Image clarity evaluation method, focusing method and related equipment

Abstract

The present invention provides an image clarity evaluation method, comprising: obtaining a preset image; determining all pixel points of the preset image in a preset direction, wherein the preset direction includes several directions; calculating a first Reiney entropy sum value of all the pixel points in each direction; calculating a Reiney entropy target value of the preset image according to the first Reiney entropy sum value; and evaluating the clarity of the preset image according to the Reiney entropy target value. The present invention also provides a focusing method, a gene sequencing system, a gene sequencer, and a storage medium. By using the present invention, image clarity evaluation operations and focusing operations can be optimized.

Description

Technical Field

[0001] The present invention relates to the field of gene sequencing technology, and in particular to an image clarity evaluation method, a focusing method, a gene sequencing system, a gene sequencer and a storage medium. Background Art

[0002] Gene sequencing refers to the analysis of the base sequence of a specific DNA fragment, that is, the arrangement of adenine (A), thymine (T), cytosine (C) and guanine (G). One of the commonly used sequencing methods at present is that the above four bases carry different fluorescent groups, and different fluorescent groups emit fluorescence of different wavelengths (colors) after being excited. By identifying the fluorescence wavelength, the type of synthesized base can be identified, thereby reading the base sequence. The second-generation sequencing technology uses a high-resolution microscopic imaging system to take pictures and collect the fluorescent molecular images of DNA nanoballs (DNB, DNA Nanoballs) on the biochip (gene sequencing chip), and send the fluorescent molecular images to the base recognition software to interpret the image signals to obtain the base sequence. The imaging quality of the microscopic imaging link of the gene sequencer has a great influence on the accuracy of base recognition. When taking pictures, the platform for loading the biochip is generally moved, and the camera does not move. However, a small movement of the platform will cause the fluorescent molecular image to be out of focus. The autofocus software traverses the nearby focal planes at the current position, and uses a specific image clarity evaluation method to move the platform to the focal plane with the highest clarity.

[0003] In the prior art, Fourier transform method or Gaussian fitting method is generally used to evaluate the clarity of fluorescent images. When the Fourier transform method is used to evaluate the clarity of fluorescent images, the low-frequency area mean is required as a reference, and the image cannot be evaluated without reference; and the low-frequency area mean of the fluorescent image is obtained by low-pass filtering. The parameters of the low-pass filter need to be adjusted for different models of gene sequencers and biochips, which is not universal. When the Gaussian fitting method is used to evaluate the clarity of fluorescent images, the spot images of two adjacent DNA nanoballs will be partially superimposed, resulting in the intensity distribution of the two spot images not conforming to the Gaussian distribution; and in order to reduce the superposition of grayscale, the existing algorithm traverses the fluorescent molecules in the image to find relatively isolated fluorescent molecules. This method is also easy to classify noise points as fluorescent molecules, resulting in inaccurate image clarity evaluation. In addition, due to the presence of image background and background noise, the parameters of the Gaussian fitting model need to be adjusted for different models of gene sequencers and biochips, so it is not universal.

[0004] Therefore, there is an urgent need to provide a method for image clarity evaluation and focusing that is highly universal and reference-free. Summary of the invention

[0005] In view of the above, it is necessary to propose an image clarity evaluation method, a focusing method, a gene sequencing system, a gene sequencer and a computer-readable storage medium, which can optimize the image clarity evaluation and focusing operation.

[0006] A first aspect of an embodiment of the present invention provides an image clarity evaluation method, the image clarity evaluation method comprising:

[0007] Get the preset image;

[0008] Determine all pixel points of the preset image in a preset direction, where the preset direction includes several directions;

[0009] Calculate the first Rainey entropy sum value of all the pixel points in each direction;

[0010] Calculating a Raney entropy target value of the preset image according to the first Raney entropy sum value;

[0011] The clarity of the preset image is evaluated according to the Rainey entropy target value.

[0012] Furthermore, in the above-mentioned image clarity evaluation method provided by the embodiment of the present invention,

[0013] The calculating of the first Rainey entropy sum value of all the pixel points in each direction comprises:

[0014] Obtain all pixel points of the preset image in each direction;

[0015] Determine the position information of each pixel point in the preset image and the preset window length;

[0016] Formula 1 is called according to the position information and the preset window length to obtain one-dimensional pseudo-Wigner distribution data corresponding to each pixel point;

[0017]

[0018] Where n is the position information of each pixel, N is the preset window length, k is the frequency variable, and m is the discrete translation parameter;

[0019] Formula 2 is called according to the one-dimensional pseudo-Wigner distribution data to obtain the Raney entropy value of each pixel in the preset image;

[0020]

[0021] A first Raney entropy sum value of all the pixels in each direction is calculated according to the Raney entropy value of each pixel.

[0022] Furthermore, in the above-mentioned image clarity evaluation method provided by an embodiment of the present invention, the calculating the Raney entropy target value of the preset image according to the first Raney entropy sum value comprises:

[0023] Calculating a second Reiney entropy sum value of the preset image in a preset direction according to the first Reiney entropy sum value;

[0024] or calculating a second Reiney entropy sum value of the preset image in a preset direction according to the first Reiney entropy sum value, and calculating the Reiney entropy average value of the preset image according to the second Reiney entropy sum value by calling formula 4;

[0025]

[0026] Where S is the number of preset directions, θ s is the direction variable value, t is the number mark of the preset image, is the first Reine entropy sum, is the second Reiney entropy sum;

[0027] or calculating a second Reiney entropy sum value of the preset image in a preset direction according to the first Reiney entropy sum value, and calculating a Reiney entropy standard deviation value of the preset image according to formula 5 based on the second Reiney entropy sum value;

[0028]

[0029] Alternatively, a second Reiney entropy sum value of the preset image in a preset direction is calculated according to the first Reiney entropy sum value, and Formula 6 is called according to the second Reiney entropy sum value to calculate a normalized standard deviation value of the Reiney entropy of the preset image.

[0030]

[0031] Furthermore, in the above-mentioned image clarity evaluation method provided by an embodiment of the present invention, calculating the second Reiney entropy sum value of the preset image in a preset direction according to the first Reiney entropy sum value includes:

[0032] Obtaining a direction variable value corresponding to the preset direction;

[0033] Determining the number of the preset directions;

[0034] Formula 3 is called according to the first Reiney entropy sum value, the direction variable value and the quantity to obtain a second Reiney entropy sum value of the preset image in the preset direction;

[0035]

[0036] Where S is the number of preset directions, θ sis the direction variable value, t is the number mark of the preset image, is the first Reine entropy sum.

[0037] A second aspect of an embodiment of the present invention provides a method for focusing using any one of the above-mentioned image clarity evaluation methods, the focusing method comprising:

[0038] Acquire a preset objective lens position, wherein the preset objective lens position includes a first objective lens position and a second objective lens position;

[0039] Calling the objective lens to capture the target image corresponding to the preset objective lens position;

[0040] Calculate the Rainey entropy target value of the target image according to the image clarity evaluation method;

[0041] Determine the preset objective lens position with the largest Rainey entropy target value as the target objective lens position;

[0042] Adjust the objective lens to the target objective lens position.

[0043] Furthermore, in the above-mentioned focusing method provided by an embodiment of the present invention, the step of calling the objective lens to capture the target image corresponding to the preset objective lens position is:

[0044] Acquire an initial position of the objective lens, wherein the initial position is consistent with the position of the first objective lens;

[0045] Calling the objective lens to capture a first image corresponding to the position of the first objective lens;

[0046] Move the objective lens to a second objective lens position according to a preset step;

[0047] The objective lens is called to capture a second image corresponding to the position of the second objective lens.

[0048] Furthermore, in the above-mentioned focusing method provided by an embodiment of the present invention, the step of adjusting the objective lens to the target objective lens position includes:

[0049] Get the current objective lens position;

[0050] Acquire the moving path of the current objective lens position and the target objective lens position;

[0051] The objective lens is moved to the target objective lens position according to the moving path and at a preset step.

[0052] A third aspect of an embodiment of the present invention further provides a gene sequencing system, the gene sequencing system comprising:

[0053] An image acquisition module, used for acquiring a preset image;

[0054] A pixel point determination module, used to determine all pixel points of the preset image in a preset direction, where the preset direction includes several directions;

[0055] A first sum calculation module, used for calculating the first Rainey entropy sum value of all the pixel points in each direction;

[0056] A target value calculation module, used for calculating a target value of the Raney entropy of the preset image according to the first Raney entropy sum value;

[0057] The clarity evaluation module is used to evaluate the clarity of the preset image according to the Rainey entropy target value.

[0058] A fourth aspect of an embodiment of the present invention further provides a gene sequencer, wherein the sequencer includes a processor, and the processor is used to implement the steps of the image clarity evaluation method as described in any one of the above and the focusing method as described in any one of the above when executing a computer program stored in a memory.

[0059] A fifth aspect of an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the image clarity evaluation method as described in any one of the above items and the focusing method as described in any one of the above items are implemented.

[0060] The embodiment of the present invention provides an image clarity evaluation method, a focusing method, a gene sequencing system, a gene sequencer, and a computer-readable storage medium, which obtain a preset image; determine all pixel points of the preset image in a preset direction, wherein the preset direction includes several directions; calculate the first Reiney entropy sum value of all the pixel points in each direction; calculate the Reiney entropy target value of the preset image according to the first Reiney entropy sum value; and evaluate the clarity of the preset image according to the Reiney entropy target value. By using the present invention, there is no need to adjust the image clarity evaluation function for different models of biochips and different models of gene sequencers, and the present invention has good universality; and the present invention does not need to refer to the background image when evaluating the clarity of the image, and has good non-reference; in addition, the present invention evaluates the image clarity based on the entire image or a partial image, avoids using a single point to evaluate the clarity, has comprehensiveness, and improves the accuracy of the image clarity evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a flow chart of an image clarity evaluation method provided by an embodiment of the present invention.

[0062] Figure 2 is a flow chart of a focusing method provided by an embodiment of the present invention.

[0063] FIG. 3( a ) is a schematic diagram of a fluorescent image of a preset objective lens position provided in an embodiment of the present invention.

[0064] FIG3( b ) is a graph showing the relationship between the clarity of the fluorescent image shown in FIG3( a ) and the position of the objective lens.

[0065] Figure 4 It is a schematic diagram of the structure of a gene sequencer according to an embodiment of the present invention.

[0066] Figure 5 yes Figure 4 An exemplary functional module diagram of a gene sequencer is shown.

[0067] Figure 6 yes Figure 4 Another exemplary functional module diagram of a gene sequencer is shown.

[0068] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0069] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0070] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. The embodiments described are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0072] Figure 1 is a flow chart of an image clarity evaluation method provided by an embodiment of the present invention. The image clarity evaluation method can be used to evaluate the clarity of an image. In one embodiment, the image clarity evaluation method can be used to evaluate the clarity of a fluorescent image corresponding to a biochip, and the biochip can be a gene sequencing chip. Figure 1 As shown, the image clarity evaluation method may include the following steps:

[0073] S11, obtaining a preset image.

[0074] In at least one embodiment of the present invention, a preset image is obtained, and the preset image can be an image captured by any optical imaging system. Taking the preset image as a fluorescent image as an example, the fluorescent image can be an image obtained by the emission of fluorescent molecules during the sequencing process, and a microscopic camera can be used to continuously photograph the biochip to obtain a number of fluorescent images. It should be noted that in the present invention, "fluorescent image" refers to an image obtained by locally magnifying a field of view (FOV) obtained by photographing the biochip with a microscopic camera at one time. The field of view of a microscopic camera is generally small, and during the sequencing process, hundreds or thousands of fluorescent images can be taken of the biochip.

[0075] For some types of chips, the horizontal and vertical directions of the fluorescent image are each distributed with several track lines, and the intersection of the track lines is a track cross. The area between two adjacent horizontal and vertical track lines of the fluorescent image is called a block, and each block is filled with spots. Preferably, the spots are evenly distributed. The spots are used to adsorb DNA nanoball molecules (DNB), which can be amplified products including DNA fragments. The DNA nanoball molecules carry fluorescent molecules when synthesizing bases, and the fluorescent molecules emit fluorescent signals when excited.

[0076] S12: Determine all pixel points of the preset image in a preset direction, where the preset direction includes several directions.

[0077] In at least one embodiment of the present invention, all pixel points of the preset image in a preset direction are determined, wherein the pixel point can be understood as the smallest image unit recognizable by the optical imaging system, and the position information of all pixel points of the preset image in the preset direction can be determined.

[0078] The number of preset directions is several, and the number of preset directions and the direction variable values ​​of the preset directions can be determined according to actual sequencing requirements. For example, the number of preset directions is 6, and the direction variable values ​​can be: 0°, 30°, 60°, 90°, 120°, 150°, which are not limited here.

[0079] S13, calculating the first Raney entropy sum value of all the pixel points in each direction.

[0080] In at least one embodiment of the present invention, the clarity of the preset image is evaluated by combining the generalized Renyi entropy with the normalized pseudo-Wigner distribution. The randomness of the grayscale value of the pixel is evaluated by calculating the Renyi entropy value of each pixel on the preset image. The direction selection when calculating the Renyi entropy value can be implemented by, but not limited to, one-dimensional pseudo-Wigner distribution (in other embodiments, improvements similar to one-dimensional pseudo-Wigner distribution can also be used). The change in the Renyi entropy value is a function of the direction and can be used as an evaluation index of the anisotropy of the preset image. The greater the degree of anisotropy, the better the clarity of the preset image; the smaller the degree of anisotropy, the worse the clarity of the preset image.

[0081] In one embodiment, the Rainey entropy generally applied to discrete space-frequency distribution P[n,k] can be expressed as:

[0082]

[0083] Here, n and k represent spatial and frequency variables, and α ≥ 2.

[0084] In the application process of the Reiney entropy, the Reiney entropy value needs to be normalized so that the Reiney entropy value can be used as a unified standard to compare the image clarity under different distribution conditions. In one embodiment, the steps of normalizing the Reiney entropy value include but are not limited to: signal energy normalization, distribution capacity normalization and quantum normalization. For example, when signal energy normalization is adopted, the normalized Reiney entropy RE α for:

[0085]

[0086] When the distribution capacity is used for normalization, the normalized Rainey entropy RV α (usually α=3) is:

[0087]

[0088] When quantum normalization is used, a similar approach to quantum mechanics is used to represent the spatial-frequency distribution P of a specific position n using a wave function, through The probability distribution function can be calculated and then normalized to satisfy For example, when α = 3, the Raney entropy in formula (1) is:

[0089]

[0090] For a specific position n, formula (4) can be simplified to:

[0091]

[0092] in use After normalization, we can get Satisfy the normalization conditions: For any n, 1≤n≤M, -N / 2≤k≤N / 2-1 is satisfied. Here, M is the size of the data, which can be regarded as the size of the fluorescence image collected by the gene sequencer, that is, the maximum number of all pixels in the fluorescence image, and N is the preset window length for calculating the Rainey entropy.

[0093] In at least one embodiment of the present invention, the step of calculating the first Reiney entropy sum value of all the pixel points in each direction includes: obtaining all pixel points of the preset image in each direction; determining the position information and the preset window length of each pixel point in the preset image; calling formula 1 according to the position information and the preset window length to obtain the one-dimensional pseudo-Wigner distribution data corresponding to each pixel point; calling formula 2 according to the one-dimensional pseudo-Wigner distribution data to obtain the Reiney entropy value of each pixel point in the preset image; and calculating the first Reiney entropy sum value of all pixel points in each direction according to the Reiney entropy value of each pixel point.

[0094]

[0095]

[0096] Among them, n is the position information of each pixel, N is the preset window length, k is the frequency variable, and m is the discrete translation parameter.

[0097] In at least one embodiment of the present invention, for a single pixel in the preset image (the position of the pixel is n), a specific one-dimensional pseudo-Wigner distribution (because it is not a standard Wigner distribution, it is called a pseudo-Wigner distribution) corresponds, and the one-dimensional pseudo-Wigner distribution can be obtained by calculating adjacent pixels with a preset window length of N. It can be understood that by using a one-dimensional transformation of the preset image with a preset window length of N, the Raney entropy value can be calculated in any direction of the preset image; and compared with the two-dimensional pseudo-Wigner distribution, the calculation time of the one-dimensional pseudo-Wigner distribution is shorter; in addition, the one-dimensional pseudo-Wigner distribution is a reversible function, which can ensure that information is not lost during the transformation process.

[0098] Specifically, Formula 1 can be used to process the one-dimensional pseudo-Wigner distribution of a single pixel, where {z[n]} in Formula 1 is the one-dimensional grayscale value data of the preset window with a length of N pixels along the preset direction of the preset image. Formula 1 can be regarded as z[n+m]z *[nm] is discrete Fourier transformed (* indicates complex conjugate), and the frequency domain distribution information can be obtained in the [-N / 2, N / 2-1] window area at the pixel position n. When the window is moved on the preset image, the frequency domain distribution information of each pixel can be obtained. The window can be moved in any direction along the preset image, and the frequency domain distribution information of each pixel on the preset image along any direction can be obtained.

[0099] In at least one embodiment of the present invention, for a discrete sequence z[n], within a window centered at position n and having a preset window length of N, a one-dimensional pseudo-Wigner distribution can be obtained according to Formula 1; then the local one-dimensional pseudo-Wigner distribution is subjected to the aforementioned quantum normalization, Formula (5) is simplified, and the Rainey entropy value corresponding to the pixel point at position n on the preset image is obtained (as shown in Formula 2).

[0100] In at least one embodiment of the present invention, formula (6) is called according to the Raney entropy value of each pixel point to calculate the first Raney entropy sum value of all the pixel points in each direction.

[0101]

[0102] Wherein, t(t∈[1,2,…,T]) is the number mark of the preset images, T is the number of preset images near the focus (T can be set according to actual needs), S is the number of the preset directions, θ s is the direction variable value, M is the size of the data, which can be regarded as the size of the preset image collected by the gene sequencer, that is, the maximum number of all pixels in the preset image.

[0103] S14. Calculating a Raney entropy target value of the preset image according to the first Raney entropy sum value.

[0104] In at least one embodiment of the present invention, the Rainey entropy target value is used to evaluate the image clarity of the preset image, and the function used to evaluate the image clarity is also called an image clarity evaluation function.

[0105] The target value of the Raney entropy includes one of the second Raney entropy sum value, the average value of the Raney entropy calculated by the second Raney entropy sum value, the standard deviation value of the Raney entropy calculated by the second Raney entropy sum value, and the normalized standard deviation value of the Raney entropy calculated by the second Raney entropy sum value. Preferably, the target value of the Raney entropy is the average value of the Raney entropy. It can be understood that since the present invention considers each pixel point when calculating the average value of the Raney entropy, compared with the Gaussian fitting method which only considers some isolated spots, the evaluation of the image clarity of the present invention is comprehensive; and since the present invention does not need to adjust parameters like the Gaussian fitting method and the Fourier transform method for different models of gene sequencers and different models of biochips, the image clarity evaluation method provided by the present invention is more universal; in addition, the present invention does not need to consider the background image when calculating the average value of the Raney entropy, compared with the Fourier transform method which needs to calculate the difference between the peak value of the high-frequency region and the mean value of the low-frequency region (which can be regarded as the background image), and needs to use the mean value of the low-frequency region as a reference, the image clarity evaluation method provided by the present invention has good non-reference property.

[0106] Specifically, the calculating the Reiney entropy target value of the preset image according to the first Reiney entropy sum value includes: calculating a second Reiney entropy sum value of the preset image in a preset direction according to the first Reiney entropy sum value;

[0107] or calculating a second Raney entropy sum value of the preset image in a preset direction according to the first Raney entropy sum value, and calculating the Raney entropy average value of the fluorescence image according to Formula 4 based on the second Raney entropy sum value;

[0108]

[0109] Where S is the number of preset directions, θ s is the direction variable value, t is the number mark of the preset image, is the first Reine entropy sum, is the second Reiney entropy sum;

[0110] or calculating a second Reiney entropy sum value of the preset image in a preset direction according to the first Reiney entropy sum value, and calculating a Reiney entropy standard deviation value of the preset image according to formula 5 based on the second Reiney entropy sum value;

[0111]

[0112] Alternatively, a second Reiney entropy sum value of the preset image in a preset direction is calculated according to the first Reiney entropy sum value, and a normalized standard deviation value of the Reiney entropy of the preset image is calculated by calling Formula 6 according to the second Reiney entropy sum value.

[0113]

[0114] In at least one embodiment of the present invention, the clarity of an image can be evaluated by anisotropy, and the anisotropy can be evaluated by calculating the Raney entropy of each pixel in the image along multiple directions. The Raney entropy value of each pixel in the image can be obtained according to Formula 2. In order to calculate the anisotropy, the directional variable value θ is added to Formula 2. s (s∈[1,2,…,S]), S is the number of the preset directions.

[0115] The step of determining the second Reiney entropy sum value of the preset image in the preset direction according to the first Reiney entropy sum value comprises: obtaining a direction variable value corresponding to the preset direction; determining the number of the preset directions; calling formula 3 according to the first Reiney entropy sum value, the direction variable value and the number to obtain the second Reiney entropy sum value of the preset image in the preset direction;

[0116]

[0117] Where S is the number of preset directions, θ s is the direction variable value, t is the number mark of the preset image, is the first Reine entropy sum.

[0118] S15. Evaluate the clarity of the preset image according to the Rainey entropy target value.

[0119] In at least one embodiment of the present invention, the Raney entropy target value reflects the degree of anisotropy of the image, and the Raney entropy target value can be used to evaluate the clarity of the preset image. As can be seen from the above description, the Raney entropy target value includes multiple variables, including: S (the number of the preset directions), θ s (direction variable value) and n (position information of each pixel point). When the values ​​of multiple variables of the Reiney entropy target value are the same, the higher the Reiney entropy target value, the better the clarity of the corresponding preset image; conversely, the lower the Reiney entropy target value, the worse the clarity of the corresponding preset image.

[0120] In at least one embodiment of the present invention, the clarity of the preset image can be evaluated in multiple application scenarios according to the Raney entropy target value. For example, the Raney entropy target value can be used to evaluate the clarity of the image in a focusing scene, which is not limited here.

[0121] The embodiment of the present invention provides an image clarity evaluation method, which includes obtaining a preset image; determining all pixel points of the preset image in a preset direction, wherein the preset direction includes several directions; calculating a first Reiney entropy sum value of all the pixel points in each direction; calculating a Reiney entropy target value of the preset image according to the first Reiney entropy sum value; and evaluating the clarity of the preset image according to the Reiney entropy target value. The present invention does not need to adjust the image clarity evaluation function for different models of biochips and different models of gene sequencers, and has good universality; and the present invention does not need to refer to a background image when analyzing the clarity of an image, and has good non-reference performance; in addition, the present invention evaluates the image clarity based on the entire image or a partial image, avoids using a single pixel point to analyze the image clarity, has comprehensiveness, and improves the accuracy of image clarity evaluation.

[0122] Figure 2 is a flow chart of a focusing method provided by an embodiment of the present invention. The focusing method can use the image clarity evaluation method provided by an embodiment of the present invention to evaluate image clarity, thereby achieving focusing of an optical imaging system (the optical imaging system includes an objective lens). Figure 2 As shown, the focusing method may include the following steps:

[0123] S21, obtaining a preset objective lens position, wherein the preset objective lens position includes a first objective lens position and a second objective lens position.

[0124] In at least one embodiment of the present invention, a preset objective lens position is obtained, and the preset objective lens position includes a first objective lens position and a second objective lens position. The first objective lens position may correspond to the initial position of the objective lens, the second objective lens position may be a position near the focal point of the objective lens, and the second objective lens position and the number of the second objective lens positions may be preset by a focusing person according to actual needs, and are not limited here.

[0125] S22, calling the objective lens to capture the target image corresponding to the preset objective lens position.

[0126] In at least one embodiment of the present invention, the step of calling the objective lens to capture the target image corresponding to the preset objective lens position includes: obtaining the initial position of the objective lens, the initial position being consistent with the first objective lens position; calling the objective lens to capture the first image corresponding to the first objective lens position; moving the objective lens to the second objective lens position according to the preset step; calling the objective lens to capture the second image corresponding to the second objective lens position. The smaller the preset step distance, the higher the focusing accuracy.

[0127] S23. Calculate the Raney entropy target value of the target image according to the image clarity evaluation method.

[0128] In at least one embodiment of the present invention, the target value of the Raney entropy of the target image is calculated according to the image clarity evaluation method, wherein the target value of the Raney entropy includes one of the second Raney entropy sum value, the Raney entropy average value calculated by the second Raney entropy sum value, the Raney entropy standard deviation value calculated by the second Raney entropy sum value, and the Raney entropy normalized standard deviation value, and preferably, the Raney entropy target value is the Raney entropy average value. The calculation method of the Raney entropy target value has been described in detail above and will not be repeated here.

[0129] In at least one embodiment of the present invention, the method further includes: when the number of the target images is greater than 1, obtaining the number of the target images; calling subthreads corresponding to the number; and performing image clarity evaluation operations in parallel through the subthreads. It is understandable that by using a multi-threaded approach to perform image clarity evaluation on the target images in parallel, the image clarity evaluation rate can be increased, thereby improving the focusing efficiency.

[0130] S24, determining the preset objective lens position with the largest Rainey entropy target value as the target objective lens position.

[0131] In at least one embodiment of the present invention, the Raney entropy target value corresponds to the target image one-to-one, and the target image corresponds to the objective lens position one-to-one. After obtaining the maximum value of the Raney entropy target value, the target image corresponding to the maximum value is matched according to the mapping relationship, and then the target objective lens position corresponding to the target image is determined. The target objective lens position is the position closest to the focus.

[0132] Exemplarily, as shown in FIG3(a), the objective lens is called to collect a total of 9 fluorescence images corresponding to the preset objective lens position (respectively (a1)-(a9)), and the image clarity evaluation method provided by the embodiment of the present invention is used to evaluate the image clarity of each fluorescence image (in one embodiment, the target value of the Raney entropy is taken as the average value of the Raney entropy as an example), and the average values ​​of the Raney entropy of the 9 fluorescence images are obtained as follows: [0.5226, 0.6662, 0.7833, 0.8337, 0.8543, 0.8703, 0.7945, 0.7139, 0.6235]. By comparison, it is found that the maximum value of the average value of the Raney entropy is 0.8703, which corresponds to the 6th fluorescence image, so that the focal position corresponding to the 6th fluorescence image is determined to be the target objective lens position (as shown in the black solid point in FIG3(b)).

[0133] S25, adjusting the objective lens to the target objective lens position.

[0134] In at least one embodiment of the present invention, the step of adjusting the objective lens to the target objective lens position includes: obtaining the current objective lens position; obtaining the moving path of the current objective lens position and the target objective lens position; and moving the objective lens to the target objective lens position according to a preset step based on the moving path.

[0135] In at least one embodiment of the present invention, after obtaining the moving path between the current objective lens position and the target objective lens position, the method may further include: obtaining a step value corresponding to the moving path; determining a target moving path corresponding to the minimum step value; and controlling the objective lens to move to the target objective lens position according to the target moving path. It is understandable that the number of moving paths between the current objective lens position and the target objective lens position may be one or more. When the number of moving paths is more than one, by selecting the target moving path with the minimum step value to adjust the objective lens, the adjustment time of the objective lens can be reduced and the focusing efficiency can be improved.

[0136] After the objective lens is called to the target objective lens position, the objective lens is focused. After the objective lens is focused, the objective lens can be called to scan the biochip in a preset scanning order to obtain a fluorescent image. The scanning order can be preset by the sequencer, and the preset scanning order includes, but is not limited to, scanning in a top-down order.

[0137] In at least one embodiment of the present invention, the objective lens can be focused before each movement of the chip platform loaded with the biochip, so as to ensure the clarity of the collected fluorescence image (i.e., the focusing operation is performed multiple times). Alternatively, the objective lens only needs to be focused when the objective lens is called to collect the fluorescence image for the first time, so as to ensure the clarity of the collected fluorescence image (i.e., the focusing operation is performed once). Preferably, in the actual sequencing process, since the axial offset caused by the moving chip platform in the horizontal plane after the objective lens is focused has little effect on the clarity of the fluorescence image, the focus only needs to be performed once to ensure the clarity of the fluorescence image.

[0138] The embodiment of the present invention provides a focusing method, which includes obtaining a preset objective lens position, wherein the preset objective lens position includes a first objective lens position and a second objective lens position; calling an objective lens to collect a target image corresponding to the preset objective lens position; calculating the target Raney entropy value of the target image according to the image clarity evaluation method; determining the preset objective lens position with the largest Raney entropy target value as the target objective lens position; and adjusting the objective lens to the target objective lens position. The embodiment of the present invention can optimize the focusing operation.

[0139] The above is a detailed description of the method provided by the embodiment of the present invention. According to different requirements, the execution order of the blocks in the flowchart can be changed, and some blocks can be omitted. The gene sequencer 1 provided by the embodiment of the present invention is described below.

[0140] An embodiment of the present invention further provides a gene sequencer, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the image clarity evaluation method and the focusing method described in any of the above embodiments are implemented. It should be noted that the gene sequencer may include a chip platform, an optical system, and a liquid system. Among them, the chip platform can be used to load a biochip, the optical system can be used to obtain a fluorescent image, and the liquid system can be used to perform a biochemical reaction using a preset reagent.

[0141] Figure 4 FIG. 1 is a schematic diagram of the structure of a gene sequencer according to an embodiment of the present invention. Figure 4 As shown, the gene sequencer 1 includes a memory 10, in which the gene sequencing system 100 is stored. The gene sequencing system 100 can obtain a preset image; determine all pixel points of the preset image in a preset direction, and the preset direction includes several directions; calculate the first Reiney entropy sum value of all the pixel points in each direction; calculate the Reiney entropy target value of the preset image according to the first Reiney entropy sum value; and evaluate the clarity of the preset image according to the Reiney entropy target value. By using the embodiment of the present invention, the universality and non-reference of the image clarity evaluation method are improved.

[0142] The gene sequencing system 100 can also obtain a preset objective lens position, wherein the preset objective lens position includes a first objective lens position and a second objective lens position; call the objective lens to collect a target image corresponding to the preset objective lens position; calculate the Raney entropy target value of the target image according to the image clarity evaluation method; determine the preset objective lens position with the largest Raney entropy target value as the target objective lens position; and adjust the objective lens to the target objective lens position. By using the embodiment of the present invention, the focusing operation can be optimized.

[0143] In this embodiment, the gene sequencer 1 may further include a display screen 20 and a processor 30. The memory 10 and the display screen 20 may be electrically connected to the processor 30, respectively.

[0144] The memory 10 can be different types of storage devices for storing various types of data. For example, it can be the memory or internal memory of the gene sequencer 1, or it can be a memory card that can be externally connected to the gene sequencer 1, such as a flash memory, a SM card (SmartMedia Card), an SD card (Secure Digital Card), etc. In addition, the memory 10 may include a non-volatile memory, such as a hard disk, an internal memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other non-volatile solid-state storage devices. The memory 10 is used to store various types of data, for example, various applications installed in the gene sequencer 1, and information such as data set and obtained by applying the above-mentioned image clarity evaluation method and focusing method.

[0145] The display screen 20 is installed on the gene sequencer 1 and is used to display information.

[0146] The processor 30 is used to execute the image clarity evaluation method / focusing method and various software installed in the gene sequencer 1, such as an operating system and application display software. The processor 30 includes but is not limited to a processor (Central Processing Unit, CPU), a microcontroller unit (Micro Controller Unit, MCU) and other devices used to interpret computer instructions and process data in computer software.

[0147] The gene sequencing system 100 may include one or more modules, which are stored in the memory 10 of the gene sequencer 1 and are configured to be executed by one or more processors (a processor 30 in this embodiment) to complete an embodiment of the present invention.

[0148] See also Figure 5 As shown, when the gene sequencing system 100 is used to evaluate the image clarity, the gene sequencing system 100 may include an image acquisition module 101, a pixel determination module 102, a first sum calculation module 103, a target value calculation module 104, and a clarity evaluation module 105. The module referred to in the embodiment of the present invention may be a program segment that performs a specific function, which is more suitable for describing the execution process of the software in the processor 30 than a program.

[0149] It is understandable that, corresponding to each embodiment of the above-mentioned image clarity evaluation method, the gene sequencing system 100 may include Figure 5The functions of each module will be described in detail below. It should be noted that the same nouns and related nouns and their specific explanations in each embodiment of the above image clarity evaluation method can also be applied to the following introduction to the functions of each module. In order to save space and avoid repetition, they will not be repeated here.

[0150] The image acquisition module 101 can be used to acquire a preset image.

[0151] The pixel point determination module 102 may be used to determine all pixel points of the preset image in a preset direction, where the preset direction includes several directions.

[0152] The first sum value calculation module 103 may be used to calculate the first Rainey entropy sum value of all the pixel points in each direction.

[0153] The target value calculation module 104 may be configured to calculate the Raney entropy target value of the preset image according to the first Raney entropy sum value.

[0154] The clarity evaluation module 105 may be configured to evaluate the clarity of the preset image according to the Rainey entropy target value.

[0155] See also Figure 6 As shown, when the gene sequencing system 100 is used to focus the objective lens, the gene sequencing system 100 may further include a position acquisition module 201, an image acquisition module 202, an entropy value calculation module 203, a position determination module 204 and a position adjustment module 205.

[0156] It is understandable that, corresponding to each embodiment of the above-mentioned focusing method, the gene sequencing system 100 may include Figure 6 Part or all of the functional modules shown in the figure, the functions of each module will be specifically introduced below.

[0157] The position acquisition module 201 may be used to acquire a preset objective lens position, where the preset objective lens position includes a first objective lens position and a second objective lens position.

[0158] The image acquisition module 202 may be used to call an objective lens to acquire a target image corresponding to the preset objective lens position.

[0159] The entropy value calculation module 203 can be used to calculate the Raney entropy target value of the target image according to the image clarity evaluation method.

[0160] The position determination module 204 may be used to determine the preset objective lens position with the largest Rainey entropy target value as the target objective lens position.

[0161] The position adjustment module 205 may be used to adjust the objective lens to the target objective lens position.

[0162] The embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by the processor 30, the steps of the image clarity evaluation method and the focusing method in any of the above-mentioned embodiments are implemented.

[0163] If the module / unit integrated in the gene sequencing system 100 / gene sequencer is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned implementation method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor 30, the steps of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable storage medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), etc.

[0164] The processor 30 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor 30 is the control center of the gene sequencing system 100 / gene sequencer 1, and uses various interfaces and lines to connect various parts of the entire gene sequencing system 100 / gene sequencer 1.

[0165] The memory 10 is used to store the computer programs and / or modules. The processor 30 implements various functions of the gene sequencing system 100 / gene sequencer 1 by running or executing the computer programs and / or modules stored in the memory 10 and calling the data stored in the memory 10. The memory 10 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the gene sequencer 1, etc.

[0166] In the several specific embodiments provided by the present invention, it should be understood that the disclosed gene sequencer and method can be implemented in other ways. For example, the system implementation described above is only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0167] For those skilled in the art, it is obvious that the embodiments of the present invention are not limited to the details of the above exemplary embodiments, and the embodiments of the present invention can be implemented in other specific forms without departing from the spirit or basic features of the embodiments of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the embodiments of the present invention is defined by the attached claims rather than the above description, so it is intended to include all changes within the meaning and scope of the equivalent elements of the claims in the embodiments of the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved. Multiple units, modules or devices stated in the system, device or gene sequencer claims can also be implemented by the same unit, module or device through software or hardware.

[0168] The above implementation modes are only used to illustrate the technical solutions of the embodiments of the present invention and are not intended to limit the present invention. Although the embodiments of the present invention are described in detail with reference to the above preferred implementation modes, those skilled in the art should understand that the technical solutions of the embodiments of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating image clarity, characterized in that: The image clarity evaluation method comprises: Get the preset image; Determine all pixel points of the preset image in a preset direction, where the preset direction includes several directions; Calculate the first Rainey entropy sum value of all the pixel points in each direction; The Reney entropy target value of the preset image is calculated according to the first Reney entropy sum value, and the Reney entropy target value includes at least one of a second Reney entropy sum value, a Reney entropy average value calculated according to the second Reney entropy sum value, a Reney entropy standard deviation value calculated according to the second Reney entropy sum value, and a Reney entropy normalized standard deviation value calculated according to the second Reney entropy sum value; wherein the second Reney entropy sum value of the preset image in the preset direction is calculated according to the first Reney entropy sum value, the direction variable value corresponding to the preset direction, and the number of the preset directions; The clarity of the preset image is evaluated according to the Rainey entropy target value.

2. The image clarity evaluation method according to claim 1, characterized in that: The calculating of the first Rainey entropy sum value of all the pixel points in each direction comprises: Obtain all pixel points of the preset image in each direction; Determine the position information of each pixel point in the preset image and the preset window length; Formula 1 is called according to the position information and the preset window length to obtain one-dimensional pseudo-Wigner distribution data corresponding to each pixel point; Formula 1 in, is the position information of each pixel, N is the preset window length, k is the frequency variable, and m is the discrete translation parameter; Formula 2 is called according to the one-dimensional pseudo-Wigner distribution data to obtain the Raney entropy value of each pixel in the preset image; Formula 2 A first Raney entropy sum value of all the pixels in each direction is calculated according to the Raney entropy value of each pixel.

3. The image clarity evaluation method according to claim 1, characterized in that: The step of calculating the Raney entropy target value of the preset image according to the first Raney entropy sum value comprises: Calculating the second Reiney entropy sum value of the preset image in the preset direction according to the first Reiney entropy sum value; or calculating the second Reiney entropy sum value of the preset image in the preset direction according to the first Reiney entropy sum value, and calculating the Reiney entropy average value of the preset image according to the second Reiney entropy sum value by calling formula 4; Equation 4 in, is the number of the preset directions, is the direction variable value, Mark the number of preset images. is the first Reine entropy sum, is the second Reiney entropy sum; or calculating the second Reiney entropy sum value of the preset image in the preset direction according to the first Reiney entropy sum value, and calculating the Reiney entropy standard deviation value of the preset image according to the second Reiney entropy sum value by calling formula 5; Formula 5 Alternatively, a second Reiney entropy sum value of the preset image in the preset direction is calculated according to the first Reiney entropy sum value, and formula 6 is called according to the second Reiney entropy sum value to calculate the normalized standard deviation value of the Reiney entropy of the preset image. Formula 6.

4. The image clarity evaluation method according to claim 3, characterized in that: Calculating the second Reiney entropy sum value of the preset image in the preset direction according to the first Reiney entropy sum value comprises: Obtaining a direction variable value corresponding to the preset direction; Determining the number of the preset directions; Formula 3 is called according to the first Reiney entropy sum value, the direction variable value and the quantity to obtain a second Reiney entropy sum value of the preset image in the preset direction; Formula 3 in, is the number of the preset directions, is the direction variable value, Mark the number of preset images. is the first Reine entropy sum.

5. A method for focusing using the image clarity evaluation method according to any one of claims 1 to 4, characterized in that: The focusing method comprises: Acquire a preset objective lens position, wherein the preset objective lens position includes a first objective lens position and a second objective lens position; Calling the objective lens to capture the target image corresponding to the preset objective lens position; Calculate the Rainey entropy target value of the target image according to the image clarity evaluation method; Determine the preset objective lens position with the largest Rainey entropy target value as the target objective lens position; Adjust the objective lens to the target objective lens position.

6. The focusing method according to claim 5, characterized in that: The step of calling the objective lens to collect the target image corresponding to the preset objective lens position: Acquire an initial position of the objective lens, wherein the initial position is consistent with the position of the first objective lens; Calling the objective lens to capture a first image corresponding to the position of the first objective lens; Move the objective lens to a second objective lens position according to a preset step; The objective lens is called to capture a second image corresponding to the position of the second objective lens.

7. The focusing method according to claim 5, characterized in that: The step of adjusting the objective lens to the target objective lens position comprises: Get the current objective lens position; Acquire the moving path of the current objective lens position and the target objective lens position; The objective lens is moved to the target objective lens position according to the moving path and at a preset step.

8. A gene sequencing system, characterized in that: The gene sequencing system comprises: An image acquisition module, used for acquiring a preset image; A pixel point determination module, used to determine all pixel points of the preset image in a preset direction, where the preset direction includes several directions; A first sum calculation module, used for calculating the first Rainey entropy sum value of all the pixel points in each direction; a target value calculation module, configured to calculate a Reney entropy target value of the preset image according to the first Reney entropy sum value, wherein the Reney entropy target value includes at least one of a second Reney entropy sum value, a Reney entropy average value calculated according to the second Reney entropy sum value, a Reney entropy standard deviation value calculated according to the second Reney entropy sum value, and a Reney entropy normalized standard deviation value calculated according to the second Reney entropy sum value; wherein the second Reney entropy sum value of the preset image in the preset direction is calculated according to the first Reney entropy sum value, a direction variable value corresponding to the preset direction, and the number of the preset directions; The clarity evaluation module is used to evaluate the clarity of the preset image according to the Rainey entropy target value.

9. A gene sequencer, characterized in that: The gene sequencer includes a processor, which is used to implement the steps of the image clarity evaluation method according to any one of claims 1 to 4 and the focusing method according to any one of claims 5 to 7 when executing a computer program stored in a memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the image clarity evaluation method according to any one of claims 1 to 4 and the focusing method according to any one of claims 5 to 7 are implemented.

Images