A hierarchical position determination method

Abstract

This application relates to a method for determining the location of different layers in an ultrasound image. The method includes: acquiring an ultrasound image; determining the brightness value of each pixel in the ultrasound image; determining a pixel circumference centered at a center point in the ultrasound image, resulting in multiple pixel circumferences; and determining the location of different layers in the ultrasound image based on the brightness value of each pixel and the pixel circumferences. This method can accurately determine the location of different layers in an ultrasound image.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and in particular to a method for determining layered positions. Background Technology

[0002] With the rapid development of electronic and medical technologies, enteroendoscopy for acquiring ultrasound images of the small intestine has emerged. The normal intestinal wall of the small intestine is divided into five layers, from the inside out: mucosa, muscularis mucosae, submucosa, muscularis propria, and serosa. The signal intensity of the ultrasound echoes in these five layers exhibits high, low, high, low, and high characteristics from the inside out, respectively.

[0003] When lesions are present in the small intestine, the layers of the small intestine become unclear; that is, the wall thickness corresponding to the lesion layer increases. Based on this, doctors can make a diagnosis by observing the wall thickness of different layers of the small intestine. However, currently, doctors still need to manually mark the different layers of the small intestine, and manual stratification is usually based on visual inspection. Obviously, manual stratification will severely reduce diagnostic efficiency and accuracy. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer device, computer-readable storage medium, and computer program product for determining the layer position of different layers in an ultrasound image, which can accurately determine the position of different layers in the ultrasound image, in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides a method for determining the layer position, including:

[0006] Acquire ultrasound images;

[0007] Determine the brightness value of each pixel in the ultrasound image;

[0008] Determine the pixel circumference centered at the center point in the ultrasound image to obtain multiple pixel circumferences;

[0009] The location of different layers in the ultrasound image is determined based on the brightness value of each pixel and the circumference of each pixel.

[0010] Secondly, this application also provides a layer position determination device, comprising:

[0011] The acquisition module is used to acquire ultrasound images;

[0012] The first determining module is used to determine the brightness value of each pixel in the ultrasound image;

[0013] The second determining module is used to determine the pixel circumference in the ultrasound image with the center point as the center, and obtain multiple pixel circumferences;

[0014] The third determining module is used to determine the position of different layers in the ultrasound image based on the brightness value of each pixel and the circumference of each pixel.

[0015] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement some or all of the steps described in any method of the first aspect of the embodiments of this application.

[0016] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements some or all of the steps described in any method of the first aspect of the embodiments of this application.

[0017] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements some or all of the steps described in any method of the first aspect of the embodiments of this application.

[0018] The aforementioned layer position determination method, apparatus, computer equipment, computer-readable storage medium, and computer program product acquire an ultrasound image; determine the brightness value of each pixel in the ultrasound image; determine the pixel circumference centered at a center point in the ultrasound image, obtaining multiple pixel circumferences; and determine the position of different layers in the ultrasound image based on the brightness value of each pixel and the pixel circumferences. Using the layer position determination method provided in this application, based on the brightness value of each pixel and the pixel circumferences, the position of different layers in the ultrasound image can be accurately determined, avoiding the inaccurate layer position determination that may occur when manually determining different layer positions. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is an application environment diagram of the layer location determination method in one embodiment;

[0021] Figure 2 This is a flowchart illustrating a method for determining layer positions in one embodiment;

[0022] Figure 3 This is a schematic diagram of the structure of an ultrasound image in one embodiment;

[0023] Figure 4 This is a structural block diagram of a layer position determination device in one embodiment;

[0024] Figure 5 This is an internal structural diagram of a computer device in one embodiment;

[0025] Figure 6 This is a diagram of the internal structure of a computer device in another embodiment. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0027] The layer location determination method provided in this application embodiment can be applied to, for example, Figure 1 In the application environment shown, terminal 102 is connected to ultrasound probe 104. Ultrasonic probe 104 includes a transducer and is covered by a flexible outer sheath. The transducer generates ultrasound signals, performs a 360° mechanical scan to emit ultrasound signals into the surrounding environment, and receives reflected signals from human tissue. The terminal can generate an ultrasound image 106 with a 360° coverage area based on the reflected signals received by the transducer. The outer sheath isolates the transducer from human tissue to prevent direct contact between the transducer and the tissue. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, and tablets.

[0028] In one exemplary embodiment, such as Figure 2 As shown, a method for determining the layer location is provided, which can be applied to... Figure 1 Taking the terminal in the example, the explanation includes the following steps 202 to 208. Wherein:

[0029] Step 202: Acquire ultrasound images.

[0030] Among them, ultrasound image refers to a two-dimensional grayscale image obtained by the terminal through ultrasound imaging technology, that is, a two-dimensional grayscale image obtained by the terminal after performing image generation processing on the transmitted signal received by the transducer in the ultrasound probe.

[0031] Optionally, the ultrasound image is a small bowel ultrasound image. A small bowel ultrasound image refers to an ultrasound image used to show the layered structure of the small bowel wall and the condition of the surrounding tissues.

[0032] Optionally, the ultrasound image can be a square image with the same length and width. Optionally, the resolution of the ultrasound image can be 1024×1024 pixels.

[0033] Optionally, the resolution of the ultrasound image and the resolution of the terminal display screen can be different. For example, if the resolution of the ultrasound image is 1024×1024 pixels, the resolution of the terminal display screen can be 1920×1080 pixels.

[0034] Because the ultrasound probe is wrapped with a soft outer sheath, the distance between the transducer in the ultrasound probe and the outer sheath is the blind zone distance of the transducer. The reflected signal within the blind zone distance is not obtained by the reflection of human tissue. Therefore, image content in the ultrasound image whose distance from the center point of the ultrasound image is less than the blind zone distance is invalid image content that cannot be used as a diagnostic reference.

[0035] Since ultrasound images are obtained by a 360° mechanical scan of the transducer, and the transducer has a preset maximum scanning depth, the effective image content in an ultrasound image is a concentric ring composed of multiple pixel circles with the center point as the center, the minimum radius length corresponding to the blind zone distance, and the maximum radius length corresponding to the maximum scanning depth. The radial width corresponding to the superposition of all the rings is the difference between the maximum scanning depth and the blind zone distance. In an ultrasound image, the image content whose distance from the center point is greater than the maximum scanning depth, and the image content whose distance from the center point is less than the blind zone distance, are all invalid image content.

[0036] In the case of a square ultrasound image, it is easy to understand from mathematical and geometric relationships that the maximum scanning depth corresponds to half the length (or half the width) of the ultrasound image.

[0037] It should be noted that the physical length of the corresponding human tissue in an ultrasound image is determined by the scanning depth of the transducer at the corresponding location; the scanning depth refers to the physical detection distance of the transducer. However, in the terminal, ultrasound images are represented using pixels as the smallest unit. Therefore, there is a conversion relationship between pixels and scanning depth in an ultrasound image.

[0038] The conversion relationship between pixels and scan depth can be used to convert the scan depth of an ultrasound image into the corresponding number of pixels, or to convert the number of pixels along a line in an ultrasound image into the corresponding scan depth. Based on this, the conversion relationship between pixels and scan depth can be used to determine how many pixels represent a 1mm scan depth in an ultrasound image; similarly, the scan depth corresponding to a certain number of pixels in an ultrasound image can also be determined.

[0039] This can be understood as the conversion relationship between pixels and scanning depth, which can represent both the scanning depth corresponding to 1 pixel in an ultrasound image and the number of pixels corresponding to 1 mm of scanning depth.

[0040] Optionally, the conversion relationship between pixels and scanning depth can be determined by the maximum scanning depth of the ultrasound image and the number of pixels corresponding to half the length (or half the width) of the ultrasound image.

[0041] For example, the resolution of an ultrasound image is represented as P×P pixels, where P is an integer greater than 1. The blind zone distance of the transducer is represented as R0, and the maximum scanning depth of the transducer is represented as R1. Based on the characteristics of ultrasound images and mathematical geometric relationships, it is easy to understand that R1 = P / 2. The number of pixels corresponding to a scanning depth of 1 mm is represented as Ratio1, and the scanning depth length corresponding to 1 pixel is represented as Ratio2. Then, Ratio1 = (P / 2) / R1 = P / 2R1. It is easy to understand that Ratio1 and Ratio2 are reciprocals of each other, that is, their product is 1. Therefore, Ratio2 = 1 / Ratio1 = 2R1 / P.

[0042] As a further example, assuming P=1024, that is, the resolution of the ultrasound image is 1024×1024 pixels, and the maximum scanning depth of the transducer is R1=15mm, it is easy to understand that the maximum radius length of the ultrasound image with the maximum distance from the center point is 512 pixels. Based on this, in the conversion relationship between pixels and scanning depth, the number of pixels corresponding to 1mm scanning depth is represented as Ratio1=(P / 2) / R1=512 / 15≈34. Conversely, the scanning depth length corresponding to 1 pixel is Ratio2=1 / 34≈0.03mm.

[0043] Because the intensity of reflected ultrasound signals varies after being reflected by different tissues, in the case of a small bowel ultrasound image, the resulting ultrasound image, based on the five-layered structure of the human small bowel (mucosa, muscularis mucosae, submucosa, muscularis propria, and serosa), includes five layers. The grayscale values ​​of these five layers, from the inside out, will respectively exhibit high, low, high, low, and high characteristics. Since grayscale values ​​can be used to represent brightness, these five layers will form alternating bright and dark stripes and be clearly displayed in the small bowel ultrasound image.

[0044] Based on the characteristics of ultrasound images, it is easy to understand that the five layers of structure—mucosa, muscularis mucosae, submucosa, muscularis propria, and serosa—are respectively presented as a bright ring, a dark ring, a bright ring, a dark ring, and a bright ring in ultrasound images, with the five rings being concentric rings centered on the center point of the ultrasound image.

[0045] For example, such as Figure 3 As shown, in the case of a small bowel ultrasound image, the central region of the small bowel ultrasound image is the blind zone region 302 corresponding to the distance of the transducer's blind zone. The small bowel ultrasound image consists of five layers from the inside out: the mucosa layer 304, which appears as a bright ring; the muscularis mucosae layer 306, which appears as a dark ring; the submucosa layer 308, which appears as a bright ring; the muscularis propria layer 310, which appears as a dark ring; and the serosa layer 312, which appears as a bright ring.

[0046] Step 204: Determine the brightness value of each pixel in the ultrasound image.

[0047] A pixel is the smallest unit in an ultrasound image, and each pixel has a corresponding brightness value.

[0048] The brightness value of a pixel refers to the lightness or darkness of each pixel in an ultrasound image. The brightness value of a pixel can be represented by its grayscale value. That is, when determining the brightness value of each pixel in an ultrasound image, the terminal can do so using the grayscale histogram of the ultrasound image; the grayscale value and the brightness value are positively correlated.

[0049] Step 206: Determine the pixel circumference in the ultrasound image with the center point as the center, and obtain multiple pixel circumferences.

[0050] The pixel circumference refers to the set of multiple pixels distributed along the same circular path, and the distance from the multiple pixels distributed along the same circular path to the center point (i.e., the center of the circle) of the ultrasound image is the same.

[0051] Multiple pixel circles can be understood as multiple concentric pixel circles that share the same center point as the center point of the ultrasound image.

[0052] The center point of an ultrasound image is its geometric center. To put it simply, multiple pixels on the same pixel circumference are equidistant from the center point (i.e., the center of the circle) of the ultrasound image.

[0053] The number of pixels corresponding to the radius length of each pixel circle in a multi-pixel circle is determined by the corresponding scan depth and the conversion relationship between pixels and scan depth. Specifically, it is determined by the corresponding scan depth and the number of pixels Ratio1 corresponding to 1mm scan depth.

[0054] The number of multiple pixel circles is determined by the largest pixel circle with the maximum distance from the center point and the smallest pixel circle with the minimum distance from the center point. The radius length corresponding to the largest pixel circle corresponds to the maximum scan depth R1, and the radius length corresponding to the smallest pixel circle corresponds to the blind zone distance R0. Therefore, specifically, the number of multiple pixel circles is determined by the number of pixels corresponding to the radius difference between the largest and smallest pixel circles, that is, the number of multiple pixel circles = (R1-R0)×Ratio1.

[0055] As can be easily understood from mathematical and geometric relationships, the number of pixels included in each pixel circle is determined by the radius of the corresponding pixel circle and the conversion relationship between pixels and scanning depth. Specifically, the number of pixels included in each pixel circle is determined by the circumference of the corresponding pixel circle and the number of pixels Ratio1 corresponding to a scanning depth of 1mm.

[0056] For example, assuming the transducer's maximum scanning depth R1 = 15 mm, the blind zone distance R0 = 2 mm, and the number of pixels corresponding to a 1 mm scanning depth Ratio1 = 512 / 15 ≈ 34 pixels, then the radius length corresponding to R1 = R1 × Ratio1 = 512 pixels, representing the distance between the largest pixel circle and the center point in the ultrasound image is 512 pixels. Similarly, the radius length corresponding to R0 = R0 × Ratio1 ≈ 68 pixels, representing the distance between the smallest pixel circle and the center point in the ultrasound image is 68 pixels. The number of multiple pixel circles = (R1 - R0) × Ratio1 = (15 - 2) × 34 = 442. The number of pixels included in the smallest pixel circle = 2π × R0 × Ratio1 = 2π × 68 × 34 ≈ 14520 pixels, and the number of pixels included in the largest pixel circle = 2π × R1 × Ratio1 = 2π × 512 × 34 ≈ 109322 pixels.

[0057] Step 208: Determine the position of different layers in the ultrasound image based on the brightness value of each pixel and the circumference of each pixel.

[0058] Since the brightness value of each pixel can be used to determine the brightness value distribution of each pixel's circumference, the location of different layers in the ultrasound image can be determined based on the characteristics of human tissue and the brightness value distribution of each pixel's circumference.

[0059] It should be noted that the layer position determination method provided in this embodiment is applied to the terminal. Therefore, the radius length of the pixel circumference in this embodiment is relative to the terminal. That is, the smallest unit of the radius length of the pixel circumference is the pixel point. The same applies below, so it will not be repeated.

[0060] In the above-described method for determining the layer position, an ultrasound image is acquired; the brightness value of each pixel in the ultrasound image is determined; a pixel circumference centered at the center point in the ultrasound image is determined, resulting in multiple pixel circumferences; and the positions of different layers in the ultrasound image are determined based on the brightness value of each pixel and the pixel circumferences. Using the layer position determination method provided in this application, based on the brightness value of each pixel and the pixel circumferences, the positions of different layers in the ultrasound image can be accurately determined, avoiding the inaccurate layer positions that may result from manually determining different layer positions.

[0061] In an exemplary embodiment, determining the position of different layers in an ultrasound image based on the brightness value of each pixel and the circumference of each pixel includes:

[0062] Based on the number of pixels around each pixel circle and the brightness value of each pixel, the average brightness value of each pixel circle is determined, resulting in multiple first average brightness values.

[0063] Each pixel is grouped into multiple first pixel groups by circumference. The average brightness value of each first pixel group is determined, and multiple second average brightness values ​​are obtained.

[0064] The location of different layers in the ultrasound image is determined based on multiple first average brightness values ​​and multiple second average brightness values.

[0065] The first average brightness value refers to the average brightness value of all pixels in the corresponding pixel circle.

[0066] Each first pixel group contains the same number of pixels, at least one pixel in each first pixel group is arranged continuously, and there are no overlapping pixels between the first pixel groups.

[0067] Optionally, each first pixel group may include 3 pixels.

[0068] The second average brightness value refers to the average brightness value of all pixels included in the first pixel group within the corresponding pixel circle. In other words, the average brightness value of a first pixel group is determined by the average brightness value of all pixels it includes.

[0069] For example, suppose a pixel circumference includes 99 pixels (pixel 1, pixel 2, pixel 3, ..., pixel 97, pixel 98, pixel 99), and a first pixel group includes 3 pixels. Then, grouping the pixel circumference into 33 first pixel groups (first pixel group 1, ..., first pixel group 33), where first pixel group 1 includes pixel 1, pixel 2, and pixel 3, ..., first pixel group 33 includes pixel 97, pixel 98, and pixel 99. Thus, the first flat surface of the pixel circumference... The average brightness value is the average of the brightness values ​​of 99 pixels; the circumference of the pixel has 33 second average brightness values, which are the average of the brightness values ​​of all pixels included in the 33 first pixel groups. Among them, the second average brightness value of the first pixel group 1 is the average of the brightness values ​​of pixel 1, pixel 2 and pixel 3, ..., and the second average brightness value of the first pixel group 33 is the average of the brightness values ​​of pixel 97, pixel 98 and pixel 99.

[0070] It is easy to understand that since a pixel circumference can be grouped into multiple first pixel groups, there is only one first average brightness value corresponding to the same pixel circumference, but there will be multiple second average brightness values. Based on this, in an ultrasound image, the number of multiple first average brightness values ​​determined is less than the number of multiple second average brightness values ​​determined.

[0071] In this embodiment, since the positions of different layers in the ultrasound image are determined based on the average brightness value of each pixel circumference (first average brightness value) and the average brightness value of each first pixel group (second average brightness value), the inaccurate layering position caused by layering solely based on the average brightness value of each pixel circumference can be avoided. By combining the coarse segmentation element of the average brightness value of each pixel circumference and the fine segmentation element of the average brightness value of each first pixel group, the accuracy of determining the positions of different layers in the ultrasound image can be significantly improved.

[0072] In an exemplary embodiment, determining the location of different layers in an ultrasound image based on multiple first average brightness values ​​and multiple second average brightness values ​​includes:

[0073] Based on the first average brightness value of two adjacent pixel circumferences, the brightness change rate between the two adjacent pixel circumferences is determined, and the first brightness change rate is obtained.

[0074] When the first brightness change rate is greater than or equal to the first preset change rate, the position of different layers in the ultrasound image is determined based on the second average brightness value of each first pixel group in two adjacent pixel circles.

[0075] The first brightness change rate can characterize the degree of brightness value change from one pixel circle to another adjacent pixel circle.

[0076] Optionally, the first brightness change rate can be the relative change rate between the brightness values ​​of two adjacent pixel circles. In this case, among two adjacent pixel circles, the first brightness change rate is the ratio between the absolute value of the brightness difference between the brightness value of the pixel circle with the larger radius and the brightness value of the pixel circle with the smaller radius, and the brightness value of the pixel circle with the smaller radius. It is easy to understand that the pixel circle with the larger radius is located on the side of the pixel circle with the smaller radius that is furthest from the center point.

[0077] For example, there are two adjacent pixel circles, Circle1 and Circle2, where the radius of circle1 is greater than that of circle2. The first average brightness value of circle1 is denoted as AvgCircle1, and the first average brightness value of circle2 is denoted as AvgCircle2. Then, the first brightness change rate between circle1 and circle2 is (|AvgCircle1 - AvgCircle2|) / AvgCircle2.

[0078] Optionally, the first preset rate of change can be 45%, 50%, 55%, or other rates of change.

[0079] In this embodiment, when the first brightness change rate is greater than or equal to the first preset change rate, it indicates that the brightness value between two adjacent pixel circumferences has changed significantly, and there is a possibility of layering. Therefore, based on the second average brightness value of each first pixel group in two adjacent pixel circumferences, the position of different layers in the ultrasound image is further determined. Thus, by avoiding the possibility of misjudgment that may be caused by a single first brightness change rate, the accuracy of the determination result of the position of different layers in the ultrasound image can be significantly improved.

[0080] In an exemplary embodiment, determining the position of different layers in an ultrasound image based on the second average brightness value of each first pixel group in two adjacent pixel circumferences includes:

[0081] Determine the growth rate of the number of the first pixel group corresponding to each of two adjacent pixel circles.

[0082] Based on the growth rate, some first pixel groups are removed from the multiple first pixel groups corresponding to the first pixel circle to obtain M first pixel groups; M is the number of first pixel groups contained in the second pixel circle, the first pixel circle is adjacent to the second pixel circle, and the radius of the first pixel circle is greater than the radius of the second pixel circle, and M is an integer greater than 1.

[0083] Based on the second average brightness value of each first pixel group in the M first pixel groups of the first pixel circle, the second average brightness value of each first pixel group in the second pixel circle, and the correspondence between each first pixel group in the M first pixel groups of the first pixel circle and each first pixel group in the second pixel circle, the brightness change rate corresponding to each of the M first pixel groups is determined, and the M second brightness change rates are obtained.

[0084] Based on M second brightness change rates, the positions of different layers in the ultrasound image are determined.

[0085] The growth rate of the number of first pixel groups corresponding to each of two adjacent pixel circumferences refers to the relative growth rate between the number of first pixel groups corresponding to one pixel circumference and the number of first pixel groups corresponding to the other pixel circumference in an ultrasound image.

[0086] The growth rate of the number of the first pixel group corresponding to each of two adjacent pixel circles is obtained by subtracting 1 from the ratio between the pixel circle with the larger radius and the pixel circle with the smaller radius. That is, the growth rate of the number of the first pixel group corresponding to two adjacent pixel circles is greater than 0.

[0087] The first pixel circle and the second pixel circle are adjacent, meaning that the difference in length between the radius of the first pixel circle and the radius of the second pixel circle is 1 pixel.

[0088] The radius of the first pixel circle is greater than the radius of the second pixel circle, meaning that the first pixel circle is located on the side of the second pixel circle away from the center point.

[0089] M represents the number of first pixel groups contained in the second pixel circle. Therefore, there is a one-to-one correspondence between the M first pixel groups in the first pixel circle and each first pixel group in the second pixel circle. Based on this, the correspondence between each first pixel group in the M first pixel groups of the first pixel circle and each first pixel group in the second pixel circle can refer to the correspondence between a first pixel group in the M first pixel groups of the first pixel circle that has the same sequence number, ordered from the same angle and direction, and a first pixel group in the second pixel circle. Through this one-to-one correspondence, the structural features of two adjacent pixel circles can be accurately analyzed and compared.

[0090] The second brightness change rate refers to the rate of change in brightness between the second average brightness value of each of the M first pixel groups in the first pixel circle and the second average brightness value of the corresponding first pixel group in the second pixel circle. The second brightness change rate can characterize the degree of change in the second average brightness value between the first pixel group of one pixel circle and the corresponding first pixel group of another adjacent pixel circle.

[0091] Optionally, the second brightness change rate can be the relative change rate between the second average brightness values ​​of two corresponding first pixel groups in two adjacent pixel circles. In this case, within two adjacent pixel circles, the second brightness change rate is the ratio between the absolute value of the brightness difference between the second average brightness value of the first pixel group in the pixel circle with the larger radius and the second average brightness value of the corresponding first pixel group in the pixel circle with the smaller radius, and the second average brightness value of the corresponding first pixel group in the pixel circle with the smaller radius.

[0092] For example, the radius of pixel circle 2 is smaller than the radius of pixel circle 1. The second average brightness value of a certain first pixel group in pixel circle 1 is represented as Group1, and the second average brightness value of a corresponding first pixel group in pixel circle 2 is represented as Group2. Then the first brightness change rate between pixel circle 1 and pixel circle 2 is (|Group1-Group2|) / Group2.

[0093] In an exemplary embodiment, the above-described method of removing a portion of the first pixel group from the first pixel group corresponding to the circumference of the first pixel based on the growth rate to obtain M first pixel groups includes:

[0094] Determine the reciprocal of the growth rate.

[0095] Round the inverse of the growth rate up to the nearest integer to obtain the target value.

[0096] Determine the sequence number of each first pixel group within the circumference of the first pixel.

[0097] Remove the first pixel group whose index is a multiple of the target value from the circle corresponding to the first pixel, and obtain M first pixel groups.

[0098] The "rounding up the reciprocal of the growth rate" option means rounding the reciprocal of the growth rate to the nearest integer. If the reciprocal of the growth rate is already an integer, the growth rate remains unchanged; if the reciprocal of the growth rate contains a decimal part, the growth rate is rounded up to the next larger integer.

[0099] For example, if the reciprocal of the growth rate is 50, the target value is the growth rate itself, which is 50; if the reciprocal of the growth rate is 50.5, the reciprocal of the growth rate is rounded up to the nearest integer to obtain the target value of 51.

[0100] Determining the sequence number of each first pixel group within the first pixel circle means assigning a unique sequence number to each first pixel group sequentially along the circumferential direction of the first pixel circle, starting from a certain starting point.

[0101] For example, assuming that each first pixel group includes Q pixels, and that the number of pixels along the radius of the second pixel circle is x, then the number of pixels along the radius of the first pixel circle is (x+1). Let M represent the number of multiple first pixel groups corresponding to the first pixel circle, and L represent the number of multiple first pixel groups corresponding to the second pixel circle. Then, the number of multiple first pixel groups corresponding to the second pixel circle is L=2π×x / Q, and the number of multiple first pixel groups corresponding to the first pixel circle is M=2π×(x+1) / Q. Let Factor represent the growth rate of the number of first pixel groups corresponding to two adjacent pixel circles. Then, Factor=M / L-1 represents the growth rate of the number of first pixel groups corresponding to the first pixel circle and the second pixel circle.

[0102] For example, assuming that the number of pixels in each first pixel group is Q=3, and that the second pixel circumference is the pixel circumference corresponding to the blind zone distance, with a blind zone distance R0=2mm, a maximum scanning depth R1=15mm, and the number of pixels in the length of the ultrasound image P=1024, then the number of pixels in the radius length corresponding to the second pixel circumference is R0×Ratio1= R0×(P / 2) / R1=2×512 / 15≈68 pixels. Based on this, the number of pixels in the radius length corresponding to the first pixel circumference adjacent to the second pixel circumference is 68+1=69 pixels. Therefore, the number of multiple first pixel groups corresponding to the second pixel circumference is L=2π×68 / 3≈142, and the number of multiple first pixel groups corresponding to the first pixel circumference is M=2π×(68+1) / 3≈145. The reciprocal of the growth rate = 1 / Factor = 1 / (M / L-1) = 1 / (145 / 142-1)≈47.33. Rounding up the inverse of the growth rate, we get a target value of 48. Therefore, we assign serial numbers 1, ..., 145 to the 145 first pixel groups within the first pixel circle. We then remove the first pixel groups whose serial numbers are multiples of 48, specifically the groups with serial numbers 48, 96, and 144. We update the serial numbers of all first pixel groups within the first pixel circle, resulting in 142 first pixel groups with serial numbers 1-142. At this point, the first and second pixel circles have the same number of first pixel groups. This allows for a one-to-one comparison of the second average brightness values ​​of corresponding first pixel groups within adjacent pixel circles, enabling a more precise determination of the degree of brightness variation between adjacent pixel circles.

[0103] It should be noted that in determining the first pixel group within different pixel circumferences, since different pixel circumferences may correspond to different numbers of pixels, some pixel circumferences may not be divisible by the number of pixels Q included in the first pixel group. In such cases, the pixels corresponding to the remainder are grouped into a first pixel group. For example, assuming Q=3, if a pixel circumference has 100 pixels, then it is considered that the pixel circumference includes 33 first pixel groups containing 3 pixels each and 1 first pixel group containing 1 pixel.

[0104] In this embodiment, based on the growth rate of the number of first pixel groups corresponding to two adjacent pixel circumferences, some first pixel groups are removed from the multiple first pixel groups corresponding to the first pixel circumference, resulting in M ​​first pixel groups corresponding to the first pixel circumference. Thus, the number of first pixel groups included in the first pixel circumference is the same as the number of first pixel groups included in the second pixel circumference. Further, based on the correspondence between each first pixel group in the M first pixel groups of the first pixel circumference and each first pixel group in the second pixel circumference, the brightness change rate corresponding to each of the M first pixel groups is determined, and the positions of different layers in the ultrasound image are determined based on the obtained M second brightness change rates. It can be seen that this embodiment, by comparing the second average brightness values ​​of two corresponding first pixel groups in two adjacent pixel circumferences, can significantly improve the accuracy of determining the positions of different layers in the ultrasound image.

[0105] It should be noted that in the process of removing the first pixel group whose index is a multiple of the target value from the first pixel circle to obtain M first pixel groups from the first pixel circle, the first pixel group whose index is a multiple of the target value is not deleted from the first pixel circle. Rather, in determining the second brightness change rate of the first pixel circle and the second pixel circle, the first pixel group whose index is a multiple of the target value is not considered; these first pixel groups are skipped. That is, these first pixel groups are not used to determine the second brightness change rate between the first pixel circle and the second pixel circle. Instead, the M second brightness change rates are obtained only from the brightness change rates corresponding to the M first pixel groups obtained after the removal. In other words, in the process of determining the position of different layers in the ultrasound image, no pixel data is deleted from the ultrasound image before and after determining the position of different layers. The number of pixels in the ultrasound image is the same before and after determining the position of different layers.

[0106] In an exemplary embodiment, determining the location of different layers in an ultrasound image based on M second brightness change rates includes:

[0107] Select the first pixel group whose second brightness change rate is greater than or equal to the second preset change rate from the M first pixel groups to obtain N first pixel groups, where N is an integer greater than 1.

[0108] Determine the ratio of N to M.

[0109] If the ratio is greater than or equal to a preset ratio, the first pixel circle and the second pixel circle are determined to belong to different layers, thus obtaining the positions of different layers in the ultrasound image.

[0110] Optionally, the second preset rate of change can be 45%, 50%, 55%, or other rates of change.

[0111] Optionally, the preset ratio can be 50%, 55%, 60%, or other values.

[0112] Optionally, the preset ratio can be greater than the second brightness change rate.

[0113] In this embodiment, N represents the number of first pixel groups with significant brightness value variations. A large ratio of N to M indicates that among the M first pixel groups with corresponding relationships between adjacent pixel circumferences, there are a significant number of corresponding first pixel groups with large brightness variations. This means that a substantial change in image content has occurred between adjacent pixel circumferences. Therefore, these adjacent pixel circumferences can be considered to belong to different layers, and based on this, the positions of different layers in the ultrasound image can be determined. It can be seen that this embodiment, by comparing the second average brightness values ​​of corresponding first pixel groups within adjacent pixel circumferences, can significantly improve the accuracy of determining the positions of different layers in the ultrasound image.

[0114] In an exemplary embodiment, the above-described determination of pixel circumferences centered at a center point in an ultrasound image to obtain multiple pixel circumferences includes:

[0115] By determining the pixel circumference centered at the center point in the ultrasound image, multiple third pixel circumferences are obtained.

[0116] Filtering is performed on multiple third-pixel circles to obtain multiple pixel circles.

[0117] The third pixel circle refers to the unfiltered original pixel circles in the ultrasound image, which include a certain degree of noise or artifacts compared to the filtered pixel circles.

[0118] In this embodiment, after determining the pixel circumference centered at the center point in the ultrasound image and obtaining multiple third pixel circumferences, filtering is performed on these multiple third pixel circumferences to obtain multiple pixel circumferences. This effectively removes noise or artifacts from the ultrasound image, thus playing a role in de-interference and improving the clarity of the image content of the obtained multiple pixel circumferences. Furthermore, based on the multiple pixel circumferences with higher image display effect, the accuracy of the determination results of the positions of different layers in the ultrasound image can be ensured.

[0119] In an exemplary embodiment, the above-described filtering process on multiple third pixel circumferences to obtain multiple pixel circumferences includes:

[0120] Each pixel is grouped into multiple second pixel groups, with overlapping pixels between adjacent second pixel groups within the pixel circle.

[0121] The average brightness value of the second pixel group in each pixel circle is determined, and multiple third average brightness values ​​are obtained.

[0122] The brightness change rate of adjacent second pixel groups within the circumference of each pixel is determined to obtain the third brightness change rate.

[0123] When the third brightness change rate is greater than the third preset change rate, the brightness value of the target pixel is replaced by the third average brightness value of the previous second pixel group to obtain multiple pixel circles; the target pixel is the pixel in the next second pixel group that does not overlap with the previous second pixel group, and the next second pixel group is the next second pixel group adjacent to the previous second pixel group.

[0124] Each second pixel group includes the same number of pixels, and there is at least one overlapping pixel between two adjacent second pixel groups in the pixel circumference.

[0125] Optionally, the number of overlapping pixels between two adjacent second pixel groups in the pixel circumference can be one.

[0126] When there are at least two overlapping pixels between two adjacent second pixel groups in the pixel circumference, if the number of individual pixels remaining at the end is insufficient to form a second pixel, then adjacent pixels are searched forward based on that pixel to supplement the number, so as to ensure that the number of pixels included in each second pixel group is the same.

[0127] The third average brightness value refers to the average brightness value of all pixels included in the second pixel group within the corresponding pixel circle. In other words, the average brightness value of a second pixel group is determined by the average brightness value of all the pixels it includes.

[0128] The third brightness change rate refers to the rate of change in brightness between the third average brightness value of each of the multiple second pixel groups within the same pixel circumference and the third average brightness value of an adjacent second pixel group. The third brightness change rate characterizes the degree of change in the third average brightness value from one second pixel group to another adjacent second pixel group within the same pixel circumference.

[0129] Optionally, the third preset rate of change can be 50%, 55%, 60%, or other rates of change.

[0130] When the third brightness change rate between adjacent second pixel groups is greater than the third preset change rate, it indicates that the pixels in the subsequent second pixel group that do not overlap with the previous second pixel group have a large degree of change in brightness value. This pixel may contain noise or artifacts. Therefore, in order to make the brightness value of the pixel circumference have better smoothness, the brightness value of the target pixel is replaced with the third average brightness value of the previous second pixel group.

[0131] For example, suppose a pixel circle includes 99 pixels (pixel 1, pixel 2, pixel 3, pixel 4, pixel 5, ..., pixel 97, pixel 98, pixel 99), a second pixel group includes 3 pixels, and the number of overlapping pixels between two adjacent second pixel groups in the pixel circle is one. The pixel circumference is then divided into 97 second pixel groups (second pixel group 1, second pixel group 2, second pixel group 3, ..., first pixel group 97). Second pixel group 1 includes pixel 1, pixel 2, and pixel 3; second pixel group 2 includes pixel 2, pixel 3, and pixel 4; second pixel group 3 includes pixel 3, pixel 4, and pixel 5; ... second pixel group 97 includes pixel 97, pixel 98, and pixel 99. Thus, the average brightness value of the 97 second pixel groups within the pixel circumference is determined, resulting in 97 third average brightness values. Specifically, the third average brightness value of second pixel group 1 is the average of the brightness values ​​of pixel 1, pixel 2, and pixel 3; the third average brightness value of second pixel group 2 is the average of the brightness values ​​of pixel 2, pixel 3, and pixel 4; ... Assuming that the third brightness change rate between the second pixel group 2 and the second pixel group 3 is greater than the third preset change rate, and pixel 5 in the second pixel group 3 is not present in the second pixel group 2, it can be understood that pixel 5 has a larger brightness value change relative to pixels 1-4. Then, the brightness value of pixel 5 is replaced by the third average brightness value of the second pixel group 2, so that the brightness value of the second pixel group 3 has better smoothness with the brightness value of the second pixel group 2.

[0132] In this embodiment, if there is a large difference in brightness between two adjacent second pixel groups on the same pixel circumference, it indicates that there is significant noise or artifact at that location. Therefore, the brightness value of the target pixel is replaced by the third average brightness value of the previous second pixel group. Based on this, the brightness values ​​of pixels on the same pixel circumference in the ultrasound image can be made smoother, which can effectively reduce noise or artifacts in the ultrasound image, improve the image display effect of the ultrasound image, and help ensure the accuracy of the determination results of the positions of different layers in the ultrasound image obtained in subsequent steps.

[0133] In one exemplary embodiment, the method further includes:

[0134] The radius length corresponding to each layer is determined based on the location of the different layers.

[0135] Based on the radius length corresponding to each layer, the radius difference between the positions of two adjacent layers is determined.

[0136] The thickness of different layers in ultrasound images is determined based on the radius difference and the conversion relationship between pixel points and scanning depth.

[0137] Specifically, determining the radius length corresponding to each layer based on the position of different layers means determining the radius length corresponding to the pixel circumference of each layer based on the pixel circumference of each layer, thus obtaining the radius length corresponding to each layer.

[0138] The radius difference between two adjacent layers refers to the number of pixels in the outermost layer that lie on the same line in the same angular direction, which corresponds to the actual thickness of the outermost layer.

[0139] Based on the conversion relationship between pixels and scanning depth, the scanning depth length corresponding to one pixel, i.e., Ratio2, can be determined. Thus, the thickness of different layers in an ultrasound image can be determined based on the number of pixels included in the radius difference and the scanning depth length Ratio2 corresponding to one pixel.

[0140] The thickness of different layers refers to the radial distance between two adjacent layers.

[0141] Optionally, after determining the thickness of different layers in the ultrasound image, the terminal can mark the different layers with location markers so that doctors can intuitively observe the location of different layers from the ultrasound image, thereby improving diagnostic efficiency and accuracy.

[0142] For example, when the ultrasound image is a small bowel ultrasound image, after determining the thickness of different layers in the ultrasound image, the terminal can sequentially label the different layers from the inside out as the mucosa, muscularis mucosae, submucosa, muscularis propria, and serosa.

[0143] In this embodiment, the radius difference between two adjacent layers is determined based on the radius length corresponding to each layer. The radius difference between two adjacent layers corresponds to the actual thickness of the outermost layer. Therefore, based on the radius difference and the conversion relationship between pixels and scanning depth, the thickness of different layers in the ultrasound image can be accurately determined.

[0144] In one exemplary embodiment, the method further includes:

[0145] If the thickness of the target layer is greater than or equal to the preset thickness of the target layer, it is determined that there is a lesion in the target layer.

[0146] In particular, different preset thicknesses will be corresponding to different target layers.

[0147] For example, when the ultrasound image is a small bowel ultrasound image, the mucosa, muscularis mucosae, submucosa, muscularis propria, and serosa each have their own preset thickness.

[0148] Optionally, if a lesion is identified in the target layer, the terminal can mark the target layer using special markers. For example, these special markers can be highlight marks, symbol marks, or other marking methods that can distinguish the target layer among multiple layers. Marking the target layer with special markers helps doctors intuitively identify the target layer containing the lesion from the ultrasound image.

[0149] In an easy-to-understand way, based on the thickness of different layers determined by the ultrasound image, the terminal can also determine the size of the lesion, the level of origin of the lesion, and the echo characteristics, which helps doctors to further clarify the nature of the lesion corresponding to the ultrasound image.

[0150] In this embodiment, when the thickness of the target layer is greater than or equal to the preset thickness corresponding to the target layer, it indicates that the thickness of the target layer has exceeded the normal thickness that the layer should have. Therefore, the target layer is identified as having a lesion, which is beneficial for doctors to directly observe the target layer for diagnosis, thereby improving diagnostic efficiency and accuracy.

[0151] The application process of the above-mentioned layered location determination method is illustrated below with a detailed embodiment. The layered location determination method is applied to a terminal, as follows:

[0152] (1) The terminal acquires ultrasound images.

[0153] (2) The terminal determines the brightness value of each pixel in the ultrasound image.

[0154] (3) The process of determining the circumference of multiple pixels:

[0155] The terminal determines the pixel circumference in the ultrasound image with the center point as the center, and obtains multiple third pixel circumferences;

[0156] The terminal groups each pixel circumference into multiple second pixel groups, and there are overlapping pixels between two adjacent second pixel groups in the pixel circumference.

[0157] The terminal determines the average brightness value of the second pixel group in the circumference of each pixel, and obtains multiple third average brightness values;

[0158] The terminal determines the brightness change rate of adjacent second pixel groups in the circumference of each pixel to obtain the third brightness change rate;

[0159] When the third brightness change rate is greater than the third preset change rate, the terminal replaces the brightness value of the target pixel with the third average brightness value of the previous second pixel group to obtain multiple pixel circles; the target pixel is the pixel in the next second pixel group that does not overlap with the previous second pixel group, and the next second pixel group is the next second pixel group adjacent to the previous second pixel group.

[0160] (4) The process of determining the location of different layers in ultrasound images:

[0161] The terminal determines the average brightness value of each pixel circle based on the number of pixels around each pixel circle and the brightness value of each pixel circle, thus obtaining multiple first average brightness values.

[0162] The terminal groups each pixel into a circular group to obtain multiple first pixel groups, determines the average brightness value of each first pixel group, and obtains multiple second average brightness values.

[0163] The terminal determines the brightness change rate between two adjacent pixel circumferences based on the first average brightness value of two adjacent pixel circumferences, and obtains the first brightness change rate.

[0164] When the first brightness change rate is greater than or equal to the first preset change rate, the terminal determines the growth rate of the number of the first pixel group corresponding to each of the two adjacent pixel circumferences.

[0165] The terminal determines the reciprocal of the growth rate;

[0166] The terminal rounds up to the nearest integer the inverse of the growth rate to obtain the target value;

[0167] The terminal determines the sequence number of each first pixel group within the circumference of the first pixel;

[0168] The terminal removes the first pixel group whose index is a multiple of the target value from the first pixel circle, resulting in M ​​first pixel groups; M is the number of first pixel groups contained in the second pixel circle, the first pixel circle and the second pixel circle are adjacent, and the radius of the first pixel circle is greater than the radius of the second pixel circle, and M is an integer greater than 1.

[0169] Based on the second average brightness value of each first pixel group in the M first pixel groups of the first pixel circumference, the second average brightness value of each first pixel group in the second pixel circumference, and the correspondence between each first pixel group in the M first pixel groups of the first pixel circumference and each first pixel group in the second pixel circumference, the terminal determines the brightness change rate corresponding to each of the M first pixel groups and obtains the M second brightness change rates.

[0170] The terminal selects the corresponding first pixel group from the M first pixel groups whose second brightness change rate is greater than or equal to the second preset change rate, to obtain N first pixel groups, where N is an integer greater than 1;

[0171] The terminal determines the ratio of N to M;

[0172] When the ratio is greater than or equal to a preset ratio, the terminal determines that the first pixel circle and the second pixel circle belong to different layers, thus obtaining the positions of different layers in the ultrasound image.

[0173] (5) The process of determining the target layer where lesions exist:

[0174] The terminal determines the radius length corresponding to each layer based on the location of each layer;

[0175] The terminal determines the radius difference between two adjacent layers based on the radius length corresponding to each layer;

[0176] The terminal determines the thickness of different layers in the ultrasound image based on the radius difference and the conversion relationship between pixels and scanning depth;

[0177] If the thickness of the target layer is greater than or equal to the preset thickness of the target layer, the terminal determines that there is a lesion in the target layer.

[0178] In this embodiment, the position of different layers in the ultrasound image can be accurately determined based on the brightness value of each pixel and the circumference of each pixel. This avoids the inaccuracy of layer position that may be caused by manually determining the position of different layers. Furthermore, it can also determine the thickness of different layers in the ultrasound image and identify the target layer where lesions exist, so that doctors can make a diagnosis intuitively based on the ultrasound image, which significantly improves the diagnostic efficiency and accuracy.

[0179] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0180] Based on the same inventive concept, this application also provides a layered position determination apparatus for implementing the layered position determination method described above. The solution provided by this apparatus is similar to the solution described in the above method; therefore, the specific limitations in one or more embodiments of the layered position determination apparatus provided below can be found in the limitations of the layered position determination method described above, and will not be repeated here.

[0181] In one exemplary embodiment, such as Figure 4 As shown, a layered position determination device is provided, comprising: an acquisition module 402, a first determination module 404, a second determination module 406, and a third determination module 408, wherein:

[0182] The acquisition module 402 is used to acquire ultrasound images.

[0183] The first determining module 404 is used to determine the brightness value of each pixel in the ultrasound image.

[0184] The second determining module 406 is used to determine the pixel circumference in the ultrasound image with the center point as the center, and obtain multiple pixel circumferences.

[0185] The third determining module 408 is used to determine the position of different layers in the ultrasound image based on the brightness value of each pixel and the circumference of each pixel.

[0186] In an exemplary embodiment, the third determining module 408 is specifically used to determine the average brightness value of each pixel circumference based on the number of pixels on each pixel circumference and the brightness value of each pixel, thereby obtaining a plurality of first average brightness values; group each pixel circumference into a plurality of first pixel groups, determine the average brightness value of each first pixel group, thereby obtaining a plurality of second average brightness values; and determine the position of different layers in the ultrasound image based on the plurality of first average brightness values ​​and the plurality of second average brightness values.

[0187] In an exemplary embodiment, the third determining module 408 is specifically used to determine the brightness change rate between two adjacent pixel circumferences based on the first average brightness value of two adjacent pixel circumferences, and obtain the first brightness change rate; when the first brightness change rate is greater than or equal to the first preset change rate, the position of different layers in the ultrasound image is determined based on the second average brightness value of each first pixel group in the two adjacent pixel circumferences.

[0188] In an exemplary embodiment, the third determining module 408 is specifically used to determine the growth rate of the number of first pixel groups corresponding to each of two adjacent pixel circumferences; based on the growth rate, some first pixel groups are removed from the multiple first pixel groups corresponding to the first pixel circumference to obtain M first pixel groups; M is the number of first pixel groups contained in the second pixel circumference, the first pixel circumference is adjacent to the second pixel circumference, and the radius of the first pixel circumference is greater than the radius of the second pixel circumference, and M is an integer greater than 1; based on the second average brightness value of each first pixel group in the M first pixel groups of the first pixel circumference, the second average brightness value of each first pixel group in the second pixel circumference, and the correspondence between each first pixel group in the M first pixel groups of the first pixel circumference and each first pixel group in the second pixel circumference, the brightness change rate corresponding to the M first pixel groups is determined to obtain M second brightness change rates; based on the M second brightness change rates, the positions of different layers in the ultrasound image are determined.

[0189] In an exemplary embodiment, the third determining module 408 is specifically used to select a first pixel group from M first pixel groups whose corresponding second brightness change rate is greater than or equal to a second preset change rate, to obtain N first pixel groups, where N is an integer greater than 1; determine the ratio of N to M; and if the ratio is greater than or equal to a preset ratio, determine that the circumference of the first pixel and the circumference of the second pixel belong to different layers, thereby obtaining the positions of different layers in the ultrasound image.

[0190] In an exemplary embodiment, the third determining module 408 is specifically used to determine the reciprocal of the growth rate; round up the reciprocal of the growth rate to obtain the target value; determine the sequence number of each first pixel group in the first pixel circle; and remove the first pixel group whose sequence number is a multiple of the target value from the first pixel circle to obtain M first pixel groups.

[0191] In an exemplary embodiment, the second determining module 406 is specifically used to determine the pixel circumference in the ultrasound image with the center point as the center, and obtain a plurality of third pixel circumferences; and to perform filtering processing on the plurality of third pixel circumferences to obtain a plurality of pixel circumferences.

[0192] In an exemplary embodiment, the second determining module 406 is specifically used to group each pixel circumference to obtain multiple second pixel groups, wherein there are overlapping pixels between adjacent second pixel groups in the pixel circumference; determine the average brightness value of the second pixel groups in each pixel circumference to obtain multiple third average brightness values; determine the brightness change rate of adjacent second pixel groups in each pixel circumference to obtain a third brightness change rate; if the third brightness change rate is greater than a third preset change rate, replace the brightness value of the target pixel with the third average brightness value of the previous second pixel group to obtain multiple pixel circumferences; the target pixel is a pixel in the next second pixel group that does not overlap with the previous second pixel group, and the next second pixel group is the next second pixel group adjacent to the previous second pixel group.

[0193] In an exemplary embodiment, the third determining module 408 is further configured to determine the radius length corresponding to each layer based on the position of different layers; determine the radius difference between adjacent layers based on the radius length corresponding to each layer; determine the thickness of different layers in the ultrasound image based on the radius difference and the conversion relationship between pixel points and scanning depth; and the mapping coefficient is the pixel point and the depth of scanning depth.

[0194] In an exemplary embodiment, the third determining module 408 is further configured to determine that a lesion exists in the target layer when the thickness of the target layer is greater than or equal to the preset thickness corresponding to the target layer.

[0195] Each module in the aforementioned layered location determination device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0196] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores ultrasound image data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When executed by the processor, the computer program implements a hierarchical location determination method.

[0197] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 6As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements a hierarchical location determination method. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0198] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0199] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0200] In one exemplary embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above-described method embodiments.

[0201] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0202] It should be noted that the data involved in this application (including but not limited to data used for analysis, data stored, data displayed, etc.) are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0203] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0204] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0205] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for determining the layer position, characterized in that, The method includes: Acquire ultrasound images; Determine the brightness value of each pixel in the ultrasound image; Determine the pixel circumference in the ultrasound image with the center point as the center, and obtain multiple pixel circumferences; Based on the number of pixels on each pixel circumference and the brightness value of each pixel, the average brightness value of each pixel circumference is determined, resulting in multiple first average brightness values. Each pixel circumference is then grouped to obtain multiple first pixel groups, and the average brightness value of each first pixel group is determined, resulting in multiple second average brightness values. Based on the first average brightness values ​​of two adjacent pixel circumferences, the brightness change rate between two adjacent pixel circumferences is determined, resulting in a first brightness change rate. If the first brightness change rate is greater than or equal to a first preset change rate, the positions of different layers in the ultrasound image are determined based on the second average brightness values ​​of each first pixel group in two adjacent pixel circumferences.

2. The method according to claim 1, characterized in that, The ultrasound image is a square image.

3. The method according to claim 2, characterized in that, The resolution of the ultrasound image is 1024×1024 pixels.

4. The method according to claim 1, characterized in that, Determining the position of different layers in the ultrasound image based on the second average brightness value of each of the first pixel groups in two adjacent pixel circumferences includes: Determine the growth rate of the number of the first pixel group corresponding to each of two adjacent pixel circumferences; Based on the growth rate, some first pixel groups are removed from the multiple first pixel groups corresponding to the first pixel circumference to obtain M first pixel groups; M is the number of first pixel groups contained in the second pixel circumference, the first pixel circumference is adjacent to the second pixel circumference, and the radius of the first pixel circumference is greater than the radius of the second pixel circumference, and M is an integer greater than 1. Based on the second average brightness value of each first pixel group in the M first pixel groups of the first pixel circumference, the second average brightness value of each first pixel group in the second pixel circumference, and the correspondence between each first pixel group in the M first pixel groups of the first pixel circumference and each first pixel group in the second pixel circumference, the brightness change rate corresponding to each of the M first pixel groups is determined, and M second brightness change rates are obtained. Based on M of the second brightness change rates, the positions of different layers in the ultrasound image are determined.

5. The method according to claim 4, characterized in that, The step of determining the location of different layers in the ultrasound image based on M of the second brightness change rates includes: Select the first pixel group whose second brightness change rate is greater than or equal to the second preset change rate from the M first pixel groups to obtain N first pixel groups, where N is an integer greater than 1; Determine the ratio of N to M; If the ratio is greater than or equal to a preset ratio, it is determined that the first pixel circumference and the second pixel circumference belong to different layers, thus obtaining the positions of different layers in the ultrasound image.

6. The method according to claim 4, characterized in that, Based on the growth rate, a portion of the first pixel group is removed from the first pixel group corresponding to the circumference of the first pixel to obtain M first pixel groups, including: Determine the reciprocal of the growth rate; Round the reciprocal of the growth rate up to the nearest integer to obtain the target value; Determine the sequence number of each first pixel group within the circumference of the first pixel; Remove the first pixel group whose corresponding index is a multiple of the target value from the circumference of the first pixel, and obtain M first pixel groups.

7. The method according to claim 1, characterized in that, The process of determining the pixel circumference centered at the center point in the ultrasound image, resulting in multiple pixel circumferences, includes: Determine the pixel circumference centered at the center point in the ultrasound image to obtain multiple third pixel circumferences; The multiple third pixel circumferences are filtered to obtain the multiple pixel circumferences.

8. The method according to claim 7, characterized in that, The step of filtering the multiple third pixel circumferences to obtain the multiple pixel circumferences includes: Each pixel is grouped into multiple second pixel groups, and there are overlapping pixels between two adjacent second pixel groups in the pixel circumference. Determine the average brightness value of the second pixel group in each pixel circumference to obtain multiple third average brightness values; The brightness change rate of adjacent second pixel groups in each pixel circumference is determined to obtain the third brightness change rate; When the third brightness change rate is greater than the third preset change rate, the brightness value of the target pixel is replaced by the third average brightness value of the previous second pixel group to obtain a plurality of pixel circumferences; the target pixel is a pixel in the next second pixel group that does not overlap with the previous second pixel group, and the next second pixel group is the next second pixel group adjacent to the previous second pixel group.

9. The method according to claim 1, characterized in that, The method further includes: Based on the location of different layers, determine the radius length corresponding to each layer; Based on the radius length corresponding to each layer, determine the radius difference between the positions of two adjacent layers; Based on the radius difference and the conversion relationship between pixel points and scanning depth, the thickness of different layers in the ultrasound image is determined.

10. The method according to claim 9, characterized in that, The method further includes: If the thickness of the target layer is greater than or equal to the preset thickness corresponding to the target layer, it is determined that there is a lesion in the target layer.

Images