A method for calculating bladder volume and an ultrasound imaging device

Abstract

This invention discloses a method for calculating bladder volume and an ultrasound imaging device. The method includes: acquiring an ultrasound image of the bladder to be tested and identifying classification information of the ultrasound image; determining a size parameter in the ultrasound image that matches the classification information; and calculating the determined size parameter to obtain the volume of the bladder to be tested. The technical solution provided by this invention can conveniently calculate the bladder volume with high accuracy.

Description

Technical Field

[0001] This invention relates to the field of medical devices, specifically to a method for calculating bladder volume and an ultrasound imaging device. Background Technology

[0002] Currently, to effectively diagnose the bladder, it is usually necessary to calculate the bladder volume based on ultrasound images. The conventional method for calculating bladder volume typically involves identifying the shape of the bladder from ultrasound images and then measuring its volume accordingly.

[0003] Existing methods for calculating bladder volume typically require two parallel longitudinal images of the bladder, and then the bladder volume is measured based on the distance between these two images.

[0004] However, the distance between two bladder images is not easy to obtain, and the accuracy cannot be guaranteed. Therefore, the existing volume calculation method is cumbersome and not very accurate. Summary of the Invention

[0005] In view of this, the present invention provides a method for calculating bladder volume and an ultrasound imaging device, which can conveniently calculate bladder volume with high accuracy.

[0006] The present invention provides a method for calculating bladder volume, the method comprising: acquiring an ultrasound image of a bladder to be tested and identifying classification information of the ultrasound image; determining a size parameter in the ultrasound image that matches the classification information; and calculating the determined size parameter to obtain the volume of the bladder to be tested.

[0007] In one embodiment, determining the size parameters in the ultrasound image that match the classification information includes: if the classification information indicates that the ultrasound image is a transverse image, extracting the transverse diameter and thickness diameter of the bladder region in the ultrasound image; if the classification information indicates that the ultrasound image is a longitudinal image, extracting the long diameter of the bladder region in the ultrasound image.

[0008] In one embodiment, extracting the transverse diameter and thickness of the bladder region in the ultrasound image includes: determining the minimum bounding rectangle of the bladder region and determining the midpoints on the four sides of the minimum bounding rectangle; connecting the two midpoints of opposite sides of the minimum bounding rectangle to form a first auxiliary line segment and a second auxiliary line segment; determining a first line segment of the first auxiliary line segment located within the bladder region and a second line segment of the second auxiliary line segment located within the bladder region, taking the longer of the first line segment and the second line segment as the transverse diameter and the shorter of the two as the thickness.

[0009] In one embodiment, extracting the major axis of the bladder region in the ultrasound image includes: if the bladder region displayed in the longitudinal image is ellipsoidal, determining the minimum bounding rectangle of the bladder region, and determining the midpoints on the four sides of the minimum bounding rectangle; connecting the two midpoints of opposite sides of the minimum bounding rectangle to form a first auxiliary line segment and a second auxiliary line segment; determining a first line segment of the first auxiliary line segment located within the bladder region, and determining a second line segment of the second auxiliary line segment located within the bladder region, and taking the longer of the first line segment and the second line segment as the major axis of the bladder region.

[0010] In one embodiment, extracting the major axis of the bladder region in the ultrasound image includes: if the bladder region displayed in the longitudinal image is a triangular pyramid, counting the line segments passing through the centroid of the bladder region, and taking the longest line segment as the major axis of the bladder region.

[0011] In one embodiment, calculating the determined size parameters to obtain the volume of the bladder to be tested includes: identifying the bladder shape of the bladder to be tested based on the classification information of the ultrasound image, and selecting a calculation method that matches the bladder shape; wherein the bladder shape includes an ellipsoid or a triangular pyramid; and calculating the size parameters based on the selected calculation method to obtain the volume of the bladder to be tested.

[0012] In one embodiment, after obtaining the volume of the bladder to be tested, the method further includes: displaying a numerical value of the volume in the ultrasound image, wherein the numerical value of the volume has a color indicator, the color indicator being used to indicate whether the numerical value of the volume is within a specified volume range.

[0013] In one embodiment, the method further includes: displaying the envelope of the bladder to be tested in the ultrasound image, and marking the line segments corresponding to the size parameters in the area defined by the envelope.

[0014] In one embodiment, the method further includes: displaying ultrasound probe guidance information in the ultrasound image that matches the classification information of the ultrasound image, the ultrasound probe guidance information being used to characterize the scanning direction of the ultrasound probe when scanning to obtain the ultrasound image.

[0015] In one embodiment, after obtaining the volume of the bladder to be tested, the method further includes: displaying a volume change graph of the bladder to be tested over a specified time period, wherein the volume at each time point in the volume change graph has its own test state, the test state including a pre-urination state or a post-urination state.

[0016] In one embodiment, after obtaining the volume of the bladder to be tested, the method further includes: displaying a volume change graph of the bladder to be tested, the volume change graph including a pre-urination volume change curve, a post-urination volume change curve, and a standard volume reference line, wherein each volume in the post-urination volume change curve is color-coded, the color being determined by the difference between the current volume and a reference value in the standard volume reference line.

[0017] In another aspect, the present invention provides an ultrasound imaging device, comprising: an ultrasound probe for acquiring an ultrasound image of a bladder to be tested; a processor for identifying classification information of the ultrasound image; determining a size parameter in the ultrasound image that matches the classification information; calculating the determined size parameter to obtain the volume of the bladder to be tested; and a display screen for displaying the ultrasound image and the calculated volume value of the bladder to be tested, wherein the volume value has a color identifier, the color identifier being used to indicate whether the volume value is within a specified volume range.

[0018] In another aspect, the present invention provides a computer storage medium for storing a computer program, which, when executed by a processor, implements the above-described method for calculating bladder volume.

[0019] The technical solution provided in this application can first classify the bladder to be tested displayed in the ultrasound image. The purpose of classification can be to determine whether the current ultrasound image represents a transverse or longitudinal section. After classifying the ultrasound image, dimensional parameters matching the classification information can be determined in the ultrasound image. The purpose of this process is that different types of ultrasound images usually contain different dimensional parameters. For example, in a transverse section, the dimensional parameters can be the transverse diameter and thickness, while in a longitudinal section, the dimensional parameter can be the long diameter.

[0020] After obtaining the corresponding size parameters under different classification results, the above size parameters can be calculated to obtain the accurate volume.

[0021] As can be seen from the above, the technical solution provided in this application does not require obtaining the distance between two ultrasound images. Instead, it can obtain accurate size parameters through classification information and process the size parameters, thereby simplifying the volume calculation process and improving the accuracy of volume calculation. Attached Figure Description

[0022] The features and advantages of the invention will be more clearly understood by referring to the accompanying drawings, which are schematic and should not be construed as limiting the invention in any way. In the drawings:

[0023] Figure 1A schematic diagram of the structure of an ultrasound imaging device according to one embodiment of the present invention is shown;

[0024] Figure 2 The figure shows the steps of a scanning guidance method for an ultrasonic probe according to one embodiment of the present invention;

[0025] Figure 3 This diagram illustrates the control distribution of the intelligent guidance function in one embodiment of the present invention.

[0026] Figure 4 A schematic diagram of the control distribution for the intelligent guidance function in another embodiment of the present invention is shown;

[0027] Figure 5 This diagram illustrates a first display of scanning prompt information according to one embodiment of the present invention;

[0028] Figure 6 This diagram illustrates a second display of scanning prompt information according to one embodiment of the present invention;

[0029] Figure 7 This diagram illustrates a third display of scanning prompt information according to one embodiment of the present invention;

[0030] Figure 8 A schematic diagram of operation prompt information in one embodiment of the present invention is shown;

[0031] Figure 9 This diagram illustrates the display of operation prompt information in one embodiment of the present invention;

[0032] Figure 10 A schematic diagram of a bladder scanning process according to one embodiment of the present invention is shown;

[0033] Figure 11 A schematic diagram illustrating the steps of a volume calculation method according to one embodiment of the present invention is shown;

[0034] Figure 12 A schematic diagram of the transverse diameter and thickness diameter is shown in one embodiment of the present invention;

[0035] Figure 13 A schematic diagram of the major axis corresponding to the ellipsoid in one embodiment of the present invention is shown;

[0036] Figure 14 A schematic diagram of the major axis corresponding to the triangular pyramid in one embodiment of the present invention is shown;

[0037] Figure 15 A schematic diagram showing the scanning results according to one embodiment of the present invention is shown;

[0038] Figure 16A schematic diagram of the volume change curve is shown in one embodiment of the present invention. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of the present invention more apparent, exemplary embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely a part of the embodiments of the present invention, and not all of them. It should be understood that the present invention is not limited to the exemplary embodiments described herein. Based on the embodiments described in the present invention, all other embodiments obtained by those skilled in the art without inventive effort should fall within the protection scope of the present invention.

[0040] In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the invention. However, it will be apparent to those skilled in the art that the invention can be practiced without one or more of these details. In other instances, certain technical features well-known in the art have not been described in order to avoid obscuring the invention.

[0041] It should be understood that the present invention can be embodied in various forms and should not be construed as being limited to the embodiments set forth herein. Rather, providing these embodiments will make the disclosure thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0042] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. When used herein, the singular forms “a,” “an,” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising” and / or “including,” when used in this specification, identify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups. When used herein, the term “and / or” includes any and all combinations of the associated listed items.

[0043] To fully understand this invention, a detailed structure will be presented in the following description to illustrate the technical solution proposed by this invention. Optional embodiments of the invention are described in detail below; however, in addition to these detailed descriptions, the invention may also have other embodiments.

[0044] Please see Figure 1 , Figure 1A schematic diagram of the structure of an ultrasound imaging device 100 according to an embodiment of the present invention is shown. The ultrasound imaging device 100 includes an ultrasound probe 101, a transmitting circuit 102, a receiving circuit 103, a transmitting / receiving selection switch 104, a processor 105, and a human-computer interaction device 106. The transmitting circuit 102 and the receiving circuit 103 can be connected to the ultrasound probe 101 through the transmitting / receiving selection switch 104.

[0045] During ultrasound imaging, the transmitting circuit 102 sends a delayed-focused transmission pulse with a certain amplitude and polarity to the ultrasound probe 101 via a transmit / receive selection switch 104 to excite the ultrasound probe 101 to emit ultrasound waves. After a certain delay, the receiving circuit 103 receives the echo of the ultrasound wave via the transmit / receive selection switch 104, obtaining an ultrasound echo signal. This echo signal is then amplified, converted from analog to digital, and beamformed. The processed ultrasound echo signal is then sent to the processor 105 for further processing. The processor 105 processes the ultrasound echo signal to obtain the corresponding ultrasound image. The contrast images and / or tissue reference images obtained by the processor 105 can be stored in the memory 107. These images can be displayed on the screen of the human-computer interaction device 106.

[0046] The human-computer interaction device 106 is connected to the processor 105. For example, the processor 105 can be connected to the human-computer interaction device 106 via an external input / output port. The human-computer interaction device 106 can detect user input information, which may be, for example, control commands for ultrasonic wave transmission and reception timing, operation input commands for starting static image capture, dynamic video capture, and / or dynamic image storage, or other command types. The human-computer interaction device 106 may include one or more of the following: keyboard, mouse, scroll wheel, trackball, mobile input device (such as a mobile device with a touch screen, a mobile phone, etc.), multi-function knob, buttons, etc. Therefore, the corresponding external input / output port may be a wireless communication module, a wired communication module, or a combination of both. The external input / output port may also be implemented based on USB, bus protocols such as CAN, and / or wired network protocols.

[0047] The human-computer interaction device 106 also includes a display screen that can display ultrasound images acquired by the processor 105. Furthermore, during ultrasound imaging or when displaying ultrasound images, the display screen can provide a graphical interface for user interaction. One or more controlled objects can be set on the graphical interface, allowing the user to input operation commands through the human-computer interaction device 106 to control these controlled objects and perform corresponding control operations. For example, icons can be displayed on the graphical interface, and the human-computer interaction device can operate on these icons to perform specific functions, such as the function of storing dynamic images while simultaneously capturing static images / movie clips. In practical applications, the display screen can be a touch screen. Furthermore, the display screen in this embodiment may include one display screen or multiple display screens.

[0048] In this embodiment of the invention, the processor 105 is further configured to receive an instruction to store the ultrasound image, and in response to the instruction, store dynamic images, static images, or short animated videos of the ultrasound image, thereby facilitating user (e.g., doctor) to review and perform diagnosis. The terms "dynamic image," "static image," or "short animated video" can refer to simultaneously presented grayscale images of tissue structures and contrast images, or can refer to contrast images alone.

[0049] In this application, the ultrasound imaging device can provide a built-in scan guidance function. When this scan guidance function is activated, the user can complete the bladder scan process under the guidance of the ultrasound imaging device, thereby acquiring multiple qualified ultrasound images of the bladder to be tested. The specific implementation of the scan guidance function can be described as follows.

[0050] Please see Figure 2 The ultrasound probe scanning guidance method provided in this application may include the following steps.

[0051] S1: Acquire the ultrasound image currently captured by the ultrasound probe and generate the corresponding scanning prompt information for the ultrasound image.

[0052] In this embodiment, when using the ultrasound imaging device, the user can select whether to enable the intelligent guidance function on the device's display screen. To facilitate user selection, the intelligent guidance function's on / off control can be placed on the current interface. For example, this control can be located in the upper left corner of the current interface. The implementation of this control can vary. Figure 3 and Figure 4 Each example illustrates a common control implementation method in practical applications. Figure 3 In the diagram, when the circular movable component is on the left, it indicates that the Smart Guide function is off, while when the circular movable component is on the right, it indicates that the Smart Guide function is on. Figure 4In the code, when the Smart Guide checkbox is selected (filled in black), it indicates that the Smart Guide feature is enabled; when the Smart Guide checkbox is unselected (filled in blank), it indicates that the Smart Guide feature is disabled. Of course, as application scenarios change and technology continues to advance, the above control can be implemented in many more ways, which will not be listed here.

[0053] In this embodiment, when the intelligent guidance function is activated, the ultrasound imaging device can execute a built-in guidance strategy to assist the user in scanning with the ultrasound probe. Specifically, when a user attempts to scan a part of the human body using an ultrasound probe, due to a lack of professional knowledge, the user may not be able to accurately identify the area being examined. In this case, the ultrasound imaging device can acquire the ultrasound image currently being scanned by the ultrasound probe in real time. By recognizing the ultrasound image, it can determine whether the content displayed in the ultrasound image corresponds to the area being examined, and generate corresponding scanning prompt information based on the judgment result. This scanning prompt information can be used to inform the user whether the currently scanned area is located within the target area of ​​the area being examined, or it can be used to inform the user whether the quality of the ultrasound image acquired by the ultrasound probe meets the standards. In this application, whether the quality of the ultrasound image meets the standards refers to whether the content in the ultrasound image can clearly display the characteristics of the area being examined.

[0054] In practical applications, the generation of scanning prompts can take many forms. For example, in one implementation, a preset standard image corresponding to the examined area can be pre-stored in the ultrasound imaging device. This preset standard image can be an image that clearly displays the features of the examined area. By calculating the similarity between the ultrasound image acquired by the ultrasound probe and the preset standard image, scanning prompts matching the similarity can be generated. The generated scanning prompts can be color labels or text information used to characterize image quality, which can be determined by the similarity between the ultrasound image and the preset standard image; higher similarity indicates higher image quality. Different image qualities can correspond to different color labels or text information.

[0055] Please see Figure 5The color-coded label representing image quality can be the envelope (thick line) of the scanned area in the ultrasound image. This envelope can display different colors depending on the image quality. For example, when the quality is poor, the envelope may be red, indicating that the currently scanned area may not have reached the target area of ​​the examined site. When the quality is average, the envelope may be yellow, indicating that the currently scanned area is within the target area of ​​the examined site, but there is still some deviation from the center. When the quality is good, the envelope may be green, indicating that the currently scanned area has a high degree of overlap with the target area of ​​the examined site. Different image qualities can be determined by the similarity between the ultrasound image and a preset standard image. For example, a similarity below 60% indicates poor quality; a similarity between 60% and 80% indicates average quality; and a similarity above 80% indicates good quality.

[0056] It should be noted that the above-mentioned envelope with different colors is only one way to implement color labels. In practical applications, color labels can also be implemented in other ways. For example, in Figure 6 In this context, color labels can be displayed as a rectangular filled color block after the "Quality Tip:" text. Other similar implementations will not be listed here.

[0057] In another implementation, the textual information characterizing image quality can be directly expressed in text form, indicating the current ultrasound image's quality. For example, in... Figure 7 In the process, the interface of the ultrasound image can display text information such as "Image Quality: Average". The adjectives indicating image quality, such as "Average", "Excellent", or "Poor", are determined based on the similarity between the ultrasound image and a preset standard image. For details on the implementation method, please refer to the description of the above implementation method; it will not be repeated here.

[0058] In practical applications, scanning prompts can also take other forms, such as a combination of color labels and text information. Those skilled in the art should understand that anything that reflects the image quality of the current ultrasound image should fall within the protection scope of this application.

[0059] S2: Display the scanning prompt information to guide the ultrasound probe to the target area where the examined part is located.

[0060] In this embodiment, after the scanning prompt information is generated, it can be displayed on the screen. The display method of the scanning prompt information can be found in [reference needed]. Figures 5 to 7Users can check the current ultrasound image quality by observing the scan prompts on the display screen. If the ultrasound image quality is not up to standard, users can try moving the ultrasound probe until the quality is satisfactory. In this way, the ultrasound probe can ultimately be guided to the target area of ​​the examined site by following the scan prompts displayed on the screen.

[0061] Specifically, when the ultrasound probe is guided to the target area of ​​the examined site, the image quality represented by the aforementioned color label or text information will be within the specified quality range. Here, "image quality within the specified quality range" can mean that the color in the color label is one or more specified colors. For example, when the color is yellow or green, the image quality can be considered to be within the specified quality range. Furthermore, "image quality within the specified quality range" can also mean that the quality level indicated in the text information is one or more specified quality levels. For example, when the quality level is "moderate" or "excellent," the image quality can be considered to be within the specified quality range.

[0062] During ultrasound scanning, the ultrasound imaging device can display real-time scanning prompts for each ultrasound image on the screen. The closer the ultrasound probe is to the target area of ​​the examined site, the closer the displayed scanning prompts will be to the preset acceptable information. These preset acceptable information can be set using color labels or text information. For color labels, the preset acceptable information can be one or more specified colors; for text information, the preset acceptable information can be one or more specified quality levels. When the color label or text information displayed on the interface corresponds to the specified color or quality level, the user knows that the ultrasound probe is currently located within the target area of ​​the examined site.

[0063] S3: When the ultrasound probe scans the target area, the cross-sectional information is identified from the ultrasound image acquired by the ultrasound probe, and an operation prompt message is generated based on the cross-sectional information.

[0064] In this embodiment, when the ultrasonic probe scans the area to be examined, it can be divided into transverse scanning and longitudinal scanning depending on the direction of the probe. Generally, the direction of the ultrasonic probe in transverse scanning and longitudinal scanning states can differ by 90°. Therefore, when the ultrasonic probe scans the target area of ​​the area to be examined, in order to comprehensively acquire the ultrasonic image of the area, the cross-sectional information can be identified from the current ultrasonic image, and operation prompts can be generated based on this cross-sectional information. These operation prompts can guide the user on how to change the direction of the ultrasonic probe.

[0065] Specifically, in ultrasound imaging equipment, a standard image set can be pre-stored. Each standard image in this set is a high-quality ultrasound image acquired with the ultrasound probe in either a transverse or longitudinal section of the area being examined. Each standard image can be labeled with its own section information to indicate whether it was acquired in a transverse or longitudinal section. In practical applications, after the ultrasound probe acquires an ultrasound image within the target area, this image can be compared with the standard images in the set to determine the target standard image that matches the acquired image. The similarity between the matching ultrasound image and the target standard image can exceed a certain threshold. For example, a similarity greater than or equal to 90% is considered a match between the ultrasound image and the target standard image.

[0066] After identifying a matching target standard image, the cross-sectional information of that target standard image can be identified and used as the cross-sectional information identified from the ultrasound image acquired by the ultrasound probe. For example, if the cross-sectional information of the target standard image matching the ultrasound image represents a transverse section, then it can be assumed that the current ultrasound image was acquired when the ultrasound probe was in a transverse section state.

[0067] In this embodiment, after identifying the cross-sectional information of the ultrasound image, if the cross-sectional information represents a transverse section, then an operation prompt message can be generated to switch from a transverse section to a longitudinal section. Conversely, if the cross-sectional information represents a longitudinal section, then an operation prompt message can be generated to switch from a longitudinal section to a transverse section.

[0068] In practical applications, the presentation of operation prompts can take many forms. These prompts can be voice, image, or video information indicating the direction of ultrasound probe rotation. For example, the generated voice message could be "Please rotate the ultrasound probe 90° to switch to state XX," where "XX" can be filled in as "horizontal cut" or "vertical cut" depending on the specific situation. Another example is... Figure 8 The image shown can remind the user to rotate the ultrasound probe in the direction indicated by the arrow. Furthermore, to facilitate user understanding, a video can be generated showing the specific rotation process of the ultrasound probe. Of course, there are many other ways to implement operation prompts, which will not be listed here.

[0069] S4: Display the operation prompt information to guide the ultrasound probe from the first direction represented by the section information to the second direction.

[0070] In this embodiment, after the operation prompt information is generated, it can be displayed in the current ultrasound image or played through a speaker. For example, in Figure 9 In this process, the generated image information can be located in the lower left corner of the ultrasound image for easy viewing by the user. The user can follow the operation prompts to rotate the ultrasound probe, thus guiding it from the first direction represented by the current section information to the second direction to be scanned.

[0071] In one implementation, the aforementioned scanning prompts and section information can be determined using machine learning. The scanning prompts and section information can serve as labels for the ultrasound images, and by training on a training sample set, a recognition model capable of accurately predicting the scanning prompts and section information can be obtained.

[0072] Specifically, an image training sample set can be obtained first. This set includes both forward and reverse image samples. Forward image samples can be high-quality ultrasound images, while reverse image samples can be low-quality ultrasound images. For each image sample, a corresponding sample label can be assigned. This label represents the scanning prompts and cross-sectional information of the image sample. For example, for a forward image sample, the corresponding sample label could be {"Excellent", "Horizontal"}, and for a reverse image sample, the corresponding sample label could be {"Poor", "None"}. Of course, the sample labels can be described using a computer-recognizable language. For instance, scanning prompts can be represented by binary numbers such as 00, 01, and 10, representing different image qualities; cross-sectional information can be represented by 0, 1, and none, where 0 represents a horizontal cross-section, 1 represents a vertical cross-section, and none represents no cross-sectional information (the "None" in the sample label above).

[0073] After obtaining the aforementioned training image sample set, a pre-defined recognition model can be trained based on the image samples labeled with sample tags. This recognition model can be implemented using existing neural network architectures in deep learning. For example, the recognition model could be a FastCNN neural network architecture. After training with a large number of image samples, the trained recognition model can output scanning prompts and cross-sectional information corresponding to the input ultrasound image. Subsequently, the ultrasound imaging device can generate corresponding operation prompts based on the cross-sectional information. In this way, during the ultrasound probe scanning process, relying on the recognition model, the ultrasound imaging device can recognize the acquired ultrasound images in real time and display scanning prompts and subsequent operation prompts on the current interface to guide the user to position the ultrasound probe to the target area of ​​the examined part and guide the user to adjust the direction of the ultrasound probe.

[0074] The technical solution provided in this application does not require users to possess extensive professional knowledge. Instead, it guides users through the ultrasound image acquisition process via intelligent guidance. Specifically, when a user acquires ultrasound images using an ultrasound probe, the ultrasound imaging device can generate real-time scanning prompts corresponding to the ultrasound images. By displaying these prompts on the screen, the user is guided to move the ultrasound probe to the target area of ​​the area being examined. When the ultrasound probe is scanning the target area, the ultrasound imaging device can identify the cross-sectional information of the ultrasound image, indicating whether the ultrasound probe is performing a transverse or longitudinal scan. Based on this cross-sectional information, further operation prompts can be generated. By displaying these prompts, the user is guided to change the orientation of the ultrasound probe, thereby completing a comprehensive transverse and longitudinal scan.

[0075] As can be seen from the above, the ultrasound imaging equipment in this application can still guide users to complete the ultrasound image acquisition process even when they lack professional knowledge, and can also ensure the quality and comprehensiveness of the ultrasound images during the acquisition process. Therefore, the technical solution provided by this application can not only lower the threshold for using ultrasound imaging equipment, but also capture ultrasound images of the required quality.

[0076] For a specific application example, please refer to Figure 10 Taking a bladder scan as an example, after selecting the ultrasound probe for the scan, the user can trigger the intelligent guidance function on the ultrasound imaging device's display screen. During the ultrasound probe scan, the ultrasound imaging device can identify the image quality corresponding to the current ultrasound image and display it using a colored envelope. Based on the displayed image quality, the user can continuously move the ultrasound probe until the envelope color reaches yellow or green.

[0077] When the envelope color reaches yellow or green, it indicates that the current ultrasound image quality meets the standard. At this time, the ultrasound imaging device can display the current slice information on the screen. If the slice information represents a transverse section, the screen can display an operation prompt to switch from transverse to longitudinal section; conversely, if the slice information represents a longitudinal section, the screen can display an operation prompt to switch from longitudinal to transverse section. Based on the displayed operation prompts, the user can rotate the ultrasound probe to acquire a more complete bladder image.

[0078] The ultrasound images of the bladder to be tested can be acquired using the methods described above. Please refer to [link / reference]. Figure 11 The method for calculating bladder volume provided in this application may include the following steps.

[0079] S21: Acquire an ultrasound image of the bladder to be tested and identify the classification information of the ultrasound image.

[0080] In this embodiment, ultrasound images can be acquired using the intelligent guidance method described above, thereby obtaining multiple ultrasound images of the bladder to be tested that meet the requirements.

[0081] After acquiring the aforementioned ultrasound images, a series of optimization processes can be performed on them to provide an accurate basis for subsequent volume calculations. Specifically, the ultrasound images can be preprocessed using various methods, such as normalization, adaptive histogram equalization, standardization, and gamma correction. In practical applications, one or more of these preprocessing methods can be selected as needed.

[0082] In one implementation, after preprocessing the ultrasound image, image segmentation can be performed to generate a segmentation feature image corresponding to the ultrasound image. In practical applications, deep learning models such as U-Net, the maximum inter-class variance method, and the watershed method can be used to segment the ultrasound image. After generating the segmentation feature image, it can be binarized, where the gray value of the foreground (bladder region) pixels can be 255, and the gray value of the background (non-bladder region) pixels can be 0. In this way, by representing the foreground and background, the bladder region can be clearly marked in the ultrasound image.

[0083] In one implementation, considering that regions with fewer pixels may have lower accuracy in image recognition, these regions can be removed to avoid affecting the recognition results of the bladder region. Specifically, contour lines in the segmentation feature image can be identified. Generally, the region defined by the largest contour line should be the bladder region. Other contour lines located inside the largest contour line may be misclassified regions due to device or image display issues, and these regions usually contain fewer pixels. Therefore, the number of pixels in the regions defined by each contour line can be counted, and one or more regions in the segmentation feature image can be removed based on the counted number of pixels. Specifically, regions with fewer pixels than a specified threshold can be removed from the segmentation feature image. In this way, while retaining the largest contour line, regions with fewer pixels in the bladder region can be removed to avoid interference from these regions in the subsequent results.

[0084] In this embodiment, removing small regions with few pixels results in holes in the segmented feature image. These holes, formed by region removal, can be filled with grayscale values ​​based on the grayscale values ​​of pixels in the neighboring region. Specifically, for any target pixel within a hole, the number of pixels with a specified grayscale value within the neighborhood centered on that target pixel can be counted. For example, a 3x3 neighborhood centered on the target pixel can be selected, containing 9 pixels. The number of pixels with a grayscale value of 255 among these 9 pixels can then be counted; this grayscale value of 255 can be the specified grayscale value mentioned above. If the number of pixels with the specified grayscale value is greater than or equal to a specified threshold, the grayscale value of the target pixel can be set to the specified grayscale value. For example, the specified threshold could be 5. If the number of pixels with a grayscale value of 255 in the neighborhood is greater than or equal to 5, then at least 5 of these 9 pixels belong to the foreground. In this case, the grayscale value of the target pixel can be set to 255, and it is considered a foreground pixel. Conversely, if the number of pixels with the specified grayscale value is less than the specified threshold, the grayscale value of the target pixel can be set to another grayscale value. For example, this other grayscale value could be 0, representing the background.

[0085] After processing the segmented feature image as described above, edge smoothing can be performed. Specifically, this can be achieved by constructing a Gaussian convolution kernel and then convolving the segmented feature image with the kernel. In practical applications, a horizontal Gaussian convolution kernel can be generated first, and then a vertical Gaussian convolution kernel can be obtained through matrix transposition. The segmented feature image is then convolved with the horizontal Gaussian convolution kernel, and the result is then convolved with the vertical Gaussian convolution kernel to complete the edge smoothing process.

[0086] In one implementation, considering that some patients have large bladders that may exceed the scanning range of the ultrasound probe, information beyond the ultrasound probe may be misidentified as the bladder area during image segmentation. Therefore, during image segmentation, the portion of the image exceeding the ultrasound probe's scanning range needs to be erased to avoid misidentification of the bladder area.

[0087] In one implementation, after the above processing, the grayscale value of pixels in the bladder region of the segmented feature image is 255, while the grayscale value of pixels in the non-bladder region is 0. By judging the grayscale values ​​of the pixel neighborhoods, the pixels on the envelope of the bladder region can be determined. In practical applications, this envelope can be displayed on a screen, allowing the user to visually view the bladder region.

[0088] In this embodiment, machine learning algorithms can be used to train a recognition model for identifying image types. These machine learning algorithms may include, for example, k-means algorithm, support vector machine, convolutional neural network, recurrent neural network, etc. During the training phase, cross-sectional images, longitudinally sectioned ellipsoidal images, and longitudinally sectioned triangular pyramidal images can be provided. Thus, by inputting the segmented feature images into the trained recognition model, corresponding classification information can be obtained. This classification information can characterize the cross-sectional image, longitudinally sectioned ellipsoidal image, and longitudinally sectioned triangular pyramidal image.

[0089] S22: Determine the size parameters in the ultrasound image that match the classification information.

[0090] In this embodiment, the dimensional parameters used to calculate the volume differ for different types of ultrasound images. Specifically, if the classification information indicates that the ultrasound image is a transverse image, the transverse diameter and thickness of the bladder region in the ultrasound image can be extracted. If the classification information indicates that the ultrasound image is a longitudinal image, the long diameter of the bladder region in the ultrasound image can be extracted.

[0091] The transverse diameter and thickness diameter in a cross-sectional image can be as follows: Figure 12As shown, when determining the transverse diameter and thickness, we can first determine the smallest bounding rectangle of the bladder region (shown by the dashed line), and then determine the midpoints on each of the four sides of this smallest bounding rectangle. Then, we can connect the two midpoints of opposite sides of the smallest bounding rectangle to form a first auxiliary line segment and a second auxiliary line segment. Both the first and second auxiliary line segments intersect the envelope of the bladder region. We determine the first segment of the first auxiliary line segment that lies within the bladder region, and the second segment of the second auxiliary line segment that lies within the bladder region. Finally, we can use the longer of the first and second segments as the transverse diameter and the shorter of the two as the thickness.

[0092] The bladder region in the longitudinal section image can be further subdivided into ellipsoidal and triangular pyramidal shapes. If the bladder region shown in the longitudinal section image is ellipsoidal, then the longer line segment can be used as the major axis, following the method described above for determining the transverse and thickness axes. Specifically, the smallest bounding rectangle of the bladder region can be determined, and the midpoints of the four sides of the smallest bounding rectangle can be determined respectively. Connecting the two midpoints of opposite sides of the smallest bounding rectangle forms a first auxiliary line segment and a second auxiliary line segment. The first line segment of the first auxiliary line segment located within the bladder region is determined, and the second line segment of the second auxiliary line segment located within the bladder region is determined. The longer of the first and second line segments is taken as the major axis of the bladder region. Finally, the determined major axis can be determined as follows: Figure 13 As shown.

[0093] If the bladder region shown in the longitudinal section image is a triangular pyramid, the line segments passing through the centroid within the bladder region can be counted, and the longest line segment obtained can be taken as the major axis of the bladder region. For example, in Figure 14 In the case of a triangular pyramidal bladder, the major axis can be determined as shown in the figure. This major axis is the longest line segment passing through the centroid in the bladder region.

[0094] Of course, in practical applications, if it is not necessary to automatically obtain the above-mentioned size parameters, users can also manually input the corresponding size parameters into the ultrasound imaging device.

[0095] S23: Calculate the determined size parameters to obtain the volume of the bladder to be tested.

[0096] In this embodiment, the classification information of the ultrasound image can characterize in detail whether the bladder shape is triangular pyramidal or ellipsoidal. Different calculation methods can be used for different bladder shapes to calculate a more accurate volume.

[0097] In practical applications, for an ellipsoidal bladder, the calculation formula can be:

[0098]

[0099] For a triangular pyramidal bladder, the calculation formula can be:

[0100]

[0101] Where V represents the calculated bladder volume, D1 represents the transverse diameter, D2 represents the thickness diameter, and D3 represents the length diameter.

[0102] In this embodiment, based on the actual shape of the bladder to be tested, a corresponding calculation method can be selected. By substituting the size parameters obtained in the above steps into the corresponding calculation method, the volume of the bladder to be tested can be obtained.

[0103] In one implementation, after calculating the volume of the bladder to be tested, this volume can be displayed in an ultrasound image so that the user can know the current bladder volume while viewing the ultrasound image. For details, please refer to... Figure 15 The ultrasound image display screen can show both transverse and longitudinal ultrasound images, and the bladder volume can be labeled in the displayed images. For example, in Figure 15 The ultrasound image may display "Bladder parameter: 150ml". However, for users without professional knowledge, even if the volume value is marked on the ultrasound image, they cannot determine whether the value is abnormal. Therefore, color coding can be used to display the volume value, where the color indicates whether the volume value is within a specified volume range. This specified volume range can be a normal volume range; if it is within the specified volume range, the volume value is considered normal and is displayed in green. If it is outside the specified volume range, the volume value is considered abnormal and is displayed in red. Of course, in practical applications, the specified volume range can be further subdivided, and different subdivisions can correspond to different color coding. For example, the specified volume range could be divided into green and yellow, where green corresponds to a more normal volume value than yellow.

[0104] In one implementation, further information can be displayed in the ultrasound images, allowing the user to better understand the condition of the bladder being tested. For details, please refer to [link to relevant documentation]. Figure 15 The ultrasound image can also display the envelope of the bladder being tested, and the color of this envelope can be consistent with the color of the volume value. Within the area defined by the envelope, line segments corresponding to the various dimensional parameters can be marked. For example, in a transverse ultrasound image, the transverse diameter and thickness can be marked, while in a longitudinal ultrasound image, the major diameter can be marked. When a line segment within the area defined by the envelope is selected, the corresponding dimensional parameter can be displayed on the screen. Similarly, the dimensional parameters and line segments can also have the same color coding, and the color coding can indicate whether the dimensional parameters are within the normal range.

[0105] In this embodiment, ultrasound probe guidance information matching the classification information of the ultrasound image can also be displayed in the ultrasound image. The classification information can represent a transverse or longitudinal section, and the ultrasound probe guidance information can represent the scanning direction of the ultrasound probe when obtaining the corresponding ultrasound image. The ultrasound probe guidance information can be displayed in the corresponding ultrasound image as a static image. For example, in... Figure 15 In the image, the left side shows a transverse ultrasound image, and the right side shows a longitudinal ultrasound image. The scanning direction of the ultrasound probe can be seen in the lower left corner of each of these two ultrasound images.

[0106] In one implementation, after collecting multiple bladder volume values ​​over a period of time, the ultrasound imaging device can create a volume change graph of the bladder under test. Specifically, the volume change graph can display the volume values ​​at various time points. To better assist doctors in diagnosis, the volume at each time point can have its own test status, including pre-urination or post-urination status. Thus, when a doctor or user selects a volume value, it can be displayed whether the volume value was measured in the pre-urination or post-urination state. The purpose of this is that for patients with urinary system problems, a significant amount of urine may remain in the bladder after urination. In this case, without indicating the test status, the post-urination volume value might be mistaken for the pre-urination volume value, leading to misdiagnosis. Therefore, indicating the test status in the volume change graph can reduce the possibility of misdiagnosis.

[0107] Please see Figure 16 In one embodiment, when displaying the volume change graph of the bladder to be tested, the pre-urination volume change curve, the post-urination volume change curve, and the standard volume reference line can be displayed simultaneously. This allows for a clear comparison of the volume difference before and after urination in the volume change graph, and also enables a determination of whether the volume value is normal when compared with the standard volume reference line.

[0108] Specifically, Figure 16 The solid line represents the pre-urination volume change curve, the dashed line represents the post-urination volume change curve, and the dotted line represents the standard volume reference line. The standard volume reference line serves as a standard for the post-urination volume value. Each volume in the post-urination volume change curve can have its own color indicator, determined by the difference between the current volume and the reference value in the standard volume reference line. If the difference is within the acceptable range, it is displayed in green; if the difference is outside the acceptable range, it is displayed in red. Of course, in practical applications, more detailed range divisions can be used to display even more different color indicators, which will not be elaborated upon here.

[0109] It should be noted that volume change graphs can be implemented in many other ways. For example, they can be dynamically displayed on a screen, showing the volume values ​​at each time point step by step. Alternatively, they can be displayed as bar charts, showing the volume values ​​before and after urination, as well as the standard reference value, at each time point.

[0110] The technical solution provided in this application can first classify the bladder to be tested displayed in the ultrasound image. The purpose of classification can be to determine whether the current ultrasound image represents a transverse or longitudinal section. After classifying the ultrasound image, dimensional parameters matching the classification information can be determined in the ultrasound image. The purpose of this process is that different types of ultrasound images usually contain different dimensional parameters. For example, in a transverse section, the dimensional parameters can be the transverse diameter and thickness, while in a longitudinal section, the dimensional parameter can be the long diameter.

[0111] After obtaining the corresponding size parameters under different classification results, the shape of the bladder can be further identified. Different bladder shapes require different calculation methods. By using an appropriate calculation method to calculate the aforementioned size parameters, an accurate volume can be determined.

[0112] As can be seen from the above, the technical solution provided in this application does not require obtaining the distance between two ultrasound images. Instead, it can obtain accurate size parameters through classification information and use an appropriate calculation method to process the size parameters, thereby simplifying the volume calculation process and improving the accuracy of volume calculation.

[0113] Please combine Figure 1 One embodiment of this application also provides an ultrasound imaging device, the ultrasound imaging device comprising:

[0114] Ultrasound probe 101 is used to acquire ultrasound images of the bladder to be tested;

[0115] The processor 105 is configured to: identify classification information of the ultrasound image; determine size parameters in the ultrasound image that match the classification information; identify the bladder shape of the bladder to be tested based on the classification information of the ultrasound image, and select a calculation method that matches the bladder shape; calculate the size parameters based on the selected calculation method to obtain the volume of the bladder to be tested.

[0116] The display screen (located in the human-computer interaction device 106, not shown) is used to display the ultrasound image and the calculated volume value of the bladder to be tested, wherein the volume value has a color indicator, and the color indicator is used to indicate whether the volume value is within a specified volume range.

[0117] This application also provides an ultrasound imaging device, which includes a processor and a memory. The memory is used to store a computer program, which, when executed by the processor, implements the above-described method for calculating bladder volume.

[0118] This application also provides a computer storage medium for storing a computer program, which, when executed by a processor, implements the above-described method for calculating bladder volume.

[0119] The processor can be a central processing unit (CPU). It can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations thereof.

[0120] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the methods in the embodiments of this invention. The processor executes various functional applications and data processing by running the non-transitory software programs, instructions, and modules stored in the memory, thereby implementing the methods described in the above embodiments.

[0121] The memory may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the processor, etc. Furthermore, the memory may include high-speed random access memory and non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0122] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0123] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed.

[0124] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0125] Similarly, it should be understood that, in order to simplify the invention and aid in understanding one or more of the various aspects of the invention, features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of the invention. However, this approach should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the corresponding claims, its inventive point lies in solving the corresponding technical problem with fewer features than all of a single disclosed embodiment. Therefore, the claims following the detailed description are thus expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0126] Those skilled in the art will understand that, apart from the mutual exclusion of features, all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or elements of any method or apparatus so disclosed can be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature serving the same, equivalent, or similar purpose.

[0127] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any one of the claimed embodiments can be used in any combination.

[0128] The various components of this invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some modules according to embodiments of the invention. The invention can also be implemented as an apparatus program (e.g., a computer program and computer program product) for performing some or all of the methods described herein. Such programs implementing the invention can be stored on a computer-readable medium or can take the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0129] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

Claims

1. A method for calculating bladder volume, characterized in that, The method includes: Acquire ultrasound images of the bladder to be tested and identify the classification information of the ultrasound images; Determine the size parameters in the ultrasound image that match the classification information; wherein, the determination includes: if the classification information indicates that the ultrasound image is a transverse image, extracting the transverse diameter and thickness diameter of the bladder region in the ultrasound image; if the classification information indicates that the ultrasound image is a longitudinal image, extracting the long diameter of the bladder region in the ultrasound image. The determined size parameters are calculated to obtain the volume of the bladder to be tested; wherein, the calculation includes: identifying the shape of the bladder to be tested based on the classification information of the ultrasound image, and selecting a calculation method suitable for the bladder shape; wherein, the bladder shape includes an ellipsoid or a triangular pyramid; the size parameters are calculated based on the selected calculation method to obtain the volume of the bladder to be tested; for an ellipsoidal bladder shape, the calculation method is as follows: For a triangular pyramidal bladder shape, the calculation method is as follows: In the formula, This represents the calculated bladder volume. Indicates the transverse diameter. Indicates thickness diameter, Indicates the major axis.

2. The method according to claim 1, characterized in that, Extracting the transverse and thickness diameters of the bladder region from the ultrasound image includes: Determine the minimum bounding rectangle of the bladder region, and determine the midpoints on the four sides of the minimum bounding rectangle; Connect the two midpoints of opposite sides of the minimum bounding rectangle to form the first auxiliary line segment and the second auxiliary line segment; Identify a first line segment within the bladder region from the first auxiliary line segment, and a second line segment within the bladder region from the second auxiliary line segment. Use the longer of the first and second line segments as the transverse diameter, and the shorter of the two as the thickness diameter.

3. The method according to claim 1, characterized in that, Extracting the long axis of the bladder region from the ultrasound image includes: If the bladder region shown in the longitudinal section image is ellipsoidal, determine the minimum bounding rectangle of the bladder region, and determine the midpoints on the four sides of the minimum bounding rectangle respectively; Connect the two midpoints of opposite sides of the minimum bounding rectangle to form the first auxiliary line segment and the second auxiliary line segment; Identify a first line segment within the bladder region from the first auxiliary line segment, and a second line segment within the bladder region from the second auxiliary line segment, and take the longer of the first and second line segments as the major axis of the bladder region.

4. The method according to claim 1, characterized in that, Extracting the long axis of the bladder region from the ultrasound image includes: If the bladder region shown in the longitudinal section image is a triangular pyramid, count the line segments passing through the centroid within the bladder region, and take the longest line segment as the major axis of the bladder region.

5. The method according to claim 1, characterized in that, After obtaining the volume of the bladder to be tested, the method further includes: The volume value is displayed in the ultrasound image, wherein the volume value is color-coded to indicate whether the volume value is within a specified volume range.

6. The method according to claim 1 or 5, characterized in that, The method further includes: The envelope of the bladder to be tested is displayed in the ultrasound image, and the line segments corresponding to the size parameters are marked in the area defined by the envelope.

7. The method according to claim 1 or 5, characterized in that, The method further includes: Ultrasonic probe guidance information that matches the classification information of the ultrasonic image is displayed in the ultrasonic image. The ultrasonic probe guidance information is used to characterize the scanning direction of the ultrasonic probe when scanning to obtain the ultrasonic image.

8. The method according to claim 1, characterized in that, After obtaining the volume of the bladder to be tested, the method further includes: The graph displays the volume change of the bladder under test over a specified period of time. In the volume change graph, the volume at each time point has its own test state, which includes the pre-urination state or the post-urination state.

9. The method according to claim 1, characterized in that, After obtaining the volume of the bladder to be tested, the method further includes: The diagram displays the volume change of the bladder under test, which includes a pre-urination volume change curve, a post-urination volume change curve, and a standard volume reference line. Each volume in the post-urination volume change curve is color-coded, and the color is determined by the difference between the current volume and the reference value in the standard volume reference line.

10. An ultrasonic imaging device, characterized in that, The ultrasound imaging device includes: An ultrasound probe is used to acquire ultrasound images of the bladder being tested. A processor is configured to: identify classification information of the ultrasound image; determine size parameters in the ultrasound image that match the classification information; calculate the determined size parameters to obtain the volume of the bladder to be tested; specifically, it is configured to: if the classification information indicates that the ultrasound image is a transverse image, extract the transverse diameter and thickness diameter of the bladder region in the ultrasound image; if the classification information indicates that the ultrasound image is a longitudinal image, extract the major diameter of the bladder region in the ultrasound image; identify the bladder shape of the bladder to be tested based on the classification information of the ultrasound image, and select a calculation method suitable for the bladder shape; wherein the bladder shape includes an ellipsoid or a triangular pyramid; calculate the size parameters based on the selected calculation method to obtain the volume of the bladder to be tested; for an ellipsoidal bladder shape, the calculation method is: For a triangular pyramidal bladder shape, the calculation method is as follows: In the formula, This represents the calculated bladder volume. Indicates the transverse diameter. Indicates thickness diameter, Indicates the major axis; The display screen is used to display the ultrasound image and the calculated volume value of the bladder to be tested, wherein the volume value has a color indicator, and the color indicator is used to indicate whether the volume value is within a specified volume range.

11. A computer storage medium, characterized in that, The computer storage medium is used to store a computer program, which, when executed by a processor, implements the method described in any one of claims 1 to 9.

Images