Ultrasound measurement method, apparatus, and storage medium

Abstract

The application provides an ultrasonic measurement method, device and storage medium, the method comprising: controlling a probe to emit ultrasonic waves to a target region of a measured object, receiving echoes of the ultrasonic waves, and obtaining an ultrasonic echo signal based on the echoes of the ultrasonic waves; generating a breast ultrasonic image based on the ultrasonic echo signal, and detecting a lesion and a preset target part in the breast ultrasonic image, the preset target part comprising skin and / or a nipple; and calculating a distance from the lesion to the preset target part based on a result of the detection. The ultrasonic measurement method, device and storage medium according to the embodiments of the application can automatically or semi-automatically detect a lesion and a preset target part in a breast ultrasonic image, and automatically calculate a distance from the lesion to the preset target part, thereby not only simplifying a measurement process of the distance from the lesion to the part, improving measurement efficiency, but also improving accuracy of a measurement result.

Description

Technical Field

[0001] This application relates to the field of ultrasonic technology, and more specifically to an ultrasonic measurement method, apparatus, and storage medium. Background Technology

[0002] In modern medical imaging, ultrasound technology has become the most widely used, most frequently used, and fastest-adopting new technology in examinations due to its advantages such as high reliability, speed, convenience, real-time imaging, and repeatability. The development of new ultrasound technologies has further promoted the application of ultrasound imaging in clinical diagnosis and treatment.

[0003] Currently, in actual clinical examinations, users often need to manually determine the location of lesions on ultrasound images, or manually determine measurement points on ultrasound images to measure the distance from lesions to certain areas. This process is not only time-consuming and laborious, but also prone to errors due to the inherent inconsistencies in manually determined locations or selected measurement points, making it difficult to guarantee the accuracy of the measurement results. Summary of the Invention

[0004] This application proposes an ultrasound measurement scheme that simplifies the measurement process of the distance from the lesion to the skin / nipple and improves the accuracy of the measurement results. The ultrasound measurement scheme proposed in this application is briefly described below; further details will be described in detail in subsequent embodiments with reference to the accompanying drawings.

[0005] According to one aspect of this application, an ultrasound measurement method is provided, the method comprising: controlling a probe to emit ultrasonic waves toward a target area of ​​a test object, receiving the echo of the ultrasonic waves, and acquiring an ultrasonic echo signal based on the ultrasonic echo; generating a breast ultrasound image based on the ultrasonic echo signal, and detecting lesions and preset target sites in the breast ultrasound image, the preset target sites including skin and / or nipples; and calculating the distance from the lesion to the preset target site based on the detection results.

[0006] In one embodiment of this application, detecting the lesion in the ultrasound image includes: detecting the area where the lesion is located and obtaining the boundary of the lesion.

[0007] In one embodiment of this application, the preset target area is skin, and the detection of the preset target area in the breast ultrasound image includes: detecting the position of the top layer of the breast ultrasound image as the position of the preset target area; or detecting the position in the upper preset region of the breast ultrasound image where the brightness is greater than a preset threshold as the position of the preset target area.

[0008] In one embodiment of this application, calculating the distance from the lesion to the preset target location based on the detection result includes: determining the point with the smallest depth direction coordinate on the boundary of the lesion as the target point; and calculating the distance from the position of the target point to the position of the preset target location as the distance from the lesion to the preset target location.

[0009] In one embodiment of this application, the preset target area is the nipple, and the detection of the preset target area in the breast ultrasound image includes: detecting the area where the preset target area is located, and obtaining the position of the center point of the preset target area as the position of the preset target area.

[0010] In one embodiment of this application, obtaining the position of the center point of the preset target area includes: projecting all points in the area along the vertical direction of the breast ultrasound image; calculating the position of the midpoint of the line segment corresponding to the top horizontal layer of the breast ultrasound image after projection, as the position of the center point of the preset target area.

[0011] In one embodiment of this application, the step of calculating the distance from the lesion to the preset target site based on the detection result includes: determining the point on the boundary of the lesion that is closest to the center point of the preset target site as the target point; and calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site.

[0012] In one embodiment of this application, determining the point on the boundary of the lesion that is closest to the center point of the preset target site as the target point includes: traversing all points on the boundary of the lesion to determine the point that is closest to the center point of the preset target site as the target point.

[0013] In one embodiment of this application, determining the point on the boundary of the lesion closest to the center point of the preset target site as the target point includes: determining the centroid point in the area surrounded by the boundary of the lesion, and connecting the centroid point with the center point of the preset target site to form a line segment; and determining the point in a preset area near the intersection of the line segment and the boundary of the lesion that is closest to the center point of the preset target site as the target point.

[0014] In one embodiment of this application, calculating the distance from the lesion to the preset target site based on the detection result includes: mapping points on the boundary of the lesion to the top layer of the breast ultrasound image to obtain quasi-target points, and determining the point among the quasi-target points that is closest to the preset target site to obtain a target point; and calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site.

[0015] In one embodiment of this application, the preset target location is the nipple, and the detection of the preset target location in the breast ultrasound image includes: detecting the area where the preset target location is located, and obtaining a line segment for defining the preset target location as the position of the preset target location.

[0016] In one embodiment of this application, calculating the distance from the lesion to the preset target location based on the detection result includes: calculating the minimum distance of the figure formed by the line segment and the boundary of the lesion, as the distance from the lesion to the preset target location.

[0017] In one embodiment of this application, the preset target area is the nipple, and the detection of the preset target area in the breast ultrasound image includes: detecting one side of the breast ultrasound image where there is an image marker, and obtaining the position of the point on the top layer of the breast ultrasound image among the points on the one side, as the position of the preset target area.

[0018] In one embodiment of this application, the preset target location is the nipple. Detecting the preset target location in the breast ultrasound image includes: if it is determined that the user used the marked end of the probe to align with the center of the nipple, then the position of a point on the top layer of the breast ultrasound image on the side with the image mark is obtained as the position of the preset target location; or, if it is determined that the user did not use the marked end of the probe to align with the center of the nipple, then the position of a point on the top layer of the breast ultrasound image on the opposite side of the side with the image mark is obtained as the position of the preset target location.

[0019] In one embodiment of this application, calculating the distance from the lesion to the preset target site based on the detection result includes: mapping points on the boundary of the lesion to the top layer of the breast ultrasound image to obtain quasi-target points, and determining the point among the quasi-target points that is closest to the preset target site to obtain a target point; and calculating the distance from the target point to the preset target site as the distance from the lesion to the preset target site.

[0020] In one embodiment of this application, the preset target site is the nipple, and the method further includes: if the lesion is detected only in the breast ultrasound image and the nipple region is not detected, then a prompt is issued indicating that the nipple region is not detected in the current section; or if the distance between the lesion and the nipple is detected in the breast ultrasound image and exceeds a predefined threshold, then a prompt is issued to enter a wide field of view or to use a stitched image for measurement.

[0021] In one embodiment of this application, the preset target location is the nipple, and the detection of the preset target location in the breast ultrasound image includes: receiving the location of the preset target location input by the user as the location of the preset target location.

[0022] In one embodiment of this application, the detection of the lesion and / or the preset target site is based on fully automatic detection or semi-automatic detection, wherein the semi-automatic detection includes: receiving a predefined region of the lesion and / or the preset target site input by the user; and detecting the lesion and / or the preset target site based on the predefined region.

[0023] In one embodiment of this application, the detection of the lesion and / or the preset target site is based on at least one of the following algorithms: boundary segmentation algorithm, target detection algorithm, machine learning algorithm, and deep learning algorithm.

[0024] In one embodiment of this application, the method further includes: after calculating the distance from the lesion to the preset target site, displaying the result of the calculation.

[0025] In one embodiment of this application, the method further includes: after calculating the distance from the lesion to the preset target site, generating an ultrasound report based on the calculation result.

[0026] In one embodiment of this application, the method further includes: displaying the breast ultrasound image, wherein the calculation result is displayed on the breast ultrasound image.

[0027] According to another aspect of this application, an ultrasound measurement method is provided, the method comprising: controlling a probe to emit ultrasonic waves toward a target area of ​​a test object, receiving the echo of the ultrasonic waves, and acquiring an ultrasonic echo signal based on the echo of the ultrasonic waves; generating an ultrasound image based on the ultrasonic echo signal, and detecting lesions and preset target sites in the ultrasound image; and calculating the distance from the lesion to the preset target site based on the detection results.

[0028] According to another aspect of this application, an ultrasound measurement device is provided, the device comprising: an ultrasound probe, a transmit / receive sequence controller, and a processor, wherein: the transmit / receive sequence controller is used to excite the ultrasound probe to emit ultrasound waves toward a target area of ​​the object being measured, receive the echoes of the ultrasound waves, and acquire ultrasound echo signals based on the echoes of the ultrasound waves; the processor is used to generate a breast ultrasound image based on the ultrasound echo signals, detect lesions and preset target sites in the breast ultrasound image, and calculate the distance from the lesion to the preset target site based on the detection results, wherein the preset target site includes skin and / or nipple.

[0029] In one embodiment of this application, the processor detects lesions in the breast ultrasound image, including: detecting the region where the lesion is located and obtaining the boundary of the lesion.

[0030] In one embodiment of this application, the preset target area is skin, and the processor detects the preset target area in the breast ultrasound image, including: detecting the position of the top layer of the image in the breast ultrasound image as the position of the preset target area; or detecting the position in the upper preset region of the breast ultrasound image where the brightness is greater than a preset threshold as the position of the preset target area.

[0031] In one embodiment of this application, the processor calculates the distance from the lesion to the preset target location based on the detection result, including: determining the point with the smallest depth direction coordinate on the boundary of the lesion as the target point; and calculating the distance from the position of the target point to the position of the preset target location as the distance from the lesion to the preset target location.

[0032] In one embodiment of this application, the preset target area is the nipple, and the processor detects the preset target area in the breast ultrasound image, including: detecting the area where the preset target area is located, and obtaining the position of the center point of the preset target area as the position of the preset target area.

[0033] In one embodiment of this application, the processor obtains the position of the center point of the preset target area by: projecting all points in the area along the vertical direction of the breast ultrasound image; and calculating the position of the midpoint of the line segment corresponding to the top horizontal direction of the breast ultrasound image after projection, as the position of the center point of the preset target area.

[0034] In one embodiment of this application, the processor calculates the distance from the lesion to the preset target site based on the detection result, including: determining the point on the boundary of the lesion that is closest to the center point of the preset target site as the target point; and calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site.

[0035] In one embodiment of this application, the processor determines the point on the boundary of the lesion that is closest to the center point of the preset target site as the target point, which includes: traversing all points on the boundary of the lesion to determine the point that is closest to the center point of the preset target site as the target point.

[0036] In one embodiment of this application, the processor determines the point on the boundary of the lesion that is closest to the center point of the preset target site as the target point, including: determining the centroid point in the area surrounded by the boundary of the lesion, and connecting the centroid point with the center point of the preset target site to form a line segment; and determining the point in a preset area near the intersection of the line segment and the boundary of the lesion that is closest to the center point of the preset target site as the target point.

[0037] In one embodiment of this application, the processor calculates the distance from the lesion to the preset target site based on the detection result, including: mapping points on the boundary of the lesion to the top layer of the breast ultrasound image to obtain quasi-target points, and determining the point among the quasi-target points that is closest to the preset target site to obtain a target point; and calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site.

[0038] In one embodiment of this application, the preset target location is the nipple. The processor detects the preset target location in the breast ultrasound image, including: detecting the area where the preset target location is located, and obtaining a line segment for defining the preset target location as the position of the preset target location.

[0039] In one embodiment of this application, the processor calculates the distance from the lesion to the preset target location based on the detection result, including: calculating the minimum distance of the figure formed by the line segment and the boundary of the lesion, as the distance from the lesion to the preset target location.

[0040] In one embodiment of this application, the preset target area is the nipple. The processor detects the preset target area in the breast ultrasound image by: detecting one side of the breast ultrasound image where there is an image marker, and obtaining the position of the point on the top layer of the breast ultrasound image among the points on the one side, as the position of the preset target area.

[0041] In one embodiment of this application, the preset target location is the nipple. The processor detects the preset target location in the breast ultrasound image, including: if it is determined that the user used the marked end of the probe to align with the center of the nipple, then the position of a point on the top layer of the breast ultrasound image on the side with the image mark is obtained as the position of the preset target location; or, if it is determined that the user did not use the marked end of the probe to align with the center of the nipple, then the position of a point on the top layer of the breast ultrasound image on the opposite side of the side with the image mark is obtained as the position of the preset target location.

[0042] In one embodiment of this application, the processor calculates the distance from the lesion to the preset target site based on the detection result, including: mapping points on the boundary of the lesion to the top layer of the breast ultrasound image to obtain quasi-target points, determining the point among the quasi-target points that is closest to the preset target site, and mapping the determined point to the top layer of the breast ultrasound image to obtain a target point; and calculating the distance from the target point to the preset target site as the distance from the lesion to the preset target site.

[0043] In one embodiment of this application, the preset target site is the nipple, and the processor is further configured to: issue a prompt that no nipple region is detected in the current section if the lesion is detected only in the breast ultrasound image and no nipple region is detected; or prompt to enter a wide-view or use a stitched image for measurement if the distance between the lesion and the nipple in the breast ultrasound image exceeds a predefined threshold.

[0044] According to another aspect of this application, an ultrasonic measuring device is provided, the device including a memory and a processor, the memory storing a computer program executed by the processor, the computer program performing the above-described ultrasonic measuring method when run by the processor.

[0045] According to another aspect of this application, a storage medium is provided, on which a computer program is stored, which executes the above-described ultrasonic measurement method when running.

[0046] According to another aspect of this application, a computer program is provided, which is executed by a computer or processor to perform the above-described ultrasonic measurement method.

[0047] The ultrasound measurement method and apparatus according to the embodiments of this application can automatically or semi-automatically detect lesions in breast ultrasound images as well as skin and / or nipples, and automatically calculate the distance from the lesion to the skin and / or nipple. This not only simplifies the measurement process of the distance from the lesion to the skin and / or nipple and improves the measurement efficiency, but also improves the accuracy of the measurement results. Attached Figure Description

[0048] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The accompanying drawings are used to provide a further understanding of the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0049] Figure 1 A schematic block diagram of an exemplary ultrasonic measuring apparatus for implementing an ultrasonic measuring method according to an embodiment of this application is shown.

[0050] Figure 2 A schematic flowchart of an ultrasonic measurement method according to an embodiment of this application is shown.

[0051] Figure 3 An exemplary schematic diagram showing the distance between the lesion and the skin.

[0052] Figure 4A A schematic diagram showing an example of the distance between the lesion and the nipple.

[0053] Figure 4B A schematic diagram showing another example of the distance between the lesion and the nipple.

[0054] Figure 4C A schematic diagram showing another example of the distance between the lesion and the nipple.

[0055] Figure 5 A schematic flowchart of an ultrasonic measurement method according to another embodiment of this application is shown.

[0056] Figure 6 A schematic block diagram of an ultrasonic measuring device according to an embodiment of this application is shown.

[0057] Figure 7 A schematic block diagram of an ultrasonic measuring device according to another embodiment of this application is shown. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this application more apparent, exemplary embodiments according to this application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein. Based on the embodiments of this application described herein, all other embodiments obtained by those skilled in the art without inventive effort should fall within the protection scope of this application.

[0059] First, refer to Figure 1 This describes an exemplary ultrasonic measuring apparatus for implementing the ultrasonic measuring method of the embodiments of this application.

[0060] Figure 1 This is a schematic structural block diagram of an exemplary ultrasonic measuring device 10 used to implement the ultrasonic measuring method of the embodiments of this application. Figure 1 As shown, the ultrasonic measuring device 10 may include an ultrasonic probe 100, a transmit / receive selection switch 101, a transmit / receive sequence controller 102, a processor 103, a display 104, and a memory 105. The transmit / receive sequence controller 102 can excite the ultrasonic probe 100 to emit ultrasonic waves towards the target object (the object being measured), and can also control the ultrasonic probe 100 to receive ultrasonic echoes returned from the target object, thereby obtaining ultrasonic echo signals / data. The processor 103 processes the ultrasonic echo signals / data to obtain tissue-related parameters and ultrasonic images of the target object. The ultrasonic images obtained by the processor 103 can be stored in the memory 105, and these ultrasonic images can be displayed on the display 104.

[0061] In this embodiment, the display 104 of the aforementioned ultrasonic measuring device 10 can be a touch screen, a liquid crystal display, or an independent display device such as a liquid crystal display or a television set, separate from the ultrasonic measuring device 10. It can also be a display screen on an electronic device such as a mobile phone or a tablet computer.

[0062] In this embodiment, the memory 105 of the aforementioned ultrasonic measuring device 10 can be a flash memory card, solid-state memory, hard disk, etc.

[0063] This application also provides a computer-readable storage medium storing multiple program instructions. When these multiple program instructions are called and executed by the processor 103, they can execute some or all of the steps or any combination of the steps in the ultrasonic measurement method in various embodiments of this application.

[0064] In one embodiment, the computer-readable storage medium may be a memory 105, which may be a non-volatile storage medium such as a flash memory card, a solid-state memory, or a hard disk.

[0065] In this embodiment, the processor 103 of the aforementioned ultrasonic measuring device 10 can be implemented by software, hardware, firmware, or a combination thereof. It can use circuits, one or more application-specific integrated circuits (ASICs), one or more general-purpose integrated circuits, one or more microprocessors, one or more programmable logic devices, or a combination of the aforementioned circuits or devices, or other suitable circuits or devices, so that the processor 103 can execute the corresponding steps of the ultrasonic measuring method in each embodiment.

[0066] The following is combined with Figures 2 to 5 The ultrasonic measurement method in this application is described in detail. The method can be performed by the aforementioned ultrasonic measurement device 10.

[0067] Figure 2 A schematic flowchart of an ultrasonic measurement method 200 according to an embodiment of this application is shown. Figure 2 As shown, the ultrasonic measurement method 200 may include the following steps:

[0068] In step S210, the probe is controlled to emit ultrasonic waves toward the target area of ​​the object being measured, the echo of the ultrasonic waves is received, and the ultrasonic echo signal is obtained based on the echo of the ultrasonic waves.

[0069] In step S220, a breast ultrasound image is generated based on the ultrasound echo signal, and lesions and preset target areas in the breast ultrasound image are detected. The preset target areas include the skin and / or the nipple.

[0070] In step S230, the distance from the lesion to the preset target site is calculated based on the detection results.

[0071] In the embodiments of this application, the subject of the ultrasound examination can be a person undergoing an ultrasound examination, and the target area of ​​the subject can be an area of ​​the subject's body that needs to be examined by ultrasound. For example, the target area can be the breast area, and correspondingly, the ultrasound examination is a breast ultrasound examination. In a breast ultrasound examination, a breast ultrasound report is usually generated that includes the following parts: (1) a record of patient information; (2) a general sonographic description of bilateral breast tissue; and (3) a sonographic description of significant abnormalities and lesions. Among them, the sonographic description of lesions should clearly record the location of the lesions, requiring consistent and repeatable systematic localization, usually using the distance from the lesion to the skin and the distance from the lesion to the nipple. Therefore, in a breast ultrasound examination, it is necessary to measure the distance from the lesion to the skin and / or the distance from the lesion to the nipple. The distance between the lesion and the skin can be as follows: Figure 3 As shown, this generally refers to the minimum distance from the skin layer to the edge of the lesion. The distance between the lesion and the nipple can be as follows: Figures 4A to 4C As shown, among them, Figure 4A The image shown is the distance from the center of the nipple to the edge of the lesion mapped onto the body surface when the probe is positioned with its side facing the center of the nipple to acquire an image. Figure 4B This figure shows the distance from the center of the nipple to the edge of the lesion mapped onto the body surface when the probe acquires breast images that simultaneously cover the nipple and the lesion. Figure 4C The diagram shows the minimum straight-line distance from the center of the nipple to the lesion. The distance from the lesion to the skin and the distance from the lesion to the nipple are key values ​​for locating and differentiating lesions, and are crucial for follow-up and clinical protocol development. However, in most cases, the edge morphology of breast lesions is irregular, and currently users generally need to manually select measurement points, which introduces some error and is relatively cumbersome, time-consuming, and laborious. Therefore, the ultrasound measurement scheme provided in this application can solve such problems. In the following description, the ultrasound measurement scheme of this application is mainly based on breast ultrasound measurement as an example, because the scheme of this application is very suitable for related measurements during breast ultrasound examinations. However, it should be understood that this is only exemplary, and the ultrasound measurement scheme of this application can also be used for ultrasound examinations and measurements of any other site.

[0072] In embodiments of this application, ultrasound echo signals are processed to obtain breast ultrasound images. Exemplarily, ultrasound echo signals can be processed using techniques such as gain compensation, beamforming, orthogonal demodulation, and image enhancement to obtain breast ultrasound images of the target region of the tested object.

[0073] Specifically, the ultrasonic equipment emits ultrasonic signals, which are converted from electrical signals to acoustic signals by the transducer array elements of the probe and transmitted to the target object. Then, the acoustic signals of the ultrasonic echoes are converted back into electrical signals by the transducer array elements. These signals are then filtered and amplified by analog circuitry and converted into digital signals by an analog-to-digital converter. Further, the data from each array element channel is processed by traveling wave beamforming to obtain radio frequency (RF) signals, which are then orthogonally demodulated to obtain in-phase and quadrature signals, which are sent to the subsequent imaging processing module. Gain compensation is used on the received ultrasonic echo signals to mitigate the subsequent processing problems caused by the signal strength decreasing with depth. The signal after this processing is actually an analog signal; therefore, to improve signal processing efficiency and reduce hardware platform complexity, an analog-to-digital converter is needed to convert the analog echo signals into digital echo signals. After the analog-to-digital conversion of the channel data, digital beamforming can be performed based on the delay differences caused by the difference in distance from the focal point to the channel to form scan line data. The data processing performed before this can be collectively referred to as front-end processing. The data obtained after this stage can be called radio frequency (RF) signal data. The term "radio frequency" (RF) refers to the fact that the signal contains the probe's receiving clock frequency, which happens to fall within the radio frequency band of the communication field. After acquiring the RF signal data, the carrier wave is removed through in-phase / quadrature demodulation, the tissue structure information contained in the signal is extracted, and noise is removed through filtering. The signal acquired at this point is the baseband signal. All the processing required to convert the RF signal to the baseband signal can be collectively referred to as mid-range processing. Finally, the intensity of the baseband signal is calculated, and its grayscale levels are logarithmically compressed and converted to obtain the breast ultrasound image. The processing completed at this stage can be collectively referred to as back-end processing. At this point, a single frame of a breast ultrasound image ready for display is obtained.

[0074] In the embodiments of this application, lesions and preset target sites in the breast ultrasound image of the target area of ​​the tested object can be detected by fully automatic detection or semi-automatic detection.

[0075] Fully automated detection methods include, for example, using boundary segmentation or object detection algorithms to detect lesions and preset target areas in ultrasound images; alternatively, they can be based on machine learning or deep learning algorithms. Machine learning or deep learning algorithms involve feeding images with labeled lesion boundaries / preset target areas, along with the coordinates of the bounding boxes of the boundaries / regions of interest (ROIs), into a deep learning segmentation or object detection network (convolutional neural network) for training. During training, the error between the predicted value (i.e., the position of the lesion boundary / preset target area output by the neural network) and the labeled position is calculated iteratively to gradually approximate the correct value, thus obtaining a reference model for lesion / preset target area detection. Using fully automated detection methods for lesion and preset target areas enables rapid detection and accurate results, improving detection efficiency and accuracy, and consequently, the efficiency and accuracy of subsequent measurements based on the detection results.

[0076] In one example, a semi-automatic detection method may include: receiving a predefined region of the lesion and / or the preset target site input by the user; and detecting the lesion and / or the preset target site based on the predefined region. That is, in a semi-automatic detection method, the user first determines the approximate region of the lesion and / or the preset target site based on the ultrasound image, and then uses at least one algorithm selected from boundary segmentation algorithms, target detection algorithms, machine learning algorithms, and deep learning algorithms to further detect the lesion and / or the preset target site within that approximate region. In another example, a semi-automatic detection method may also involve: first detecting the lesion and / or the preset target site using the fully automatic detection method described above, and then having the user verify or correct the detection results. Although semi-automatic detection requires user participation, it can further improve the accuracy of the detection results.

[0077] Now, taking the breast ultrasound examination mentioned above as an example, we will describe the detection of lesions and preset target sites in breast ultrasound images. As mentioned earlier, this is merely exemplary, and the ultrasound measurement method of this application can also be used for the detection of lesions and preset target sites, as well as the measurement of the distance between lesions and preset target sites, in any other ultrasound examination.

[0078] In embodiments of this application, lesion location detection may involve detecting the area where the lesion is located and obtaining the lesion's boundary. Based on the detected lesion's location and boundary, the distance from the lesion to a preset target site (skin and / or nipple) can be calculated.

[0079] For example, in a breast ultrasound examination, the preset target area may include the skin and / or the nipple. Let's take the skin as an example. In embodiments of this application, when the preset target area is the skin, detecting the preset target area in the ultrasound image may include: detecting the position of the top layer of the ultrasound image (i.e., the top edge of the image) as the position of the preset target area; or detecting the position in the upper preset region of the ultrasound image where the brightness is greater than a preset threshold as the position of the preset target area. Generally, for breast ultrasound images, the top layer of the image is the skin layer, so the position of the top layer of the ultrasound image can be detected as the position of the skin. Alternatively, generally in breast ultrasound images, the brighter area at the top of the image is the position of the skin, so a preset region and a preset threshold can be set as needed, and the position in the upper preset region of the ultrasound image where the brightness is greater than the preset threshold can be detected as the position of the skin.

[0080] Accordingly, calculating the distance from the lesion to the preset target site (i.e., the skin) based on the detection results may include: determining the point with the smallest depth coordinate on the boundary of the lesion as the target point; and calculating the distance from the target point to the preset target site as the distance from the lesion to the preset target site. Since the minimum distance between the skin layer and the edge of the lesion is usually taken as the distance from the lesion to the skin in breast ultrasound examinations, the point with the smallest distance from the skin on the lesion boundary can be selected as the target point, and the distance between the target point and the skin can be calculated as the distance from the lesion to the skin. Generally, the point with the smallest depth coordinate on the lesion boundary (generally, in the image area, the higher the area, the smaller the depth coordinate, and the lower the area, the larger the depth coordinate) is the point with the smallest distance from the skin on the lesion boundary. Therefore, this point can be selected as the target point, and the distance between the target point and the skin can be calculated as the distance from the lesion to the skin.

[0081] In one embodiment of this application, when the preset target site is the nipple, the distance from the lesion to the nipple can be defined as the distance between the position of the lesion edge mapped onto the body surface and the position of the nipple center (as described above). Figure 4A and Figure 4B As shown above, it can also be defined as the straight-line spatial distance between the edge of the lesion and the center of the nipple (as mentioned above). Figure 4C (As shown), each of them will be described in detail below.

[0082] first, Figure 4AThe illustration shows a scenario where the probe is aligned with the center of the nipple for image acquisition. In this scenario, the leftmost or rightmost edge of the image area can be approximated as the nipple center. Generally, if the marked end of the probe is aligned with the nipple center, the point on the top layer of the image (the upper left corner) on the marked side of the breast ultrasound image (usually the leftmost edge of the image area) can be considered the nipple center. Conversely, if the marked end of the probe is not aligned with the nipple center, the point on the top layer of the image (the upper right corner) on the opposite side (usually the rightmost edge of the image area) can be considered the nipple center. Generally, it can be assumed that the user scans the subject with the marked end of the probe aligned with the nipple center. However, the user can also determine whether to align the marked end of the probe with the nipple center, and the nipple center position is obtained based on the user's choice.

[0083] Based on this, in the example where the default user aligns the marked end of the probe with the center of the nipple to scan the object being tested, detecting the preset target area in the breast ultrasound image may include: detecting one side of the breast ultrasound image where there is an image mark, and obtaining the position of the point on the top layer of the breast ultrasound image among the points on the same side, as the position of the preset target area.

[0084] In an example where the user does not default to aligning the marked end of the probe with the nipple center when scanning the subject, detecting a preset target area in the breast ultrasound image may include: if it is determined that the user used the marked end of the probe to align with the nipple center, then the position of a point on the top layer of the breast ultrasound image on the side with the image mark is obtained as the position of the preset target area; or, if it is determined that the user did not use the marked end of the probe to align with the nipple center, then the position of a point on the top layer of the breast ultrasound image on the opposite side of the side with the image mark is obtained as the position of the preset target area.

[0085] Based on the determined location of the preset target site (i.e., the nipple), the distance from the lesion to the preset target site is calculated based on the detection results. This may include: mapping points on the boundary of the lesion to the top layer of the breast ultrasound image to obtain quasi-target points, and determining the point among the quasi-target points that is closest to the preset target site to obtain the target point; calculating the distance from the target point to the preset target site as the distance from the lesion to the preset target site, such as... Figure 4A As shown by the dashed line.

[0086] Figure 4B and Figure 4C The image shown depicts a scenario where a probe-acquired breast image simultaneously covers both the nipple and the lesion. In this scenario, an acoustic shadow is typically present behind the nipple in the ultrasound image. Generally, the location of the nipple can be determined during the doctor's procedure, ensuring it is definitely in the scan image. Based on the tissue characteristics of the nipple, there is a distinct dark area of ​​acoustic shadowing behind the image, such as in 4B and [other ultrasound images]. Figure 4C As shown, the approximate location of the nipple is determined by the location of the largest sound shadow area in the depth direction. The black areas on the left and right sides of the image are relatively small and do not represent the approximate location of the nipple. Based on the approximate location of the nipple, a straight line is projected. The midpoint of the corresponding line segment in the horizontal direction at the top layer of the image after projection can be considered the center of the nipple. (See image for details.) Figure 4B and Figure 4C As shown, the dark gray straight line at the top edge of the image represents the horizontal extent of the nipple on the body surface, while the vertical dashed line represents the acoustic shadow area behind the nipple. Figure 4B and Figure 4C The difference shown is that, Figure 4B The distance from the lesion to the nipple shown is defined as the distance between the position of the lesion edge mapped onto the body surface and the position of the nipple center. Figure 4C The distance from the lesion to the nipple shown is defined as the straight-line distance between the edge of the lesion and the center of the nipple.

[0087] Based on this, Figure 4B In the example shown, detecting a preset target area (i.e., the nipple) in the breast ultrasound image can include: detecting the region where the preset target area is located and obtaining the position of the center point of the preset target area as the position of the preset target area. In this embodiment, the entire region where the nipple is located can be detected, the boundaries of the nipple can be segmented, and the position of the center point of the nipple can be determined and obtained as the position of the nipple. For example, the region where the nipple is located can be detected by image processing, machine learning, deep learning, etc. Its typical image feature is that there is obvious acoustic shadow (black) in the back of the ultrasound image (including near field, mid field, and far field); after detecting the region, the range of values ​​of all points in the region in the horizontal direction in the image can be calculated, which is equivalent to projecting all points in the region along the vertical direction of the image, and calculating the position of the midpoint of the corresponding line segment in the horizontal direction at the top of the image after projection, as the position of the center point of the nipple, i.e., the position of the nipple. Accordingly, calculating the distance from the lesion to the preset target site based on the detection results may include: mapping points on the boundary of the lesion to the top layer of the breast ultrasound image to obtain quasi-target points, and determining the point among the quasi-target points that is closest to the preset target site to obtain the target point; calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site, such as... Figure 4B As shown by the horizontal dashed line.

[0088] exist Figure 4C In the example shown, detecting a preset target area (i.e., the nipple) in the breast ultrasound image can include: detecting the region where the preset target area is located and obtaining the position of the center point of the preset target area as the position of the preset target area. In this embodiment, the entire region where the nipple is located can be detected, the boundaries of the nipple can be segmented, and the position of the center point of the nipple can be determined and obtained as the position of the nipple. For example, the region where the nipple is located can be detected by image processing, machine learning, deep learning, etc. Its typical image feature is that there is obvious acoustic shadow (black) in the back of the ultrasound image (including near field, mid field, and far field); after detecting the region, the range of values ​​of all points in the region in the horizontal direction in the image can be calculated, which is equivalent to projecting all points in the region along the vertical direction of the image, and calculating the position of the midpoint of the corresponding line segment in the horizontal direction at the top of the image after projection, as the position of the center point of the nipple, i.e., the position of the nipple. Accordingly, calculating the distance from the lesion to the preset target site based on the detection results may include: determining the point on the boundary of the lesion closest to the center point of the preset target site as the target point; calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site, such as... Figure 4C As shown by the slanted dashed line.

[0089] One method to determine the target point is to traverse all points on the boundary of the lesion and identify the point closest to the nipple center as the target point. Alternatively, the target point can be determined by: identifying the centroid of the region enclosed by the lesion's boundary, connecting the centroid to the nipple center to form a line segment, and identifying the point closest to the nipple center within a preset area near the intersection of this line segment and the lesion's boundary as the target point. For example, if the nipple center is defined as N and the lesion's centroid as M, then the point closest to N within a preset area near the intersection of line segment MN and the lesion's boundary (e.g., defined as X) is the target point. Calculating the distance between this target point and the nipple center yields the distance from the lesion to the nipple. The pre-defined area near intersection point X can be understood as follows: Centered on intersection point X, extend a certain distance to the left and right sides of the lesion boundary to obtain point X1 to the left of X on the lesion boundary, and point X2 to the right of X on the lesion boundary. The points between X1 and X2 on the lesion boundary constitute the aforementioned pre-defined area. The point closest to N within this area is the target point. The angle a1 between line segments NX1 and NX can be equal to the angle a2 between line segments NX2 and NX. Therefore, an angle a can be pre-defined such that angles a1 and a2 are both half of angle a, thus obtaining the distances to extend to the left and right sides of X, thereby obtaining points X1 and X2, and consequently, the aforementioned pre-defined area.

[0090] Furthermore, in scenarios where the probe is positioned with its side facing the center of the nipple to acquire images, if the distance from the lesion to the nipple is defined as the straight-line distance between the edge of the lesion and the center of the nipple, and the distance between the position of the edge mapped onto the body surface and the position of the nipple center, then calculating the distance from the lesion to the preset target site based on the detection results can include: determining the point on the boundary of the lesion closest to the center point of the preset target site as the target point; and calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site. The method for determining this target point can be as described above and will not be repeated here.

[0091] Alternatively, in another embodiment of this application, when the preset target location is the nipple, the detection of the preset target location in the ultrasound image may include: detecting the area where the preset target location is located, and obtaining a line segment used to define the preset target location as the position of the preset target location. In this embodiment, the nipple is defined as a line segment, and the position of the line segment is the position of the nipple. Accordingly, calculating the distance from the lesion to the preset target location based on the detection result may include: determining the point on the boundary of the lesion closest to the center point of the preset target location as the target point; calculating the distance from the target point to the center point of the preset target location as the distance from the lesion to the preset target location.

[0092] In another embodiment of this application, when the preset target location is the nipple, the nipple can be defined as a line segment, and the detection result of the nipple location can be the location of a line segment. The detection result of the lesion location is the area where the lesion is located and its boundary. Based on this, calculating the distance from the lesion to the preset target location based on the detection result can include: calculating the minimum distance of the figure formed by the line segment and the boundary of the lesion, as the distance from the lesion to the preset target location.

[0093] In another embodiment of this application, when the preset target location is the nipple, the user (e.g., a doctor) can be prompted to select the current nipple location after the distance measurement is initiated. Since the center of the nipple is at the top of the image, the shortest distance between the doctor's click location and the lesion (e.g., mapped to the skin) can be calculated as the distance from the lesion to the nipple. In this embodiment, the detection of the preset target location in the breast ultrasound image may include: receiving the location of the preset target location input by the user, as the location of the preset target location. Accordingly, calculating the distance from the lesion to the preset target site based on the detection results may include: mapping points on the boundary of the lesion to the top layer of the breast ultrasound image to obtain quasi-target points, and determining the point among the quasi-target points that is closest to the preset target site to obtain a target point, and calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site; or, determining the point on the boundary of the lesion that is closest to the center point of the preset target site as the target point, and calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site.

[0094] Furthermore, in embodiments of this application, if only a lesion is detected in the ultrasound image but not the nipple, a message "No nipple image detected in the current section" can be displayed, prompting the user to reselect a section to obtain an ultrasound image for detection. When acquiring data with one end of the probe aligned with the center of the nipple, in most cases there will be no obvious acoustic shadow behind the nipple in the ultrasound image; this situation can also be indicated for the doctor to confirm. Additionally, if a lesion is detected in the ultrasound image that is far from the nipple (e.g., the distance between them exceeds a predetermined threshold), the user can be prompted to switch to a wide-view mode or use a stitched image for measurement, where the stitched image can be a dual-screen stitch.

[0095] Based on the above description, the ultrasound measurement method according to the embodiments of this application can automatically locate the position of the lesion and the preset target site (skin and / or nipple), and automatically calculate the distance from the lesion to the preset target site (skin and / or nipple). This not only simplifies the measurement process of the distance from the lesion to the site (skin and / or nipple) and improves the measurement efficiency, but also improves the accuracy of the measurement results.

[0096] In the embodiments of this application, after calculating the distance from the lesion to the preset target site, the calculation result can be displayed, for example, on an ultrasound image, for the user to view or record. Furthermore, in the embodiments of this application, after calculating the distance from the lesion to the preset target site, an ultrasound report can also be generated based on the calculation result, thereby further reducing the user's burden of writing documents, improving work efficiency, and reducing the possibility of report errors.

[0097] The above exemplarily illustrates an ultrasonic measurement method according to an embodiment of this application. The following, in conjunction with... Figure 5 Describes an ultrasonic measurement method according to another embodiment of this application. Figure 5 A schematic flowchart of an ultrasonic measurement method 500 according to another embodiment of this application is shown. Figure 5 As shown, the ultrasonic measurement method 500 may include the following steps:

[0098] In step S510, the probe is controlled to emit ultrasonic waves toward the target area of ​​the object being measured, the echo of the ultrasonic waves is received, and the ultrasonic echo signal is obtained based on the echo of the ultrasonic waves.

[0099] In step S520, an ultrasound image is generated based on the ultrasound echo signal, and lesions and preset target areas in the ultrasound image are detected.

[0100] In step S530, the distance from the lesion to the preset target site is calculated based on the detection results.

[0101] Reference Figure 5Steps S510 to S530 of the ultrasonic measurement method 500 according to embodiments of this application are described in conjunction with reference to [reference needed]. Figure 2 Steps S210 to S230 of the ultrasound measurement method 200 according to the embodiments of this application are similar, all involving the detection of lesions and preset target sites in ultrasound images and the calculation of the distance from the lesion to the preset target site based on the detection results. This part can be found in the preceding description and will not be repeated here for brevity. (Refer to the reference...) Figure 2 The ultrasonic measurement method 200 described according to the embodiments of this application differs from that described below, except that reference is made to... Figure 5 The ultrasound measurement method 500 described according to the embodiments of this application is not only used for breast ultrasound examination, but also for ultrasound examination of any other site, and can be used to measure the distance between a lesion in any other site and a preset target site.

[0102] The following is combined with Figure 6 Describes an ultrasonic measuring device provided according to another aspect of this application. Figure 6 A schematic block diagram of an ultrasonic measuring device 600 according to an embodiment of this application is shown. Figure 6 As shown, the ultrasound measurement device 600 may include a transmit / receive sequence controller 610, an ultrasound probe 620, and a processor 630. The transmit / receive sequence controller 610 is used to excite the ultrasound probe 620 to emit ultrasound waves toward a target area of ​​the object being measured, receive the echoes of the ultrasound waves, and acquire ultrasound echo signals based on the echoes. The processor 630 is used to generate a breast ultrasound image based on the ultrasound echo signals, detect lesions and preset target sites in the ultrasound image, and calculate the distance from the lesion to the preset target site based on the detection results, wherein the preset target site includes skin and / or the nipple.

[0103] In the embodiments of this application, the subject of the ultrasound examination can be a person undergoing an ultrasound examination, and the target area of ​​the subject can be an area of ​​the subject's body that needs to be examined by ultrasound. For example, the target area can be the breast area, and correspondingly, the ultrasound examination is a breast ultrasound examination. In a breast ultrasound examination, a breast ultrasound report is usually generated that includes the following parts: (1) a record of patient information; (2) a general sonographic description of bilateral breast tissue; and (3) a sonographic description of significant abnormalities and lesions. Among them, the sonographic description of lesions should clearly record the location of the lesions, requiring consistent and repeatable systematic localization, usually using the distance from the lesion to the skin and the distance from the lesion to the nipple. Therefore, in a breast ultrasound examination, it is necessary to measure the distance from the lesion to the skin and / or the distance from the lesion to the nipple. The distance between the lesion and the skin can be as follows: Figure 3 As shown, this generally refers to the minimum distance from the skin layer to the edge of the lesion. The distance between the lesion and the nipple can be as follows: Figures 4A to 4C As shown, among them, Figure 4A The image shown is the distance from the center of the nipple to the edge of the lesion mapped onto the body surface when the probe is positioned with its side facing the center of the nipple to acquire an image. Figure 4B This figure shows the distance from the center of the nipple to the edge of the lesion mapped onto the body surface when the probe acquires breast images that simultaneously cover the nipple and the lesion. Figure 4C The diagram shows the minimum straight-line distance from the center of the nipple to the lesion. The distance from the lesion to the skin and the distance from the lesion to the nipple are key values ​​for locating and differentiating lesions, and are crucial for follow-up and clinical protocol development. However, in most cases, the edge morphology of breast lesions is irregular, and currently users generally need to manually select measurement points, which introduces some error and is relatively cumbersome, time-consuming, and laborious. Therefore, the ultrasound measurement scheme provided in this application can solve such problems. In the following description, the ultrasound measurement scheme of this application is mainly based on breast ultrasound measurement as an example, because the scheme of this application is very suitable for related measurements during breast ultrasound examinations. However, it should be understood that this is only exemplary, and the ultrasound measurement scheme of this application can also be used for ultrasound examinations and measurements of any other site.

[0104] In embodiments of this application, the processor 630 may include an image processing module that processes ultrasound echo signals to obtain breast ultrasound images. Exemplarily, the image processing module may perform processes on the ultrasound echo signals such as gain compensation, beamforming, orthogonal demodulation, and image enhancement to obtain breast ultrasound images of the target region of the tested object.

[0105] Specifically, the transmit / receive sequence controller 610 excites the ultrasonic probe 620 to transmit ultrasonic signals. The transducer array elements of the ultrasonic probe 620 convert the electrical signals into acoustic signals, which are then transmitted to the target object. The acoustic signals of the ultrasonic echo are then converted back into electrical signals by the transducer array elements of the ultrasonic probe 620. The analog circuit of the image processing module performs front-end filtering and amplification on this signal, and then the analog-to-digital converter of the image processing module converts it into a digital signal. The image processing module further processes the data from each array element channel using traveling wave beamforming to obtain radio frequency signals, which are then orthogonally demodulated to obtain in-phase and quadrature signals for imaging processing. Gain compensation in the image processing module for the received ultrasonic echo signals can mitigate the subsequent processing problems caused by the signal strength decreasing with depth. Since the signal after this processing is actually an analog signal, an analog-to-digital converter is needed to convert the analog echo signal into a digital echo signal to improve signal processing efficiency and reduce hardware platform complexity. After the channel data undergoes analog-to-digital conversion, digital beamforming is used to form scan line data based on the delay differences caused by the distance between the focal point and the channel. All data processing performed before this stage can be referred to as front-end processing. The data obtained after this stage is called radio frequency (RF) signal data. It is called "RF" because the signal contains the probe's receiving clock frequency, which happens to fall within the radio frequency band of the communication field. After acquiring the RF signal data, the carrier wave is removed through in-phase / quadrature demodulation, the tissue structure information contained in the signal is extracted, and noise is removed through filtering. The acquired signal at this point is the baseband signal. All processing required to convert the RF signal to the baseband signal can be referred to as mid-range processing. Finally, the intensity of the baseband signal is calculated, and its grayscale levels are logarithmically compressed and converted to obtain the breast ultrasound image. The processing completed at this stage can be referred to as back-end processing. At this point, a single frame of breast ultrasound image ready for display is obtained.

[0106] In the embodiments of this application, the processor 630 can detect lesions and preset target sites in the breast ultrasound image of the target area of ​​the tested object through fully automatic detection or semi-automatic detection.

[0107] Fully automated detection methods include, for example, using boundary segmentation or object detection algorithms to detect lesions and preset target areas in ultrasound images; alternatively, they can be based on machine learning or deep learning algorithms. Machine learning or deep learning algorithms involve feeding images with labeled lesion boundaries / preset target areas, along with the coordinates of the bounding boxes of the boundaries / regions of interest (ROIs), into a deep learning segmentation or object detection network (convolutional neural network) for training. During training, the error between the predicted value (i.e., the position of the lesion boundary / preset target area output by the neural network) and the labeled position is calculated iteratively to gradually approximate the correct value, thus obtaining a reference model for lesion / preset target area detection. Using fully automated detection methods for lesion and preset target areas enables rapid detection and accurate results, improving detection efficiency and accuracy, and consequently, the efficiency and accuracy of subsequent measurements based on the detection results.

[0108] In one example, semi-automatic detection methods may include: receiving user input via a human-computer interaction device (not in...) Figure 6 (As shown in the image) A predefined area of ​​the lesion and / or the preset target site is input; the lesion and / or the preset target site is detected based on the predefined area. In other words, the semi-automatic detection method involves the user first determining the predefined area based on the display device (not shown in the image). Figure 6 The ultrasound image displayed on the interface (shown in the diagram) determines the approximate area of ​​the lesion and / or the preset target site. Then, the processor 630 uses at least one of the following algorithms: boundary segmentation algorithm, target detection algorithm, machine learning algorithm, and deep learning algorithm, to further detect the lesion and / or the preset target site within this approximate area. In another example, the semi-automatic detection method can also be as follows: the processor 630 first detects the lesion and / or the preset target site using the fully automatic detection method described above, and then the user verifies or corrects the detection results using a human-computer interaction device. Although semi-automatic detection requires user participation, it can further improve the accuracy of the detection results.

[0109] The following description uses the breast ultrasound examination mentioned earlier as an example to illustrate the detection of lesions and preset target sites in breast ultrasound images. As previously stated, this is merely exemplary, and the ultrasound measuring device of this application can also be used for the detection of lesions and preset target sites, as well as the measurement of the distance between lesions and preset target sites, in any other ultrasound examination.

[0110] In embodiments of this application, lesion location detection may involve detecting the area where the lesion is located and obtaining the lesion's boundary. Based on the detected lesion's location and boundary, the processor 630 can calculate the distance from the lesion to a preset target site (skin and / or nipple).

[0111] For example, in a breast ultrasound examination, the preset target area may include the skin and / or the nipple. Let's take the skin as an example. In embodiments of this application, when the preset target area is the skin, the processor 630 detects the preset target area in the ultrasound image, which may include: detecting the position of the top layer of the ultrasound image as the position of the preset target area; or detecting the position in the upper preset region of the ultrasound image where the brightness is greater than a preset threshold as the position of the preset target area. Generally, for breast ultrasound images, the top layer of the image is the skin layer, so the processor 630 can detect the position of the top layer of the ultrasound image as the skin position. Alternatively, generally in breast ultrasound images, the brighter area at the top of the image is the skin position, so the processor 630 can set a preset region and a preset threshold as needed, and detect the position in the upper preset region of the ultrasound image where the brightness is greater than the preset threshold as the skin position.

[0112] Accordingly, the processor 630 calculates the distance from the lesion to the preset target site based on the detection results, which may include: determining the point with the smallest depth coordinate on the boundary of the lesion as the target point; and calculating the distance from the target point to the preset target site as the distance from the lesion to the preset target site. Since the minimum distance between the skin layer and the edge of the lesion is usually taken as the distance from the lesion to the skin in breast ultrasound examination, the processor 630 can select the point with the smallest distance from the skin on the lesion boundary as the target point and calculate the distance between the target point and the skin as the distance from the lesion to the skin. Generally, the point with the smallest depth coordinate on the lesion boundary is also the point with the smallest distance from the skin on the lesion boundary; therefore, the processor 630 can select this point as the target point and calculate the distance between the target point and the skin as the distance from the lesion to the skin.

[0113] In one embodiment of this application, when the preset target site is the nipple, the distance from the lesion to the nipple can be defined as the distance between the position of the lesion edge mapped onto the body surface and the position of the nipple center (as described above). Figure 4A and Figure 4B As shown above, it can also be defined as the straight-line spatial distance between the edge of the lesion and the center of the nipple (as mentioned above). Figure 4C shown).

[0114] Figure 4AThe illustration shows a scenario where the probe is aligned with the center of the nipple for image acquisition. In this scenario, the leftmost or rightmost edge of the image area can be approximated as the nipple center. Generally, if the marked end of the probe is aligned with the nipple center, the point on the top layer of the image (the upper left corner) on the marked side of the breast ultrasound image (usually the leftmost edge of the image area) can be considered the nipple center. Conversely, if the marked end of the probe is not aligned with the nipple center, the point on the top layer of the image (the upper right corner) on the opposite side (usually the rightmost edge of the image area) can be considered the nipple center. Generally, it can be assumed that the user scans the subject with the marked end of the probe aligned with the nipple center. However, the user can also determine whether to align the marked end of the probe with the nipple center, and the nipple center position is obtained based on the user's choice.

[0115] Based on this, in the example where the default user scans the object being tested by aligning the marked end of the probe with the center of the nipple, the processor 630 may detect a preset target area in the breast ultrasound image by: detecting one side of the breast ultrasound image where the image mark is present, and obtaining the position of the point on the top layer of the breast ultrasound image among the points on the same side, as the position of the preset target area.

[0116] In an example where the user does not default to aligning the marked end of the probe with the nipple center when scanning the object, the processor 630 may detect a preset target area in the breast ultrasound image by: determining that the user used the marked end of the probe to align with the nipple center, and then obtaining the position of a point on the top layer of the breast ultrasound image on the side with the image mark, as the position of the preset target area; or, determining that the user did not use the marked end of the probe to align with the nipple center, and then obtaining the position of a point on the top layer of the breast ultrasound image on the opposite side of the side with the image mark, as the position of the preset target area.

[0117] Based on the determined location of the preset target site (i.e., the nipple), the processor 630 calculates the distance from the lesion to the preset target site based on the detection results. This may include: mapping points on the boundary of the lesion to the top layer of the breast ultrasound image to obtain quasi-target points, and determining the point among the quasi-target points that is closest to the preset target site to obtain the target point; calculating the distance from the target point to the preset target site as the distance from the lesion to the preset target site, such as... Figure 4A As shown by the dashed line.

[0118] Figure 4B and Figure 4C The image shown depicts a scenario where a probe-acquired breast image simultaneously covers both the nipple and the lesion. In this scenario, an acoustic shadow is typically present behind the nipple in the ultrasound image. Generally, the location of the nipple can be determined during the doctor's procedure, ensuring it is definitely in the scan image. Based on the tissue characteristics of the nipple, there is a distinct dark area of ​​acoustic shadowing behind the image, such as in 4B and [other ultrasound images]. Figure 4C As shown, the approximate location of the nipple is determined by the location of the largest sound shadow area in the depth direction. The black areas on the left and right sides of the image are relatively small and do not represent the approximate location of the nipple. Based on the approximate location of the nipple, a straight line is projected. The midpoint of the corresponding line segment in the horizontal direction at the top layer of the image after projection can be considered the center of the nipple. (See image for details.) Figure 4B and Figure 4C As shown, the dark gray straight line at the top edge of the image represents the horizontal extent of the nipple on the body surface, while the vertical dashed line represents the acoustic shadow area behind the nipple. Figure 4B and Figure 4C The difference shown is that, Figure 4B The distance from the lesion to the nipple shown is defined as the distance between the position of the lesion edge mapped onto the body surface and the position of the nipple center. Figure 4C The distance from the lesion to the nipple shown is defined as the straight-line distance between the edge of the lesion and the center of the nipple.

[0119] Based on this, Figure 4B In the example shown, the processor 630 detects a preset target area (i.e., the nipple) in the breast ultrasound image. This can include: detecting the region where the preset target area is located and obtaining the position of the center point of the preset target area as the position of the preset target area. In this embodiment, the processor 630 can detect the entire region where the nipple is located, segment the boundary of the nipple, determine and obtain the position of the center point of the nipple as the position of the nipple. Exemplarily, the processor 630 can detect the region where the nipple is located through image processing, machine learning, deep learning, etc. Its typical image feature is that there is obvious acoustic shadow (black) in the back of the ultrasound image (including near field, mid field, and far field). After detecting the region, the processor can calculate the range of values ​​of all points in the region in the horizontal direction in the image. That is, it is equivalent to projecting all points in the region along the vertical direction of the image and calculating the position of the midpoint of the corresponding line segment in the horizontal direction at the top of the image after projection, which is used as the position of the center point of the nipple, i.e., the position of the nipple.

[0120] Accordingly, the processor 630 calculates the distance from the lesion to the preset target site based on the detection results, which may include: mapping points on the boundary of the lesion to the top layer of the breast ultrasound image to obtain quasi-target points, and determining the point among the quasi-target points that is closest to the preset target site to obtain the target point; calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site, such as... Figure 4B As shown by the horizontal dashed line.

[0121] exist Figure 4C In the example shown, the processor 630 detects a preset target area (i.e., the nipple) in the breast ultrasound image. This can include: detecting the region where the preset target area is located and obtaining the position of the center point of the preset target area as the position of the preset target area. In this embodiment, the entire region where the nipple is located can be detected, the boundaries of the nipple can be segmented, and the position of the center point of the nipple can be determined and obtained as the position of the nipple. For example, the region where the nipple is located can be detected by image processing, machine learning, deep learning, etc. Its typical image feature is that there is obvious acoustic shadow (black) in the back of the ultrasound image (including near field, mid field, and far field). After detecting the region, the range of values ​​of all points in the region in the horizontal direction in the image can be calculated. That is, it is equivalent to projecting all points in the region along the vertical direction of the image and calculating the position of the midpoint of the corresponding line segment in the horizontal direction at the top of the image after projection, which is used as the position of the center point of the nipple, i.e., the position of the nipple.

[0122] Accordingly, the processor 630 calculates the distance from the lesion to the preset target site based on the detection results, which may include: determining the point on the boundary of the lesion closest to the center point of the preset target site as the target point; calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site, such as... Figure 4C As shown by the slanted dashed line.

[0123] The processor 630 determines the target point by: traversing all points on the boundary of the lesion to determine the point closest to the nipple center point as the target point. Alternatively, the target point can be determined by: identifying the centroid of the region enclosed by the boundary of the lesion, connecting the centroid to the nipple center point to form a line segment, and determining the point closest to the nipple center point within a preset area near the intersection of the line segment and the boundary of the lesion as the target point. For example, if the nipple center point is defined as N and the lesion centroid as M, then the point closest to N at the intersection of line segment MN and the lesion boundary (e.g., defined as X) is the target point. Calculating the distance between the target point and the nipple center point yields the distance from the lesion to the nipple. The pre-defined area near intersection point X can be understood as follows: Centered on intersection point X, extend a certain distance to the left and right sides of the lesion boundary to obtain point X1 to the left of X on the lesion boundary, and point X2 to the right of X on the lesion boundary. The points between X1 and X2 on the lesion boundary constitute the aforementioned pre-defined area. The point closest to N within this area is the target point. The angle a1 between line segments NX1 and NX can be equal to the angle a2 between line segments NX2 and NX. Therefore, an angle a can be pre-defined such that angles a1 and a2 are both half of angle a, thus obtaining the distances to extend to the left and right sides of X, thereby obtaining points X1 and X2, and consequently, the aforementioned pre-defined area.

[0124] Furthermore, in scenarios where the probe is positioned with its side facing the center of the nipple to acquire images, if the distance from the lesion to the nipple is defined as the straight-line distance between the edge of the lesion and the center of the nipple, and the distance between the position of the edge mapped onto the body surface and the position of the nipple center, then the processor 630 calculates the distance from the lesion to the preset target site based on the detection results. This can include: determining the point on the boundary of the lesion closest to the center point of the preset target site as the target point; and calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site. The method for determining the target point can be as described above and will not be repeated here.

[0125] Alternatively, in another embodiment of this application, when the preset target location is the nipple, the processor 630 detects the preset target location in the ultrasound image, which may include: detecting the area where the preset target location is located, and obtaining a line segment used to define the preset target location as the position of the preset target location. In this embodiment, the nipple is defined as a line segment, and the position of the line segment is the position of the nipple. Accordingly, the processor 630 calculates the distance from the lesion to the preset target location based on the detection result, which may include: determining the point on the boundary of the lesion closest to the center point of the preset target location as the target point; and calculating the distance from the target point to the center point of the preset target location as the distance from the lesion to the preset target location.

[0126] In another embodiment of this application, when the preset target location is the nipple, the nipple can be defined as a line segment, and the detection result of the nipple location can be the location of a line segment. The detection result of the lesion location is the area where the lesion is located and its boundary. Based on this, the processor 630 calculates the distance from the lesion to the preset target location based on the detection result, which may include: calculating the minimum distance of the figure formed by the line segment and the boundary of the lesion, as the distance from the lesion to the preset target location.

[0127] In another embodiment of this application, when the preset target location is the nipple, the user (e.g., a doctor) can be prompted to select the current nipple position after the distance measurement is initiated. Since the center of the nipple is at the top of the image, the processor 630 can calculate the shortest distance between the doctor's click location and the lesion (e.g., mapped to the skin) as the distance from the lesion to the nipple. In this embodiment, the processor 630's detection of the preset target location in the breast ultrasound image may include: receiving the location of the preset target location input by the user as the location of the preset target location. Accordingly, the processor 630 calculates the distance from the lesion to the preset target site based on the detection results, which may include: mapping points on the boundary of the lesion to the top layer of the breast ultrasound image to obtain quasi-target points, and determining the point among the quasi-target points that is closest to the preset target site to obtain a target point, and calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site; or, determining the point on the boundary of the lesion that is closest to the center point of the preset target site as the target point, and calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site.

[0128] Furthermore, in embodiments of this application, if only a lesion is detected in the ultrasound image but not the nipple, the processor 630 can prompt "No nipple image detected in the current section" through a human-computer interaction interface, such as via voice or text, to encourage the user to reselect a section to obtain an ultrasound image for detection. When acquiring data with one end of the probe aligned with the nipple center, in most cases there will be no obvious acoustic shadow behind the nipple in the ultrasound image; in such cases, a prompt can also be given for the doctor to confirm. Additionally, if a lesion is detected in the ultrasound image that is far from the nipple (e.g., the distance between them exceeds a predetermined threshold), the user can be prompted to switch to a wide-view view or use a stitched image for measurement, where the stitched image can be a dual-screen stitch.

[0129] Based on the above description, the ultrasound measuring device according to the embodiments of this application can automatically locate the position of the lesion and the preset target site (skin and / or nipple), and automatically calculate the distance from the lesion to the preset target site (skin and / or nipple). This not only simplifies the measurement process of the distance from the lesion to the site (skin and / or nipple) and improves the measurement efficiency, but also improves the accuracy of the measurement results.

[0130] In the embodiments of this application, after the processor 630 calculates the distance from the lesion to the preset target site, the calculation result can be displayed on a display device, such as on an ultrasound image, for the user to view or record. Furthermore, in the embodiments of this application, after calculating the distance from the lesion to the preset target site, the processor 630 can also generate an ultrasound report based on the calculation result, thereby further reducing the user's burden of writing documents, improving work efficiency, and reducing the possibility of report errors.

[0131] The following is combined with Figure 7 Describes an ultrasonic measuring device according to another embodiment of this application. Figure 7 A schematic block diagram of an ultrasonic measuring device 700 according to an embodiment of this application is shown. Figure 7 As shown, the ultrasonic measuring device 700 includes a memory 710 and a processor 720. The memory 710 stores program code for implementing corresponding steps in the ultrasonic measuring method 500 according to embodiments of this application. The processor 720 runs the program code stored in the memory 710 to execute corresponding steps of the ultrasonic measuring methods 200 and 500 according to embodiments of this application.

[0132] Furthermore, according to embodiments of this application, a storage medium is also provided, on which program instructions are stored. When executed by a computer or processor, these program instructions are used to perform corresponding steps of the ultrasonic measurement methods 200 and 500 of the embodiments of this application. The storage medium may, for example, include a memory card of a smartphone, a storage component of a tablet computer, a hard disk of a personal computer, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disc read-only memory (CD-ROM), a USB memory, or any combination of the above storage media.

[0133] Furthermore, according to embodiments of this application, a computer program is also provided, which can be stored on a cloud or local storage medium. When this computer program is run by a computer or processor, it is used to perform the corresponding steps of the ultrasonic measurement method of the embodiments of this application.

[0134] The ultrasound measurement method and apparatus according to the embodiments of this application can automatically or semi-automatically detect lesions and preset target sites (skin and / or nipples) in ultrasound images, and automatically calculate the distance from the lesion to the preset target site (skin and / or nipple). This not only simplifies the measurement process of the distance from the lesion to the site (skin and / or nipple) and improves the measurement efficiency, but also improves the accuracy of the measurement results.

[0135] Although exemplary embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above exemplary embodiments are merely illustrative and are not intended to limit the scope of this application. Various changes and modifications can be made therein by those skilled in the art without departing from the scope and spirit of this application. All such changes and modifications are intended to be included within the scope of this application as claimed in the appended claims.

[0136] 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 implementation should not be considered beyond the scope of this application.

[0137] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus 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 apparatus, or some features may be ignored or not executed.

[0138] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application 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.

[0139] Similarly, it should be understood that, in order to simplify this application and aid in understanding one or more aspects of the various applications, features of this application are sometimes grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of this application. However, this approach should not be construed as reflecting an intention that the claimed application requires more features than are expressly recited in each claim. Rather, as reflected in the corresponding claims, the inventive point lies in solving the corresponding technical problem with fewer features than all features of a single disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of this application.

[0140] Those skilled in the art will understand that, apart from mutually exclusive features, all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or apparatus so disclosed can be combined in any combination. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0141] 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 intended to be within the scope of this application and form different embodiments. For example, in the claims, any one of the claimed embodiments can be used in any combination.

[0142] The various component embodiments of this application 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 in the article analysis apparatus according to embodiments of this application. This application can also be implemented as an apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such an implementation of this application can be stored on a computer-readable medium, or can be in 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.

[0143] It should be noted that the above embodiments are illustrative of this application 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 word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. This application 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.

[0144] The above description is merely a specific embodiment or illustration of the embodiments of this application. The scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. The scope of protection of this application shall be determined by the scope of the claims.

Claims

1. An ultrasonic measurement method, characterized in that, The method includes: The probe is controlled to emit ultrasonic waves toward the target area of ​​the object being measured, the echo of the ultrasonic waves is received, and the ultrasonic echo signal is obtained based on the echo of the ultrasonic waves. A breast ultrasound image is generated based on the ultrasound echo signal, and lesions and preset target areas in the breast ultrasound image are detected automatically. This allows for the detection of the lesions and preset target areas based on the breast ultrasound image. The preset target areas include the skin and / or nipple. The distance from the lesion to the preset target site is calculated based on the detection results; The preset target area is the nipple. Detecting the preset target area in the breast ultrasound image includes: detecting the region where the preset target area is located, and obtaining the position of the center point of the preset target area as the position of the preset target area. The step of obtaining the position of the center point of the preset target area includes: projecting all points in the area along the vertical direction of the breast ultrasound image; calculating the position of the midpoint of the line segment corresponding to the top horizontal direction of the breast ultrasound image after projection, as the position of the center point of the preset target area; The step of calculating the distance from the lesion to the preset target site based on the detection results includes: mapping points on the boundary of the lesion to the top layer of the breast ultrasound image to obtain quasi-target points, and determining the point among the quasi-target points that is closest to the preset target site to obtain a target point; and calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site.

2. The method according to claim 1, characterized in that, The detection of lesions in the breast ultrasound image includes: The area where the lesion is located is detected and the boundary of the lesion is obtained.

3. The method according to claim 1, characterized in that, The preset target area is the skin, and the detection of the preset target area in the breast ultrasound image includes: The position of the top layer of the breast ultrasound image is detected as the position of the preset target area; or The location of the preset target area is determined by detecting the position in the upper preset region of the breast ultrasound image where the brightness is greater than a preset threshold.

4. The method according to claim 3, characterized in that, The step of calculating the distance from the lesion to the preset target site based on the detection results includes: The point with the smallest depth coordinate on the boundary of the lesion is determined as the target point; Calculate the distance from the target point to the preset target location, and use it as the distance from the lesion to the preset target location.

5. The method according to claim 1, characterized in that, The preset target area is the nipple, and the method further includes: If the lesion is detected only in the breast ultrasound image and the nipple region is not detected, a prompt will be issued indicating that the nipple region is not detected in the current section; or If the distance between the lesion and the nipple is detected in the breast ultrasound image to exceed a predefined threshold, a prompt is made to switch to a wide-view image or use a stitched image for measurement.

6. The method according to claim 1, characterized in that, The detection of the lesion and / or the preset target site is based on fully automated or semi-automated detection, wherein the semi-automated detection includes: Receives a predefined region of the lesion and / or the preset target site input by the user; and The lesion and / or the preset target site are detected based on the predefined region.

7. The method according to claim 1 or 6, characterized in that, The detection of the lesion and / or the preset target site is based on at least one of the following algorithms: boundary segmentation algorithm, target detection algorithm, machine learning algorithm, and deep learning algorithm.

8. The method according to claim 1, characterized in that, The method further includes: After calculating the distance from the lesion to the preset target site, the result of the calculation is displayed.

9. The method according to claim 1 or 8, characterized in that, The method further includes: After calculating the distance from the lesion to the preset target site, an ultrasound report is generated based on the calculation results.

10. The method according to claim 1 or 8, characterized in that, The method further includes: displaying the breast ultrasound image, wherein the calculation result is displayed on the breast ultrasound image.

11. An ultrasonic measurement method, characterized in that, The method includes: The probe is controlled to emit ultrasonic waves toward the target area of ​​the object being measured, the echo of the ultrasonic waves is received, and the ultrasonic echo signal is obtained based on the echo of the ultrasonic waves. An ultrasound image is generated based on the ultrasound echo signal, and lesions and preset target areas in the ultrasound image are detected by automatic detection, thereby obtaining the detection results of the lesions and preset target areas based on the ultrasound image; and The distance from the lesion to the preset target site is calculated based on the detection results; The preset target area includes the nipple. Detecting the preset target area in the breast ultrasound image includes: detecting the region where the preset target area is located, and obtaining the position of the center point of the preset target area as the position of the preset target area. The step of obtaining the position of the center point of the preset target area includes: projecting all points in the area along the vertical direction of the breast ultrasound image; calculating the position of the midpoint of the line segment corresponding to the top horizontal direction of the breast ultrasound image after projection, as the position of the center point of the preset target area; The step of calculating the distance from the lesion to the preset target site based on the detection results includes: mapping points on the boundary of the lesion to the top layer of the breast ultrasound image to obtain quasi-target points, and determining the point among the quasi-target points that is closest to the preset target site to obtain a target point; and calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site.

12. An ultrasonic measuring device, characterized in that, The device includes an ultrasound probe, a transmit / receive sequence controller, and a processor, wherein: The transmit / receive sequence controller is used to excite the ultrasonic probe to emit ultrasonic waves toward the target area of ​​the object being tested, receive the echo of the ultrasonic waves, and obtain the ultrasonic echo signal based on the echo of the ultrasonic waves. The processor is used to generate a breast ultrasound image based on the ultrasound echo signal, and to detect lesions and preset target areas in the breast ultrasound image through automatic detection, so as to obtain the detection results of the lesions and preset target areas based on the breast ultrasound image, and to calculate the distance from the lesion to the preset target area based on the detection results, wherein the preset target area includes skin and / or nipple; The preset target area is the nipple. The processor detects the preset target area in the breast ultrasound image, including: detecting the area where the preset target area is located, and obtaining the position of the center point of the preset target area as the position of the preset target area. The processor obtains the position of the center point of the preset target area by: projecting all points in the area along the vertical direction of the breast ultrasound image; and calculating the position of the midpoint of the line segment corresponding to the top layer of the breast ultrasound image after projection, as the position of the center point of the preset target area. The processor calculates the distance from the lesion to the preset target site based on the detection results, including: mapping points on the boundary of the lesion to the top layer of the breast ultrasound image to obtain quasi-target points, and determining the point among the quasi-target points that is closest to the preset target site to obtain a target point; and calculating the distance from the target point to the center point of the preset target site as the distance from the lesion to the preset target site.

13. The apparatus according to claim 12, characterized in that, The processor detects lesions in the breast ultrasound image, including: The area where the lesion is located is detected and the boundary of the lesion is obtained.

14. The apparatus according to claim 12, characterized in that, The preset target area is the skin, and the processor detects the preset target area in the breast ultrasound image, including: The position of the top layer of the breast ultrasound image is detected as the position of the preset target area; or The location of the preset target area is determined by detecting the position in the upper preset region of the breast ultrasound image where the brightness is greater than a preset threshold.

15. The apparatus according to claim 14, characterized in that, The processor calculates the distance from the lesion to the preset target site based on the detection results, including: The point with the smallest depth coordinate on the boundary of the lesion is determined as the target point; Calculate the distance from the target point to the preset target location, and use it as the distance from the lesion to the preset target location.

16. The apparatus according to claim 12, characterized in that, The preset target area is the nipple, and the processor is further configured to: If the lesion is detected only in the breast ultrasound image and the nipple region is not detected, a prompt will be issued indicating that the nipple region is not detected in the current section; or If the distance between the lesion and the nipple is detected in the breast ultrasound image to exceed a predefined threshold, a prompt is made to switch to a wide-view image or use a stitched image for measurement.

17. The apparatus according to claim 12, characterized in that, The processor is further configured to: receive the location of the preset target site input by the user, so as to calculate the distance from the lesion to the preset target site.

18. An ultrasonic measuring device, characterized in that, The device includes a memory and a processor, the memory storing a computer program executed by the processor, the computer program performing the ultrasonic measurement method as described in any one of claims 1-11 when executed by the processor.

19. A storage medium, characterized in that, The storage medium stores a computer program that, when executed, performs the ultrasonic measurement method as described in any one of claims 1-11.

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