range, adaptive interpolation processing is performed on each target ultrasound image based on each target ultrasound image; When the diameter of the IVC in the target image is not within the preset diameter range, an error message is output, and the corresponding region of interest in the target image is adjusted.

9. An ultrasonic device, characterized in that, include: The system includes a human-computer interaction device and at least one probe interface, wherein the at least one probe interface is used for communicative connection between at least one probe and the human-computer interaction device, and the human-computer interaction device is used for... Multiple ultrasound images are acquired; the types of ultrasound images include IVC transverse sections and IVC longitudinal sections; The ultrasound image is compared with the target IVC cross-sectional image to determine and display the image quality of the ultrasound image, so as to obtain a target ultrasound image that meets the preset quality conditions. Based on the type and characteristics of the target ultrasound image, the location of the sampling line is determined to identify the region of interest. The IVC parameters are determined based on the features of the image of the region of interest. The step of determining the location of the sampling line based on the type and characteristics of the target ultrasound image to determine the region of interest includes: Based on the type and characteristics of the target ultrasound image, the sampling points are determined; Based on the location of the sampling point and the location information of the IVC in the target ultrasound image, the location of the sampling line is determined to determine the image of the region of interest; When the image quality near the sampling point meets the preset requirements, the region of interest is determined based on the location of the sampling point; The region of interest is subjected to quality detection to determine the image quality of the region of interest, and the image quality of the region of interest is displayed.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the parameter detection method according to any one of claims 1-8.

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