Blood collection tube identification proofreading method and system, terminal and medium

Abstract

The invention relates to the technical field of blood collection tube inspection, and discloses a blood collection tube recognition and proofreading method and system, a terminal and a medium, and the blood collection tube recognition and proofreading method comprises the steps: obtaining feature information and label information of a blood collection tube; according to the feature information and the label information, obtaining actual color features of the blood collection tube and a target inspection item of a user; acquiring preset comparison data of a blood collection tube and an inspection item, and determining a matching result of the blood collection tube and the current inspection item according to the preset comparison data, the actual color feature and the target inspection item; and sending a prompt to a worker according to the matching result. The physical characteristics of the blood collection tube are corrected through image recognition, so that specimen scrapping and repeated blood collection caused by tube type errors are avoided from the source, and the blood collection accuracy and efficiency are improved.

Description

Technical Field

[0001] This application relates to the field of blood collection tube testing technology, and in particular to a blood collection tube identification and calibration method, system, terminal and medium. Background Technology

[0002] During intravenous blood collection in hospitals, different colored and sized blood collection tubes are used depending on the blood test performed, and labels containing user information and the test results are affixed to the tubes. This process is crucial for ensuring the accuracy of test results. Currently, the common blood collection procedure involves medical staff manually selecting blood collection tubes, affixing pre-printed labels, and using a portable data terminal (PDA) at the bedside to scan the user's wristband QR code to verify the user's identity, and scanning the barcode on the test tube to confirm that the test results match the user information.

[0003] The existing PDA scanning verification method has obvious shortcomings and cannot identify the type of blood collection tube: the existing technology can only verify electronic information (user identity, test items), but cannot identify whether the physical characteristics of the blood collection tube itself (such as the color of the tip and the specifications) match the test tube type required by the test items.

[0004] Therefore, existing technologies still need to be improved and developed. Summary of the Invention

[0005] The main purpose of this application is to provide a blood collection tube identification and verification method, system, terminal and medium, which aims to solve the problem that in the prior art, when staff use PDAs to scan codes to verify user identity and test tube test items, they cannot identify the unique characteristics of the blood collection tubes, which easily leads to mismatch between the blood collection tubes and test items, requiring blood to be drawn again, resulting in low efficiency.

[0006] The first aspect of this application provides a blood collection tube identification and calibration method, which includes the following steps: Obtain the characteristic and label information of the blood collection tubes; Based on the feature information and the label information, the actual color characteristics of the blood collection tube and the user's target inspection items are obtained; Obtain preset comparison data between blood collection tubes and test items, and determine the matching result between the blood collection tubes and the current test items based on the preset comparison data, the actual color characteristics, and the target test items; A reminder will be sent to staff based on the matching results.

[0007] Optionally, in one embodiment of this application, the step of obtaining the feature information and tag information of the blood collection tube further includes: Obtain the user's target information; The target information is authenticated to obtain the authentication result; When the verification result is successful, the feature information and label information of the blood collection tube are obtained.

[0008] Optionally, in one embodiment of this application, the feature information includes test tube type, and the label information includes project label; The acquisition of the feature information and tag information of the blood collection tube specifically includes: Acquire the target image within the set range of the blood collection tube; Identify the test tube type and item label corresponding to the blood collection tube in the target image.

[0009] Optionally, in one embodiment of this application, obtaining the actual color characteristics of the blood collection tube and the user's target inspection items based on the feature information and the label information specifically includes: The user's target testing items are determined based on the project tags; The actual color characteristics of the blood collection tube are obtained based on the test tube type and the item label.

[0010] Optionally, in one embodiment of this application, the test tube type includes image color features, and the item label includes label color features; The step of obtaining the actual color characteristics of the blood collection tube based on the test tube type and the item label specifically includes: Based on the color characteristics of the label, the color deviation data of the blood collection tube is obtained; The actual color features of the blood collection tube are obtained based on the image color features and the color deviation data.

[0011] Optionally, in one embodiment of this application, obtaining the actual color features of the blood collection tube based on the image color features and the color deviation data specifically includes: A color deviation model is constructed, and the color deviation model is trained based on the color deviation data to obtain a trained color deviation model; The image color features are input into a trained color deviation model for color correction to obtain the actual color features of the blood collection tube.

[0012] Optionally, in one embodiment of this application, determining the matching result between the blood collection tube and the current test item based on the preset comparison data, the actual color features, and the target test item specifically includes: Based on the preset comparison data and the target inspection item, determine the target color feature of the user's current inspection item; The actual color features are compared with the target color features to obtain the difference data; If the difference data is within the preset tolerance threshold, then the matching result between the blood collection tube and the current test item is determined to be a correct match; If the difference data is not within the preset tolerance threshold, then the matching result between the blood collection tube and the current test item is determined to be a matching error.

[0013] A second aspect of this application also provides a blood collection tube identification and calibration system, wherein the blood collection tube identification and calibration system is applied to the blood collection tube identification and calibration method described in any of the above solutions; the blood collection tube identification and calibration system includes: The information acquisition module is used to acquire the feature information and tag information of the blood collection tubes; The feature recognition module is used to obtain the actual color features of the blood collection tube and the user's target inspection items based on the feature information and the label information. The item matching module is used to acquire preset comparison data between blood collection tubes and test items, and determine the matching result between the blood collection tube and the current test item based on the preset comparison data, the actual color features, and the target test item. The result notification module is used to send reminders to staff based on the matching results.

[0014] A third aspect of this application also provides a terminal, wherein the terminal includes: a memory, a processor, and a blood collection tube identification and calibration program stored in the memory and executable on the processor, wherein when the blood collection tube identification and calibration program is executed by the processor, it implements the steps of the blood collection tube identification and calibration method as described above.

[0015] A fourth aspect of this application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a blood collection tube identification and calibration program, and the blood collection tube identification and calibration program, when executed by a processor, implements the steps of the blood collection tube identification and calibration method as described above.

[0016] Beneficial effects: This application provides a blood collection tube identification and calibration method, system, terminal and medium. This application calibrates the physical characteristics of blood collection tubes through image recognition, thereby avoiding specimen rejection and repeated blood collection due to incorrect tube type at the source, and improving the accuracy and efficiency of blood collection. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a preferred embodiment of the blood collection tube identification and calibration method of this application; Figure 2 This is a structural diagram of a preferred embodiment of the blood collection tube identification and calibration system of this application; Figure 3 This is a structural diagram of a preferred embodiment of the terminal of this application.

[0019] Explanation of reference numerals in the attached figures: 100. Information Acquisition Module; 200. Feature Recognition Module; 300. Item Matching Module; 400. Result Prompt Module. Detailed Implementation

[0020] To make the objectives, technical solutions, and effects of this application clearer and more explicit, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. The described embodiments are only possible technical implementations of this application and not all possible implementations. Based on the embodiments in this application, those skilled in the art can obtain other embodiments without creative effort, and these embodiments are also within the protection scope of this application.

[0021] In these related technologies, manual operation is highly dependent on the entire process, from tube collection and labeling to verification. This relies on visual judgment and manual operation, making it extremely easy for human errors such as picking the wrong tube or labeling the wrong item to occur under busy or fatigued conditions. Furthermore, error correction is delayed; these errors are often only discovered after the sample has arrived at the laboratory, requiring the hospital to contact the user for re-collection of blood. This not only severely impacts user experience and medical quality but also increases the hospital's operating costs.

[0022] Based on existing user identity and barcode information verification, this application introduces image recognition technology to actively identify the color of the blood collection tube tip through the camera of a mobile terminal (such as a PDA), and automatically compare it with the standard blood collection tube color preset by the system that corresponds to the test item. The comparison result is then broadcast in real time to guide the staff in operation.

[0023] This invention achieves accurate calibration of blood collection tube types through automated recognition and real-time voice feedback, thereby preventing specimen waste and repeated blood collection caused by incorrect blood collection tube types. It significantly improves the accuracy and efficiency of the blood collection process, reduces the workload and pressure on medical staff, and ensures medical safety.

[0024] The technical solutions of this application will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0025] First, the system architecture of this application is described. The system includes a mobile terminal (such as a PDA), an image acquisition module, a color recognition module, a voice prompt module, and a system dictionary that stores standard blood collection tube color information.

[0026] The preferred embodiment of the blood collection tube identification and calibration method described in this application, such as... Figure 1 As shown, the blood collection tube identification and calibration method includes the following steps: In step S101, the characteristic information and tag information of the blood collection tube are obtained.

[0027] In one possible implementation, before step S101, the user's target information is obtained; the target information is authenticated to obtain a verification result; when the verification result is successful, the feature information and tag information of the blood collection tube are obtained.

[0028] Specifically, the process begins with preparation and identity verification. Staff members bring a PDA equipped with the system and labeled blood collection tubes to the user's bedside and verbally verify the user's information. Next, electronic identity authentication is performed by scanning the user's wristband QR code with the PDA, and the system verifies the user's information. This step is mandatory; failure to verify the information prevents further operations.

[0029] In one possible implementation, the feature information includes the test tube type, and the label information includes the item label. A target image within a defined range of blood collection tubes is acquired; the test tube type and item label corresponding to the blood collection tubes in the target image are identified.

[0030] Specifically, during image acquisition, staff point the PDA lens at the blood collection tube to be collected, ensuring that both the tip of the blood collection tube (color recognition area) and the inspection label barcode are within the field of view.

[0031] In step S102, the actual color characteristics of the blood collection tube and the user's target inspection items are obtained based on the feature information and the label information.

[0032] In one possible implementation, the user's target test item is determined based on the item label; the actual color characteristics of the blood collection tube are obtained based on the test tube type and the item label.

[0033] It's worth noting that during matching, to prevent misjudging the tube header color, the barcode background color is used as the comparison object to determine the tube header color. If it falls within the color threshold range, it is correct and no correction is needed. The actual tube header color is determined based on the barcode background color (known as white), the currently collected barcode background color, and the currently collected tube header color.

[0034] In one possible implementation, the test tube type includes image color features, and the item label includes label color features. Color deviation data of the blood collection tube is obtained based on the label color features; the actual color features of the blood collection tube are obtained based on the image color features and the color deviation data.

[0035] In one possible implementation, a color deviation model is constructed and trained based on the color deviation data to obtain a trained color deviation model; the image color features are input into the trained color deviation model for color correction to obtain the actual color features of the blood collection tube.

[0036] Specifically, in the color recognition and comparison process, firstly, a baseline is established by identifying the barcode area of ​​the inspection label and obtaining its background color (known as baseline white) in the current environment (label color characteristics). Then, the deviation is calculated by comparing the theoretical value of baseline white with the actual collected value to calculate the color deviation model caused by ambient light. Next, the color is corrected by substituting the color data of the blood collection tube tip collected from the same image into the derived deviation model for inverse compensation, calculating the corrected actual color of the tube tip.

[0037] Understandably, the theoretical value of a reference white (such as sRGB standard white) is calculated by differentiating it from the actual collected value to generate a color offset vector caused by ambient light. This vector may contain independent offsets for the RGB three channels (such as ΔR=+5, ΔG=-3, ΔB=+2) to quantify the overall impact of ambient light on color. The original color data from the blood collection tube tip (color recognition area) is then substituted into the deviation model for inverse compensation. If ambient light causes red to appear orange (i.e., the R channel value is too high), the system will reduce the R channel value to make the corrected color closer to standard red.

[0038] In step S103, preset comparison data between the blood collection tube and the test item is obtained, and the matching result between the blood collection tube and the current test item is determined based on the preset comparison data, the actual color features and the target test item.

[0039] In one possible implementation, the target color feature of the user's current test item is determined based on the preset comparison data and the target test item; the actual color feature is compared with the target color feature to obtain difference data; if the difference data is within a preset tolerance threshold, the matching result between the blood collection tube and the current test item is determined to be a correct match; if the difference data is not within the preset tolerance threshold, the matching result between the blood collection tube and the current test item is determined to be an incorrect match.

[0040] Specifically, threshold matching is performed, comparing the corrected actual color of the tube head with the standard color in the dictionary. If the difference is within the preset tolerance threshold, the match is considered successful.

[0041] This application enables the automatic identification of the physical characteristics of blood collection tubes. Based on electronic information verification, it adds image recognition and automated comparison of the color characteristics of the blood collection tube body.

[0042] In step S104, a reminder is sent to the staff based on the matching result.

[0043] Specifically, the system provides feedback by matching the identified color with a standard color. If the match is successful, it announces via voice, "[Standard Color] Head tube, correct"; if the match fails, it announces, "[Standard Color] Head tube, error, please check." When the system prompts "error," the staff must reselect the correct blood collection tube and re-execute the scan (forced error correction mechanism) until it prompts "correct" before allowing the system to scan the next blood collection tube. This process is repeated until all blood collection tubes have been scanned, at which point the system announces the total number of blood collection tubes collected for final verification by both staff and the user. The staff clicks "Execute Medical Order" on the PDA to confirm the operation is complete, and the system again announces via voice that the collection is finished, completing the entire process.

[0044] This application utilizes real-time voice broadcasting based on recognition results to provide real-time feedback to the operator regarding the comparison results (correct / incorrect and standard type). It also integrates a mandatory error correction process, seamlessly combining color recognition, voice prompts, and error interception to create a closed-loop, mandatory error correction workflow. Furthermore, the inclusion of user-participatory verification enhances process security.

[0045] This application enables automatic color comparison, replacing human judgment with image recognition technology, eliminating the influence of subjective judgment errors and visual fatigue, and achieving high calibration accuracy. Real-time voice interaction and voice prompts free nurses from frequently checking the screen, achieving "eye-hand liberation," which is particularly suitable for aseptic operating environments and improves operational smoothness and safety. This application ensures the standardization and non-skipping nature of the operating procedure through a mandatory error correction mechanism of "pre-verification" and "error interception," effectively preventing the accumulation of errors. This application combines electronic scanning, image recognition, voice prompts, and patient-involved verification to form multiple security lines, greatly improving the level of medical safety.

[0046] Understandably, color recognition can be achieved through various methods, such as RGB value comparison, HSV color space analysis, or machine learning-based image classification models, to adapt to different lighting conditions. Mobile terminals are not limited to dedicated PDAs; they can also be smartphones, tablets, or dedicated handheld devices with specific applications installed. Recognition features can be expanded from color to the size (height / diameter), shape, or other markings of the blood collection tubes. The system dictionary can support network updates, facilitating hospitals to add new test tube types. Voice prompts can replace or be supplemented with screen highlighting, vibration, or other prompts.

[0047] In another implementation, RFID (Radio Frequency Identification) or NFC (Near Field Communication) technologies can be used instead of image recognition. This involves pre-attaching RFID tags to the blood collection tubes, and the PDA identifies the tube type by reading the tag information.

[0048] In another implementation, it can be designed as a fixed workstation or an integrated device mounted on a blood collection vehicle, rather than being limited to a handheld mobile terminal.

[0049] In another implementation, computationally intensive tasks such as color recognition and comparison can be processed on the server side, while the PDA is only responsible for image acquisition and result display, thus reducing the performance requirements of the terminal device.

[0050] In another implementation, it can be deeply integrated with the Hospital Information System (HIS) and Laboratory Information System (LIS) to achieve closed-loop management of the entire process, from order placement and test tube preparation to bedside collection and sample transportation.

[0051] Next, referring to the accompanying drawings, the blood collection tube identification and calibration system proposed according to the embodiments of this application is described, which is applied to the blood collection tube identification and calibration method described in any one of the above schemes.

[0052] Figure 2 This is a structural diagram of the blood collection tube identification and calibration system according to an embodiment of this application.

[0053] like Figure 2 As shown, the blood collection tube identification and verification system includes: an information acquisition module 100, a feature recognition module 200, an item matching module 300, and a result prompting module 400.

[0054] Specifically, the information acquisition module 100 is used to acquire the characteristic information and label information of the blood collection tube; The feature recognition module 200 is used to obtain the actual color features of the blood collection tube and the user's target inspection items based on the feature information and the label information. The project matching module 300 is used to acquire preset comparison data between blood collection tubes and test items, and determine the matching result between the blood collection tube and the current test item based on the preset comparison data, the actual color features and the target test item; The result notification module 400 is used to issue reminders to staff based on the matching results.

[0055] Figure 3 A structural diagram of a terminal provided in an embodiment of this application. The terminal may include: The memory 501, the processor 502, and the computer program stored on the memory 501 and capable of running on the processor 502.

[0056] When the processor 502 executes the program, it implements the blood collection tube identification and calibration method provided in the above embodiments.

[0057] Furthermore, the terminal also includes: Communication interface 503 is used for communication between memory 501 and processor 502.

[0058] The memory 501 is used to store computer programs that can run on the processor 502.

[0059] Memory 501 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0060] If the memory 501, processor 502, and communication interface 503 are implemented independently, then the communication interface 503, memory 501, and processor 502 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EIS) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0061] Optionally, in a specific implementation, if the memory 501, processor 502, and communication interface 503 are integrated on a single chip, then the memory 501, processor 502, and communication interface 503 can communicate with each other through an internal interface.

[0062] Processor 502 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0063] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described blood collection tube identification and calibration method.

[0064] One embodiment of this application provides a computer program product, including a computer program that, when executed by a processor, implements the features described in this application. Figure 1 The blood collection tube identification and calibration method provided in any of the corresponding embodiments.

[0065] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0066] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0067] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0068] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable storage medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable storage medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable storage medium could be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0069] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0070] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0071] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0072] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

[0073] It should be understood that the application of this application is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for identifying and verifying blood collection tubes, characterized in that, The blood collection tube identification and calibration method includes: Obtain the characteristic and label information of the blood collection tubes; Based on the feature information and the label information, the actual color characteristics of the blood collection tube and the user's target inspection items are obtained; Obtain preset comparison data between blood collection tubes and test items, and determine the matching result between the blood collection tubes and the current test items based on the preset comparison data, the actual color characteristics, and the target test items; A reminder will be sent to staff based on the matching results.

2. The blood collection tube identification and calibration method according to claim 1, characterized in that, The acquisition of the characteristic information and tag information of the blood collection tube also includes, prior to: Obtain the user's target information; The target information is authenticated to obtain the authentication result; When the verification result is successful, the feature information and label information of the blood collection tube are obtained.

3. The blood collection tube identification and calibration method according to claim 1, characterized in that, The feature information includes the test tube type, and the label information includes the project label; The acquisition of the feature information and tag information of the blood collection tube specifically includes: Acquire the target image within the set range of the blood collection tube; Identify the test tube type and item label corresponding to the blood collection tube in the target image.

4. The blood collection tube identification and calibration method according to claim 3, characterized in that, The step of obtaining the actual color characteristics of the blood collection tube and the user's target inspection items based on the feature information and the label information specifically includes: The user's target testing items are determined based on the project tags; The actual color characteristics of the blood collection tube are obtained based on the test tube type and the item label.

5. The blood collection tube identification and calibration method according to claim 4, characterized in that, The test tube type includes image color features, and the item label includes label color features; The step of obtaining the actual color characteristics of the blood collection tube based on the test tube type and the item label specifically includes: Based on the color characteristics of the label, the color deviation data of the blood collection tube is obtained; The actual color features of the blood collection tube are obtained based on the image color features and the color deviation data.

6. The blood collection tube identification and calibration method according to claim 5, characterized in that, The step of obtaining the actual color features of the blood collection tube based on the image color features and the color deviation data specifically includes: A color deviation model is constructed, and the color deviation model is trained based on the color deviation data to obtain a trained color deviation model; The image color features are input into a trained color deviation model for color correction to obtain the actual color features of the blood collection tube.

7. The blood collection tube identification and calibration method according to claim 5, characterized in that, The step of determining the matching result between the blood collection tube and the current test item based on the preset comparison data, the actual color features, and the target test item specifically includes: Based on the preset comparison data and the target inspection item, determine the target color feature of the user's current inspection item; The actual color features are compared with the target color features to obtain the difference data; If the difference data is within the preset tolerance threshold, then the matching result between the blood collection tube and the current test item is determined to be a correct match; If the difference data is not within the preset tolerance threshold, then the matching result between the blood collection tube and the current test item is determined to be a matching error.

8. A blood collection tube identification and verification system, characterized in that, The blood collection tube identification and calibration system is applied to the blood collection tube identification and calibration method according to any one of claims 1-7; the blood collection tube identification and calibration system includes: The information acquisition module is used to acquire the feature information and tag information of the blood collection tubes; The feature recognition module is used to obtain the actual color features of the blood collection tube and the user's target inspection items based on the feature information and the label information. The item matching module is used to acquire preset comparison data between blood collection tubes and test items, and determine the matching result between the blood collection tube and the current test item based on the preset comparison data, the actual color features, and the target test item. The result notification module is used to send reminders to staff based on the matching results.

9. A terminal, characterized in that, The terminal includes: a memory, a processor, and a blood collection tube identification and calibration program stored in the memory and executable on the processor. When the blood collection tube identification and calibration program is executed by the processor, it implements the steps of the blood collection tube identification and calibration method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a blood collection tube identification and calibration program, which, when executed by a processor, implements the steps of the blood collection tube identification and calibration method as described in any one of claims 1-7.

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