A fluorescence detection device and method for real-time detection of microfluidic system

Abstract

The present invention relates to a fluorescence detection device for real-time detection of a microfluidic system, comprising an image recognition module based on Labview and a grayscale value detection module based on Matlab; the image recognition module based on Labview recognizes the acquired real-time image and extracts the features of a designated detection area; the grayscale value detection module based on Matlab calculates the average grayscale value of the designated detection area, and imports the real-time data into Labview to draw a waveform chart, thereby obtaining a real-time curve of the average grayscale value change of the designated detection area. The present invention can detect and identify the contour of the sample detection area, calculate and store the average grayscale value of the sample area, and draw a real-time fluorescence change curve with the average grayscale value as the ordinate and time as the abscissa. According to this curve, the change of the fluorescence value of the sample as the reaction proceeds can be monitored in real time, thereby analyzing the amplification of the sample.

Description

Technical Field

[0001] The present invention belongs to the technical field of fluorescence detection, and in particular relates to a fluorescence detection device and method for real-time detection of a microfluidic system. Background Art

[0002] The fluorescence quantitative PCR instrument used to calculate the initial concentration of unknown samples (DNA or RNA, etc.) has achieved a leap from qualitative to quantitative PCR. The real-time fluorescence quantitative PCR instrument, which consists of a fluorescence quantitative system and a computer, is used to monitor the fluorescence of the cycle process. The computer connected to the real-time device collects the fluorescence data. The data is displayed in the form of a chart through the developed real-time analysis software. The raw data is plotted as a chart of fluorescence intensity relative to the number of cycles. With the continuous development of digital image processing technology, a microfluidic-based fluorescence detection software system has become possible. Compared with traditional qPCR instruments, the microfluidic fluorescence detection software system based on image recognition technology has the characteristics of simplified system structure and economy, and greatly reduces the difficulty of instrument operation, which is conducive to the development of instant detection technology. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide a fluorescence detection device and method for real-time detection of microfluidic systems, which can detect and identify the contour of the sample detection area, calculate and store the average gray value of the sample area, and draw a real-time fluorescence change curve with the average gray value as the vertical coordinate and time as the horizontal coordinate. According to this curve, the change of the fluorescence value of the sample as the reaction proceeds can be monitored in real time, so as to analyze the amplification of the sample.

[0004] To achieve the above object, the present invention adopts the following technical solution:

[0005] A fluorescence detection device for real-time detection of a microfluidic system comprises an image recognition module based on Labview and a grayscale value detection module based on Matlab; the image recognition module based on Labview recognizes an acquired real-time image and extracts features of a designated detection area; the grayscale value detection module based on Matlab calculates an average grayscale value of the designated detection area, and imports real-time data into Labview to draw a waveform chart, thereby obtaining a real-time curve of average grayscale value change of the designated detection area.

[0006] Furthermore, the features include position features, size features, and quantity features.

[0007] Furthermore, the Labview-based image recognition module includes an image acquisition unit, an image pre-processing unit, an image circular area recognition and coordinate extraction unit, and a data storage and visualization unit.

[0008] Furthermore, the grayscale value detection module based on Matlab is called by the ActiveX interface of Labview.

[0009] A detection method for a fluorescence detection device for real-time detection of a microfluidic system, comprising the following steps:

[0010] Step S1: collecting image data to be tested;

[0011] Step S2: Perform color plane extraction processing on the collected image to obtain a grayscale image;

[0012] Step S3: Detect circular shape of the processed image;

[0013] Step S4: input the path information of the collected image, the coordinate information of the circle center, and the circle radius information into the gray value detection module of Matlab, extract the gray values ​​of all pixels in the circular detection area and calculate the average value;

[0014] Step S5: Import the calculated values ​​into the waveform chart to obtain a real-time fluorescence change curve, and store the calculated values ​​by column into a table file to obtain the original data of the curve.

[0015] Compared with the prior art, the present invention has the following beneficial effects:

[0016] The present invention can detect and identify the contour of the sample detection area, calculate and store the average gray value of the sample area, and draw a real-time fluorescence change curve with the average gray value as the vertical coordinate and time as the horizontal coordinate. According to this curve, the change of the fluorescence value of the sample as the reaction proceeds can be monitored in real time, so as to analyze the amplification of the sample. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of the framework of an image recognition module according to an embodiment of the present invention;

[0018] Figure 2 A detection sample chip used in an embodiment of the present invention;

[0019] Figure 3 This is a software interface diagram of an embodiment of the present invention;

[0020] Figure 4 A software program flow chart of an embodiment of the present invention;

[0021] Figure 5 A graph showing changes of detection samples over time according to an embodiment of the present invention;

[0022] Figure 6 The real-time gray value data calculated by MATLAB of the embodiment of the present invention;

[0023] Figure 7 A waveform diagram is drawn by software according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0025] Please refer to Figure 1 The present invention provides a fluorescence detection device for real-time detection of a microfluidic system, comprising an image recognition module based on Labview and a grayscale value detection module based on Matlab; the image recognition module based on Labview recognizes the acquired real-time image and extracts the position feature, size feature and quantity feature of a designated detection area; the grayscale value detection module based on Matlab calculates the average grayscale value of the designated detection area, and imports the real-time data into Labview to draw a waveform chart, so as to obtain a real-time curve of the average grayscale value change of the designated detection area.

[0026] In this embodiment, the Labview-based image recognition module is a host computer control program written in LABVIEW©, which mainly includes an image acquisition part, an image pre-processing part, an image circular area recognition and coordinate extraction part, and a data storage and visualization part.

[0027] In this embodiment, the grayscale value detection module based on Matlab is based on MATLAB©. First, the input image is converted into a grayscale image. The grayscale image is imported as an array of 8-bit unsigned integers (range 0-255), which represents each pixel in the image. The center coordinates and radius of the fluorescent area identified by LABVIEW© are input into the MATLAB program as parameters to calculate the average grayscale value of the specified circular detection area.

[0028] Preferably, the image acquisition time is set to be once every 3 seconds, and the calculated average grayscale value is input into the LABVIEW© waveform chart to draw a real-time grayscale value curve.

[0029] Preferably, LABVIEW is combined with the MATLAB program by calling the MATLAB ActiveX interface.

[0030] In this embodiment, reference Figure 4 , and also provides a detection method for a fluorescence detection device for real-time detection of a microfluidic system, comprising the following steps:

[0031] Step S1: collecting images through a camera;

[0032] Step S2: Perform color plane extraction processing on the collected image to obtain a grayscale image;

[0033] Step S3: Detect circular shape of the processed image;

[0034] Step S4: input the path information of the collected image, the coordinate information of the circle center, and the circle radius information into the gray value detection module of Matlab, extract the gray values ​​of all pixels in the circular detection area and calculate the average value;

[0035] Step S5: Import the calculated values ​​into the waveform chart to obtain a real-time fluorescence change curve, and store the calculated values ​​by column into a table file to obtain the original data of the curve.

[0036] Embodiment 1:

[0037] like Figure 2 As shown, the detection sample chip used in the embodiment of the present invention includes two circular detection areas.

[0038] The software interface diagram of the embodiment of the present invention is as follows Figure 3 As shown in the figure, after the detection platform is installed, run this software. The specific operation steps are as follows: 1. Select to use the camera. 2. Open the camera. 3. Select the data storage file location. 4. Click "Start Recognition".

[0039] First, turn on the camera and collect images at high speed. The collected image is processed by color plane extraction. The fluorescence detected is green, so the green plane is selected as the extraction plane, and the image is grayed. The processed image is subjected to shape detection. In this embodiment, a circle is used as the detection sample area. The image is composed of pixels, and each pixel corresponds to a pixel coordinate. The pixel coordinates corresponding to the coordinates of the center of the circle are converted into a [x, y] two-dimensional array. The radius of the circle is the number of pixels from the outer contour of the circle to the center of the circle. The path information of the collected image, the coordinate information of the center of the circle, and the radius information of the circle are input into the matlab script. The script will extract the grayscale values ​​of all pixels in the specified circular area and calculate the average value. The calculated values ​​are imported into the waveform chart to obtain the real-time fluorescence change curve. The calculated values ​​are stored in the table file by column to obtain the original data of the curve.

[0040] The sample changes over time. Figure 5 The data stored after calculation by the software is as follows Figure 6 As shown, this example detects two sample areas at the same time and records two columns of data. The software collects images every 3 seconds and calculates the average gray value of the specified area. A total of 1200 points of data are recorded within 1 hour. Preferably, a waveform chart is used to draw a real-time fluorescence change curve based on the stored and recorded data, such as Figure 7 shown.

[0041] The above description is only a preferred embodiment of the present invention. All equivalent changes and modifications made according to the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. A fluorescence detection device for real-time detection of a microfluidic system, characterized in that: It includes an image recognition module based on Labview and a grayscale value detection module based on Matlab; the image recognition module based on Labview recognizes the acquired real-time image and extracts the features of the designated detection area; the grayscale value detection module based on Matlab extracts the average grayscale value of the designated detection area, and imports the real-time data into Labview to draw a waveform chart, so as to obtain a real-time curve of the average grayscale value change of the designated detection area; The grayscale value detection module based on Matlab extracts the average grayscale value of the specified detection area, specifically: firstly, the input image is converted into a grayscale image, and the grayscale image is imported as an array of 8-bit unsigned integers, and the integer range is 0-255, which represents each pixel in the image; the center coordinates and radius of the fluorescent area identified by LABVIEW© are input into the MATLAB program as parameters to calculate the average grayscale value of the specified circular detection area; The characteristics include position characteristics, size characteristics, and quantity characteristics; The Labview-based image recognition module includes an image acquisition unit, an image pre-processing unit, an image circular area recognition and coordinate extraction unit, and a data storage and visualization unit.

2. A fluorescence detection device for real-time detection of a microfluidic system according to claim 1, characterized in that: The gray value detection module based on Matlab is called by the ActiveX interface of Labview.

3. A detection method for a fluorescence detection device for real-time detection of a microfluidic system according to any one of claims 1-2, characterized in that: The following steps are involved: Step S1: collecting the image to be tested; Step S2: Perform color plane extraction processing on the collected image to obtain a grayscale image; Step S3: Detect circular shape of the processed image; Step S4: input the path information of the collected image, the coordinate information of the circle center, and the circle radius information into the gray value detection module of Matlab, extract the gray values ​​of all pixels in the circular detection area and calculate the average value; Step S5: Import the calculated values ​​into the waveform chart to obtain a real-time fluorescence change curve, and store the calculated values ​​by column into a table file to obtain the original data of the curve.

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