An intra-frame signal uniformity correction method, electronic device, storage medium

Abstract

The application relates to an intra-frame signal uniformity correction method, an electronic device and a storage medium, which comprises the following steps: controlling the emission of ultrasonic signals and the reception of echo signals of the ultrasonic signals in a rotation cycle through an ultrasonic excitation system to realize equidistant uniform sampling; combining angle tracking information of a transducer emission surface in a magnetic positioning system to update a raw time-angle mapping diagram in the rotation cycle in real time; processing the raw time-angle mapping diagram through a uniform correction algorithm; and arranging data of one rotation cycle in each angle direction according to the processed time-angle mapping diagram. The application can solve the problem of a rotation deviation angle with a certain mathematical rule in a driving magnetic field for the motion track of an interventional ultrasonic imaging catheter driven by a rotating magnetic field, complete uniform correction of an image, and obtain an accurate magnetic driving interventional image.

Description

Technical Field

[0001] This invention relates to the field of ultrasonic signal processing technology, and in particular to an intra-frame signal uniformity correction method, electronic device, and storage medium. Background Technology

[0002] Currently, most rotating imaging systems use a rigid connection where the ultrasound imaging catheter and the drive unit are in direct contact. However, the uniformity of the ultrasound signal distribution is not addressed during signal processing, resulting in errors in the angular distribution of the rotating ultrasound image compared to the actual situation.

[0003] When an ultrasound imaging catheter rotates under a magnetically driven system, the imaging guidewire is affected by magnetic force and friction from the rear conductor within the catheter lumen, resulting in an uneven distribution of the angular velocity of the single-element transducer on the guidewire at each angle. However, due to the controllability of the front-end drive system, the angular velocity of the rotating imaging unit can be more precisely distributed. Combining the simulation results of the magnetically driven rotation system, it is now possible to accurately construct the motion parameter model of the imaging unit within a single image frame (i.e., within a 360° circle), providing a theoretical basis for further adjusting the signal distribution uniformity based on actual motion conditions.

[0004] In ultrasound signal processing, linear interpolation is commonly used to smooth images and make them more detailed. However, indiscriminate interpolation between image lines cannot effectively correct the uniformity of rotating ultrasound images, and the angular velocity distribution of rotational motion should also be a key parameter in the interpolation process. Based on the above, this invention proposes a method for correcting intra-frame image uniformity. By combining the rotational characteristics of an ultrasound catheter under magnetic drive, it provides accurate data distribution and processing methods for magnetically driven rotational imaging. Summary of the Invention

[0005] In order to achieve the above-mentioned objectives and other advantages of the present invention, a first objective of the present invention is to provide an intra-frame signal uniformity correction method, comprising the following steps:

[0006] By controlling the transmission of ultrasonic signals and the reception of ultrasonic echo signals within one week through an ultrasonic excitation system, uniform sampling at equal intervals can be achieved.

[0007] By combining the angle tracking information of the transducer's emitting surface in the magnetic positioning system, the original time-angle mapping diagram within this rotation cycle is updated in real time.

[0008] The original time-angle mapping is processed using a uniform correction algorithm;

[0009] The data for one rotation cycle are arranged in each angular direction based on the processed time-angle mapping.

[0010] Furthermore, the uniform correction algorithm is a spline interpolation method, which is used to process the original time-angle mapping.

[0011] Furthermore, the step of processing the original time-angle mapping using spline interpolation includes refining the angle value calculation by increasing the number of samples in time, so that the final time-angle mapping is continuously differentiable within a preset range.

[0012] Furthermore, the final time-angle mapping includes the angle range occupied by each data line, as well as the parameters of spline interpolation used between adjacent data lines.

[0013] Furthermore, the step of processing the original time-angle mapping using spline interpolation includes the following steps:

[0014] Multiple spline piecewise interpolation is applied to the discrete data in the original time-angle mapping;

[0015] The unknowns are determined by the number of intervals formed by discrete points and by multiple splines;

[0016] The equation is determined by the multiple functions that the endpoints of the discrete data pass through, and the multiple functions that the intermediate points of the discrete data pass through.

[0017] The equation is determined by the continuity at the intermediate points of the discrete data;

[0018] The equation is determined by assuming that the multi-order derivative of the equation corresponding to the first endpoint of the discrete data is 0.

[0019] Solve the given equations simultaneously to find the unknowns.

[0020] Furthermore, the step of applying multiple spline piecewise interpolation to the discrete data in the original time-angle mapping includes applying quadratic spline piecewise interpolation to the discrete data in the original time-angle mapping, where each quadratic spline is ax. 2 +bx+c.

[0021] Furthermore, the equations determined by the multiple functions traversed by the endpoints of the discrete data and the multiple functions traversed by the intermediate points of the discrete data include the equations determined by the quadratic functions traversed by the endpoints of the discrete data and the quadratic functions traversed by the intermediate points of the discrete data.

[0022] Furthermore, the equation for determining continuity at the midpoint of discrete data includes an equation for determining continuity when the first derivatives of the left and right quadratic functions at the midpoint of discrete data are equal.

[0023] The method of determining the equation by assuming that the first endpoint of the discrete data corresponds to the equation with a multi-order derivative of 0 includes determining the equation by assuming that the first endpoint of the discrete data corresponds to the equation with a second-order derivative of 0.

[0024] A second objective of the present invention is to provide an electronic device comprising: a memory having program code stored thereon; and a processor connected to the memory, wherein when the program code is executed by the processor, an intra-frame signal uniformity correction method is implemented.

[0025] A third objective of this invention is to provide a computer-readable storage medium having program instructions stored thereon, which, when executed, implement an intra-frame signal uniformity correction method.

[0026] Compared with the prior art, the beneficial effects of the present invention are:

[0027] This invention provides an intra-frame signal uniformity correction method that can address the rotational deviation angle with a certain mathematical regularity in the driving magnetic field of the interventional ultrasound imaging catheter driven by a rotating magnetic field, thereby completing the uniform correction of the image and obtaining accurate magnetically driven interventional images.

[0028] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it according to the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings. Specific embodiments of the present invention are given in detail below with reference to the accompanying drawings. Attached Figure Description

[0029] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0030] Figure 1 This is a flowchart of an intra-frame signal uniformity correction method according to Example 1;

[0031] Figure 2 This is a schematic diagram illustrating the principle of quadratic spline interpolation in Example 1;

[0032] Figure 3 This is a schematic diagram of the electronic device in Example 2;

[0033] Figure 4 This is a schematic diagram of the storage medium in Example 3. Detailed Implementation

[0034] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments. It should be noted that, without conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments.

[0035] The trajectory of the interventional ultrasound imaging catheter is determined by the field strength distribution of the driving magnetic field, and is also affected by NERD generated by the rotational motion of the ultrasound transducer and the rear lead wire within the catheter, making it a complex stress scenario. Therefore, this invention employs a uniform correction method. By analyzing the azimuth information in the actual transmitted and received signals of the transducer, a distribution map of the angular span and time relationship of all transmitted and received signals across the transmitting surface of the ultrasound transducer during one rotation is obtained. Based on this, the current frame image is reconstructed and uniformly distributed in real time, thereby eliminating discrete motion differences between different data lines within the ultrasound image frame obtained under the drive of the rotating magnetic field, and maximizing the authenticity of the image within the frame.

[0036] Example 1

[0037] An intra-frame signal uniformity correction method, combining spline interpolation, addresses the problem of non-uniform signals generated by intra-frame rotational forces, which negatively impacts the quality of subsequent images. For example... Figure 1 As shown, the specific steps include:

[0038] By controlling the transmission of ultrasonic signals and the reception of ultrasonic echo signals within one week through an ultrasonic excitation system, uniform sampling at equal intervals can be achieved.

[0039] By combining the angle tracking information of the transducer's emitting surface in the magnetic positioning system, the original time-angle mapping diagram within this rotation cycle is updated in real time.

[0040] Considering the discreteness of the mapping map and the fluctuation of the angle value within a single sampling time, a uniform correction algorithm is used to process the original time-angle mapping map. In this embodiment, the uniform correction algorithm is a spline interpolation method. By increasing the number of samples in time, the angle value is calculated in segments to make the final time-angle mapping map continuous and differentiable within a certain range.

[0041] Spline interpolation is a mathematical method that uses variable splines to construct a smooth curve passing through a series of points. Interpolation splines consist of polynomials, each determined by two adjacent data points. Thus, any two adjacent polynomials and their derivatives are continuous at the connection points.

[0042] The original time-angle mapping map is processed using spline interpolation, including the following steps:

[0043] Multiple spline piecewise interpolation is applied to the discrete data in the original time-angle mapping plot;

[0044] The unknowns are determined by the number of intervals formed by discrete points and by multiple splines;

[0045] The equation is determined by the multiple functions that the endpoints of the discrete data pass through, and the multiple functions that the intermediate points of the discrete data pass through.

[0046] The equation is determined by the continuity at the intermediate points of the discrete data;

[0047] The equation is determined by assuming that the multi-order derivative of the equation corresponding to the first endpoint of the discrete data is 0.

[0048] Solve the given equations simultaneously to find the unknowns.

[0049] In the original time-angle mapping plot, the discrete data distribution is relatively simple, and piecewise quadratic spline interpolation can meet the requirement of smooth and differentiable curves. For example... Figure 2 As shown, taking four discrete points x0, x1, x2, and x3 as an example, three intervals require three quadratic splines, each quadratic spline being ax 2 Therefore, there are a total of 9 unknowns, where bx + c. The solution process is as follows:

[0050] ①Since a quadratic function passes through both endpoints x0 and x3, two equations can be determined;

[0051] ②Two quadratic functions pass through the two intermediate points x1 and x2, thus four equations can be determined;

[0052] ③ The function must be continuous at the midpoint, ensuring that the first derivatives of the left and right quadratic functions are equal.

[0053]

[0054] Two equations can be determined, and now we have eight equations.

[0055] ④ Here, we assume the second derivative of the first equation is 0, i.e., a1 = 0, which gives us another equation, making a total of 9 equations. These can be solved simultaneously.

[0056] Due to the complexity of the imaging environment and the large numerical differences between tissue structures and image lines, spline interpolation can be performed using functions of higher order to obtain a smoother effect, following the same calculation principles as described above.

[0057] The processed time-angle map accurately arranges the data from one rotation in each angular direction. The final time-angle map includes the angular range occupied by each data line and the spline interpolation parameters used between adjacent data lines, ensuring a uniform transition in size and pixel values ​​between image lines without affecting image flatness.

[0058] Example 2

[0059] An electronic device 200, such as Figure 3 As shown, the method includes, but is not limited to: a memory 201 storing program code; and a processor 202 connected to the memory, which, when executed by the processor, implements an intra-frame signal uniformity correction method. For a detailed description of the method, please refer to the corresponding description in the above method embodiments, which will not be repeated here.

[0060] Example 3

[0061] A computer-readable storage medium, such as Figure 4 As shown, it stores program instructions, which, when executed, implement an intra-frame signal uniformity correction method. For a detailed description of the method, please refer to the corresponding description in the above method embodiments; it will not be repeated here.

[0062] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0063] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0064] The above are merely embodiments of this specification and are not intended to limit the scope of one or more embodiments of this specification. Various modifications and variations can be made to one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of one or more embodiments of this specification.

Claims

1. A method for intra-frame signal uniformity correction, characterized in that, Includes the following steps: By controlling the transmission of ultrasonic signals and the reception of ultrasonic echo signals within one week through an ultrasonic excitation system, uniform sampling at equal intervals can be achieved. By combining the angle tracking information of the transducer's emitting surface in the magnetic positioning system, the original time-angle mapping diagram within this rotation cycle is updated in real time. The original time-angle mapping is processed using a uniform correction algorithm; Arrange the data for one rotation cycle in each angular direction based on the processed time-angle mapping; The uniform correction algorithm is a spline interpolation method, which is used to process the original time-angle mapping. The step of processing the original time-angle mapping using spline interpolation includes the following steps: Multiple spline piecewise interpolation is applied to the discrete data in the original time-angle mapping; The unknowns are determined by the number of intervals formed by discrete points and by multiple splines; The equation is determined by the multiple functions that the endpoints of the discrete data pass through, and the multiple functions that the intermediate points of the discrete data pass through. The equation is determined by the continuity at the intermediate points of the discrete data; The equation is determined by assuming that the multi-order derivative of the equation corresponding to the first endpoint of the discrete data is 0. Solve the given equations simultaneously to find the unknowns; The step of applying multiple spline piecewise interpolation to the discrete data in the original time-angle map includes applying quadratic spline piecewise interpolation to the discrete data in the original time-angle map, where each quadratic spline is... ; The equations determined by multiple functions passing through the endpoints of discrete data and multiple functions passing through the midpoints of discrete data include quadratic functions passing through the endpoints of discrete data and quadratic functions passing through the midpoints of discrete data. The equation for determining continuity at the midpoint of discrete data includes an equation for determining continuity when the first derivatives of the left and right quadratic functions are equal at the midpoint of discrete data. The method of determining the equation by assuming that the first endpoint of the discrete data corresponds to the equation with a multi-order derivative of 0 includes determining the equation by assuming that the first endpoint of the discrete data corresponds to the equation with a second-order derivative of 0.

2. The intra-frame signal uniformity correction method as described in claim 1, characterized in that: The step of processing the original time-angle mapping using spline interpolation includes increasing the number of time samples and refining the angle value calculation by segmentation, so that the final time-angle mapping is continuous and differentiable within a preset range.

3. The intra-frame signal uniformity correction method as described in claim 2, characterized in that: The final time-angle mapping includes the angle range occupied by each data line, as well as the spline interpolation parameters used between adjacent data lines.

4. An electronic device, characterized in that, include: A memory that stores program code; A processor, which is connected to the memory, and which, when the program code is executed by the processor, implements the method as described in any one of claims 1 to 3.

5. A computer-readable storage medium, characterized in that, It stores program instructions that, when executed, implement the method as described in any one of claims 1 to 3.

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