Blood group test agglutination reaction result p-hsv comprehensive judgment method

Abstract

The P-HSV comprehensive judgment method of agglutination reaction result of blood type detection relates to the technical field of blood type detection and comprises the following steps: S1, mixing a blood sample with an antibody detection reagent to generate an agglutination reaction; S2, obtaining an original image; S3, extracting each reaction cavity image from the original image; S4, pretreating each reaction cavity image to remove the edges and noise of each reaction cavity image; S5, size judgment; S6, color judgment; and S7, comprehensive judgment according to the size judgment result and the color judgment result. The present application reduces the workload of the staff, shortens the detection time, improves the detection efficiency, and can be widely applied to the blood type detection technology.

Description

Technical Field

[0001] This invention relates to the field of blood typing technology, specifically to a comprehensive method for determining P-HSV agglutination reaction results in blood typing. Background Technology

[0002] Blood typing is a method used to determine the type of human blood. It has broad research value and significance in the field of medical testing, and is essential for blood transfusions, prevention of neonatal hemolytic disease, and organ transplantation. A crucial step in blood typing is determining the agglutination reaction result of red blood cells and antibody testing reagents. In traditional blood typing, the judgment of the degree of agglutination between red blood cells and antibody testing reagents usually relies on experienced personnel. These personnel visually observe the agglutination state of red blood cells after the reaction with different antibody testing reagents to determine the blood type. If red blood cells form agglutinated clumps after reacting with the antibody testing reagents, the red blood cells are identified as belonging to that blood type; if a homogeneous suspension of red blood cells is formed, the red blood cells are identified as not belonging to that blood type. This not only increases the workload of personnel but also increases testing time and reduces efficiency. Furthermore, this method cannot accurately determine weak agglutination reactions, which can lead to a certain degree of misjudgment and serious consequences. Therefore, scholars both domestically and internationally have conducted a series of studies to improve the speed and accuracy of blood typing. Summary of the Invention

[0003] The purpose of this invention is to provide a comprehensive method for determining P-HSV in blood typing agglutination reaction results.

[0004] The technical solution adopted by this invention to solve the technical problem is as follows:

[0005] The method for comprehensive determination of P-HSV agglutination reaction results in blood typing of the present invention includes the following steps:

[0006] Step S1: Mix the blood sample with the antibody test reagent to produce an agglutination reaction;

[0007] Step S2: Obtain the original image;

[0008] Step S3: Extract the images of each reaction chamber from the original image;

[0009] Step S4: Preprocess the images of each reaction chamber to remove edges and noise;

[0010] Step S5: Size determination;

[0011] Step S6: Color determination;

[0012] Step S7: Make a comprehensive judgment based on the size judgment result and the color judgment result.

[0013] Furthermore, in step S1, the preparation method of the antibody detection reagent is as follows:

[0014] Monoclonal IgM blood group antibody was mixed with 0.5M trehalose at a volume ratio of 9:1. 6 μL of the mixture of monoclonal IgM blood group antibody and trehalose was deposited in the center of the reaction chamber using a pipette and dried in a laboratory incubator at 25°C for 30 min to obtain the antibody detection reagent.

[0015] Furthermore, the specific operation steps of step S2 are as follows:

[0016] A CCD camera is used to acquire the original image of the blood detection chip after the reaction.

[0017] Furthermore, in step S4, a Gaussian algorithm is used to denoise the images of each reaction chamber.

[0018] Furthermore, the specific operation steps of step S5 are as follows:

[0019] Step S5.1: Extract the agglomerate edge image from the preprocessed reaction chamber image using the Canny algorithm;

[0020] Step S5.2: Calculate the number n of agglomerates in the agglomerate edge image and the perimeter of the edge contour of each agglomerate;

[0021] Step S5.3: Determine the grade of the agglomeration reaction result based on the sum of the perimeters L of the edge contours of all agglomerates and the number n of agglomerates.

[0022] Furthermore, in step S5, the size determination rules are as follows:

[0023] (1) If there is no agglomerate in the edge image of the agglomerate, the agglomeration reaction result is judged to be negative;

[0024] (2) If L≤500 and n≤4 in the edge image of the agglomerate, the grade of the agglomeration reaction result is judged as positive grade 4;

[0025] (3) If 500 < L ≤ 1500 and 4 < n ≤ 10 in the edge image of the agglomerate, the grade of the agglomeration reaction result is judged as positive grade 3.

[0026] (4) If 1500 < L ≤ 2500 and 10 < n ≤ 15 in the edge image of the agglomerate, the grade of the agglomeration reaction result is judged as positive grade 2.

[0027] (5) If L > 2500 and n > 15 in the edge image of the agglomerate, the grade of the agglomeration reaction result is determined to be positive grade 1.

[0028] Furthermore, the specific operation steps of step S6 are as follows:

[0029] Based on the HSV color image, agglutination blocks were extracted from the preprocessed reaction chamber images using MATLAB software; the S / V value of each agglutination block was calculated using formulas (1), (2) and (3); the grade of the agglutination reaction result was determined based on the S / V value of the red blood cell region in the preprocessed reaction chamber images.

[0030] S=f1(ρ) (1)

[0031]

[0032]

[0033] In the formula, S is the saturation coefficient, V is the brightness coefficient, and ρ is the number of red blood cells per unit area, i.e., the degree of aggregation.

[0034] Furthermore, in step S6, the color determination rules are as follows:

[0035] (1) If S / V≥110%, the grade of the agglutination reaction result is determined to be positive grade 4;

[0036] (2) If 100% ≤ S / V < 110%, the grade of the agglutination reaction result is determined to be positive grade 3;

[0037] (3) If 90% ≤ S / V < 100%, the grade of the agglutination reaction result is determined to be positive grade 2;

[0038] (4) If 60% ≤ S / V < 90%, the grade of the agglutination reaction result is determined to be positive grade 1;

[0039] (5) If S / V < 60% and there are no agglomerates, the agglomeration reaction result is judged as negative.

[0040] Furthermore, in step S7, the comprehensive determination rules are as follows:

[0041] (1) If the agglomeration reaction result level obtained after size determination is consistent with the agglomeration reaction result level obtained after color determination, then the agglomeration reaction result level obtained after size determination or the agglomeration reaction result level obtained after color determination shall be selected as the final agglomeration reaction result level.

[0042] (2) If the agglomeration reaction result grade obtained after size determination is inconsistent with the agglomeration reaction result grade obtained after color determination, the lower agglomeration reaction result grade shall be selected as the final agglomeration reaction result grade.

[0043] The beneficial effects of this invention are:

[0044] This invention provides a comprehensive P-HSV determination method for blood typing agglutination reaction results. It classifies and interprets agglutination reaction results through three main stages: image preprocessing, feature extraction, and classification. This method solves the problem of traditional discrimination methods being unable to accurately determine weak agglutination reaction results, reduces the time spent on manual result interpretation, increases the accuracy of results, reduces the workload of staff, shortens testing time, and improves testing efficiency. Attached Figure Description

[0045] Figure 1 This is a flowchart of the P-HSV comprehensive determination method for blood type detection agglutination reaction results according to the present invention.

[0046] Figure 2 This is the original image of the blood detection chip after the agglutination reaction in Example 2.

[0047] Figure 3 These are images of each reaction chamber extracted from the original image in Example 2.

[0048] Figure 4 The images are of each reaction chamber after preprocessing in Example 2.

[0049] Figure 5 This is the image obtained in Example 2 after segmenting and determining the edges of each agglomerate block in the preprocessed reaction chamber image. Detailed Implementation

[0050] The P-HSV comprehensive judgment method for blood type detection agglutination reaction results of the present invention comprehensively judges the blood type detection agglutination reaction results from two aspects: agglutination block size and color. Here, P-HSV is a self-defined term of the present invention. In P-HSV, P is an abbreviation for Perimeter, representing the perimeter of the agglutination block's edge contour. HSV (Hue, Saturation, Value) is a color representation method that conforms to people's daily habits, where H (Hue) is hue, S (Saturation) is saturation, and V (Value) is lightness.

[0051] like Figure 1 As shown, the specific operation process of the blood type detection agglutination reaction result P-HSV comprehensive determination method of the present invention is as follows:

[0052] Step S1: Aggregation reaction;

[0053] When a blood sample is mixed with an antibody test reagent, the positive red blood cells in the blood react with the test reagent after being stirred evenly, resulting in an agglutination reaction.

[0054] The preparation method of the antibody detection reagent is as follows: monoclonal IgM blood group antibody and 0.5M trehalose are mixed at a volume ratio of 9:1 (v:v). 6μL of the mixture of monoclonal IgM blood group antibody and trehalose is taken with a pipette and deposited in the center of the reaction chamber. The mixture is then dried in a laboratory incubator at 25℃ for 30 min to obtain the antibody detection reagent.

[0055] The IgM blood group antibody used is a commercially produced monoclonal IgM blood group antibody used to detect the blood type of human blood; it includes five antibodies: anti-A, anti-B, anti-D, anti-C, and anti-E.

[0056] Trehalose, a stabilizer, is commonly used in identification plates made from monoclonal antibodies against dried red blood cells. Identification plates made with trehalose can be stored at room temperature for more than two years without changing their agglutination properties, and blood types can be detected in just one minute. Using trehalose as a stabilizer can greatly improve the durability and stability of the identification plate, making it a reliable tool that is convenient for medical staff and patients to use.

[0057] Step S2: Read the original image;

[0058] A CCD camera is used to acquire the original image of the blood detection chip after the reaction.

[0059] Step S3: Segment the reaction chamber image;

[0060] Extract the images of each reaction chamber from the original image obtained in step S1.

[0061] Step S4: Remove edges and noise;

[0062] After extracting the reaction chamber images, preprocessing is required to accurately determine the level of the agglomeration reaction result. Due to the constraints of the reaction chamber surface shape, the edges of the reaction chamber will be subject to certain interference during photography and should be considered invalid images and removed. Therefore, Gaussian algorithm is used to denoise each reaction chamber image to avoid unnecessary interference.

[0063] Step S5: Size determination;

[0064] Step S5.1: Extract the agglomerate edge image from the reaction chamber image after preprocessing in step S4 using the Canny algorithm. Specifically, the Canny algorithm is used to segment and determine the edges of each agglomerate in each reaction chamber image after preprocessing in step S4.

[0065] Step S5.2: Calculate the number n of agglomerates in the agglomerate edge image and the perimeter of the edge contour of each agglomerate.

[0066] Step S5.3: Determine the level of the agglomeration reaction result based on the sum of the perimeters L of all agglomerate edge contours and the number of agglomerates n. Calculate the pixel perimeter of the outer edge of the reaction chamber based on its diameter and perimeter, thereby determining the ratio between the actual perimeter of the reaction chamber and the pixel perimeter. When classifying the agglomeration reaction result based on the sum of the perimeters L of all agglomerate edge contours, L is the sum of the pixel perimeters of all agglomerate edge contours after removing the pixel perimeter of the outer edge of the reaction chamber.

[0067] The size determination rules are as follows:

[0068] (1) If there is no agglomerate in the edge image of the agglomerate, the agglomeration reaction result is judged to be negative;

[0069] (2) If L≤500 and n≤4 in the edge image of the agglomerate, the grade of the agglomeration reaction result is judged as positive grade 4;

[0070] (3) If 500 < L ≤ 1500 and 4 < n ≤ 10 in the edge image of the agglomerate, the grade of the agglomeration reaction result is judged as positive grade 3.

[0071] (4) If 1500 < L ≤ 2500 and 10 < n ≤ 15 in the edge image of the agglomerate, the grade of the agglomeration reaction result is judged as positive grade 2.

[0072] (5) If L > 2500 and n > 15 in the edge image of the agglomerate, the grade of the agglomeration reaction result is determined to be positive grade 1.

[0073] Step S6: Color determination;

[0074] Step S6.1: Define the HSV (Hue, Saturation, Value) color model;

[0075] HSV is a color representation method that aligns with people's daily habits.

[0076] H: Hue, measured in angles, with a value range of 0°-360°. It is calculated counterclockwise starting from red, with red at 0°, green at 120°, and blue at 240°. Their complementary colors are yellow at 60°, cyan at 180°, and violet at 300°.

[0077] S: Saturation, representing how close a color is to a spectral color. A color can be seen as the result of mixing a certain spectral color with white. The greater the proportion of the spectral color, the closer the color is to the spectral color, and the higher the color saturation. High saturation results in a deep and vibrant color. Spectral colors have zero white light component, reaching their highest saturation. The value typically ranges from 0% to 100%; the higher the value, the more saturated the color.

[0078] V: Brightness, representing the degree of lightness or darkness of a color. For light source colors, the brightness value is related to the luminance of the light source; for object colors, this value is related to the transmittance or reflectance of the object. It typically ranges from 0% (black) to 100% (white).

[0079] Step S6.2: Color determination principle;

[0080] Step S6.2.1: Based on the HSV color image, extract the agglutination blocks from each reaction chamber image after preprocessing in step S4 using MATLAB software. Specifically, the H value of red blood cells in the reaction chamber image is between 355 and 10. Considering the background color of the antibody detection reagent, in actual work, extensive experiments have confirmed that the H value of red blood cells in the reaction chamber image is between 350 and 20, and the color of red blood cells does not change with concentration. For the same sample, its H value remains basically unchanged.

[0081] Step S6.2.2: Calculate the S / V value of each agglutination block. Specifically: After the agglutination reaction occurs, the red blood cells agglutinate together. During this process, the H value in the reaction chamber image does not change because the concentration of red blood cells increases after agglutination, and the saturation of the reaction chamber image increases, that is, the S value increases. The relationship between the S value and the number of red blood cells per unit area is a monotonically increasing function.

[0082] Light flux is inversely proportional to the number of red blood cells per unit area. That is, the more red blood cells per unit area, the weaker the light transmission capacity, i.e., the smaller the V value. The relationship between the V value and the number of red blood cells per unit area is a monotonically decreasing function.

[0083] That is, in this invention, the number of red blood cells per unit area is defined as ρ (degree of agglutination), the saturation coefficient as S, and the brightness coefficient as V, let:

[0084] S=f1(ρ) (1)

[0085]

[0086] The value of S increases with the increase of the value of ρ, and the value of 1 / V also increases with the increase of the value of ρ.

[0087] The following can be derived from formulas (1) and (2):

[0088]

[0089] The number of red blood cells per unit area (agglutination degree ρ) is a high-order monotonically increasing function with S / V as the variable, that is, there is a one-to-one mapping relationship between S / V and agglutination degree ρ.

[0090] Step S6.2.3: Determine the grade of agglutination reaction result based on the S / V value of the red blood cell region in the images of each reaction chamber after preprocessing in step S4.

[0091] The color determination rules are as follows:

[0092] (1) If S / V≥110%, the grade of the agglutination reaction result is determined to be positive grade 4;

[0093] (2) If 100% ≤ S / V < 110%, the grade of the agglutination reaction result is determined to be positive grade 3;

[0094] (3) If 90% ≤ S / V < 100%, the grade of the agglutination reaction result is determined to be positive grade 2;

[0095] (4) If 60% ≤ S / V < 90%, the grade of the agglutination reaction result is determined to be positive grade 1;

[0096] (5) If S / V < 60% and there are no agglomerates, the agglomeration reaction result is judged as negative.

[0097] Step S7: Comprehensive judgment;

[0098] A comprehensive judgment is made based on the size determination result of step S5 and the color determination result of step S6.

[0099] The comprehensive judgment rules are as follows:

[0100] (1) If the agglomeration reaction result level obtained after size determination in step S5 is consistent with the agglomeration reaction result level obtained after color determination in step S6, then the agglomeration reaction result level obtained after size determination or the agglomeration reaction result level obtained after color determination shall be selected as the final agglomeration reaction result level.

[0101] (2) If the agglomeration reaction result grade obtained after size determination in step S5 is inconsistent with the agglomeration reaction result grade obtained after color determination in step S6, the lower grade of agglomeration reaction result grade shall be selected as the final agglomeration reaction result grade.

[0102] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0103] Example 1: Blood Type Testing Agglutination Reaction Results and P-HSV Comprehensive Judgment Method

[0104] Blood samples were mixed with antibody detection reagents (monoclonal IgM blood group antibody and 0.5M trehalose were mixed at a volume ratio of 9:1; 6 μL of the mixture was pipetted and deposited in the center of the reaction chamber; and then dried in a laboratory incubator at 25°C for 30 min to obtain the antibody detection reagents). When the positive red blood cells in the blood and the detection reagents were thoroughly stirred, a reaction occurred, resulting in agglutination. The original image of the blood detection chip (manufacturer: Suzhou Hanguang Micro-Nano Technology Co., Ltd.) after the reaction was acquired using a CCD camera, as shown below. Figure 2 As shown. Images of each reaction chamber are extracted from the acquired raw image. Figure 3 As shown, five reaction chamber images, numbered a, e, and a respectively, can be extracted. Gaussian algorithm is used to denoise each reaction chamber image, removing edges and noise. The preprocessed reaction chamber images are shown below. Figure 4 As shown in ae. The following steps involve size and color determination, followed by a comprehensive determination.

[0105] 1. Size determination

[0106] The Canny algorithm was used to segment and determine the edges of each agglomerate block in the preprocessed reaction chamber images. The extracted agglomerate block edge images are shown below. Figure 5 As shown in Figure ae, the number n of agglomerates in the agglomerate edge image and the perimeter of each agglomerate edge contour are calculated. The grade of the agglomeration reaction result is determined based on the sum L of the perimeters of all agglomerate edge contours and the number n of agglomerates. Given that the reaction chamber diameter is 5 mm and the perimeter is 15.7 mm, the calculated pixel perimeter of the outer edge of the reaction chamber is 728. This determines the ratio between the actual perimeter of the reaction chamber and the pixel perimeter. When grading the agglomeration reaction result based on the sum L of the perimeters of all agglomerate edge contours, L is the sum of the pixel perimeters of all agglomerate edge contours after removing the pixel perimeter of the outer edge of the reaction chamber.

[0107] The size determination rules are as follows:

[0108] (1) If there is no agglutination mass in the edge image of the agglutination mass, and the red blood cells have the largest area, filling the reaction cavity, then the agglutination reaction result is judged as negative; Figure 4 As shown in e, the agglomeration reaction result shown in size determination diagram e is negative;

[0109] (2) If L≤500 and n≤4 in the edge image of the agglomerate, the grade of the agglomeration reaction result is determined to be positive, grade 4; Figure 4 As shown in Figure a, the agglutination reaction result shown in Figure a is positive at level 4, indicating the strongest agglutination. The red blood cells are basically agglutinated into a large mass, concentrated together, with a very small area.

[0110] (3) If 500 < L ≤ 1500 and 4 < n ≤ 10 in the edge image of the agglomerate, then the grade of the agglomeration reaction result is determined to be positive, level 3; Figure 4 As shown in b, the agglutination reaction result shown in Figure b is positive grade 3, with red blood cells agglutinated into one large mass and several small masses, and the area is slightly larger than that of positive grade 4.

[0111] (4) If 1500 < L ≤ 2500 and 10 < n ≤ 15 in the edge image of the agglomerate, then the grade of the agglomeration reaction result is determined to be positive, grade 2; Figure 4 As shown in Figure c, the agglutination reaction result shown in Figure c is positive grade 2, indicating that the red blood cells agglutinate into several small pieces with a larger area.

[0112] (5) If L > 2500 and n > 15 in the edge image of the agglomerate, the grade of the agglomeration reaction result is determined to be positive, level 1; Figure 4 As shown in d, the agglutination reaction result shown in the size determination diagram d is positive grade 1, with red blood cells agglutinating into many small pieces with a larger area.

[0113] 2. Color Determination

[0114] Agglutination blocks were extracted from the preprocessed reaction chamber images based on HSV color images using MATLAB software; the S / V value of each agglutination block was calculated using formulas (1), (2), and (3). The grade of the agglutination reaction result was determined based on the S / V value of the red blood cell region in the preprocessed reaction chamber images.

[0115] S=f1(ρ) (1)

[0116]

[0117]

[0118] In the formula, S is the saturation coefficient, V is the brightness coefficient, and ρ is the number of red blood cells per unit area, i.e., the degree of aggregation.

[0119] The color determination rules are as follows:

[0120] (1) If S / V ≥ 110%, the agglutination reaction result is classified as positive grade 4; Figure 4 As shown in Figure a, the agglutination reaction result shown in Figure a is positive at level 4, indicating the strongest agglutination. The red blood cells are basically agglutinated into a large mass, concentrated together, with a very small area.

[0121] (2) If 100% ≤ S / V < 110%, the agglutination reaction result is classified as positive grade 3; Figure 4As shown in b, the agglutination reaction result shown in Figure b is positive grade 3, with red blood cells agglutinated into one large mass and several small masses, and the area is slightly larger than that of positive grade 4.

[0122] (3) If 90% ≤ S / V < 100%, the agglutination reaction result is classified as positive grade 2; Figure 4 As shown in Figure c, the agglutination reaction result shown in Figure c is positive grade 2, indicating that the red blood cells agglutinate into several small pieces with a larger area.

[0123] (4) If 60% ≤ S / V < 90%, the agglutination reaction result is classified as positive grade 1; Figure 4 As shown in d, the agglutination reaction result shown in the size determination diagram d is positive grade 1, with red blood cells agglutinating into many small pieces with a larger area.

[0124] (5) If S / V < 60%, there is no agglutination clot, the red blood cells have the largest surface area, filling the reaction cavity, then the agglutination reaction result is judged as negative; Figure 4 As shown in Figure e, the agglomeration reaction result shown in Figure e is negative after size determination.

[0125] 3. Comprehensive judgment

[0126] The comprehensive judgment rules are as follows:

[0127] (1) If the agglomeration reaction result level obtained after size determination in step S5 is consistent with the agglomeration reaction result level obtained after color determination in step S6, then the agglomeration reaction result level obtained after size determination in step S5 or the agglomeration reaction result level obtained after color determination in step S6 shall be selected as the final agglomeration reaction result level. For example, if the agglomeration reaction result level obtained after size determination in step S5 is positive level 1 and the agglomeration reaction result level obtained after color determination in step S6 is positive level 2, then the agglomeration reaction result level obtained after size determination in step S5 (positive level 1) shall be selected as the final agglomeration reaction result level.

[0128] (2) If the agglomeration reaction result grade obtained after size determination in step S5 is inconsistent with the agglomeration reaction result grade obtained after color determination in step S6, the lower grade of agglomeration reaction result grade shall be selected as the final agglomeration reaction result grade.

[0129] Therefore, based on the aforementioned comprehensive judgment rules, a comprehensive judgment is made on each reaction chamber image extracted from the original image. Figure 4 The agglutination reaction results shown in Figure ae were classified as positive grade 4, positive grade 3, positive grade 2, positive grade 1, and negative, respectively.

[0130] This invention discloses a comprehensive P-HSV determination method for blood typing agglutination reaction results. Those skilled in the art can refer to this document and appropriately modify the process parameters to achieve the desired result. It is particularly important to note that all similar substitutions and modifications are obvious to those skilled in the art and are considered to be included in this invention. The product of this invention has been described through preferred embodiments, and those skilled in the art can clearly modify or appropriately change and combine the product described herein without departing from the content, spirit, and scope of this invention to realize and apply the technology of this invention.

Claims

1. A method for comprehensively judging the results of blood group detection agglutination reactions, characterized by, In the P-HSV, P represents the perimeter of the agglomerate's edge contour, H represents hue, S represents saturation, and V represents brightness. The method includes the following steps: Step S1: Mix the blood sample with the antibody test reagent to produce an agglutination reaction; The preparation method of the antibody detection reagent is as follows: Monoclonal IgM blood group antibody and 0.5 M trehalose were mixed at a volume ratio of 9:

1. 6 μL of the mixture of monoclonal IgM blood group antibody and trehalose was taken with a pipette and deposited in the center of the reaction chamber. The mixture was then dried in a laboratory incubator at 25°C for 30 min to obtain the antibody detection reagent. Step S2: Obtain the original image; Step S3: Extract the images of each reaction chamber from the original image; Step S4: Preprocess the images of each reaction chamber to remove edges and noise; Step S5: Size determination; Step S5.1: Extract the agglomerate edge image from the preprocessed reaction chamber image using the Canny algorithm; Step S5.2: Calculate the number n of agglomerates in the agglomerate edge image and the perimeter of the edge contour of each agglomerate; Step S5.3: Determine the grade of the agglomeration reaction result based on the sum of the perimeters L of the edge contours of all agglomerates and the number of agglomerates n; The size determination rules are as follows: (1) If there are no agglomerates in the edge image of the agglomerates, the agglomeration reaction result is judged to be negative; (2) If L≤500 and n≤4 in the edge image of the agglomerate, the grade of the agglomeration reaction result is judged as positive grade 4; (3) If 500 < L ≤ 1500 and 4 < n ≤ 10 in the edge image of the agglomerate, then the grade of the agglomeration reaction result is determined to be positive grade 3; (4) If 1500 < L ≤ 2500 and 10 < n ≤ 15 in the edge image of the agglomerate, the grade of the agglomeration reaction result is judged as positive grade 2; (5) If L > 2500 and n > 15 in the edge image of the agglomerate, the grade of the agglomeration reaction result is determined to be positive grade 1; Step S6: Color determination; Based on the HSV color image, agglutination blocks were extracted from the preprocessed reaction chamber images using MATLAB software; the S / V value of each agglutination block was calculated using formulas (1), (2) and (3); the grade of the agglutination reaction result was determined based on the S / V value of the red blood cell region in the preprocessed reaction chamber images. （1）； （2）； （3）； In the formula, S is the saturation, V is the brightness, the S value increases with the increase of the ρ value, and the value of 1 / V increases with the increase of the ρ value; The red blood cell quantity in a unit area, i.e. the agglomeration degree, is a high-order monotone increasing function of S / V, i.e. there is a one-to-one mapping relationship between S / V and the agglomeration degree ρ. The color determination rules are as follows: (1) If S / V≥110%, the grade of the agglutination reaction result is determined to be positive grade 4; (2) If 100%≤S / V<110%, the grade of the agglutination reaction result is determined to be positive grade 3; (3) If 90%≤S / V<100%, the grade of the agglutination reaction result is determined to be positive grade 2; (4) If 60%≤S / V<90%, the grade of the agglutination reaction result is determined to be positive grade 1; (5) If S / V < 60% and there are no agglomerates, the agglomeration reaction result is judged as negative; Step S7: Make a comprehensive judgment based on the size judgment result and the color judgment result; The comprehensive judgment rules are as follows: (1) If the agglomeration reaction result level obtained after size determination is consistent with the agglomeration reaction result level obtained after color determination, then the agglomeration reaction result level obtained after size determination or the agglomeration reaction result level obtained after color determination shall be selected as the final agglomeration reaction result level. (2) If the agglomeration reaction result grade obtained after size determination is inconsistent with the agglomeration reaction result grade obtained after color determination, the lower agglomeration reaction result grade shall be selected as the final agglomeration reaction result grade.

2. The method according to claim 1, wherein the method is characterized by, The specific steps of step S2 are as follows: A CCD camera is used to acquire the original image of the blood detection chip after the reaction.

3. The method according to claim 1, wherein the method is characterized by, In step S4, the Gaussian algorithm is used to denoise the images of each reaction chamber.

Images