Full-automatic electrophoresis apparatus self-checking method

Abstract

The invention discloses a self-inspection method for a full-automatic electrophoresis apparatus, which comprises the following steps of: acquiring an electrophoresis real-time image through an image acquisition unit, calling a self-inspection evaluation program to evaluate the acquired electrophoresis image, judging an evaluation result according to a set condition, completing self-inspection if self-inspection is passed, and outputting abnormal information if the self-inspection is not passed. The technical scheme has the advantages of saving time and labor. On one hand, a full-automatic electrophoresis apparatus manufacturer uses the technical scheme in the production process, normal performance of the full-automatic electrophoresis apparatus leaving a factory can be ensured, and on the other hand, a user of the full-automatic electrophoresis apparatus can regularly perform equipment self-inspection by adopting the technical scheme, so that normal operation of the equipment can be ensured.

Description

Technical Field

[0001] The invention belongs to the technical field of electrophoresis equipment detection, and particularly relates to a full-automatic electrophoresis instrument self-detection method. Background Art

[0002] Gel electrophoresis is a technique used to separate biological macromolecules (such as DNA, RNA, and proteins). This technique uses an electric field to move charged molecules in a gel matrix, thereby separating them according to their size and charge characteristics. Gel electrophoresis is widely used in fields such as molecular biology, genetics, and biochemistry, and is used for research such as genome analysis, DNA fingerprinting, and protein analysis. The current mainstream use of electrophoresis is for the operator to connect the electrophoresis tank to a DC adjustable high-voltage power supply, add electrophoresis buffer to the electrophoresis tank, and then use a handheld manual pipette to add the samples one by one to the prepared gel loading wells in the electrophoresis tank. The power supply voltage or current value of the electrophoresis instrument is then manually set for electrophoresis. This manual loading method places high demands on the operator, is time-consuming, and is prone to contact with reagents that are harmful to health. In addition, due to the small size of the loading wells and the refraction problem in the liquid, the sample cannot be accurately added during the loading process, resulting in detection errors. Chinese patent document CN 221100597U discloses an automatic sampling and loading electrophoresis device, which, through the coordination between structures such as an electric pipette, an electrophoresis tank, an X-axis moving mechanism, a Y-axis moving mechanism, and a Z-axis moving mechanism, can not only realize the automatic replacement of the pipette tip and the automatic sampling and loading of the sample, but also can accurately load the sample into the loading hole in the electrophoresis tank, thereby improving the detection efficiency while improving the loading and detection accuracy, avoiding the tedious manual operation of the electrophoresis process and the potential risk of adding the wrong sample. Although the above patent can realize the automatic loading of the electrophoresis instrument, it lacks the self-checking of whether the loading is accurate and whether the electrophoresis instrument is working properly. These tasks can only be verified by skilled technicians through relevant experiments, which not only wastes manpower but also requires a long testing time. Therefore, there is an urgent need for a method that can complete the self-check of a fully automatic electrophoresis instrument. Summary of the Invention

[0003] In response to the above-mentioned problems existing in the prior art, the present invention provides a self-inspection method for a fully automatic electrophoresis instrument. Through the present invention, the performance self-inspection of the fully automatic electrophoresis instrument can be automatically completed. On the one hand, the manufacturers of the fully automatic electrophoresis instrument use this technical solution during the production process to ensure that the performance of the fully automatic electrophoresis instrument leaving the factory is normal. On the other hand, users of the fully automatic electrophoresis instrument can use this technical solution to regularly perform equipment self-inspection to ensure that the equipment can operate normally.

[0004] The present invention adopts the following technical solutions:

[0005] A self-test method for a fully automatic electrophoresis instrument collects real-time images of electrophoresis through an image acquisition unit installed in the fully automatic electrophoresis instrument, calls a self-test evaluation program to evaluate the collected electrophoresis images, and judges the self-test results based on set conditions. If the self-test passes, the self-test is completed; otherwise, an abnormality message is output.

[0006] Preferably, the self-assessment procedure specifically includes the following steps:

[0007] 1) Obtaining self-test electrophoresis images;

[0008] 2) Perform noise reduction on the electrophoresis image;

[0009] 3) grayscale and binarization processing of the electrophoresis image;

[0010] 4) performing affine transformation on the electrophoresis image;

[0011] 5) Capture the target ROI area in the image;

[0012] 6) Extract the outer contour and parameters of the electrophoresis band in the image;

[0013] 7) Calculate the characteristic parameters of the marker electrophoresis bands and the standard sample electrophoresis bands in the image;

[0014] 8) Call the set parameters;

[0015] 9) Compare the characteristic parameters of the Marker electrophoresis band and the standard sample electrophoresis band calculated in step 7) with the parameters set in step 8), and determine whether the self-test has passed by setting judgment conditions.

[0016] Preferably, step 2) is specifically as follows: using a 3×3 window median filter and a 5×5 window adaptive mean filter to process the noise of the electrophoresis image.

[0017] Preferably, step 3) is as follows: first, the denoised image is converted into a single-channel grayscale image, and the conversion formula is Igray = 0.299R + 0.587G + 0.114B, where Igray is the converted pixel value, and R, G, and B represent the pixel values ​​of the red, green, and blue channels respectively; then, the improved Bradley algorithm is used for binarization:

[0018] a) Dynamic window division: set the window size;

[0019] b) Local threshold calculation: mean μ and standard deviation σ of pixels in the window, threshold T = μ-0.8σ;

[0020] c) Binarization output: Among them, I binary (x,y) is the binary output, Igray (x,y) is the grayscale input.

[0021] Preferably, step 4) is as follows: first find all the contours in the binary image, select the largest contour, then perform rectangular approximation on the contour, find the minimum enclosing rectangle, and finally calculate the rotation matrix by the difference between the long side and the horizontal position, and use affine transformation to correct the image tilt.

[0022] Preferably, step 5) is specifically as follows: first, the image pixel values ​​obtained in step 4) are projected in the x-axis and y-axis directions, and then according to the projected values, the target ROI area is intercepted for identification; the specific steps are as follows:

[0023] a) Horizontal projection: Count the pixels in each row along the x-axis to determine the upper and lower boundaries y min 、y max ;

[0024] b) Vertical projection: Count the sum of pixels in each column along the y-axis to determine the left and right boundaries x min 、x max ;

[0025] c) ROI extraction: intercept the rectangular area [x min :x max ,y min :y max ].

[0026] Preferably, step 6) is as follows: use OpenCV's findContours function to extract the outer contour of the electrophoresis strip from the image, and obtain the geometric parameters of all n Marker electrophoresis strips and put these parameters into an array from top to bottom according to the spatial position. The i-th strip geometric parameters include: geometric center (Xci, Yci), circumscribed rectangle length Wi, circumscribed rectangle width Hi, strip area Si; obtain the geometric parameters of all m standard sample electrophoresis strips and put these parameters into an array from left to right according to the spatial position. The j-th strip geometric parameters include: geometric center (Xcj, Ycj), circumscribed rectangle length Wj, circumscribed rectangle width Hj, strip area Sj.

[0027] Preferably, step 7) is as follows: calculate the parameters of the Marker electrophoresis band Gapm(Xc)=Max(Xci)-Min(Xci); Gapm(W)=Max(Wi)-Min(Wi); Gapm(H)=Max(Hi)-Min(Hi); Gapm(S)=Max(Si)-Min(Si); calculate the parameters of the standard sample electrophoresis band Gaps(Yc)=Max(Ycj)-Min(Ycj); Gaps(W)=Max(Wj)-Min(Wj); Gaps(H)=Max(Hj)-Min(Hj); Gaps(S)=Max(Sj)-Min(Sj); wherein Max represents the maximum value and Min represents the minimum value.

[0028] Preferably, step 8) is specifically as follows: call the set parameters M, N, GapmX, GapmW, GapmH, GapmS, GapsY, GapsW, GapsH, GapsS.

[0029] Preferably, step 9) is specifically as follows: The judgment conditions are as follows: when m=M, n=N, Gapm(Xc)<=GapmX, Gapm(W)<=GapmW, Gapm(H)<=GapmH, Gapm(S)<=GapmS, Gaps(Yc)<=GapsY, Gaps(W)<=GapsW, Gaps(H)<=GapsH, Gaps(S)<=GapsS, the self-test passes; otherwise, the self-test fails and a failure prompt is given.

[0030] The present invention can automatically complete the self-test of the performance of the fully automatic electrophoresis instrument, which has the advantages of saving time and labor. The technical solution of the present invention can be used by fully automatic electrophoresis instrument manufacturers during the production process to ensure that the fully automatic electrophoresis instrument performs normally after leaving the factory. On the other hand, users of the fully automatic electrophoresis instrument can use this technical solution to regularly perform equipment self-tests to ensure that the equipment is operating normally. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a simplified structural diagram of a fully automatic electrophoresis instrument according to a preferred embodiment of the present invention.

[0032] Figure 2 is the original electropherogram collected.

[0033] Figure 3 It is an electrophoresis image after being processed by the present invention (affine transformation, noise reduction, grayscale, binarization, target ROI area interception and other operations). DETAILED DESCRIPTION

[0034] The preferred embodiments of the present invention are described in detail below.

[0035] The fully automatic electrophoresis instrument involved in the self-checking method of the fully automatic electrophoresis instrument in this embodiment is a fully automatic electrophoresis instrument equipped with an image acquisition unit on the basis of an existing fully automatic electrophoresis instrument. Figure 1 As shown, the image acquisition unit adopts a camera. The structure of the fully automatic electrophoresis instrument includes an equipment control and data processing host, a light source 1, an image acquisition unit 2, etc.

[0036] The specific process of a fully automatic electrophoresis instrument self-test method according to a preferred embodiment of the present invention is as follows:

[0037] Load reagent A (DNA Marker), reagent B (standard DNA for plasmid sample extraction), electrophoresis gel, and a tip box (filled with tips) into the fully automatic electrophoresis instrument; start the fully automatic electrophoresis instrument, and the fully automatic electrophoresis instrument completes the sample loading according to the set sample loading and running program; while starting the electrophoresis instrument, the image acquisition unit begins to regularly capture real-time images of the electrophoresis until the electrophoresis time is over; the equipment control and data processing host receives and saves all images captured by the image acquisition unit and calls the self-test evaluation program to evaluate the images and judge the self-test results of the fully automatic electrophoresis instrument. If the self-test passes, the instrument self-test is completed; if the self-test fails, an abnormal prompt and abnormal image are displayed to prompt the user to perform maintenance.

[0038] In this embodiment, the self-check evaluation procedure includes the following steps:

[0039] 1. Obtain a self-test electrophoresis image.

[0040] 2. Noise reduction processing.

[0041] Salt and pepper noise and Gaussian noise in gel electrophoresis images have the most significant impact on the overall image. This embodiment applies 3×3 window median filtering and 5×5 window adaptive mean filtering to process the above noises, thereby improving the signal-to-noise ratio of the image.

[0042] 3. Grayscale and binarization processing.

[0043] First, the denoised image is converted into a single-channel grayscale image using the conversion formula Igray = 0.299R + 0.587G + 0.114B (where Igray is the converted pixel value, and R, G, and B represent the pixel values ​​of the red, green, and blue channels, respectively). The improved Bradley algorithm is then used for binarization to improve the binarization effect under uneven lighting conditions. Improved binarization method:

[0044] a) Dynamic window partitioning: Window size W = max(32, image width / 20), that is, the window size is 32 or image width / 20, whichever is larger;

[0045] b) Local threshold calculation: mean μ and standard deviation σ of pixels in the window, threshold T = μ-0.8σ;

[0046] c) Binarization output: Among them, I binary (x,y) is the binary output, I gray (x,y)

[0047] is grayscale input.

[0048] 4. Perform affine transformation on the image.

[0049] The image captured by the image acquisition unit may be tilted. To reduce the impact of tilted images on recognition due to different positions, this embodiment applies an affine transformation to correct the image tilt and rotate the image to the same position. First, all contours in the binary image are found, and the largest contour is selected, namely the contour that contains all bands in the gel electrophoresis. Then, a rectangular approximation is performed on the contour to find the minimum enclosing rectangle. Finally, the rotation matrix is ​​calculated by the difference between the long side and the horizontal position, and the image tilt is corrected using the affine transformation.

[0050] 5.Cut the target ROI area.

[0051] First, the image pixel values ​​are projected in the x-axis and y-axis directions, and then the target ROI area is intercepted based on the projected values ​​for recognition. Specific steps:

[0052] 1) Horizontal projection: Count the pixels in each row along the x-axis to determine the upper and lower boundaries y min 、y max .

[0053] 2) Vertical projection: Count the sum of pixels in each column along the y-axis to determine the left and right boundaries x min 、x max .

[0054] 3) ROI extraction: intercept the rectangular area [x min :x max ,y min :y max ].

[0055] 6. Use OpenCV's findContours function to extract the outer contour of the electrophoresis strips from the image, and obtain the geometric parameters of all n Marker electrophoresis strips and put these parameters into an array from top to bottom according to the spatial position. The i-th strip geometric parameters include: geometric center (Xci, Yci), circumscribed rectangle length Wi, circumscribed rectangle width Hi, strip area Si; obtain the geometric parameters of all m standard sample electrophoresis strips and put these parameters into an array from left to right according to the spatial position. The j-th strip geometric parameters include: geometric center (Xcj, Ycj), circumscribed rectangle length Wj, circumscribed rectangle width Hj, strip area Sj.

[0056] 7. Calculate the marker electrophoresis band parameters Gapm(Xc)=Max(Xci)-Min(Xci); Gapm(W)=Max(Wi)-Min(Wi); Gapm(H)=Max(Hi)-Min(Hi); Gapm(S)=Max(Si)-Min(Si); and the standard sample electrophoresis band parameters Gaps(Yc)=Max(Ycj)-Min(Ycj); Gaps(W)=Max(Wj)-Min(Wj); Gaps(H)=Max(Hj)-Min(Hj); Gaps(S)=Max(Sj)-Min(Sj); wherein Max represents the maximum value and Min represents the minimum value.

[0057] 8. Call the set parameters M, N, GapmX, GapmW, GapmH, GapmS, GapsY, GapsW, GapsH, GapsS.

[0058] 9. The judgment conditions are as follows: When m=M,n=N,Gapm(Xc)<=GapmX,Gapm(W)<=GapmW,Gapm(H)<=GapmH,Gapm(S)<=GapmS,Gaps(Yc)<=GapsY,Gaps(W)<=GapsW,Gaps(H)<=GapsH,Gaps(S<=GapsS,all meet the conditions, the self-test passes. If any of the conditions are not met, the input self-test fails, and the output prompts "failed" and guides the user to perform the corresponding actions and then repeat the self-test until the self-test passes.

[0059] The superiority of the technical solution of the present invention is verified by experiments below.

[0060] Experimental configuration: Place reagent A (DM100 DNA Marker consists of three linear double-stranded DNA fragments of 100 bp, 500 bp, and 1500 bp; each band contains approximately 50 ng in 5 μl of product) and reagent B (standard DNA for plasmid sample extraction) into the instrument. Operating parameters: sample volume: 2 μl, marker volume: 2 μl, electrophoresis voltage: 120 V, electrophoresis time: 20 min.

[0061] According to the above experimental configuration, the experiment was carried out. After completion, the collected images were as follows: Figure 2 As shown, the image after being processed by the method of the present invention (affine transformation, noise reduction, grayscale, binarization, interception of target ROI area, etc.) is as shown in FIG. Figure 3 As shown, Figure 3 After electrophoresis band identification, the electrophoresis band parameters shown in Table 1 were obtained.

[0062] Table 1 Figure 3 List of electrophoresis band identification parameters

[0063]

[0064]

[0065] Substituting the defined formulas from Table 1, we obtain m = 3, n = 13, Gapm(Xc) = 0.6, Gapm(W) = 0.5, Gapm(H) = 2, Gapm(S) = 4.4, Gaps(Yc) = 2.5, Gaps(W) = 1.8, Gaps(H) = 1.2, and Gaps(S) = 12. Compare this with the set values ​​of M = 3, N = 13, GapmX = 3, GapmW = 5, GapmH = 3, GapmS = 15, GapsY = 5, GapsW = 6, GapsH = 4, and GapsS = 20. The comparison result meets the conditions in step 8, so the self-test passes.

[0066] The preferred embodiments of the present invention have been described in detail above, but the present invention is not limited to the above embodiments.

Claims

1. A fully automatic electrophoresis instrument self-test method, characterized by: The real-time image of electrophoresis is collected by the image acquisition unit installed in the fully automatic electrophoresis instrument, and the self-test evaluation program is called to evaluate the collected electrophoresis image. The self-test result is judged based on the set conditions. If the self-test passes, the self-test is completed. Otherwise, an abnormal information is output.

2. A fully automatic electrophoresis instrument self-test method as claimed in claim 1, characterized in that: The self-examination and evaluation procedure specifically includes the following steps: 1) Obtaining self-test electrophoresis images; 2) Perform noise reduction on the electrophoresis image; 3) grayscale and binarization processing of the electrophoresis image; 4) performing affine transformation on the electrophoresis image; 5) Capture the target ROI area in the image; 6) Extract the outer contour and parameters of the electrophoresis band in the image; 7) Calculate the characteristic parameters of the marker electrophoresis bands and the standard sample electrophoresis bands in the image; 8) Call the set parameters; 9) Compare the characteristic parameters of the Marker electrophoresis band and the standard electrophoresis sample band calculated in step 7) with the parameters set in step 8), and determine whether the self-test has passed by setting judgment conditions.

3. A fully automatic electrophoresis instrument self-test method as claimed in claim 2, characterized in that: Step 2) is specifically as follows: using a 3×3 window median filter and a 5×5 window adaptive mean filter to process the noise of the electrophoresis image.

4. A fully automatic electrophoresis apparatus self-test method as claimed in claim 3, characterized in that: Step 3) is as follows: first, convert the denoised image into a single-channel grayscale image using the conversion formula Igray = 0.299R + 0.587G + 0.114B, where Igray is the converted pixel value, and R, G, and B represent the pixel values ​​of the red, green, and blue channels, respectively; then, use the improved Bradley algorithm for binarization: a) Dynamic window division: set the window size; b) Local threshold calculation: mean μ and standard deviation σ of pixels in the window, threshold T = μ-0.8σ; c) Binarization output: Among them, I binary (x,y) is the binary output, I gray (x,y) is the grayscale input.

5. A fully automatic electrophoresis instrument self-test method as claimed in claim 4, characterized in that: Step 4) is as follows: first find all the contours in the binary image, select the largest contour, then perform rectangular approximation on the contour to find the minimum enclosing rectangle, and finally calculate the rotation matrix by the difference between the long side and the horizontal position, and use affine transformation to correct the image tilt.

6. A fully automatic electrophoresis apparatus self-test method as claimed in claim 5, characterized in that: Step 5) is as follows: first, project the image pixel values ​​obtained in step 4) in the x-axis and y-axis directions, and then intercept the target ROI area for identification based on the projected values; the specific steps are as follows: a) Horizontal projection: Count the pixels in each row along the x-axis to determine the upper and lower boundaries y min 、y max ; b) Vertical projection: Count the sum of pixels in each column along the y-axis to determine the left and right boundaries x min 、x max ; c) ROI extraction: intercept the rectangular area [x min :x max ,y min :y max ].

7. A fully automatic electrophoresis apparatus self-test method as claimed in claim 6, characterized in that: Step 6) is as follows: use OpenCV's findContours function to extract the outer contour of the electrophoresis band from the image, and obtain the geometric parameters of all n Marker electrophoresis bands and put these parameters into an array from top to bottom according to the spatial position. The i-th band geometric parameters include: geometric center (Xci, Yci), circumscribed rectangle length Wi, circumscribed rectangle width Hi, and band area Si; obtain the geometric parameters of all m standard sample electrophoresis bands and put these parameters into an array from left to right according to the spatial position. The j-th band geometric parameters include: geometric center (Xcj, Ycj), circumscribed rectangle length Wj, circumscribed rectangle width Hj, and band area Sj.

8. A fully automatic electrophoresis apparatus self-test method as claimed in claim 7, characterized in that: Step 7) is specifically as follows: calculate the characteristic parameters of the Marker electrophoresis band: Gapm(Xc)=Max(Xci)-Min(Xci); Gapm(W)=Max(Wi)-Min(Wi); Gapm(H)=Max(Hi)-Min(Hi); Gapm(S)=Max(Si)-Min(Si); calculate the characteristic parameters of the standard sample electrophoresis band: Gaps(Yc)=Max(Ycj)-Min(Ycj); Gaps(W)=Max(Wj)-Min(Wj); Gaps(H)=Max(Hj)-Min(Hj); Gaps(S)=Max(Sj)-Min(Sj); wherein Max represents the maximum value and Min represents the minimum value.

9. A fully automatic electrophoresis apparatus self-test method as claimed in claim 8, characterized in that: Step 8) is specifically as follows: call the set parameters M, N, GapmX, GapmW, GapmH, GapmS, GapsY, GapsW, GapsH, GapsS.

10. A fully automatic electrophoresis apparatus self-test method as claimed in claim 9, characterized in that: Step 9) is specifically as follows: The judgment conditions are as follows: when m=M, n=N, Gapm(Xc)<=GapmX, Gapm(W)<=GapmW, Gapm(H)<=GapmH, Gapm(S)<=GapmS, Gaps(Yc)<=GapsY, Gaps(W)<=GapsW, Gaps(H)<=GapsH, Gaps(S)<=GapsS, the self-test passes; otherwise, the self-test fails and a failure prompt is given.

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