Upper gastrointestinal tract ultrasound image processing method and apparatus, device, and medium

Abstract

An upper gastrointestinal tract ultrasound image processing method and apparatus, a device, and a medium. The method comprises: positioning, from an upper gastrointestinal tract ultrasound image, a position of a starting contour line corresponding to an ultrasonic probe (S11); acquiring a position of a lesion image region contained in the upper gastrointestinal tract ultrasound image (S12); expanding outward on the basis of the position of the starting contour line, and positioning, from the upper gastrointestinal tract ultrasound image, a position of each layer of anatomical structure boundary contour line of an upper gastrointestinal tract wall (S13); and outputting a positional relationship between the lesion image region and each layer of anatomical structure boundary contour line (S14).

Description

Upper digestive tract ultrasound image processing method, device, equipment and medium

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on January 17, 2024, with application number 202410069823.3 and invention name “Upper gastrointestinal tract ultrasound image processing method, device, equipment and medium”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present invention relates to the technical field of image processing, and in particular to a method, device, equipment and medium for processing upper digestive tract ultrasound images. Background Art

[0003] In the medical field, ultrasound endoscopy is commonly used to collect ultrasound images of the upper gastrointestinal tract (other probes can also be used). In ultrasound images, the digestive tract wall of the upper gastrointestinal tract can be presented as a five-layer anatomical structure, which is shaped like a circular ring structure. In the ultrasound image, the five layers of "bright-dark-bright-dark-bright" can be identified based on the echo strength from the inside to the outside, namely the 1st layer (1st layer) to the 5th layer (5th layer), as shown in Figure 1.

[0004] When a mucosal lesion develops, the shape and echo intensity of the lesion change, making it easy to confuse it with adjacent layers. For example, at the location marked with a "+" sign in Figure 1, the lesion creates a quasi-circular protrusion, and the lesion's echo appears a similar white-gray color to the first layer (i.e., the 1st layer in the figure) and the third layer (i.e., the 3rd layer in the figure). Because the difference between light and dark is small, the stratification is not obvious, making it difficult for doctors to visually determine which layer the lesion occurs. In this case, if the doctor needs to accurately locate the layer where the lesion occurs, they need to pause the scan and spend a certain amount of time comparing the anatomical layer contours to distinguish them, resulting in low inspection and diagnosis efficiency.

[0005] In summary, how to quickly and accurately locate the layer where the lesion occurs in upper gastrointestinal ultrasound images is a problem that needs to be solved. Summary of the Invention

[0006] In view of this, the present invention aims to provide a method, apparatus, device, and medium for processing upper gastrointestinal ultrasound images, which can quickly and accurately locate the layer where the lesion occurs in upper gastrointestinal ultrasound images. The specific scheme is as follows:

[0007] In a first aspect, the present application discloses a method for processing upper digestive tract ultrasound images, comprising:

[0008] Locating the position of the starting contour line corresponding to the ultrasound probe from the upper digestive tract ultrasound image;

[0009] Acquiring a position of a lesion image region contained in the upper digestive tract ultrasound image;

[0010] Expanding outward based on the position of the initial contour line, the positions of the boundary contour lines of the anatomical structures of each layer of the upper digestive tract wall are located from the upper digestive tract ultrasound image;

[0011] The positional relationship between the lesion image area and the boundary contour lines of the anatomical structure of each layer is output.

[0012] Optionally, locating the position of the starting contour line corresponding to the ultrasound probe from the upper digestive tract ultrasound image includes:

[0013] The preset edge detection algorithm is used to locate the position of the starting contour line corresponding to the ultrasound probe from the upper gastrointestinal tract ultrasound image.

[0014] Optionally, the expanding outward based on the position of the starting contour line to locate the position of the boundary contour lines of each layer of the anatomical structure of the upper digestive tract wall from the upper digestive tract ultrasound image includes:

[0015] The starting contour line is used as the first detection contour line, and the preset pixel size is used as the moving step size. The pixel points on the Nth detection contour line are moved in a direction away from the center point of the starting contour line, and a corresponding smooth curve is generated based on the coordinates of each pixel point after movement to obtain the N+1th detection contour line, and the anatomical structure boundary contour line of the upper gastrointestinal wall is identified from the upper gastrointestinal ultrasound image based on the N+1th detection contour line, and the level of the anatomical structure boundary contour line is determined according to the order in which the anatomical structure boundary contour lines are identified, and the position of the anatomical structure boundary contour line at this level is recorded; wherein N≥1 and is an integer.

[0016] Optionally, identifying the anatomical structure boundary contour line of the upper digestive tract wall from the upper digestive tract ultrasound image according to the N+1th detected contour line includes:

[0017] Calculate the similarity between the N+1th detection contour line and the first detection contour line, or calculate the similarity between the N+1th detection contour line and the Nth detection contour line according to the pixel values ​​of the pixel points on the detection contour line;

[0018] When the similarity satisfies a preset condition, it is determined that the anatomical structure boundary contour line is identified.

[0019] Optionally, the anatomical structure boundary contour line includes a first-layer anatomical structure boundary contour line and a non-first-layer anatomical structure boundary contour line from the inner layer to the outer layer;

[0020] Correspondingly, identifying the anatomical structure boundary contour line of the upper digestive tract wall from the upper digestive tract ultrasound image according to the N+1th detected contour line includes:

[0021] Calculate the similarity between the N+1th detection contour line and the first detection contour line based on the pixel values ​​of the pixels on the detection contour line;

[0022] Before identifying the first-layer anatomical structure boundary contour line, if the calculated similarity between the currently detected contour line and a preset similarity threshold satisfies a first preset condition, then the currently detected contour line is determined to be the first-layer anatomical structure contour line of the upper digestive tract wall;

[0023] After identifying the first-level anatomical structure boundary contour line, if the similarity calculated between the currently detected contour line and the corresponding similarity of the previously identified upper-level anatomical structure boundary contour line meets the second preset condition, the currently detected contour line is determined to be a non-first-level anatomical structure boundary contour line of the upper gastrointestinal tract wall.

[0024] Optionally, an independent sample t-test is used to calculate the significance of the difference between the pixel values ​​of the two detection contour points to obtain the similarity.

[0025] Optionally, outputting the positional relationship between the lesion image area and the boundary contour lines of the anatomical structure in each layer includes:

[0026] Determine a first target coordinate point closest to the center point of the starting contour line from the boundary of the lesion image area;

[0027] The lesion origin level is determined and output based on the positional relationship between the first target coordinate point and the boundary contour lines of the anatomical structure at each layer.

[0028] Optionally, outputting the positional relationship between the lesion image area and the boundary contour lines of the anatomical structure of each layer includes:

[0029] Determine a second target coordinate point on the boundary of the lesion image area that is farthest from the center point of the starting contour line;

[0030] The lesion end level is determined and output based on the positional relationship between the second target coordinate point and the boundary contour line of the anatomical structure of each layer.

[0031] Optionally, the expanding outward based on the position of the starting contour line to locate the position of the boundary contour lines of each layer of the anatomical structure of the upper digestive tract wall from the upper digestive tract ultrasound image includes:

[0032] When the distance between the located anatomical structure boundary contour line and the center point of the starting contour line exceeds the distance between the second target coordinate point and the center point of the starting contour line, the step of expanding outward to locate the anatomical structure boundary contour line of the next level is stopped.

[0033] Optionally, outputting the positional relationship between the lesion image area and the boundary contour lines of the anatomical structure of each layer includes:

[0034] The marks of the lesion image area and the boundary contour lines of the anatomical structure of each layer are output to a display device.

[0035] Optionally, obtaining the position of the lesion image area contained in the upper digestive tract ultrasound image includes:

[0036] Acquiring the position of the lesion image area contained in the upper digestive tract ultrasound image from information input by the user; or,

[0037] The position of the lesion image area is identified from the upper digestive tract ultrasound image using a preset algorithm.

[0038] In a second aspect, the present application discloses an upper digestive tract ultrasound image processing device, comprising:

[0039] A probe contour positioning module is used to locate the position of the starting contour line corresponding to the ultrasound probe from the upper digestive tract ultrasound image;

[0040] a lesion position acquisition module, configured to acquire the position of the lesion image area contained in the upper digestive tract ultrasound image;

[0041] an anatomical structure positioning module, configured to expand outward based on the position of the starting contour line to locate the position of the boundary contour lines of each layer of the anatomical structure of the upper digestive tract wall from the upper digestive tract ultrasound image;

[0042] The information output module is used to output the positional relationship between the lesion image area and the boundary contour lines of the anatomical structure of each layer.

[0043] In a third aspect, the present application discloses an electronic device, comprising:

[0044] Memory, used to store computer programs;

[0045] A processor is used to execute the computer program to implement the steps of the upper digestive tract ultrasound image processing method disclosed above.

[0046] In a fourth aspect, the present application discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the steps of the upper gastrointestinal ultrasound image processing method disclosed above are implemented.

[0047] It can be seen that the present application locates the position of the starting contour line corresponding to the ultrasound probe from the upper gastrointestinal ultrasound image; obtains the position of the lesion image area contained in the upper gastrointestinal ultrasound image; based on the position of the starting contour line, expands outward to locate the position of the boundary contour lines of the anatomical structure of each layer of the upper gastrointestinal wall from the upper gastrointestinal ultrasound image; and outputs the positional relationship between the lesion image area and the boundary contour lines of each layer of the anatomical structure. It can be seen that the present application needs to locate the position of the starting contour line corresponding to the ultrasound probe from the upper gastrointestinal ultrasound image, and by expanding the starting contour line outward, it can locate the position of the boundary contour lines of each layer of the anatomical structure of the upper gastrointestinal wall from the upper gastrointestinal ultrasound image; finally, based on the position of the lesion image area contained in the upper gastrointestinal ultrasound image, it can output the positional relationship between the lesion image area and the boundary contour lines of each layer of the anatomical structure. In this way, the above scheme can automatically identify the position of the boundary contour lines of each layer of the anatomical structure of the upper gastrointestinal wall from the upper gastrointestinal ultrasound image, and further accurately locate the origin / end layer of the lesion based on the positional relationship between the boundary contour lines of each layer of the anatomical structure and the lesion image area, which helps to improve the efficiency of doctor's examination and diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without any creative work.

[0049] FIG1 is a schematic diagram of an ultrasound image of the anatomical structure of each layer of the digestive tract wall disclosed in the present application;

[0050] FIG2 is a flow chart of an upper digestive tract ultrasound image processing method disclosed in the present application;

[0051] FIG3 is a schematic diagram of an endoscope pipeline area in an ultrasound image disclosed in the present application;

[0052] FIG4 is a flowchart of a specific upper digestive tract ultrasound image processing method disclosed in this application;

[0053] FIG5 is a schematic structural diagram of an upper digestive tract ultrasound image processing device disclosed in the present application;

[0054] FIG6 is a structural diagram of an electronic device disclosed in this application. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0056] Currently, if a lesion occurs in the mucosa, the shape and echo strength of the lesion will change and it will be easily confused with the adjacent layers. It is difficult for doctors to see with the naked eye at which layers the lesion occurs. At this time, if the doctor needs to accurately locate the layer where the lesion occurs, he needs to pause the scan and spend a certain amount of time comparing the anatomical layer contours to distinguish them, resulting in low efficiency in inspection and diagnosis. To this end, the embodiments of the present application disclose an upper gastrointestinal ultrasound image processing method, device, equipment and medium, which can quickly and accurately locate the layer where the lesion occurs in the upper gastrointestinal ultrasound image.

[0057] 2 , the present embodiment discloses a method for processing an upper digestive tract ultrasound image, the method comprising:

[0058] Step S11: Locate the position of the starting contour line corresponding to the ultrasound probe from the upper digestive tract ultrasound image.

[0059] In this embodiment, after obtaining an ultrasound image of the upper gastrointestinal tract, it is first necessary to locate the position of the starting contour line corresponding to the ultrasound probe from the ultrasound image of the upper gastrointestinal tract, that is, to identify the ring formed by the contour of the ultrasound endoscope itself. The position referred to in this embodiment can specifically be the coordinate value of the pixel point in the image. In addition, it should be pointed out that, as shown in FIG1 , the five-layer anatomical structure of the upper gastrointestinal wall also appears as a ring-shaped image in the ultrasound image. This is because the upper gastrointestinal tract of any person (such as the esophagus) will be stretched to a near-circular shape by the circular array ultrasound endoscope. When the ultrasound probe is not inserted for examination, the esophagus is collapsed. The circular array ultrasound endoscope itself uses a circular ultrasonic transducer for imaging, so it can form the ultrasound image with a circular shape shown in FIG1 , that is, the image display of each layer of the structure is also circular, almost consistent with the shape of the pipeline layer.

[0060] It is understandable that in the medical field, ultrasonic endoscopes are commonly used to collect ultrasonic images of the upper digestive tract. Ultrasonic endoscopy is an inspection technology that combines endoscopy with ultrasound, and integrates the advantages of endoscopy and ultrasound. It places a miniature high-frequency ultrasonic probe at the front end of the endoscope. When the endoscope enters the esophagus or gastrointestinal cavity, it can directly observe the intracavitary morphology while performing real-time ultrasonic scanning. With the help of the endoscope, the surface of the digestive tract mucosa and its lesions are directly observed, and with the help of ultrasonic scanning, the histological characteristics of each layer of the digestive tract wall, the intracavitary lesions and the ultrasonic images of the surrounding adjacent important organs are obtained. Therefore, through ultrasonic endoscopy, both endoscopic images and ultrasonic images can be obtained. The embodiment of the present application mainly uses the position of each layer of the digestive tract wall to locate the origin layer of the lesion. Therefore, endoscopic images are not used, and only the detected upper digestive tract ultrasonic images need to be processed.

[0061] The upper gastrointestinal ultrasound image in this embodiment can be an image scanned by the doctor in real time through an ultrasound endoscope, that is, in a specific scenario, the doctor views the real-time image through the device interface. When the lesion is found by the naked eye / AI through ultrasound and / or endoscopic images, the doctor can choose to stop the movement of the probe, and then freeze the ultrasound image at this time, and then use the method provided in this application to automatically analyze this frame of ultrasound image; in addition, the method of this application can also be used for scenarios such as real-time calculation of dynamic ultrasound images, calculation in ultrasound movie playback, and can also calculate images of all frames or interval frames.

[0062] In a specific embodiment, the above-mentioned method of locating the position of the starting contour line corresponding to the ultrasound probe from the upper gastrointestinal ultrasound image includes: locating the position of the starting contour line corresponding to the ultrasound probe from the upper gastrointestinal ultrasound image using a preset edge detection algorithm. That is, the embodiment of the present application can use a preset edge detection algorithm to locate the position of the starting contour line of the ultrasound endoscope pipeline in the upper gastrointestinal ultrasound image. The starting contour line is a circular ring structure, and the starting contour line can be understood as the outer boundary of the ultrasound endoscope pipeline. Referring to Figure 3, the white line area in the middle close to the first layer (i.e., the 1st layer) is the pipeline of the ultrasound endoscope. The outer edge of the black area (circular contour) found by the preset edge detection algorithm is the target contour line, and the contour is displayed as a dark layer in the ultrasound image. It should be noted that in order to mark the position area of ​​the pipeline in Figure 3, a white line is artificially used for marking in this figure, but the white line does not exist in the actual ultrasound image. The actual ultrasound image should be as shown in Figure 1.

[0063] Specifically, the opencv edge detection algorithm can be used to locate the position of the starting contour line corresponding to the ultrasound probe from the upper gastrointestinal tract ultrasound image. The opencv edge detection algorithm refers to the edge detection algorithm interface encapsulated in the opencv function package. The edge detection algorithm can be directly called through the command to perform edge segmentation on the part of the image with obvious pixel differences, thereby achieving the purpose of extracting the outer boundary of the black area of ​​the ultrasound pipeline. In addition, other edge detection algorithms can also be adopted. It can be understood that the edge detection algorithm is mainly calculated based on the difference in adjacent pixel values ​​in the image. As shown in Figure 3, there is a significant difference in adjacent pixel values ​​on the outside of the ultrasound pipeline (i.e., the difference between black and white), and the boundary of the ultrasound pipeline is a regular circular shape. Therefore, in this scenario, it is easy to achieve by using the edge detection algorithm.

[0064] Step S12: Acquire the position of the lesion image area contained in the upper digestive tract ultrasound image.

[0065] In this embodiment, it is necessary to further obtain the position of the lesion image region contained in the upper gastrointestinal ultrasound image. Specifically, obtaining the position of the lesion image region contained in the upper gastrointestinal ultrasound image includes: obtaining the position of the lesion image region contained in the upper gastrointestinal ultrasound image from information input by a user; or identifying the position of the lesion image region in the upper gastrointestinal ultrasound image using a preset algorithm.

[0066] That is, in one specific embodiment, the position of the lesion image area can be obtained based on information input by the user. For example, the user can input the position coordinate information of the lesion image area in the upper gastrointestinal ultrasound image, and then use marker points to mark the position of the lesion image area in the upper gastrointestinal ultrasound image based on the position coordinate information. In another specific embodiment, the position of the lesion image area can also be obtained by identifying it through a preset algorithm. For example, a series of position coordinate information of the lesion image area can be obtained through a segmentation AI (Artificial Intelligence) algorithm, and then marked with marker points. Furthermore, this embodiment can also connect these marker points into contour lines to obtain the approximate contour area of ​​the lesion image area.

[0067] Step S13: expanding outward based on the position of the initial contour line, and locating the position of the boundary contour lines of each layer of the anatomical structure of the upper digestive tract wall from the upper digestive tract ultrasound image.

[0068] In this embodiment, the positions of the boundary contour lines of the anatomical structures of each layer of the upper digestive tract wall are located from the upper digestive tract ultrasound image by gradually expanding the starting contour line outward based on the position of the starting contour line.

[0069] Step S14: outputting the positional relationship between the lesion image area and the boundary contour lines of the anatomical structure of each layer.

[0070] In this embodiment, after determining the position of the lesion image region and the positions of the boundary contours of each anatomical structure layer of the upper gastrointestinal wall, the positional relationship between the lesion image region and the boundary contours of each anatomical structure layer is output. In other words, this solution automatically identifies the positions of the boundary contours of each anatomical structure layer of the upper gastrointestinal wall from upper gastrointestinal ultrasound images, and further accurately locates the origin and end levels of the lesion based on the positional relationship between the boundary contours of each anatomical structure layer and the lesion image region, thereby improving the efficiency of doctors' examinations and diagnoses.

[0071] In a specific embodiment, the above-mentioned output of the positional relationship between the lesion image area and the boundary contour lines of the anatomical structure of each layer includes: outputting the labels of the lesion image area and the boundary contour lines of the anatomical structure of each layer to a display device. It is understandable that in order to assist the doctor in positioning, this embodiment is also provided with a display device for displaying the labeling information of the lesion image area and the boundary contour lines of the anatomical structure of each layer. For example, the position of the lesion image area and the boundary contour lines of each layer of the anatomical structure can be marked using conspicuous marks in the upper gastrointestinal tract ultrasound image at the same time, and displayed on the display device. In addition, the numerical value of the starting and / or ending layer of the lesion area can also be directly displayed.

[0072] It can be seen that the present application locates the position of the starting contour line corresponding to the ultrasound probe from the upper gastrointestinal ultrasound image; obtains the position of the lesion image area contained in the upper gastrointestinal ultrasound image; based on the position of the starting contour line, expands outward to locate the position of the boundary contour lines of the anatomical structure of each layer of the upper gastrointestinal wall from the upper gastrointestinal ultrasound image; and outputs the positional relationship between the lesion image area and the boundary contour lines of each layer of the anatomical structure. It can be seen that the present application needs to locate the position of the starting contour line corresponding to the ultrasound probe from the upper gastrointestinal ultrasound image, and by expanding the starting contour line outward, it can locate the position of the boundary contour lines of each layer of the anatomical structure of the upper gastrointestinal wall from the upper gastrointestinal ultrasound image; finally, based on the position of the lesion image area contained in the upper gastrointestinal ultrasound image, it can output the positional relationship between the lesion image area and the boundary contour lines of each layer of the anatomical structure. In this way, the above scheme can automatically identify the position of the boundary contour lines of each layer of the anatomical structure of the upper gastrointestinal wall from the upper gastrointestinal ultrasound image, and further accurately locate the origin / end layer of the lesion based on the positional relationship between the boundary contour lines of each layer of the anatomical structure and the lesion image area, which helps to improve the efficiency of doctor's examination and diagnosis.

[0073] It should be noted that in the description of this embodiment and subsequent embodiments and the corresponding figures, the sequence numbers of the steps and the arrows in the block diagrams are merely illustrative and do not limit the actual order of the steps of the method protected by the present invention. As long as the previous steps on which the subsequent steps depend have been completed, there is no necessary order relationship between the previous steps. For example, in this embodiment, there is no order restriction between steps S11 and S12, while the implementation of step S13 depends on the first implementation of step S11, and the implementation of step S14 depends on the first implementation of steps S12 and S13.

[0074] As shown in FIG4 , the embodiment of the present application discloses a specific method for processing upper gastrointestinal ultrasound images. Compared with the previous embodiment, this embodiment further illustrates and optimizes the technical solution. Specifically, it includes:

[0075] Step S21: Locate the position of the starting contour line corresponding to the ultrasound probe from the upper digestive tract ultrasound image.

[0076] Step S22: Acquire the position of the lesion image area contained in the upper digestive tract ultrasound image.

[0077] Step S23: Using the starting contour line as the first detection contour line, using a preset pixel size as a moving step, moving the pixel points on the Nth detection contour line in a direction away from the center point of the starting contour line, and generating a corresponding smooth curve based on the coordinates of each pixel point after movement to obtain the N+1th detection contour line, and identifying the anatomical structure boundary contour line of the upper gastrointestinal wall from the upper gastrointestinal ultrasound image based on the N+1th detection contour line, determining the level of the anatomical structure boundary contour line according to the order in which the anatomical structure boundary contour line is identified, and recording the position of the anatomical structure boundary contour line at this level; wherein N ≥ 1 and is an integer.

[0078] In this embodiment, the starting contour line is used as the first detection contour line, and the pixels on the Nth detection contour line are moved in a direction away from the center point of the starting contour line with a preset pixel size as the movement step size. After each movement, a corresponding smooth curve is generated based on the coordinates of each moved pixel point to obtain the N+1th detection contour line. That is, during the first expansion, the pixels on the first detection contour line are moved in a direction away from the center point of the starting contour line, and a corresponding smooth curve is generated based on the coordinates of the moved pixels to obtain the second detection contour line; then, the pixels on the second detection contour line are moved in a direction away from the center point of the starting contour line to generate the third detection contour line, and so on.

[0079] In the process of expanding the contour line, it should be noted that the number of pixel points moved each time remains unchanged, and it is based on the pixel points on the first detected contour line. For example, assume that there are 50 pixel points on the starting contour line. Then, each subsequent expansion of the contour line is based on these 50 pixel points. That is, with the preset pixel size as the step length, these 50 pixel points are moved along the direction away from the center point of the starting contour line. Since the number of pixel points remains unchanged, as the contour expands, the pixel points will become sparser and sparser. Therefore, after each expansion, a corresponding smooth curve needs to be generated based on the coordinates of the moved pixel points to obtain the expanded detected contour line, which is convenient for subsequent positioning of which layer the lesion coordinates are located in.

[0080] In the specific implementation manner, the above-mentioned preset pixel size is used as the moving step length to move the pixel points on the Nth detected contour line along the direction away from the center point of the starting contour line, including: based on the coordinate value comparison relationship between the coordinates of each pixel point on the Nth detected contour line and the center point coordinates of the starting contour line, and using the preset pixel size as the moving step length, increase or decrease the coordinate values of the pixel point coordinates to obtain the coordinates of each moved pixel point. That is, in this embodiment, the transformation direction of each pixel point coordinate value, that is, the moving direction of the pixel point, can be determined according to the coordinate value comparison relationship between the coordinates of each pixel point on the Nth detected contour line and the center point coordinates of the starting contour line. Specifically, assume that a coordinate system is established with the lower left corner of the image as the origin and the preset pixel size is 1. Then, in the first moving process, the specific method is as follows: compare the coordinates (x, y) of each pixel point on the Nth detected contour line with the center point coordinates (c1, c2) of the target contour line. For the abscissa x, if x > c1, the x coordinate value is increased by 1; if x < c1, the x coordinate value is decreased by 1; if x = c1, the x coordinate value remains unchanged; for the ordinate y, if y > c2, the y coordinate value is increased by 1; if y < c2, the y coordinate value is decreased by 1; if y = c2, the y coordinate value remains unchanged. That is, by adopting the coordinate value comparison method in this embodiment, the pixel points on the Nth detected contour line move away from the center point of the starting contour line with a step length of 1 pixel, obtain the coordinates of each moved pixel point, and generate a corresponding smooth curve to obtain the (N + 1)th detected contour line. By this means, the shape of the expanded detected contour line can be kept consistent with that of the starting contour line.

[0081] In the above process, since the coordinates of each pixel point need to be compared with the coordinates of the center point, the embodiment of the present application also needs to calculate the specific coordinate values ​​of the center point coordinates. In one specific embodiment, the coordinates of the center point of the starting contour line can be determined based on the average value of the horizontal coordinates and the average value of the vertical coordinates of each pixel point on the starting contour line. In other words, the coordinates of the center point can be obtained by averaging the horizontal and vertical coordinates of all points on the quasi-circular contour. In addition, other mathematical methods can also be used to calculate the coordinate values ​​of the center point, depending on the definition of the technician and the convenience of calculation.

[0082] In addition, in the process of expanding the contour line, in addition to the method mentioned in the above embodiment of expanding the Nth detection contour line to obtain the N+1th detection contour line each time, it is also possible to expand on the basis of the first detection contour line each time, for example, moving the pixel points on the first detection contour line by twice the moving step length in the direction away from the center point of the starting contour line to obtain the second detection contour line; moving the pixel points on the first detection contour line by twice the moving step length in the direction away from the center point of the starting contour line to obtain the third detection contour line, and so on. Both methods can achieve the same effect.

[0083] Furthermore, each time the N+1th detection contour line is obtained from the Nth detection contour line, the anatomical structure boundary contour lines of the upper gastrointestinal wall are identified from the upper gastrointestinal ultrasound image based on the N+1th detection contour line, and the layer at which the anatomical structure boundary contour lines are located is determined based on the order in which the anatomical structure boundary contour lines are identified, and the position of the anatomical structure boundary contour lines at that layer is recorded; where N ≥ 1 and is an integer. It can be understood that when locating the anatomical structure boundary contour lines of each layer of the upper gastrointestinal wall, this embodiment locates them in the order from the inner layer to the outer layer, that is, the five layers of anatomical structure boundary contour lines of the upper gastrointestinal wall are located in sequence from the inner layer to the outer layer.

[0084] In a specific embodiment, the above-mentioned identification of the anatomical structure boundary contour line of the upper gastrointestinal wall from the upper gastrointestinal ultrasound image based on the N+1th detection contour line includes: calculating the similarity between the N+1th detection contour line and the 1st detection contour line, or calculating the similarity between the N+1th detection contour line and the Nth detection contour line based on the pixel values ​​of the pixel points on the detection contour line; when the similarity meets the preset conditions, it is determined that the anatomical structure boundary contour line is identified. From the above content, it can be seen that whether it is the ultrasound endoscope line or the five-layer structure of the upper gastrointestinal wall, it presents a circular image in the ultrasound image. Therefore, the present application locates the anatomical structure boundary contour lines of each layer of the upper gastrointestinal wall from the upper gastrointestinal ultrasound image by calculating the similarity between the N+1th detection contour line and the 1st detection contour line, or calculating the similarity between the N+1th detection contour line and the Nth detection contour line, that is, identifying the nearly circular layer in the ultrasound image. Specifically, when the calculated similarity meets the preset conditions, it is determined that the anatomical structure boundary contour line is identified.

[0085] It should be noted that, when calculating the similarity, the independent sample t test can be specifically used to calculate the significance of the difference between the pixel values ​​of the two detection contours to obtain the similarity. That is, the embodiment of the present application specifically uses the independent sample t test to calculate the significance P value of the difference between the pixel values ​​of the two detection contours, and uses the P value to represent the similarity. Among them, the smaller the P value, the greater the difference, that is, the lower the similarity. It can be understood that the independent sample t test is applicable to scenarios where the two groups of data are independent and the properties of the two groups of data are consistent. In this embodiment, the two detection contours are the pixel values ​​on the same ultrasound image, with the characteristics of consistent properties, and the two detection contours do not intersect and have the characteristics of independence. Therefore, in this scenario, it is better to use the independent sample t test to calculate the similarity. In addition, in addition to using the independent sample t test, other similarity calculation methods can also be adopted, but for the specific scenario of this application, the independent sample t test method is the best.

[0086] In which, the above-mentioned anatomical structure boundary contour line includes the first-layer anatomical structure boundary contour line from the inner layer to the outer layer and the non-first-layer anatomical structure boundary contour line; correspondingly, the identifying the anatomical structure boundary contour line of the upper digestive tract wall from the upper digestive tract ultrasound image based on the N+1th detection contour line includes: calculating the similarity between the N+1th detection contour line and the 1st detection contour line based on the pixel values ​​of the pixel points on the detection contour line; before identifying the first-layer anatomical structure boundary contour line, if the similarity calculated by the current detection contour line and the preset similarity threshold meet the first preset condition, then the current detection contour line is determined to be the first-layer anatomical structure contour line of the upper digestive tract wall; after identifying the first-layer anatomical structure boundary contour line, if the similarity calculated by the current detection contour line and the similarity corresponding to the previous identified anatomical structure boundary contour line of the previous layer meet the second preset condition, then the current detection contour line is determined to be the non-first-layer anatomical structure boundary contour line of the upper digestive tract wall.

[0087] It can be understood that the first-layer anatomical structure corresponds to the 1st layer (1st layer) in Figures 1 and 3, and the non-first-layer anatomical structure corresponds to the 2nd to 5th layers (i.e., 2nd layer-5th-layer) in Figures 1 and 3. In this embodiment, when locating the boundary contour of the first-layer anatomical structure and the boundary contour line of the non-first-layer anatomical structure, the similarity judgment conditions used are different. Specifically, this embodiment first calculates the significance P value of the difference in pixel values ​​between the N+1th detection contour line and the 1st detection contour line based on the pixel values ​​of the pixel points on the detection contour line using the independent sample t-test method, and uses the P value as the corresponding similarity.

[0088] When identifying the first-layer anatomical structure boundary contour line, if the similarity calculated between the current detection contour line and the preset similarity threshold satisfies the first preset condition, then the current detection contour line is determined to be the first-layer anatomical structure contour line of the upper digestive tract wall, wherein the first preset condition can specifically be that the similarity calculated for the current detection contour line is less than the preset similarity threshold. It can be understood that since the starting contour line is a black edge and the first-layer anatomical structure boundary (1st-layer) is a bright layer, the difference between the two should be large. The similarity between the current detection contour line and the first detection contour line is recorded as P-layer1, and assuming that the preset similarity threshold is 0.85, then if P-layer1<0.85, then the current detection contour line is determined to be the first-layer anatomical structure contour line of the upper digestive tract wall, that is, the current detection contour line is the inner boundary of the 1st-layer. That is, when identifying the first-layer anatomical structure boundary contour line, when the P value is less than a certain threshold, it is determined that the difference between the two sets of data (i.e., the pixel values ​​of the similarity on the starting contour line and the current detection contour line) is large enough, and it is determined that the first layer has been searched. The preset similarity threshold may be determined by a strategy designed by a technician, such as referring to the actual situation during the current detection process, or may be set based on an empirical value.

[0089] After identifying the first-layer anatomical structure boundary contour line, the non-first-layer anatomical structure boundary contour line is then identified. If the similarity calculated between the current detection contour line and the corresponding similarity of the previous identified anatomical structure boundary contour line of the upper layer satisfies the second preset condition, the current detection contour line is determined to be the non-first-layer anatomical structure boundary contour line of the upper digestive tract wall. It is understandable that when identifying the non-first-layer anatomical structure boundary contour line, it is not necessary to compare the similarity calculated for the current detection contour line with the preset similarity threshold, but rather to determine whether the similarity calculated for the current detection contour line and the corresponding similarity of the previous identified anatomical structure boundary contour line of the upper layer satisfies the second preset condition. If so, the current detection contour line is determined to be the non-first-layer anatomical structure boundary contour line of the upper digestive tract wall. For example, taking the positioning of the boundary contour line of the second layer anatomical structure as an example, the similarity between the current detection contour line and the first detection contour line is recorded as P-layer2. Therefore, it is necessary to compare P-layer2 with the similarity P-layer1 of the boundary contour line of the first layer (first layer) anatomical structure to determine whether the second preset condition is met; taking the positioning of the boundary contour line of the third layer anatomical structure as an example, the corresponding P-layer3 is compared with P-layer2 to determine whether the second preset condition is met, and so on.

[0090] It should be noted that, based on the hierarchical characteristic of the five-layer anatomical structure of the upper gastrointestinal tract subcutaneous image presenting "bright-dark-bright-dark-bright" from the inside to the outside, the corresponding second preset conditions are different when identifying the boundary contour lines of the anatomical structure of the even-numbered layers and the anatomical structure of the odd-numbered layers.

[0091] When identifying the boundary contours of even-numbered anatomical structures (i.e., layers 2 and 4), as previously mentioned, the starting contour is a dark layer, and layers 2 and 4 are also dark layers. Therefore, the echogenicity of the inner boundaries of layers 2 and 4 and the starting contour is similar, and the difference in pixel values ​​between them should be small, resulting in a larger calculated value for P-layer2 or P-layer4. On the other hand, since layers 1 and 3 are bright layers, the echogenicity of the inner boundaries of layers 1 and 3 and the starting contour is significantly different, and the difference in pixel values ​​between them should be large, resulting in a smaller calculated value for P-layer3 or P-layer5. Therefore, when identifying the boundary contours of even-numbered anatomical structures, the second preset condition can be specifically set to "the calculated similarity of the currently detected contour is greater than the similarity corresponding to the previously identified boundary contour of the previous anatomical structure," i.e., P-layer2 > P-layer1, and P-layer4 > P-layer3. In addition, on the basis of satisfying that the similarity calculated by the currently detected contour line is greater than the similarity corresponding to the previously identified anatomical structure boundary contour line of the previous level, it can also be additionally set that the difference must exceed a certain threshold.

[0092] When identifying the boundary contour lines of the odd-numbered layers of anatomical structures (i.e., the 3rd and 5th layers), since the echoes of the inner boundaries and the starting contour lines of the 2nd and 4th layers are similar, the corresponding P-layer2 or P-layer4 values ​​are larger, while the values ​​of P-layer3 or P-layer5 are smaller. Therefore, when identifying the boundary contour lines of the even-numbered layers of anatomical structures, the second preset condition can be specifically set to "the similarity calculated for the currently detected contour line is less than the similarity corresponding to the previously identified boundary contour line of the upper-level anatomical structure", that is, P-layer3<P-layer2, P-layer5<P-layer4. In addition, on the basis of satisfying that the similarity calculated for the currently detected contour line is less than the similarity corresponding to the previously identified boundary contour line of the upper-level anatomical structure, it can also be additionally set that the difference must exceed a certain threshold.

[0093] Step S24: outputting the positional relationship between the lesion image area and the boundary contour lines of the anatomical structure of each layer.

[0094] In this embodiment, the origin / end level of a lesion can be accurately located based on the positional relationship between the boundary contour lines of each layer of the anatomical structure and the lesion image area. It is understood that the area between two adjacent boundary contour lines of the anatomical structure is the level of the anatomical structure. For example, during the outward expansion positioning process, if the inner boundary (bright) of the first layer (bright layer) and the inner boundary (dark) of the second layer (dark layer) are found, the area between the two is the level of the first anatomical structure layer.

[0095] In the process of locating the lesion origin level, the above-mentioned output of the positional relationship between the lesion image area and the anatomical structure boundary contour lines of each layer includes: determining the first target coordinate point closest to the center point of the starting contour line from the boundary of the lesion image area; determining and outputting the lesion origin level based on the positional relationship between the first target coordinate point and the anatomical structure boundary contour lines of each layer. In this embodiment, after locating the anatomical structure boundary contour lines of each layer of the upper digestive tract wall, the lesion origin level can be accurately located based on the positional relationship between the anatomical structure boundary contour lines of each layer and the lesion image area. Specifically, it is first necessary to determine the first target coordinate point closest to the center point of the starting contour line from the boundary of the lesion image area, and then determine and output the lesion origin level based on the positional relationship between the first target coordinate point and the anatomical structure boundary contour lines of each layer. That is, the layer where the first target coordinate point is located is the lesion origin level, specifically, it is determined by which two anatomical structure boundary contour lines the first target coordinate point falls within.

[0096] During the process of locating the lesion end level, outputting the positional relationship between the lesion image region and the anatomical structure boundary contour lines of each layer includes: determining a second target coordinate point on the boundary of the lesion image region that is farthest from the center point of the starting contour line; and determining and outputting the lesion end level based on the positional relationship between the second target coordinate point and the anatomical structure boundary contour lines of each layer. In this embodiment, after locating the anatomical structure boundary contour lines of each layer of the upper digestive tract wall, the lesion end level can be accurately located based on the positional relationship between the anatomical structure boundary contour lines of each layer and the lesion image region. Specifically, it is necessary to first determine the second target coordinate point on the boundary of the lesion image region that is farthest from the center point of the target contour line. Then, based on the positional relationship between the second target coordinate point and the structure boundary contour lines of each layer, the lesion end level is determined and output. In other words, the layer where the second target coordinate point is located is the lesion end level, depending on which two anatomical structure boundary contour lines the second target coordinate point falls within. Locating the lesion end level is useful for confirming the size of the lesion and for surgical removal.

[0097] Furthermore, the above-mentioned outward expansion based on the position of the starting contour line to locate the positions of the anatomical structure boundary contour lines of each layer of the upper gastrointestinal wall from the upper gastrointestinal ultrasound image includes the step of stopping outward expansion to locate the anatomical structure boundary contour line of the next layer when the distance between the located anatomical structure boundary contour line and the center point of the starting contour line exceeds the distance between the second target coordinate point and the center point of the starting contour line. In other words, the outward expansion process can stop after searching only the outermost layer of the lesion area, which can save computing power. Specifically, when the distance between the located anatomical structure boundary contour line and the center point of the starting contour line exceeds the distance between the second target coordinate point and the center point of the starting contour line, the outward expansion step is stopped.

[0098] For more specific processing procedures of the above steps S21 and S22, reference may be made to the corresponding contents disclosed in the aforementioned embodiments, which will not be elaborated here.

[0099] It can be seen that, in the embodiment of the present application, when locating the boundary contour lines of the anatomical structures of each layer of the upper digestive tract wall, the boundary contour lines of the five layers of the anatomical structures of the upper digestive tract wall are located sequentially from the inside to the outside. Specifically, the boundary contour lines of the anatomical structures of each layer of the upper digestive tract wall can be located from the upper digestive tract ultrasound image by calculating the similarity between the N+1th detection contour line and the first detection contour line. When calculating the similarity, the independent sample t-test can be used to calculate the significance of the difference between the pixel values ​​of the pixel points on the two detection contour lines to obtain the similarity. When locating the boundary contour line of the first-layer anatomical structure, the similarity calculated by the current detection contour line needs to be less than the preset similarity threshold. When locating the boundary contour line of the non-first-layer anatomical structure, the similarity calculated by the current detection contour line and the similarity corresponding to the boundary contour line of the previous layer of anatomical structure identified last time need to meet the second preset condition. When identifying the boundary contour line of the even-numbered anatomical structure and the boundary contour line of the odd-numbered anatomical structure, the corresponding second preset condition is different. It is specifically designed based on the layered characteristics of the 5-layer anatomical structure of the upper gastrointestinal subcutaneous image, which presents "bright-dark-bright-dark-bright" from the inside to the outside. Finally, the coordinate point closest / farthest from the center point of the target contour line is determined from the boundary of the lesion image area, and the layer where the coordinate point is located is the origin / end layer of the lesion. Through the solution of the present application, the accuracy of the diagnosis of the origin layer and the end layer of the lesion subcutaneous lesion of the upper gastrointestinal tract is improved, while helping doctors improve the efficiency of inspection and diagnosis.

[0100] As shown in FIG5 , an embodiment of the present application discloses an upper digestive tract ultrasound image processing device, the device comprising:

[0101] The probe contour positioning module 11 is used to locate the position of the starting contour line corresponding to the ultrasound probe from the upper digestive tract ultrasound image;

[0102] a lesion position acquisition module 12, configured to acquire the position of the lesion image region contained in the upper digestive tract ultrasound image;

[0103] an anatomical structure positioning module 13, configured to expand outward based on the position of the starting contour line to locate the position of the boundary contour lines of each layer of the anatomical structure of the upper digestive tract wall from the upper digestive tract ultrasound image;

[0104] The information output module 14 is configured to output the positional relationship between the lesion image area and the boundary contour lines of the anatomical structure at each layer.

[0105] It can be seen that the present application locates the position of the starting contour line corresponding to the ultrasound probe from the upper gastrointestinal ultrasound image; obtains the position of the lesion image area contained in the upper gastrointestinal ultrasound image; based on the position of the starting contour line, expands outward to locate the position of the boundary contour lines of the anatomical structure of each layer of the upper gastrointestinal wall from the upper gastrointestinal ultrasound image; and outputs the positional relationship between the lesion image area and the boundary contour lines of each layer of the anatomical structure. It can be seen that the present application needs to locate the position of the starting contour line corresponding to the ultrasound probe from the upper gastrointestinal ultrasound image, and by expanding the starting contour line outward, it can locate the position of the boundary contour lines of each layer of the anatomical structure of the upper gastrointestinal wall from the upper gastrointestinal ultrasound image; finally, based on the position of the lesion image area contained in the upper gastrointestinal ultrasound image, it can output the positional relationship between the lesion image area and the boundary contour lines of each layer of the anatomical structure. In this way, the above scheme can automatically identify the position of the boundary contour lines of each layer of the anatomical structure of the upper gastrointestinal wall from the upper gastrointestinal ultrasound image, and further accurately locate the origin / end layer of the lesion based on the positional relationship between the boundary contour lines of each layer of the anatomical structure and the lesion image area, which helps to improve the efficiency of doctor's examination and diagnosis. In some specific embodiments, the probe contour positioning module 11 is specifically configured to locate a target contour line corresponding to the ultrasound probe from the upper digestive tract ultrasound image using a preset edge detection algorithm.

[0106] In some specific embodiments, the probe contour positioning module 11 can be specifically configured to locate the position of a starting contour line corresponding to the ultrasound probe from the upper gastrointestinal tract ultrasound image using a preset edge detection algorithm.

[0107] In some specific embodiments, the anatomical structure positioning module 13 can be specifically used to use the starting contour line as the first detection contour line, with a preset pixel size as the moving step size, to move the pixel points on the Nth detection contour line in a direction away from the center point of the starting contour line, and to generate a corresponding smooth curve based on the coordinates of each moved pixel point to obtain the N+1th detection contour line, and to identify the anatomical structure boundary contour line of the upper gastrointestinal tract wall from the upper gastrointestinal ultrasound image based on the N+1th detection contour line, to determine the level of the anatomical structure boundary contour line according to the order in which the anatomical structure boundary contour line is identified, and to record the position of the anatomical structure boundary contour line at this level; wherein N≥1 and is an integer.

[0108] In some specific embodiments, the anatomical structure positioning module 13 may specifically include:

[0109] a first similarity calculation unit, configured to calculate the similarity between the (N+1)th detected contour line and the first detected contour line, or the similarity between the (N+1)th detected contour line and the (N)th detected contour line, based on the pixel values ​​of the pixels on the detected contour line;

[0110] The result determination unit is configured to determine that an anatomical structure boundary contour line is identified when the similarity satisfies a preset condition.

[0111] In some specific embodiments, the anatomical structure boundary contour line includes a first-layer anatomical structure boundary contour line and a non-first-layer anatomical structure boundary contour line from the inner layer to the outer layer;

[0112] Correspondingly, the anatomical structure positioning module 13 further includes:

[0113] A second similarity calculation unit is used to calculate the similarity between the (N+1)th detected contour line and the first detected contour line according to the pixel values ​​of the pixels on the detected contour line;

[0114] a first-layer anatomical structure positioning unit, configured to determine, before identifying a first-layer anatomical structure boundary contour line, that the currently detected contour line is the first-layer anatomical structure contour line of the upper digestive tract wall if a similarity calculated between the currently detected contour line and a preset similarity threshold satisfies a first preset condition;

[0115] The non-first-layer anatomical structure positioning unit is used to determine that the current detected contour line is the non-first-layer anatomical structure boundary contour line of the upper gastrointestinal tract wall after the first-layer anatomical structure boundary contour line is identified, if the similarity calculated between the current detected contour line and the corresponding similarity of the previous identified anatomical structure boundary contour line meets the second preset condition.

[0116] In some specific embodiments, the apparatus is further configured to calculate the significance of the difference between the pixel values ​​of the two pixel points on the detection contour lines using an independent sample t-test to obtain the similarity.

[0117] In some specific embodiments, the information output module 14 may specifically include:

[0118] A first coordinate point determining unit is configured to determine a first target coordinate point closest to the center point of the starting contour line from the boundary of the lesion image area;

[0119] The lesion origin level positioning unit is used to determine and output the lesion origin level based on the positional relationship between the first target coordinate point and the boundary contour lines of the anatomical structure of each layer.

[0120] In some specific embodiments, the information output module 14 may specifically include:

[0121] A second coordinate point determining unit, configured to determine a second target coordinate point on the boundary of the lesion image area that is farthest from the center point of the starting contour line;

[0122] The lesion end level positioning unit is used to determine and output the lesion end level based on the positional relationship between the second target coordinate point and the boundary contour line of the anatomical structure of each layer.

[0123] In some specific embodiments, the anatomical structure positioning module 13 further includes:

[0124] The expansion stopping unit is used to stop the step of expanding outward to locate the anatomical structure boundary contour line of the next level when the distance between the located anatomical structure boundary contour line and the center point of the starting contour line exceeds the distance between the second target coordinate point and the center point of the starting contour line.

[0125] In some specific embodiments, the information output module 14 is specifically configured to output the markings of the lesion image region and the boundary contour lines of the anatomical structure of each layer to a display device.

[0126] In some specific embodiments, the lesion location acquisition module 12 is specifically configured to acquire the location of the lesion image area contained in the upper digestive tract ultrasound image from information input by a user.

[0127] In some specific embodiments, the lesion location acquisition module 12 is specifically configured to identify the location of the lesion image area from the upper digestive tract ultrasound image using a preset algorithm.

[0128] Figure 6 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Specifically, the device may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps of the upper gastrointestinal tract ultrasound image processing method performed by the electronic device as disclosed in any of the aforementioned embodiments.

[0129] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device. The communication protocol it follows is any communication protocol that can be applied to the technical solution of this application and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world. Its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0130] Among them, the processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 21 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 21 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0131] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or CD, etc. The resources stored thereon include an operating system 221, a computer program 222 and data 223, etc. The storage method can be temporary storage or permanent storage.

[0132] The operating system 221 is used to manage and control the hardware devices and computer program 222 on the electronic device 20, so as to enable the processor 21 to calculate and process the massive amount of data 223 in the memory 22. The operating system 221 can be Windows, Unix, Linux, etc. In addition to including computer programs capable of performing the upper gastrointestinal ultrasound image processing method performed by the electronic device 20 as disclosed in any of the aforementioned embodiments, the computer program 222 can further include computer programs capable of performing other specific tasks. The data 223 can include not only data received by the electronic device and transmitted from external devices, but also data collected by its own input and output interface 25.

[0133] Furthermore, an embodiment of the present application also discloses a computer-readable storage medium, in which a computer program is stored. When the computer program is loaded and executed by a processor, the steps of the upper gastrointestinal ultrasound image processing method disclosed in any of the aforementioned embodiments are implemented.

[0134] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from the other embodiments. Reference can be made to the descriptions of the identical or similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and the relevant parts can be referred to the descriptions of the methods.

[0135] Those skilled in the art may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the composition and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0136] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, a hard disk, a removable disk, a compact disc read-only memory (CD-ROM), or any other form of storage medium known in the art.

[0137] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0138] The above is a detailed introduction to the upper gastrointestinal ultrasound image processing method, device, equipment and storage medium provided by the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for general technical personnel in this field, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. An upper gastrointestinal ultrasound image processing method, characterized in that, Including: Locating the position of the starting contour line corresponding to the ultrasonic probe from the upper gastrointestinal ultrasonic image; Obtaining the position of the lesion image area included in the upper gastrointestinal ultrasonic image; Based on the position of the starting contour line, expanding outward, and locating the position of the boundary contour lines of each layer of anatomical structures of the upper gastrointestinal tract wall from the upper gastrointestinal ultrasonic image; Outputting the positional relationship between the lesion image area and the boundary contour lines of each layer of the anatomical structures.

2. The upper gastrointestinal ultrasound image processing method according to claim 1, wherein, The locating the position of the starting contour line corresponding to the ultrasonic probe from the upper gastrointestinal ultrasonic image includes: Locating the position of the starting contour line corresponding to the ultrasonic probe from the upper gastrointestinal ultrasonic image by using a preset edge detection algorithm.

3. The upper gastrointestinal ultrasound image processing method according to claim 1, characterized in that, The based on the position of the starting contour line, expanding outward, and locating the position of the boundary contour lines of each layer of anatomical structures of the upper gastrointestinal tract wall from the upper gastrointestinal ultrasonic image includes: Taking the starting contour line as the first detection contour line, using a preset pixel size as the moving step, moving the pixel points on the Nth detection contour line along the direction away from the center point of the starting contour line, and generating a corresponding smooth curve based on the coordinates of each moved pixel point to obtain the (N + 1)th detection contour line, and identifying the boundary contour line of the anatomical structure of the upper gastrointestinal tract wall from the upper gastrointestinal ultrasonic image according to the (N + 1)th detection contour line, determining its layer where it is located according to the order of identifying the boundary contour line of the anatomical structure, and recording the position of the boundary contour line of the anatomical structure of this layer; where N≥1 and is an integer.

4. The upper gastrointestinal ultrasound image processing method according to claim 3, characterized in that The identifying the boundary contour line of the anatomical structure of the upper gastrointestinal tract wall from the upper gastrointestinal ultrasonic image according to the (N + 1)th detection contour line includes: Calculating the similarity between the (N + 1)th detection contour line and the first detection contour line according to the pixel values of the pixel points on the detection contour line, or calculating the similarity between the (N + 1)th detection contour line and the Nth detection contour line; When the similarity meets the preset condition, it is determined that the boundary contour line of the anatomical structure is identified.

5. The upper gastrointestinal ultrasound image processing method according to claim 4, characterized in that, The boundary contour line of the anatomical structure includes the first-layer boundary contour line of the anatomical structure from the inner layer to the outer layer and the non-first-layer boundary contour line of the anatomical structure; Correspondingly, the identifying the boundary contour line of the anatomical structure of the upper gastrointestinal tract wall from the upper gastrointestinal ultrasonic image according to the (N + 1)th detection contour line includes: Calculating the similarity between the (N + 1)th detection contour line and the first detection contour line according to the pixel values of the pixel points on the detection contour line; Before the first-layer boundary contour line of the anatomical structure is identified, if the similarity calculated from the current detection contour line meets the first preset condition with the preset similarity threshold, it is determined that the current detection contour line is the first-layer anatomical structure contour line of the upper gastrointestinal tract wall; After the first-layer boundary contour line of the anatomical structure is identified, if the similarity calculated from the current detection contour line meets the second preset condition with the similarity corresponding to the previously identified upper-layer boundary contour line of the anatomical structure, it is determined that the current detection contour line is the non-first-layer boundary contour line of the anatomical structure of the upper gastrointestinal tract wall.

6. The upper gastrointestinal ultrasound image processing method according to claim 4 or 5, characterized in that Calculating the significance of the difference between the pixel values of the pixel points on the two detection contour lines by using an independent samples t-test to obtain the similarity.

7. The upper gastrointestinal ultrasound image processing method according to claim 1, characterized in that Outputting the positional relationship between the diseased image region and the boundary contour lines of each layer of the anatomical structure, including: Determining a first target coordinate point closest to the center point of the starting contour line from the boundary of the diseased image region; Determining and outputting the origin level of the lesion based on the positional relationship between the first target coordinate point and the boundary contour lines of each layer of the anatomical structure.

8. The upper gastrointestinal ultrasound image processing method according to claim 1, characterized in that, Outputting the positional relationship between the diseased image region and the boundary contour lines of each layer of the anatomical structure, including: Determining a second target coordinate point farthest from the center point of the starting contour line from the boundary of the diseased image region; Determining and outputting the end level of the lesion based on the positional relationship between the second target coordinate point and the boundary contour lines of each layer of the anatomical structure.

9. The upper gastrointestinal ultrasound image processing method according to claim 8, wherein, Positioning the boundary contour lines of each layer of the upper gastrointestinal tract wall from the upper gastrointestinal ultrasound image by expanding outward based on the position of the starting contour line, including: When the distance between the located boundary contour line of the anatomical structure and the center point of the starting contour line exceeds the distance between the second target coordinate point and the center point of the starting contour line, stopping the step of expanding outward to locate the boundary contour line of the next layer of the anatomical structure.

10. The upper gastrointestinal ultrasound image processing method according to claim 1, wherein Outputting the positional relationship between the diseased image region and the boundary contour lines of each layer of the anatomical structure, including: Outputting the markings of the diseased image region and the boundary contour lines of each layer of the anatomical structure to a display device.

11. The upper gastrointestinal ultrasound image processing method according to claim 1, characterized in that Obtaining the position of the diseased image region included in the upper gastrointestinal ultrasound image, including: Obtaining the position of the diseased image region included in the upper gastrointestinal ultrasound image from the information input by the user; or, Identifying the position of the diseased image region from the upper gastrointestinal ultrasound image through a preset algorithm.

12. An upper gastrointestinal ultrasound image processing device, characterized in that, Including: A probe contour positioning module for positioning the position of the starting contour line corresponding to the ultrasound probe from the upper gastrointestinal ultrasound image; A diseased position obtaining module for obtaining the position of the diseased image region included in the upper gastrointestinal ultrasound image; An anatomical structure positioning module for positioning the boundary contour lines of each layer of the upper gastrointestinal tract wall from the upper gastrointestinal ultrasound image by expanding outward based on the position of the starting contour line; An information output module for outputting the positional relationship between the diseased image region and the boundary contour lines of each layer of the anatomical structure.

13. An electronic device, characterized in that, Including: A memory for storing a computer program; A processor for executing the computer program to implement the steps of the upper gastrointestinal ultrasound image processing method according to any one of claims 1 to 11.

14. A computer-readable storage medium, characterized in that, For storing a computer program; wherein, when the computer program is executed by the processor, the steps of the upper gastrointestinal ultrasound image processing method according to any one of claims 1 to 11 are implemented.

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