A method, device, equipment and storage medium for detecting drug sensitivity of microorganisms

Abstract

The present application discloses a method, device, equipment and storage medium for detecting drug sensitivity of microorganisms, obtaining clinical samples of target microorganisms for a first enrichment treatment; taking the supernatant of the clinical samples and adding them to the micropores of multiple antibiotic test strips respectively; adding culture fluid to each of the antibiotic test strips for a preset period of time, injecting the liquid in the micropores of each of the antibiotic test strips into the corresponding counting plate, and performing a second enrichment treatment on each of the counting plates; collecting sample images of each of the counting plates, performing image recognition on the sample images, and determining the number of target microorganisms in each of the sample images; determining the minimum inhibitory concentration value of the antibiotic to the target microorganism according to the number of target microorganisms in the sample image and the antibiotic concentration of the antibiotic test strip corresponding to the sample image. This method can improve the accuracy and efficiency of drug sensitivity detection. The present application can be widely used in the field of medical detection technology.

Description

Technical Field

[0001] The present application relates to the field of medical detection technology, and in particular to a method, device, equipment and storage medium for detecting drug sensitivity of microorganisms. Background Art

[0002] Microbial infections such as bacteria can cause a variety of diseases, which not only have a high incidence rate but also often lead to critical illness, seriously endangering human health and life. Therefore, timely and accurate etiological detection of various microbial infection diseases is an important issue in the field of clinical laboratory medicine.

[0003] In related technologies, drug sensitivity testing mainly detects the ability of antibiotics to inhibit or kill bacteria. Its main functions include guiding clinical drug use, monitoring drug-resistant bacteria, discovering new drug resistance mechanisms, and evaluating indicators when researching new drugs. The MIC (Minimum Inhibitory Concentration) value in the drug sensitivity test result report refers to the lowest concentration value at which the antibiotic can inhibit bacterial growth. This data is helpful for clinical scientific drug use and preventing the evolution of drug-resistant strains. Traditional drug sensitivity testing methods often have problems with low accuracy or long time consumption, which affects the effectiveness of drug sensitivity testing.

[0004] In summary, the problems existing in related technologies need to be solved urgently. Summary of the invention

[0005] The purpose of this application is to solve one of the technical problems existing in the related art to at least a certain extent.

[0006] To this end, an object of the embodiments of the present application is to provide a method, device, equipment and storage medium for detecting microbial drug sensitivity.

[0007] In order to achieve the above technical objectives, the technical solutions adopted by the embodiments of the present application include:

[0008] On the one hand, the present invention provides a method for detecting drug sensitivity of microorganisms, comprising the following steps:

[0009] Obtain clinical samples of target microorganisms for first enrichment processing;

[0010] Taking the supernatant of the clinical sample, and adding it to the microwells of a plurality of antibiotic test strips respectively; the antibiotic concentrations of the plurality of antibiotic test strips are distributed in a gradient manner;

[0011] After adding culture fluid to each of the antibiotic test strips and culturing for a preset time, injecting the liquid in the micropores of each of the antibiotic test strips into a corresponding counting plate, and performing a second enrichment treatment on each of the counting plates;

[0012] Collecting sample images of each of the counting plates, performing image recognition on the sample images, and determining the number of the target microorganisms in each of the sample images;

[0013] The minimum inhibitory concentration value of the antibiotic to the target microorganism is determined according to the number of the target microorganism in the sample image and the antibiotic concentration of the antibiotic test strip corresponding to the sample image.

[0014] In addition, a microbial drug sensitivity detection method according to the above embodiment of the present application may also have the following additional technical features:

[0015] Furthermore, in one embodiment of the present application, the supernatant of the clinical sample is taken and added to the microwells of a plurality of antibiotic test strips respectively, comprising:

[0016] Taking the supernatant of the clinical sample and dividing it equally to obtain multiple supernatant samples;

[0017] Each of the supernatant samples is added into the microwell of the corresponding antibiotic test strip.

[0018] Furthermore, in one embodiment of the present application, the antibiotic test strip includes a blank control group test strip, and the antibiotic concentration in the blank control group test strip is 0.

[0019] Further, in one embodiment of the present application, the collecting of sample images of each of the counting plates includes:

[0020] The sample image is obtained by performing image acquisition operation on the counting plate through phase contrast microscopy imaging technology.

[0021] Furthermore, in one embodiment of the present application, performing image recognition on the sample images to determine the number of the target microorganisms in each of the sample images includes:

[0022] Performing image segmentation on the sample image to obtain a plurality of microorganism sub-images to be identified;

[0023] Inputting the microorganism subgraph to be identified into a trained classifier for identification, and obtaining classification results of the microorganisms in the microorganism subgraph to be identified;

[0024] The number of the target microorganisms in the sample image is determined according to the classification results corresponding to each of the to-be-identified microorganism sub-images.

[0025] Furthermore, in one embodiment of the present application, the image segmentation is performed on the sample image to obtain a plurality of microorganism sub-images to be identified, including:

[0026] Calculating a pixel mean of the sample image;

[0027] According to the pixel mean, a target pixel point is determined from the sample image; the absolute value of the difference between the pixel value of the target pixel point and the pixel mean is greater than a preset threshold;

[0028] In the sample image, determining a plurality of connected areas formed by the target pixel points;

[0029] Each of the connected areas is cropped from the sample image to obtain a plurality of microorganism sub-images to be identified.

[0030] Further, in one embodiment of the present application, determining the minimum inhibitory concentration value of the antibiotic against the target microorganism according to the number of the target microorganism in the sample image and the antibiotic concentration of the antibiotic test strip corresponding to the sample image includes:

[0031] sequentially calculating the difference in the number of target microorganisms in the sample image corresponding to two adjacent antibiotic test strips of antibiotic concentration;

[0032] When the number difference is less than a preset threshold, the smaller value of the two adjacent antibiotic concentrations is determined as the minimum inhibitory concentration value.

[0033] On the other hand, the present application provides a microbial drug sensitivity detection system, comprising:

[0034] An acquisition unit, used for acquiring a clinical sample of a target microorganism for a first enrichment process;

[0035] An adding unit is used to take the supernatant of the clinical sample and add it to the microwells of a plurality of antibiotic test strips respectively; the antibiotic concentrations of the plurality of antibiotic test strips are distributed in a gradient manner;

[0036] A culture unit, used for adding culture solution to each of the antibiotic test strips and culturing for a preset time, injecting the liquid in the micropores of each of the antibiotic test strips into a corresponding counting plate, and performing a second enrichment process on each of the counting plates;

[0037] A collection unit, used to collect sample images of each of the counting plates, perform image recognition on the sample images, and determine the number of the target microorganisms in each of the sample images;

[0038] The processing unit is used to determine the minimum inhibitory concentration value of the antibiotic to the target microorganism according to the number of the target microorganism in the sample image and the antibiotic concentration of the antibiotic test strip corresponding to the sample image.

[0039] On the other hand, an embodiment of the present application provides a computer device, including:

[0040] at least one processor;

[0041] at least one memory for storing at least one program;

[0042] When the at least one program is executed by the at least one processor, the at least one processor implements the above-mentioned microbial drug sensitivity detection method.

[0043] On the other hand, an embodiment of the present application further provides a computer-readable storage medium, which stores a program executable by a processor. When the program executable by the processor is executed by the processor, it is used to implement the above-mentioned microbial drug sensitivity detection method.

[0044] The advantages and benefits of the present application will be partially given in the following description, and partially become apparent from the following description, or be understood through the practice of the present application:

[0045] A method, device, equipment and storage medium for detecting drug sensitivity of microorganisms disclosed in the embodiments of the present application, obtains clinical samples of target microorganisms for a first enrichment process; takes the supernatant of the clinical samples and adds them to the micropores of multiple antibiotic test strips respectively; after adding culture fluid to each of the antibiotic test strips and culturing for a preset time, the liquid in the micropores of each of the antibiotic test strips is injected into the corresponding counting plate, and each of the counting plates is subjected to a second enrichment process; collects sample images of each of the counting plates, performs image recognition on the sample images, and determines the number of target microorganisms in each of the sample images; according to the number of target microorganisms in the sample images and the antibiotic concentration of the antibiotic test strip corresponding to the sample image, determines the minimum inhibitory concentration value of the antibiotic to the target microorganism. This method can improve the accuracy and efficiency of drug sensitivity detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following introduction is made to the drawings of the embodiments of the present application or the related technical solutions in the prior art. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 A schematic diagram of a process for detecting drug sensitivity of microorganisms provided in an embodiment of the present application;

[0048] Figure 2 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] The present application is further described below in conjunction with the accompanying drawings and specific embodiments. The described embodiments should not be regarded as limiting the present application, and all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0050] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0052] Microbial infections such as bacteria can cause a variety of diseases, which not only have a high incidence rate but also often lead to critical illness, seriously endangering human health and life. Therefore, timely and accurate etiological detection of various microbial infection diseases is an important issue in the field of clinical laboratory medicine.

[0053] In the related technology, the detection tasks for microorganisms include clinical drug sensitivity testing, which is to detect the MIC (Minimum Inhibitory Concentration) value of antimicrobial drugs. This data helps to improve the prognosis of patients and prevent the evolution of drug-resistant microbial strains. To determine the minimum inhibitory concentration value, it is necessary to accurately and effectively count the microorganisms. Taking bacteria as an example, traditional bacterial counting methods include turbidimetry, colony counting method, counter determination method, etc. Among them, the turbidimetry method indirectly determines the number of bacteria based on the transmittance of the bacterial suspension. The concentration of the bacterial suspension is inversely proportional to the transmittance within a certain range and is proportional to the optical density. This method is simple and fast, but it has certain requirements for the concentration of the bacterial solution. Too low or too high a concentration of bacterial solution cannot be accurately counted. The colony counting method uses the principle that each living bacterium can grow into a colony. The quantitatively diluted bacterial suspension is cultured on a plate. Based on the number of colonies cultured, the number of living bacteria in the culture can be calculated. This method has high sensitivity and is mostly used to detect the number of living bacteria in contamination. However, it is limited to microorganisms that can form colonies, and the count of too many or too few colonies will be inaccurate.

[0054] Flow cytometry is the most commonly used method for direct cell counting. It can achieve accurate counting at the single cell level and has an extremely fast analysis speed. However, since the bacterial particle size exceeds the cell size resolution limit of the flow cytometer, the results of counting bacteria using traditional flow cytometry are highly biased, and the instrument is expensive. In summary, traditional drug sensitivity testing methods often have problems such as low accuracy or long time consumption, which affects the effect of drug sensitivity testing.

[0055] In view of this, a method for detecting drug sensitivity of microorganisms is provided in an embodiment of the present application. The method enriches the microorganisms in the sample through enrichment treatment, uses microscopic imaging technology to capture high-contrast images of the enriched translucent sample, and then combines the image recognition algorithm to identify and count the microorganisms in the counting plate into which antibiotics of different concentrations are dropped. The minimum inhibitory concentration value of the antibiotic is determined by this absolute counting method, so that the antibacterial ability of the antibiotic and the drug resistance of the bacterial species can be accurately and efficiently determined.

[0056] Please refer to Figure 1 , Figure 1 1 is a flow chart of a microbial drug sensitivity detection method provided in an embodiment of the present application. The microbial drug sensitivity detection method can be configured to be executed in at least one of a terminal device or a server. Figure 1 The microbial drug sensitivity detection method includes but is not limited to:

[0057] Step 110, obtaining a clinical sample of the target microorganism and performing a first enrichment process;

[0058] In this step, the target microorganism refers to the microorganism whose drug sensitivity is to be tested, for example, it may include a certain type of infectious pathogenic bacteria. When performing drug sensitivity testing, a clinical sample of the target microorganism is first obtained, and then the clinical sample is enriched, which is recorded as the first enrichment treatment. Specifically, for example, in some embodiments, the clinical sample can be placed in a related centrifugal device, and then the clinical sample is centrifuged for a predetermined time by the centrifugal device to obtain the clinical sample after the first enrichment treatment. In the embodiment of the present application, the purpose of the first enrichment treatment is to enrich the target microorganism in the clinical sample into the supernatant, so as to facilitate subsequent culture and counting processing. It can be understood that in the embodiment of the present application, the specific implementation of the enrichment treatment is not fixed to centrifugal treatment. For example, in other embodiments, the enrichment treatment can also be carried out by shaking, shaking, etc., and the present application does not limit this.

[0059] Step 120, taking the supernatant of the clinical sample and adding it to the microwells of a plurality of antibiotic test strips respectively; the antibiotic concentrations of the plurality of antibiotic test strips are distributed in a gradient manner;

[0060] In this step, after obtaining the clinical sample for the first enrichment treatment, the supernatant of the clinical sample can be taken. As mentioned above, after the first enrichment treatment, the target microorganisms suspended in the clinical sample can be almost completely enriched in the supernatant, so the efficiency of subsequent cultivation can be improved and the time required for microbial drug sensitivity detection can be reduced. Then, these supernatants can be added to the micropores of multiple antibiotic test strips. Here, the antibiotic test strips are pre-configured with the same type of antibiotics, and the concentrations of antibiotics in different antibiotic test strips are different. Specifically, in some embodiments, the antibiotic concentration configured in the antibiotic test strips can be arranged in a gradient, and in these antibiotic test strips, a group of blank control group test strips can be set, and the antibiotic concentration in the blank control group test strips is 0, so that the inhibitory effect of antibiotics on microorganisms can be easily compared. In some embodiments, in order to improve the overall process of detection, the supernatant obtained can be evenly divided to obtain multiple supernatant samples, and then each supernatant sample is added to the micropores of the corresponding antibiotic test strips. In this way, the concentration of microorganisms in each antibiotic test strip can be made roughly the same during the initial distribution, thereby reducing the time difference caused by uneven distribution in the subsequent culture process, and greatly speeding up the overall efficiency of the test.

[0061] Step 130: After adding culture solution to each of the antibiotic test strips and culturing for a preset time, inject the liquid in the micropores of each of the antibiotic test strips into the corresponding counting plate, and perform a second enrichment treatment on each of the counting plates.

[0062] In this step, after adding supernatant to each antibiotic test strip, culture solution can be added to cultivate for a preset time. Here, the length of the preset time can be flexibly set according to actual needs, and this application is not limited to this. When the duration of the culture reaches the preset duration, the proliferation of the microorganism is terminated, and the liquid in the micropores of each antibiotic test strip is injected into the corresponding counting plate, and the counting plate here can adopt a disposable transparent counting plate. After the liquid is injected into the corresponding counting plate, the counting plate can be enriched, which is recorded as the second enrichment treatment here. After the second enrichment treatment, the microorganisms will be efficiently enriched on the bottom surface of the counting plate, which is convenient for subsequent counting and identification.

[0063] Step 140: collecting sample images of each of the counting plates, performing image recognition on the sample images, and determining the number of the target microorganisms in each of the sample images;

[0064] In this step, for each counting plate, its sample image can be collected, and then the sample image can be image recognized to determine the number of target microorganisms in each sample image. Specifically, in some embodiments, the counting plate can be imaged by phase contrast microscopy imaging technology to obtain a sample image. After obtaining the sample image, the sample image can be image recognized to determine the number of target microorganisms therein.

[0065] Specifically, in some embodiments, performing image recognition on the sample images to determine the number of the target microorganisms in each of the sample images includes:

[0066] Performing image segmentation on the sample image to obtain a plurality of microorganism sub-images to be identified;

[0067] Inputting the microorganism subgraph to be identified into a trained classifier for identification, and obtaining classification results of the microorganisms in the microorganism subgraph to be identified;

[0068] The number of the target microorganisms in the sample image is determined according to the classification results corresponding to each of the to-be-identified microorganism sub-images.

[0069] In an embodiment of the present application, when identifying the number of microorganisms in a sample image, first, the sample image can be segmented to obtain multiple sub-images of microorganisms to be identified. Each sub-image of microorganisms to be identified obtained after segmentation generally includes an image of a microorganism. Next, the sub-image of microorganisms to be identified can be input into a trained classifier, and the category of the microorganisms in the sub-image is predicted by the classifier to obtain the classification result of the microorganisms in the sub-image of microorganisms to be identified. Here, the selected classifier can be a classifier built with any model architecture in the relevant technology, and the present application does not limit the training process of the classifier.

[0070] After the classification results corresponding to each microorganism sub-image are obtained, it is possible to count how many microorganisms in the microorganism sub-image belong to the category of the target microorganism, and determine the number of target microorganisms in the sample image. It is understandable that in the embodiment of the present application, by performing microbial segmentation and recognition processing on the sample image, the microorganisms can be effectively counted and classified, and the actual number of target microorganisms can be determined more accurately, reducing the interference that other types of microorganisms may cause to the experiment, which is conducive to improving the accuracy of the minimum inhibitory concentration value obtained.

[0071] In some embodiments, the image segmentation of the sample image to obtain a plurality of microorganism sub-images to be identified includes:

[0072] Calculating a pixel mean of the sample image;

[0073] According to the pixel mean, a target pixel point is determined from the sample image; the absolute value of the difference between the pixel value of the target pixel point and the pixel mean is greater than a preset threshold;

[0074] In the sample image, determining a plurality of connected areas formed by the target pixel points;

[0075] Each of the connected areas is cropped from the sample image to obtain a plurality of microorganism sub-images to be identified.

[0076] In an embodiment of the present application, when performing image segmentation on a sample image, it can be performed based on pixel threshold segmentation. Specifically, the pixel mean of all pixels in the sample image can be calculated first, and then the target pixel point can be determined from the sample image based on the pixel mean, where the target pixel point refers to the pixel point that deviates greatly from the pixel mean. Generally speaking, the pixel difference between the color of the microorganism in the sample image and the background color is large, so the pixel point whose absolute value of the difference with the pixel mean is greater than a preset threshold can be determined as the target pixel point, and the position of the target pixel point is the microorganism. Then, the connected area formed by each target pixel point can be cropped out in the sample image, so that a plurality of microorganism sub-images to be identified can be obtained.

[0077] Step 150: Determine the minimum inhibitory concentration value of the antibiotic against the target microorganism according to the number of the target microorganism in the sample image and the antibiotic concentration of the antibiotic test strip corresponding to the sample image.

[0078] Specifically, in this step, after the number of target microorganisms in each sample image is detected, the difference in the number of target microorganisms in the sample images corresponding to the antibiotic test strips of two adjacent antibiotic concentrations can be calculated in sequence. If the difference in the number is large, it means that changing the antibiotic concentration at this time is still relatively effective in inhibiting the proliferation of the target microorganism; conversely, if the difference in the number is small, it means that changing the antibiotic concentration at this time has little effect on inhibiting the proliferation of the target microorganism, indicating that the antibiotic concentration that can inhibit the proliferation of microorganisms has been reached. Therefore, in the embodiment of the present application, it is possible to start with a lower antibiotic concentration, calculate the difference in the number of target microorganisms in the sample images corresponding to the antibiotic test strips of two adjacent antibiotic concentrations in sequence, and set a preset threshold for comparison. When the difference in the number is less than the preset threshold, the smaller value of the two adjacent antibiotic concentrations at this time is determined as the minimum inhibitory concentration value; when the difference in the number is greater than or equal to the preset threshold, continue to calculate the difference in the number of target microorganisms in the sample images corresponding to the antibiotic test strips of the next group of two adjacent antibiotic concentrations.

[0079] The implementation principle of step 150 in this application is explained below with reference to specific cases.

[0080] In the embodiment of the present application, an equal volume of an Escherichia coli sample of a certain initial concentration can be added to each micropore of an antibiotic test strip, taken out after culturing for 2 hours, and the sample in each micropore is centrifuged and analyzed by the above method. In this embodiment, the antibiotic concentration in each micropore is 0.032ug / mL, 0.064ug / mL, 0.125ug / mL, 0.25ug / mL, 0.5ug / mL, 1ug / mL, 2ug / mL, 4ug / mL, 8ug / mL, 16ug / mL, 32ug / mL, 0ug / mL (control group) in sequence. Finally, by collecting and comparing the number of Escherichia coli in each sample image, it is found that starting from the sample with an antibiotic concentration of 0.25ug / mL (the 4th), as the antibiotic concentration increases, the number of Escherichia coli has no obvious proliferation. Therefore, it can be preliminarily judged that the MIC value of the antibiotic to Escherichia coli is about 0.25ug / mL.

[0081] In an embodiment of the present application, a microbial drug sensitivity detection system is also provided, comprising:

[0082] An acquisition unit, used for acquiring a clinical sample of a target microorganism for a first enrichment process;

[0083] An adding unit is used to take the supernatant of the clinical sample and add it to the microwells of a plurality of antibiotic test strips respectively; the antibiotic concentrations of the plurality of antibiotic test strips are distributed in a gradient manner;

[0084] A culture unit, used for adding culture solution to each of the antibiotic test strips and culturing for a preset time, injecting the liquid in the micropores of each of the antibiotic test strips into a corresponding counting plate, and performing a second enrichment process on each of the counting plates;

[0085] A collection unit, used to collect sample images of each of the counting plates, perform image recognition on the sample images, and determine the number of the target microorganisms in each of the sample images;

[0086] The processing unit is used to determine the minimum inhibitory concentration value of the antibiotic to the target microorganism according to the number of the target microorganism in the sample image and the antibiotic concentration of the antibiotic test strip corresponding to the sample image.

[0087] Understandably, Figure 1 The contents of the microbial drug sensitivity detection method embodiment shown in the figure are applicable to the microbial drug sensitivity detection system embodiment of the present invention. The functions specifically implemented by the microbial drug sensitivity detection system embodiment are the same as those in the embodiment of the present invention. Figure 1 The microbial drug sensitivity detection method embodiment shown is the same as that of Figure 1 The beneficial effects achieved by the embodiment of the microbial drug sensitivity detection method shown are also the same.

[0088] Reference Figure 2 , the embodiment of the present application further discloses a computer device, including:

[0089] at least one processor 201;

[0090] At least one memory 202, used to store at least one program;

[0091] When at least one program is executed by at least one processor 201, at least one processor 201 implements the following Figure 1 An example of a method for detecting drug sensitivity of microorganisms is shown.

[0092] It is understandable that if Figure 1 The contents of the microbial drug sensitivity detection method embodiment shown in the figure are applicable to the computer device embodiment, and the functions specifically implemented by the computer device embodiment are similar to those in the example shown in the figure. Figure 1 The microbial drug sensitivity detection method embodiment shown is the same as that shown in Figure 1 The beneficial effects achieved by the embodiment of the microbial drug sensitivity detection method shown are also the same.

[0093] The present application also discloses a computer-readable storage medium in which a program executable by a processor is stored. When the program executable by the processor is executed by the processor, it is used to implement the following Figure 1 An example of a method for detecting drug sensitivity of microorganisms is shown.

[0094] It is understandable that if Figure 1 The contents of the microbial drug sensitivity detection method embodiment shown in the figure are all applicable to the computer-readable storage medium embodiment, and the functions specifically implemented by the computer-readable storage medium embodiment are similar to those in the embodiment shown in the figure. Figure 1 The microbial drug sensitivity detection method embodiment shown is the same as that shown in Figure 1 The beneficial effects achieved by the embodiment of the microbial drug sensitivity detection method shown are also the same.

[0095] In some selectable embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the application is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Selectable embodiments are expected, wherein the order of various operations is changed and the sub-operation of a part described as a larger operation is performed independently.

[0096] In addition, although the present application is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present application. More specifically, in view of the properties, functions, and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional techniques of the engineer. Therefore, those skilled in the art can implement the present application set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present application, which is determined by the full scope of the attached claims and their equivalents.

[0097] If the function 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 technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0098] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0099] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0100] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0101] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0102] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

[0103] The above is a specific description of the preferred implementation of the present application, but the present application is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present application.

[0104] In the description of this specification, the description with reference to the terms "one embodiment", "another embodiment" or "certain embodiments" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiments or examples are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0105] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims

1. A computer device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements a method for detecting drug sensitivity of microorganisms; The microbial drug sensitivity detection method comprises: Obtain clinical samples of target microorganisms for first enrichment processing; Taking the supernatant of the clinical sample, and adding it to the microwells of a plurality of antibiotic test strips respectively; the antibiotic concentrations of the plurality of antibiotic test strips are distributed in a gradient manner; After adding culture fluid to each of the antibiotic test strips and culturing for a preset time, injecting the liquid in the micropores of each of the antibiotic test strips into a corresponding counting plate, and performing a second enrichment treatment on each of the counting plates; Collecting sample images of each of the counting plates, performing image recognition on the sample images, and determining the number of the target microorganisms in each of the sample images; Determining the minimum inhibitory concentration value of the antibiotic to the target microorganism according to the number of the target microorganism in the sample image and the antibiotic concentration of the antibiotic test strip corresponding to the sample image; Determining the minimum inhibitory concentration value of the antibiotic to the target microorganism according to the number of the target microorganism in the sample image and the antibiotic concentration of the antibiotic test strip corresponding to the sample image includes: sequentially calculating the difference in the number of target microorganisms in the sample image corresponding to two adjacent antibiotic test strips of antibiotic concentration; When the number difference is less than a preset threshold, the smaller value of the two adjacent antibiotic concentrations is determined as the minimum inhibitory concentration value.

2. A computer device according to claim 1, characterized in that: The supernatant of the clinical sample is taken and added to the microwells of a plurality of antibiotic test strips respectively, comprising: Taking the supernatant of the clinical sample and dividing it equally to obtain multiple supernatant samples; Each of the supernatant samples is added into the microwell of the corresponding antibiotic test strip.

3. A computer device according to claim 1, characterized in that: The antibiotic test strips include blank control group test strips, and the antibiotic concentration in the blank control group test strips is 0.

4. A computer device according to claim 1, characterized in that: The collecting of sample images of each counting plate comprises: The sample image is obtained by performing image acquisition operation on the counting plate through phase contrast microscopy imaging technology.

5. A computer device according to claim 1, characterized in that: The performing image recognition on the sample images to determine the number of the target microorganisms in each of the sample images includes: Performing image segmentation on the sample image to obtain a plurality of microorganism sub-images to be identified; Inputting the microorganism subgraph to be identified into a trained classifier for identification, and obtaining classification results of the microorganisms in the microorganism subgraph to be identified; The number of the target microorganisms in the sample image is determined according to the classification results corresponding to each of the to-be-identified microorganism sub-images.

6. A computer device according to claim 5, characterized in that: The image segmentation of the sample image to obtain a plurality of microorganism sub-images to be identified includes: Calculating a pixel mean of the sample image; According to the pixel mean, a target pixel point is determined from the sample image; the absolute value of the difference between the pixel value of the target pixel point and the pixel mean is greater than a preset threshold; In the sample image, determining a plurality of connected areas formed by the target pixel points; Each of the connected areas is cropped from the sample image to obtain a plurality of microorganism sub-images to be identified.

7. A microbial drug sensitivity detection system, characterized in that: include: An acquisition unit, used for acquiring a clinical sample of a target microorganism for a first enrichment process; An adding unit, used for taking the supernatant of the clinical sample and adding it into the microwells of a plurality of antibiotic test strips respectively; The antibiotic concentrations of the plurality of antibiotic test strips are distributed in a gradient; A culture unit, used for adding culture solution to each of the antibiotic test strips and culturing for a preset time, injecting the liquid in the micropores of each of the antibiotic test strips into a corresponding counting plate, and performing a second enrichment process on each of the counting plates; A collection unit, used to collect sample images of each of the counting plates, perform image recognition on the sample images, and determine the number of the target microorganisms in each of the sample images; a processing unit, configured to determine a minimum inhibitory concentration value of the antibiotic against the target microorganism according to the number of the target microorganism in the sample image and the antibiotic concentration of the antibiotic test strip corresponding to the sample image; Determining the minimum inhibitory concentration value of the antibiotic to the target microorganism according to the number of the target microorganism in the sample image and the antibiotic concentration of the antibiotic test strip corresponding to the sample image includes: sequentially calculating the difference in the number of target microorganisms in the sample image corresponding to two adjacent antibiotic test strips of antibiotic concentration; When the number difference is less than a preset threshold, the smaller value of the two adjacent antibiotic concentrations is determined as the minimum inhibitory concentration value.

8. A computer-readable storage medium storing a program executable by a processor, characterized in that: The processor-executable program is used to implement a microbial drug sensitivity detection method when executed by the processor; The microbial drug sensitivity detection method comprises: Obtain clinical samples of target microorganisms for first enrichment processing; Taking the supernatant of the clinical sample, and adding it to the microwells of a plurality of antibiotic test strips respectively; the antibiotic concentrations of the plurality of antibiotic test strips are distributed in a gradient manner; After adding culture fluid to each of the antibiotic test strips and culturing for a preset time, injecting the liquid in the micropores of each of the antibiotic test strips into a corresponding counting plate, and performing a second enrichment treatment on each of the counting plates; Collecting sample images of each of the counting plates, performing image recognition on the sample images, and determining the number of the target microorganisms in each of the sample images; Determining the minimum inhibitory concentration value of the antibiotic to the target microorganism according to the number of the target microorganism in the sample image and the antibiotic concentration of the antibiotic test strip corresponding to the sample image; Determining the minimum inhibitory concentration value of the antibiotic to the target microorganism according to the number of the target microorganism in the sample image and the antibiotic concentration of the antibiotic test strip corresponding to the sample image includes: sequentially calculating the difference in the number of target microorganisms in the sample image corresponding to two adjacent antibiotic test strips of antibiotic concentration; When the number difference is less than a preset threshold, the smaller value of the two adjacent antibiotic concentrations is determined as the minimum inhibitory concentration value.

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