Method and device for controlling attenuation imaging quality, storage medium and electronic equipment

Abstract

The invention provides a method for attenuation imaging quality control, and the method mainly comprises the steps: obtaining a marked Boolean matrix based on m * n coordinate points after second marking, and the scale is m * n; counting the percentage (f) of a non-0 region in the Boolean matrix, wherein the percentage of a 0 region is (1-f); and setting weights a and b, combining the weights a and b with the percentage to form a * (f) + b * (1-f), and taking the a * (f) + b * (1-f) as information combining two dimensions of the image scale (m * n) and the time scale (t) as an evaluation standard for measuring effectiveness, and attenuating a quality control factor of the imaged image in the t-frame time sequence. According to the system, ultrasonic attenuation two-dimensional images can be continuously output, and ultrasonic attenuation values in a specific range / specific area can be selected from the continuous images changing in time. The attenuation imaging quality control factor is combined with time and space information to carry out quality control, and information of two dimensions can be more effectively used as an evaluation standard of measurement effectiveness.

Description

Technical Field

[0001] The present invention relates to the technical field of computer data processing, and in particular to a method, a device, a storage medium and an electronic device for attenuation imaging quality control. Background Art

[0002] Ultrasound attenuation imaging generates images by detecting the attenuation of ultrasound energy by tissues. The basic principle is to use the energy loss of ultrasound when it propagates in tissues. The rate of energy loss varies depending on the density and composition of the tissue. Higher attenuation usually means higher absorption or scattering rate of tissue, so different characteristics of tissues can be reflected through attenuation imaging. In this imaging mode, the ultrasound system records and analyzes the attenuation data of ultrasound signals inside tissues to distinguish different types of tissues.

[0003] In clinical practice, due to differences in operators or operating techniques, attenuation imaging images of the same clinical target are prone to large differences, so attenuation imaging image quality control is also very important. In attenuation imaging quality control, the key goal is to ensure image clarity, accuracy and consistency. To achieve this, the following quality control measures are usually adopted:

[0004] 1. Equipment calibration: Regularly calibrate the ultrasound equipment to ensure accurate measurement of the attenuation coefficient and avoid image distortion caused by equipment errors.

[0005] 2. Parameter optimization: Optimize ultrasound parameters such as gain, contrast, and depth settings to improve imaging quality and ensure that attenuation values ​​accurately reflect tissue differences.

[0006] 3. Image stability monitoring: Establish a baseline image to compare the attenuation changes of subsequent imaging, especially in the case of multiple imaging or long-term observation, to maintain the stability of the attenuation image.

[0007] In current clinical practice, the quality control of ultrasound attenuation imaging mainly relies on the analysis of inter-frame changes. Although quality control based on inter-frame changes can reflect the fluctuations in the imaging process, it cannot fully reflect the stability of the overall information on the two-dimensional image. Inter-frame changes usually focus on detecting differences in local attenuation coefficients or brightness, and may not provide comprehensive guarantees for the spatial distribution characteristics and overall consistency of the image.

[0008] Since two-dimensional images contain rich spatial and structural information, simply relying on inter-frame changes ignores the stability and consistency of the overall image information, such as image edges, textures, and important anatomical details. This local control may lead to the loss of two-dimensional image information, affecting the diagnostic accuracy and reliability of attenuation imaging in clinical applications.

[0009] Therefore, to further improve the quality control of attenuation imaging, more comprehensive indicators are needed to evaluate the spatial stability of the entire image, such as introducing spatial texture analysis or global detection of image contrast to ensure that the information on the two-dimensional image remains stable during the multi-frame image acquisition process, providing a more accurate basis for diagnosis. Summary of the invention

[0010] One of the purposes of the present invention is to provide a method for attenuation imaging quality control. The system should be able to continuously output two-dimensional images of ultrasonic attenuation, and should be able to select ultrasonic attenuation values ​​of a specific range / specific area in the continuous images that change over time. The attenuation imaging quality control factor of the present invention combines time and space information for quality control, and can more effectively use information in two dimensions as an evaluation criterion for measurement effectiveness.

[0011] An embodiment of the present invention provides a method for attenuation imaging quality control, comprising:

[0012] Acquire a time series image of attenuation imaging stored in the ultrasound system, with a scale of m*n*t, where m is the image width, n is the image depth, and t is the number of samples in the time direction;

[0013] Calculate the standard deviation and mean of t-frame attenuation imaging images along the time direction to obtain m*n standard deviations σ and m*n mean values ​​μ;

[0014] Perform the first marking: mark the position of each coordinate point with an abnormal value along the t direction among the m*n coordinate points as p, where p is the number of abnormal data, and if there is no abnormal data, it is marked as 0; the abnormal value is the value exceeding μ+k*σ;

[0015] Perform the second annotation: set the threshold value of thershold_p for the number of abnormal data. If the position p>thershold_p among the m*n coordinate points after the first annotation, it is marked as 1, otherwise it is marked as 0.

[0016] Based on the m*n coordinate points after the second annotation, a Boolean matrix after annotation is obtained, and the scale is m*n;

[0017] Count the percentage of non-zero regions in the Boolean matrix (f), and the percentage of zero regions is (1-f);

[0018] Set weights a and b, and combine weights a and b with percentages to form a*(f)+b*(1-f) as a quality control factor for attenuation imaging images in a t-frame time series, combining information from two dimensions, image scale (m*n) and time scale (t), as an evaluation standard for measuring the effectiveness; where a+b=1;

[0019] Perform attenuation imaging quality control based on quality control factors.

[0020] Optionally, k increases as t increases; k is 0.5*floor(t / 3+1), where floor means rounding down.

[0021] Optionally, thershold_p increases as m*n increases; thershold_p should be m*n / (1e5), and the minimum value of thershold_p should not be less than 1.

[0022] Optionally, the annotated Boolean matrix can also be obtained by the following steps:

[0023] Use h-order linear fits to fit m*n coordinate points along t time data; h is an algebraic representation;

[0024] The coordinate positions of the m*n coordinate points that are lower than the fitting threshold R are marked as 1, otherwise they are marked as 0, and the marked Boolean matrix is ​​obtained.

[0025] Optionally, the value of the fitting threshold R increases as the number of m*n increases; the fitting threshold R is 0.7+0.1*floor(m*n / (1e5)), where floor means rounding down.

[0026] Optionally, the attenuation imaging quality control based on the quality control factor includes:

[0027] The measured values ​​below N% of the operation results are considered invalid measurements; where N% is the percentage of the output.

[0028] An embodiment of the present invention provides a device for attenuation imaging quality control, comprising:

[0029] An acquisition module is used to acquire time series images of attenuation imaging stored in the ultrasound system, with a scale of m*n*t, where m is the image width, n is the image depth, and t is the time direction sequence of the image;

[0030] A calculation module is used to calculate the standard deviation and the average of t-frame attenuation imaging images along the time direction to obtain m*n standard deviations σ and m*n averages μ;

[0031] The first marking module is used for the first marking: marking the position with abnormal values ​​in the direction of t in each m*n coordinate point as p, where p is the number of abnormal data, and if there is no abnormal data, it is marked as 0; the abnormal value is a value exceeding μ+k*σ;

[0032] The second marking module is used for performing the second marking: setting the number threshold of abnormal data thershold_p, if the position p>thershold_p among the m*n coordinate points after the first marking is performed, it is marked as 1, otherwise it is marked as 0;

[0033] A first determination module is used to obtain a marked Boolean matrix based on the m*n coordinate points after the second marking, with a scale of m*n;

[0034] The statistical module is used to count the percentage of non-zero areas in the Boolean matrix (f), and the percentage of zero areas is (1-f);

[0035] The second determination module is used to set weights a and b, and combine the weights a and b with the percentage to form a*(f)+b*(1-f) as a quality control factor combining information of the two dimensions of image scale (m*n) and time scale (t) as an evaluation standard for measuring the effectiveness of the attenuation imaging image in the t-frame time series; wherein a+b=1;

[0036] The control module is used for performing attenuation imaging quality control based on the quality control factor.

[0037] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and a processor executes the computer program to implement any of the above methods.

[0038] An embodiment of the present invention provides an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any one of the methods described above.

[0039] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0040] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0042] Figure 1 is a schematic diagram of a method for attenuation imaging quality control in an embodiment of the present invention;

[0043] Figure 2is a schematic diagram of attenuation imaging data in an embodiment of the present invention;

[0044] Figure 3 Schematic diagram of abnormal data point identification and annotated abnormal data positions in the time t direction in an embodiment of the present invention;

[0045] Figure 4 It is a schematic diagram of a binarization into a Boolean matrix after setting a specific threshold through threshold_p in an embodiment of the present invention;

[0046] Figure 5 A schematic diagram of using calculated parameters as quality control coefficients in an embodiment of the present invention;

[0047] Figure 6 Schematic diagram of a device for attenuation imaging quality control in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0049] The embodiment of the present invention provides a method for attenuation imaging quality control, such as Figure 1 As shown, including:

[0050] S1, acquiring a time series image of attenuation imaging stored in an ultrasound system, with a scale of m*n*t, where m is the image width, n is the image depth, and t is the number of samples in the time direction;

[0051] S2, calculating the standard deviation and average of t-frame attenuation imaging images along the time direction, and obtaining m*n standard deviations σ and m*n averages μ;

[0052] S3, perform the first marking: mark the position of each coordinate point with abnormal value along the t direction among the m*n coordinate points as p, where p is the number of abnormal data, and if there is no abnormal data, it is marked as 0; the abnormal value is the value exceeding μ+k*σ; each coordinate point can be represented in two dimensions as the horizontal axis x1, x2, x3, ..., x m , vertical axis y1,y2,y3,…,y n ; For example: a coordinate point has t sampling points in the time direction (t>=3), and there are 3 outliers, then p=3;

[0053] S4, perform the second annotation: set the threshold value thershold_p for the number of abnormal data. If the position p>thershold_p in the m*n coordinate points after the first annotation is marked as 1, otherwise it is marked as 0; assuming that thershold_p is 2 (the number of abnormal points in time at this coordinate), the case of p=3 above will be marked as 1 at this coordinate, otherwise it will be marked as 0; the first annotation is the number p, and the second annotation is the Boolean value of p;

[0054] S5, obtaining a marked Boolean matrix based on the m*n coordinate points after the second marking, with a scale of m*n;

[0055] S6. Count the percentage of non-zero regions in the Boolean matrix (f), and the percentage of regions containing zero is (1-f);

[0056] S7, set weights a and b, and combine the weights a and b with the percentage to form a*(f)+b*(1-f) as the quality control factor of the attenuation imaging image in the t-frame time series, combining the information of the two dimensions of image scale (m*n) and time scale (t) as the evaluation standard for measuring the effectiveness; wherein a+b=1; this method combines the two dimensions of temporal stability (t) and spatial stability (image scale m*n) for joint evaluation;

[0057] S8. Perform attenuation imaging quality control based on quality control factors.

[0058] k increases as t increases; k is 0.5*floor(t / 3+1), where floor means rounding down.

[0059] thershold_p increases as m*n increases; thershold_p should be m*n / (1e5), and the minimum value of thershold_p should not be less than 1. 1e is 10 to the fifth power.

[0060] The annotated Boolean matrix can also be obtained by the following steps:

[0061] Use h-order linear fitting to fit m*n coordinate points along t time data; h is an algebraic representation, which can be used as 1st fitting, 2nd fitting, etc., where 1 2 is represented by h;

[0062] The coordinate positions of the m*n coordinate points that are lower than the fitting threshold R are marked as 1, otherwise they are marked as 0, and the marked Boolean matrix is ​​obtained.

[0063] The value of the fitting threshold R increases as the number of m*n increases; the fitting threshold R is 0.7+0.1*floor(m*n / (1e5)), where floor means rounding down.

[0064] The attenuation imaging quality control based on the quality control factor includes:

[0065] The measurement values ​​below N% of the operation result are considered invalid measurements. The percentage output of the step "Set weights a and b, and combine weights a and b with the percentage to be a*(f)+b*(1-f)" is N. It can be set as invalid measurements below N, for example, N=80.

[0066] Obtain the time series images of attenuation imaging stored in the ultrasound system, with a scale of m*n*t, where m is the image width, n is the image depth, and t is the time direction sequence of the image. Figure 2 shown.

[0067] Calculate the standard deviation and mean of t-frame attenuation imaging images along the time direction to obtain m*n standard deviations σ and m*n mean values ​​μ. Use m*n μ+k*σ as the standard for judging whether the data is abnormal, where k increases with the increase of t. k should be 0.5*floor(t / 3+1), where floor means rounding down.

[0068] The position with abnormal values ​​(exceeding μ+k*σ) in the direction of t in each m*n coordinate point is marked as p, where p is the number of abnormal data, and if there is no abnormal data, it is marked as 0. Figure 3 shown.

[0069] Set the number threshold of abnormal data thershold_p. If p>thershold_p, it is marked as 1, otherwise it is marked as 0. Thershold_p increases with the increase of m*n. Thershold_p should be m*n / (1e5), and the minimum value of thershold_p should not be less than 1. Figure 4 shown.

[0070] Alternatively, in step 2, h linear fits can be used to fit m*n data along time t, and the standard for judging whether the data is abnormal in step 2 is set to the fitting threshold R (the value range of R is [0,1]) for measuring the linear regression, where the value of threshold R increases with the increase of m*n. The threshold R should be 0.7+0.1*floor(m*n / (1e5)), where floor means rounding down. The positions of the outliers are also counted to obtain a Boolean matrix. The statistical method of the outliers is to mark the coordinate position below the fitting threshold as 1, otherwise it is marked as 0, and the marked Boolean matrix can be obtained.

[0071] Get the annotated Boolean matrix with a scale of m*n. Count the percentage of non-zero areas in the Boolean matrix (f), and the percentage of zero areas is (1-f). Set weights a and b, where a+b=1. Combine the weights and percentages into a*(f)+b*(1-f) as the evaluation standard for measuring the effectiveness of the attenuation imaging image in the t-frame time series by combining the information of the two dimensions of image scale (m*n) and time scale (t). Figure 5 shown.

[0072] The system should be able to continuously output two-dimensional images of ultrasonic attenuation, and should be able to select ultrasonic attenuation values ​​of a specific range / specific area in the continuous images that change over time. The attenuation imaging quality control factor of the present invention combines time and space information for quality control, and can more effectively use information in two dimensions as an evaluation criterion for measurement effectiveness.

[0073] An embodiment of the present invention provides a device for attenuation imaging quality control, such as Figure 6 As shown, including:

[0074] An acquisition module 1 is used to acquire a time series image of attenuation imaging stored in an ultrasound system, with a scale of m*n*t, where m is the image width, n is the image depth, and t is the time direction sequence of the image;

[0075] Calculation module 2, used for calculating the standard deviation and average of t-frame attenuation imaging images along the time direction, and obtaining m*n standard deviations σ and m*n averages μ;

[0076] The first marking module 3 is used to perform the first marking: the position with abnormal values ​​in the direction of t in each m*n coordinate point is marked as p, where p is the number of abnormal data, and if there is no abnormal data, it is marked as 0; the abnormal value is a value exceeding μ+k*σ;

[0077] The second marking module 4 is used for performing the second marking: setting a threshold value thershold_p for the number of abnormal data, if the position p>thershold_p among the m*n coordinate points after the first marking is performed, it is marked as 1, otherwise it is marked as 0;

[0078] A first determination module 5 is used to obtain a marked Boolean matrix based on the m*n coordinate points after the second marking, with a scale of m*n;

[0079] Statistical module 6, used for counting the percentage of non-zero regions in the Boolean matrix (f), and the percentage of regions containing zero is (1-f);

[0080] The second determination module 7 is used to set weights a and b, and combine the weights a and b with the percentage to form a*(f)+b*(1-f) as a quality control factor combining information of the two dimensions of image scale (m*n) and time scale (t) as an evaluation standard for measuring the effectiveness of the attenuation imaging image in the t-frame time series; wherein a+b=1;

[0081] The control module 8 is used to perform attenuation imaging quality control based on the quality control factor.

[0082] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and a processor executes the computer program to implement any of the above methods.

[0083] An embodiment of the present invention provides an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any one of the methods described above.

[0084] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for attenuation imaging quality control, characterized in that: include: Acquire a time series image of attenuation imaging stored in the ultrasound system, with a scale of m*n*t, where m is the image width, n is the image depth, and t is the number of samples in the time direction; Calculate the standard deviation and mean of t-frame attenuation imaging images along the time direction to obtain m*n standard deviations σ and m*n mean values ​​μ; Perform the first marking: mark the position of each coordinate point with an abnormal value along the t direction among the m*n coordinate points as p, where p is the number of abnormal data, and if there is no abnormal data, it is marked as 0; the abnormal value is the value exceeding μ+k*σ; Perform the second annotation: set the threshold value of thershold_p for the number of abnormal data. If the position p>thershold_p among the m*n coordinate points after the first annotation, it is marked as 1, otherwise it is marked as 0. Based on the m*n coordinate points after the second annotation, a Boolean matrix after annotation is obtained, and the scale is m*n; Count the percentage of non-zero regions in the Boolean matrix (f), and the percentage of zero regions is (1-f); Set weights a and b, and combine weights a and b with percentages to form a*(f)+b*(1-f) as a quality control factor for attenuation imaging images in a t-frame time series, combining information from two dimensions, image scale (m*n) and time scale (t), as an evaluation standard for measuring the effectiveness; where a+b=1; Perform attenuation imaging quality control based on quality control factors.

2. The method for attenuation imaging quality control according to claim 1, characterized in that: k increases as t increases; k is 0.5*floor(t / 3+1), where floor means rounding down.

3. The method for attenuation imaging quality control according to claim 1, characterized in that: thershold_p increases as m*n increases; thershold_p should be m*n / (1e5), and the minimum value of thershold_p should not be less than 1.

4. The method for attenuation imaging quality control according to claim 1, characterized in that: The annotated Boolean matrix can also be obtained by the following steps: Use h-order linear fits to fit m*n coordinate points along t time data; h is an algebraic representation; The coordinate positions of the m*n coordinate points that are lower than the fitting threshold R are marked as 1, otherwise they are marked as 0, and the marked Boolean matrix is ​​obtained.

5. The method for attenuation imaging quality control according to claim 4, characterized in that: The value of the fitting threshold R increases as the number of m*n increases; the fitting threshold R is 0.7+0.1*floor(m*n / (1e5)), where floor means rounding down.

6. The method for attenuation imaging quality control according to claim 1, characterized in that: The attenuation imaging quality control based on the quality control factor includes: The measured values ​​below N% of the operation results are considered invalid measurements; where N% is the percentage of the output.

7. A device for attenuation imaging quality control, characterized in that: include: An acquisition module is used to acquire time series images of attenuation imaging stored in the ultrasound system, with a scale of m*n*t, where m is the image width, n is the image depth, and t is the time direction sequence of the image; A calculation module is used to calculate the standard deviation and the average of t-frame attenuation imaging images along the time direction to obtain m*n standard deviations σ and m*n averages μ; The first marking module is used for the first marking: marking the position with abnormal values ​​in the direction of t in each m*n coordinate point as p, where p is the number of abnormal data, and if there is no abnormal data, it is marked as 0; the abnormal value is a value exceeding μ+k*σ; The second marking module is used for performing the second marking: setting the number threshold of abnormal data thershold_p, if the position p>thershold_p among the m*n coordinate points after the first marking is performed, it is marked as 1, otherwise it is marked as 0; A first determination module is used to obtain a marked Boolean matrix based on the m*n coordinate points after the second marking, with a scale of m*n; The statistical module is used to count the percentage of non-zero areas in the Boolean matrix (f), and the percentage of zero areas is (1-f); The second determination module is used to set weights a and b, and combine the weights a and b with the percentage to form a*(f)+b*(1-f) as a quality control factor combining information of the two dimensions of image scale (m*n) and time scale (t) as an evaluation standard for measuring the effectiveness of the attenuation imaging image in the t-frame time series; wherein a+b=1; The control module is used for performing attenuation imaging quality control based on the quality control factor.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the processor executes the computer program to implement the method according to any one of claims 1 to 6.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method according to any one of claims 1 to 6.

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