Specimen container intelligent checking method and system based on doctor's advice matching

Abstract

The invention relates to the technical field of medical inspection, in particular to a specimen container intelligent checking method and system based on doctor's advice matching, and the method comprises the steps: obtaining doctor's advice information based on a hospital information system, carrying out the identity checking of a patient through a mobile data terminal, determining a target patient, scanning a container barcode on a specimen container, obtaining container identification information, and carrying out the verification of the target patient; performing image acquisition on the specimen container to obtain container appearance information, judging whether a specimen container matched with the specimen container information exists or not, if the specimen container matched with the specimen container information exists, confirming the specimen container as a target specimen container, detecting the target specimen container, and judging whether the specimen container meets the specimen acquisition requirement or not; if the sample collection requirement is met, sample collection is conducted on the target patient, sample collection information is recorded, and the sample collection information is uploaded to a hospital information system. According to the invention, the problem of insufficient accuracy in the current checking process of the specimen container can be solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the medical inspection technical field, and particularly relates to a specimen container intelligent checking method and system based on medical order matching. BACKGROUND

[0002] In the medical inspection field, specimen container checking is an important link to ensure the accuracy and safety of medical diagnosis. With the development of medical technology and the increase in the number of patients, how to efficiently and accurately check the specimen container has become an important issue in medical quality control.

[0003] The traditional specimen container checking method mainly relies on manual checking. Medical staff completes the checking work by checking the appearance of the specimen container or by scanning the specimen container bar code. Although the traditional manual checking method can meet the basic specimen container checking requirements to a certain extent, in a complex medical environment, especially under high work pressure, manual checking is prone to omissions and errors, and the accuracy is difficult to guarantee. Therefore, there is a problem of insufficient accuracy in the current specimen container checking process. SUMMARY

[0004] The present application provides a specimen container intelligent checking method and system based on medical order matching, which mainly aims to solve the problem of insufficient accuracy in the current specimen container checking process.

[0005] To achieve the above-mentioned purpose, the present application provides a specimen container intelligent checking method based on medical order matching, comprising:

[0006] receiving a patient checking instruction, and determining a checking environment according to the patient checking instruction, wherein the checking environment comprises a patient to be checked, a hospital information system and a mobile data terminal;

[0007] obtaining medical order information based on the hospital information system, wherein the medical order information comprises patient identity information, specimen container information and specimen type information;

[0008] checking the identity of the patient based on the patient identity information by using the mobile data terminal, and determining a target patient;

[0009] obtaining a specimen container set, and performing the following operations on each specimen container in the specimen container set:

[0010] scanning a preset container bar code on the specimen container to obtain container identification information;

[0011] performing image acquisition on the specimen container to obtain container appearance information;

[0012] The container identification information and the container appearance information are compared with specimen container information based on a preset container matching rule to determine whether there is a specimen container matching the specimen container information;

[0013] If there is no specimen container matching the specimen container information, the matching process is terminated, and a preset first exception processing scheme is triggered;

[0014] If there is a specimen container matching the specimen container information, the specimen container is confirmed as a target specimen container;

[0015] The target specimen container is detected according to specimen type information to determine whether the target specimen container meets a preset specimen collection requirement;

[0016] If the target specimen container does not meet the specimen collection requirement, the detection process is terminated, and a preset second exception processing scheme is triggered;

[0017] If the target specimen container meets the specimen collection requirement, a specimen of a target patient is collected, and specimen collection information is recorded;

[0018] The specimen collection information is uploaded to a hospital information system to complete specimen container intelligent checking based on order matching.

[0019] Optionally, the order information is obtained based on the hospital information system, and the obtaining includes:

[0020] Patient diagnosis information is obtained, and the patient diagnosis information is uploaded to the hospital information system to obtain electronic diagnosis information;

[0021] Patient identity information is determined according to the electronic diagnosis information;

[0022] A disease test item of the patient is extracted from the electronic diagnosis information;

[0023] Based on the disease test item, specimen container information and specimen type information are obtained from a preset database by using the hospital information system;

[0024] The patient identity information is integrated with the specimen container information and the specimen type information to obtain the order information.

[0025] Optionally, the patient is checked for identity by using a mobile data terminal, and a target patient is determined, and the checking includes:

[0026] A patient identity identifier is obtained, wherein the patient identity identifier is a unique identifier that can represent patient identity information;

[0027] The patient identity identifier is scanned by using the mobile data terminal to obtain target patient identity information;

[0028] According to the target patient identity information, a target patient is determined.

[0029] Optionally, the image acquisition of the specimen container obtains container appearance information, including:

[0030] The image acquisition of the specimen container by the mobile data terminal obtains a specimen container image;

[0031] The specimen container image is subjected to a grayscale processing to obtain a container grayscale image;

[0032] The container grayscale image is subjected to an image noise reduction operation by a pre-constructed Gaussian filter algorithm to obtain a pre-processed container image, wherein the Gaussian filter algorithm is as follows:

[0033] G = H(I, (k, k), σ)

[0034] wherein G represents the pre-processed container image, H() represents a Gaussian blur formula, I represents a grayscale image, σ represents a standard deviation of the Gaussian blur formula, (k, k) represents a convolution kernel of the Gaussian blur formula, and the size of the convolution kernel is k x k;

[0035] The pre-processed container image is subjected to a feature extraction to obtain container appearance information.

[0036] Optionally, the judgment of whether there is a specimen container matching the specimen container information includes:

[0037] The specimen container information is called from a hospital information system by the mobile data terminal, wherein the specimen container information includes target container identification information and target container appearance information;

[0038] The container identification information is summarized to obtain a container identification information set;

[0039] The target container identification information is compared with each container identification information in the container identification information set, and it is judged whether the container identification information and the target container identification information are consistent;

[0040] If there is no container identification information consistent with the target container identification information, it is determined that there is no specimen container matching the specimen container information;

[0041] If there is container identification information consistent with the target container identification information, the container appearance information and the target container appearance information are subjected to a feature comparison to obtain a feature similarity, wherein the feature similarity includes a color similarity and a contour similarity;

[0042] When the feature similarity meets a pre-set similarity standard, it is determined that there is a specimen container matching the specimen container information.

[0043] Optionally, the feature comparison of the container appearance information and the target container appearance information is performed to obtain a feature similarity, including:

[0044] A container color histogram and a target container color histogram are obtained according to the container appearance information and the target container appearance information respectively, and a color similarity is calculated by using the following formula:

[0045]

[0046] wherein S c represents the color similarity, H 1，i represents a value of the container color histogram at the i th bin, H 2，i represents a value of the target container color histogram at the i th bin, N represents a bin number of the container color histogram and the target container color histogram, min(H 1，i , H 2，i ) represents a minimum value of H 1，i and H 2，i , and max(H 1，i , H 2，i ) represents a maximum value of H 1，i and H 2，i .

[0047] The contour comparison of the container appearance information and the target container appearance information is performed to obtain a contour similarity.

[0048] The color similarity and the contour similarity are integrated to obtain the feature similarity.

[0049] Optionally, the feature comparison of the container appearance information and the target container appearance information is performed to obtain the contour similarity, including:

[0050] The contour detection of the container appearance information and the target container appearance information is performed to obtain a container contour point set and a target container contour point set.

[0051] The normalization processing of the container contour point set and the target container contour point set is performed to obtain a standard container contour point set and a standard target container contour point set.

[0052] The standard container contour point set and the standard target container contour point set are encoded by using a preset chain code algorithm to obtain a container chain code and a target container chain code.

[0053] The contour similarity of the container appearance information and the target container appearance information is calculated by using a pre-constructed edge contour formula according to the container chain code and the target container chain code, wherein the edge contour formula is as follows:

[0054]

[0055] wherein S e represents the profile similarity, C1 and C2 are the container chain code and the target container chain code respectively, D e (C1, C2) represents the edit distance between the container chain code and the target container chain code, len(C1) represents the length of the container chain code, len(C2) represents the length of the target container chain code, and C(len(C1), len(C2)) represents the maximum value of len(C1) and len(C2).

[0056] Optionally, the detecting the target specimen container according to the specimen type information and determining whether the target specimen container meets the preset specimen collection requirement comprises:

[0057] The specimen type information is called from a hospital information system by using a mobile data terminal, wherein the specimen type information comprises a specimen category and a specimen collection amount.

[0058] Based on the specimen category, a standard container type is obtained from the hospital information system.

[0059] The target specimen container is detected to obtain a target container type and a target container capacity.

[0060] The target container type is compared with the standard container type.

[0061] If the target container type is inconsistent with the standard container type, it is determined that the target specimen container does not meet the specimen collection requirement.

[0062] If the target container type is consistent with the standard container type, the target container capacity is further compared with the specimen collection amount.

[0063] If the target container capacity is less than the specimen collection amount, it is determined that the target specimen container does not meet the specimen collection requirement.

[0064] If the target container capacity is not less than the specimen collection amount, it is determined that the target specimen container meets the specimen collection requirement.

[0065] Optionally, the specimen collection is performed on the target patient, and specimen collection information is recorded, comprising:

[0066] According to the specimen type information, a corresponding sampling tool is obtained.

[0067] The specimen collection is performed on the target patient by using the sampling tool to obtain a target specimen.

[0068] The target specimen is stored in the target specimen container, and a specimen storage time is recorded.

[0069] Based on the specimen type information, a specimen category identifier is obtained.

[0070] The target specimen container is marked for detection to obtain specimen container marking information, wherein the specimen container marking information indicates the completeness and clarity of the marking of the target specimen container;

[0071] The specimen collection amount, specimen storage time, specimen type identification and specimen container marking information are integrated to obtain specimen collection information.

[0072] To achieve the above-mentioned purpose, the application further provides a specimen container intelligent verification system based on medical order matching, comprising:

[0073] A verification instruction receiving module is configured to receive a patient verification instruction and determine a verification environment according to the patient verification instruction, wherein the verification environment comprises a patient to be verified, a hospital information system and a mobile data terminal;

[0074] A medical order information obtaining module is configured to obtain medical order information based on the hospital information system, wherein the medical order information comprises patient identity information, specimen container information and specimen type information, the patient identity information is used to verify the identity of the patient by using the mobile data terminal and determine a target patient;

[0075] A specimen container matching module is configured to obtain a specimen container set, scan a preset container barcode on each specimen container in the specimen container set to obtain container identification information, perform image acquisition on the specimen container to obtain container appearance information, compare the container identification information and the container appearance information with the specimen container information based on a preset container matching rule, determine whether there is a specimen container matching the specimen container information, terminate the matching process and trigger a preset first abnormal processing scheme if there is no specimen container matching the specimen container information, and confirm the specimen container as a target specimen container if there is a specimen container matching the specimen container information;

[0076] A specimen collection matching module is configured to detect the target specimen container according to the specimen type information, determine whether the target specimen container meets a preset specimen collection requirement, terminate the detection process and trigger a preset second abnormal processing scheme if the target specimen container does not meet the specimen collection requirement, collect a specimen from the target patient and record specimen collection information if the target specimen container meets the specimen collection requirement, and upload the specimen collection information to the hospital information system.

[0077] To solve the above-mentioned problems, the application further provides an electronic device, comprising:

[0078] A memory is configured to store at least one instruction, and a processor is configured to execute the instruction stored in the memory to implement the above-mentioned specimen container intelligent verification method based on medical order matching.

[0079] To solve the above problems, the application further provides a computer readable storage medium, wherein at least one instruction is stored in the computer readable storage medium, and the at least one instruction is executed by a processor in an electronic device to implement the above-mentioned specimen container intelligent verification method based on medical order matching.

[0080] To solve the problems in the background art, the application receives a patient verification instruction, determines a verification environment according to the patient verification instruction, wherein the verification environment includes a patient to be verified, a hospital information system and a mobile data terminal, acquires medical order information based on the hospital information system, the medical order information is the core basis for specimen collection and includes patient identity information, specimen container information and specimen type information, verifies the identity of the patient by using the mobile data terminal based on the patient identity information, obtains target patient identity information by scanning the patient identity identifier, determines the target patient, then acquires a specimen container set and verifies each specimen container in the specimen container set, first, scans a preset container barcode on the specimen container to obtain container identifier information, then acquires an image of each specimen container to obtain container appearance information, compares the container identifier information and the container appearance information with the specimen container information based on a preset container matching rule, determines whether there is a specimen container matching the medical order information by judging whether the specimen container information matches the container identifier information and the container appearance information, terminates the matching process and triggers a preset first abnormal handling scheme if no specimen container matching the specimen container information is found, confirms the specimen container as a target specimen container if there is a specimen container matching the specimen container information, and finally, further detects the target specimen container according to the specimen type information to determine whether it meets the preset specimen collection requirements after the target specimen container is confirmed, which ensures that the target specimen container not only matches the medical order in terms of identification and appearance, but also meets the standards and requirements of specimen collection, terminates the detection process and triggers a preset second abnormal handling scheme if the target specimen container does not meet the specimen collection requirements to prevent incorrect specimen collection operations, and performs specimen collection operations if the target specimen container meets the specimen collection requirements, records specimen collection information, uploads the specimen collection information to the hospital information system, and completes the entire specimen container intelligent verification process based on medical order matching. Therefore, the application can solve the problem of insufficient accuracy in the current specimen container verification process. BRIEF DESCRIPTION OF DRAWINGS

[0081] Figure 1 A flowchart of a specimen container intelligent verification method based on medical order matching provided by an embodiment of the application;

[0082] Figure 2 A functional module diagram of a specimen container intelligent checking system based on order matching provided by an embodiment of the present application is provided.

[0083] Figure 3 A structural schematic diagram of an electronic device for implementing the specimen container intelligent checking method based on order matching provided by an embodiment of the present application is provided.

[0084] Legend of reference signs:

[0085] 1, electronic device; 10, processor; 11, memory; 12, bus.

[0086] The implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0087] It should be understood that the specific embodiments described herein are merely intended to explain the present application and not to limit the present application.

[0088] An embodiment of the present application provides a specimen container intelligent checking method based on order matching. The execution subject of the specimen container intelligent checking method based on order matching includes but is not limited to at least one of electronic devices such as a server, a terminal and the like which can be configured to execute the method provided by the embodiment of the present application. In other words, the specimen container intelligent checking method based on order matching can be executed by software or hardware installed in a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to a single server, a server cluster, a cloud server or a cloud server cluster and the like.

[0089] Referring to Figure 1 FIG. 1 shows a flowchart of a specimen container intelligent checking method based on order matching provided by an embodiment of the present application. In the embodiment, the specimen container intelligent checking method based on order matching includes:

[0090] S1, receiving a patient checking instruction, and determining a checking environment according to the patient checking instruction, wherein the checking environment includes a patient to be checked, a hospital information system and a mobile data terminal.

[0091] It should be noted that the patient checking instruction is an operation instruction issued to start the specimen checking process of the patient, which generally includes basic information of the patient (such as age, name, etc.) and specific requirements of checking (such as specimen type, specimen collection requirements, etc.). The hospital information system refers to a comprehensive system (such as HIS, LIS, etc.) used for managing patient diagnosis and treatment information in the hospital. The mobile data terminal refers to a portable device used by medical staff to perform checking operations, such as a handheld PDA, a tablet computer, etc. The mobile data terminal has the functions of scanning barcodes, collecting images, processing data and uploading information, and can interact with the hospital information system to perform patient identity checking, specimen container information comparison, specimen collection recording and other operations.

[0092] S2, obtaining the medical order information based on the hospital information system, wherein the medical order information comprises patient identity information, specimen container information and specimen type information.

[0093] It can be understood that the medical order information refers to a set of patient medical operation instructions stored in the hospital information system. The patient identity information refers to information used to uniquely identify the identity of the patient, including but not limited to the patient's name, gender, date of birth, ID number, medical insurance card number and hospital-allocated unique patient ID. The specimen container information refers to the container information used to store the collected specimen, including container identification (such as barcode number, RFID tag, etc.), appearance characteristics (such as color, shape, etc.), etc. The specimen type information refers to information about the type and requirements of the specimen, including the type of the specimen (such as blood, urine, etc.), the collection amount of the specimen, the preservation condition of the specimen, etc. The specimen type information can be used to guide the specimen collection operation.

[0094] In detail, the medical order information is obtained based on the hospital information system, comprising:

[0095] obtaining patient diagnosis information, uploading the patient diagnosis information to the hospital information system to obtain electronic diagnosis information;

[0096] determining patient identity information according to the electronic diagnosis information;

[0097] extracting the disease test item of the patient from the electronic diagnosis information;

[0098] obtaining specimen container information and specimen type information from a preset database based on the disease test item by using the hospital information system;

[0099] integrating the patient identity information with the specimen container information and the specimen type information to obtain the medical order information.

[0100] It should be explained that the patient diagnosis information refers to detailed information about the patient's condition recorded by a doctor or medical professional, including symptoms, signs, preliminary diagnosis, medical history, etc., for guiding subsequent medical operations and selection of test items. The electronic diagnosis information refers to the digital data form of the patient diagnosis information after structured processing and storage in the hospital information system. The disease test item refers to the test item that needs to be performed according to the specific condition of the patient, such as blood test, urine test, etc. The database refers to the database in the hospital information system that stores the specimen container information and specimen type information in advance, which contains detailed information of various specimen containers (such as type, capacity, etc.) and specimen collection requirements corresponding to different disease test items (such as specimen type, collection amount, storage condition, etc.), and is the data support for obtaining the medical order information.

[0101] S3, based on the patient identity information, using a mobile data terminal to perform identity verification on the patient and determine the target patient.

[0102] It should be understood that the identity verification refers to the process of identifying the patient's identity mark through the mobile data terminal and comparing and verifying it with the patient identity information stored in the hospital information system. The target patient refers to the patient whose identity is verified and consistent with the patient identity information specified in the medical order information.

[0103] Specifically, the identity verification of the patient using the mobile data terminal and the determination of the target patient include:

[0104] Obtaining the patient identity mark, wherein the patient identity mark refers to a unique mark that can represent the patient's identity information;

[0105] Scanning the patient identity mark using the mobile data terminal to obtain the target patient identity information;

[0106] Determining the target patient according to the target patient identity information.

[0107] It should be explained that the target patient identity information refers to the specific identity information of the target patient obtained by scanning the patient identity mark using the mobile data terminal, such as the age, name, medical record number, hospitalization number, etc.

[0108] S4, obtaining a set of specimen containers, and performing the following operations on each specimen container in the set of specimen containers: scanning a pre-set container barcode on the specimen container to obtain container identification information, and performing image acquisition on the specimen container to obtain container appearance information.

[0109] It can be understood that the specimen container set refers to a set of specimen containers prepared according to the patient's medical order information for collecting and storing patient specimens. The container barcode refers to a barcode or a two-dimensional code pre-printed or pasted on the specimen container. The container barcode contains unique identification information related to the specimen container, which can be read through the scanning function of the mobile data terminal. The container identification information refers to the digital information (such as: container type, specification parameter, applicable detection item, etc.) related to the specimen container retrieved from the hospital information system after scanning the specimen container barcode. The container appearance information refers to the information reflecting the appearance characteristics of the container obtained by image acquisition of the specimen container, such as: the color, shape, size, etc. of the specimen container.

[0110] Further, the image acquisition of the specimen container to obtain the container appearance information comprises:

[0111] Image acquisition of the specimen container by using the mobile data terminal to obtain the specimen container image;

[0112] Grayscale processing of the specimen container image to obtain the container grayscale image;

[0113] Image noise reduction operation of the container grayscale image by using a pre-constructed Gaussian filter algorithm to obtain a pre-processed container image, wherein the Gaussian filter algorithm is as follows:

[0114] G = H(I, (k, k), σ)

[0115] Wherein, G represents the pre-processed container image, H() represents the Gaussian blur formula, I represents the grayscale image, σ represents the standard deviation of the Gaussian blur formula, (k, k) represents the convolution kernel of the Gaussian blur formula, and the size of the convolution kernel is k x k;

[0116] Feature extraction of the pre-processed container image to obtain the container appearance information.

[0117] It should be understood that the image acquisition refers to the process of capturing a digital image of the appearance of the specimen container by the mobile data terminal. The specimen container image refers to the RGB color image of the specimen container acquired by the mobile data terminal. The grayscale processing refers to converting the RGB color image into a grayscale image using a grayscale processing formula, which is a prior art and will not be described here. The container grayscale image refers to the specimen container image obtained after grayscale processing. The image noise reduction operation refers to smoothing the container grayscale image to remove noise points (such as randomly distributed bright spots, dark spots, or stripes, etc.) in the container grayscale image caused by factors such as light interference and sensor errors, etc. The preprocessed container image refers to the container grayscale image after Gaussian filter noise reduction processing. The feature extraction refers to extracting key features (such as color distribution, contour shape, etc.) that can represent the appearance of the container from the preprocessed container image through image processing algorithms (such as edge detection, contour recognition, histogram analysis, etc.).

[0118] For example, the image acquisition of a certain specimen container obtains a specimen container image of 1280x960 pixels. The specimen container image is converted into a container grayscale image by a grayscale processing formula. A pixel with an RGB value of (100, 150, 200) is converted into a grayscale value of 141. In a 5x5 neighborhood centered on this pixel, there are random noise points (such as fluctuation values of 130, 145, 160, etc.). A 5x5 Gaussian convolution kernel with a standard deviation of 1.0 is used for weighted averaging (in this embodiment, the center pixel weight can be set to 0.075, and the neighborhood weight decreases with distance). The final noise reduction result of this pixel is 143.

[0119] S5, based on the pre-set container matching rule, comparing the container identification information and the container appearance information with the specimen container information to determine whether there is a specimen container matching the specimen container information.

[0120] In detail, if there is no specimen container matching the specimen container information, the matching process is terminated, and a pre-set first abnormal handling scheme is triggered. If there is a specimen container matching the specimen container information, the specimen container is confirmed as the target specimen container.

[0121] It should be explained that the container matching rule refers to a series of standards and logical rules pre-set for judging whether the specimen container matches the specimen container information. The first abnormal handling scheme refers to the artificial pre-set abnormal handling process triggered when the specimen container cannot match the specimen container information in the medical order information. The target specimen container refers to the specimen container whose identification information and appearance characteristics both match the specimen container information in the medical order information after being verified by the container matching rule.

[0122] Furthermore, the container matching rules include: identification information matching priority, appearance information similarity standard, etc. Among them, the identification information matching priority uses the container identification information read by scanning the container barcode as the primary matching dimension, requiring the container identification information to be completely consistent with the target container identification information recorded in the hospital information system. The appearance information similarity standard sets quantitative standards for the appearance information such as the color and outline of the container, and requires that the similarity between the container appearance information and the target container appearance information recorded in the hospital information system reaches a pre-set similarity standard. The first exception handling solution includes: exception error reporting, manual intervention, etc. Abnormal error reporting means that when the specimen container information cannot be matched with the specimen containers in the specimen container set, an error will be triggered and the abnormal status will be marked in the hospital information system. Manual intervention means that after receiving the error message, the matching process needs to be interrupted, and the medical staff is prompted to further check and handle the abnormal situation, such as rescanning the specimen container, verifying the accuracy of the medical order information, etc.

[0123] Specifically, determining whether there is a specimen container that matches the specimen container information includes:

[0124] Using a mobile data terminal, retrieve the specimen container information from a hospital information system, wherein the specimen container information includes: target container identification information and target container appearance information;

[0125] Summarizing the container identification information to obtain a container identification information set;

[0126] Compare the target container identification information with each container identification information in the container identification information set, and determine whether the container identification information and the target container identification information are consistent;

[0127] If there is no container identification information that is consistent with the target container identification information, it is determined that there is no specimen container that matches the specimen container information;

[0128] If the container identification information is consistent with the target container identification information, then a feature comparison is performed on the container appearance information and the target container appearance information to obtain feature similarity, wherein the feature similarity includes: color similarity and contour similarity;

[0129] When the feature similarity meets a preset similarity standard, it is determined that there is a specimen container that matches the specimen container information.

[0130] It should be noted that the target container identification information refers to the unique identification information of the specimen container retrieved from the hospital information system and matching the medical order information. The target container appearance information refers to the appearance feature information of the specimen container stored in the hospital information system and matching the medical order information. The container identification information set refers to the collection of identification information of the specimen containers within the specimen container set.

[0131] It should be explained that the feature comparison refers to similarity analysis of color features and contour features in the container appearance information. The feature similarity refers to similarity values of each feature obtained by comparing the features of the container appearance information and the target container appearance information. The color similarity refers to a similarity value calculated by comparing the color features in the container appearance information and the color features in the target container appearance information. The contour similarity refers to a similarity value calculated by comparing the contour features in the container appearance information and the contour features in the target container appearance information. The similarity standard refers to a threshold value artificially set in advance for judging whether the color similarity and the contour similarity meet the requirements, for example, when the color similarity reaches 0.91 and the contour similarity reaches 0.89, it can be determined that the container appearance information of the specimen container matches the target container appearance information.

[0132] Further, the feature comparison of the container appearance information and the target container appearance information to obtain the feature similarity comprises:

[0133] The container color histogram and the target container color histogram are obtained according to the container appearance information and the target container appearance information respectively, and the color similarity is calculated by using the following formula:

[0134]

[0135] wherein, S c represents the color similarity, H 1，i represents a value of the container color histogram at the i-th bin, H 2，i represents a value of the target container color histogram at the i-th bin, n represents the number of bins of the container color histogram and the target container color histogram, min(H 1，i , H 2，i ) represents the minimum value of H 1，i and H 2，i , and max(H 1，i , H 2，i ) represents the maximum value of H 1，i and H 2，i .

[0136] The contour comparison of the container appearance information and the target container appearance information to obtain the contour similarity;

[0137] The color similarity and the contour similarity are integrated to obtain the feature similarity.

[0138] It can be understood that the container color histogram refers to a histogram obtained after color analysis of an image of a specimen container, representing statistical information of distribution of different colors in the specimen container. Generally, the color histogram divides the color space into a plurality of bins, and the value of each bin represents the number of pixels in the color interval. The target container color histogram refers to the color distribution atlas of the specimen container matched with the medical order information obtained from the hospital information system.

[0139] For example, the container color histogram of a certain specimen container is [100, 150, 200, 50, 30, 40, 60, 20], the target container color histogram is [120, 140, 190, 60, 25, 35, 55, 25], and after calculation, min(H 1，i , H 2，i ) = [100, 140, 190, 50, 25, 35, 55, 20], max(H 1，i , H 2，i ) = [120, 150, 200, 60, 30, 40, 60, 25], and the color similarity is 0.884.

[0140] In detail, the profile comparison of the container appearance information and the target container appearance information to obtain the profile similarity comprises:

[0141] The profile detection of the container appearance information and the target container appearance information to obtain a container profile point set and a target container profile point set;

[0142] The normalization processing of the container profile point set and the target container profile point set to obtain a standard container profile point set and a standard target container profile point set;

[0143] The encoding of the standard container profile point set and the standard target container profile point set by using a preset chain code algorithm to obtain a container chain code and a target container chain code;

[0144] The calculation of the profile similarity of the container appearance information and the target container appearance information according to the container chain code and the target container chain code by using a pre-constructed edge profile formula, wherein the edge profile formula is as follows:

[0145]

[0146] wherein S e represents the profile similarity, C1 and C2 are the container chain code and the target container chain code respectively, and D e(C1, C2) represents the edit distance between the container chain code and the target container chain code, len(C1) represents the length of the container chain code, len(C2) represents the length of the target container chain code, and max(len(C1), len(C2)) represents the maximum value of len(C1) and len(C2).

[0147] It should be understood that the contour detection refers to a process of extracting container boundary pixel points from a container appearance image by an image processing algorithm (such as a Canny edge detection algorithm, a Sobel operator, etc.). The container contour point set refers to a set of edge pixel coordinates of a specimen container obtained by contour detection. The target container contour point set refers to a set of edge pixel coordinates of a target specimen container obtained by contour detection. The normalization processing refers to coordinate unification and scale standardization processing of the container contour point set and the target container contour point set.

[0148] It should be understood that the standard container contour point set refers to the container contour point set after normalization processing. The standard target container contour point set refers to the target container contour point set after normalization processing. The chain code algorithm refers to an algorithm for describing the sequential relationship of the contour point set by direction coding, which may be a 16-direction Freeman chain code algorithm in this embodiment. The container chain code refers to an encoded sequence obtained by encoding the standard container contour point set by the chain code algorithm, which is used to represent the contour feature of the container. The target container chain code refers to an encoded sequence obtained by encoding the standard target container contour point set by the chain code algorithm.

[0149] For example, after the standard container contour point set of a certain specimen container is encoded, the container code is [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 0, 1], the target container code is [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 0, 0], and the calculated contour similarity is 0.9375.

[0150] S6, detecting the target specimen container according to the specimen type information to determine whether the target specimen container meets the preset specimen collection requirement.

[0151] It should be understood that the specimen collection requirement refers to a collection standard for ensuring that the specimen collection process meets the medical standard, which is set in advance according to the specimen type information.

[0152] Specifically, the detecting the target specimen container according to the specimen type information to determine whether the target specimen container meets the preset specimen collection requirement includes:

[0153] The mobile data terminal is used to call the specimen type information from a hospital information system, wherein the specimen type information includes a specimen category and a specimen collection amount.

[0154] acquire a standard container type from a hospital information system based on the specimen type;

[0155] container detection is performed on the target specimen container to obtain a target container type and a target container capacity;

[0156] the target container type is compared with the standard container type;

[0157] if the target container type is inconsistent with the standard container type, it is determined that the target specimen container does not meet the specimen collection requirement;

[0158] if the target container type is consistent with the standard container type, the target container capacity is further compared with the specimen collection amount;

[0159] if the target container capacity is less than the specimen collection amount, it is determined that the target specimen container does not meet the specimen collection requirement;

[0160] if the target container capacity is not less than the specimen collection amount, it is determined that the target specimen container meets the specimen collection requirement.

[0161] It should be noted that the specimen type refers to the type of specimen that needs to be collected, such as blood, urine, tissue specimen, saliva, etc. The specimen collection amount refers to the volume or weight of specimen required to complete the disease test item, for example, 2-3 mL of venous blood is required for blood routine test. The standard container type refers to the specimen container stored in the hospital information system that matches the specimen type. Container detection refers to the detection of the physical characteristics of the target specimen container, including container type, container capacity, etc. The target container type refers to the container type of the target specimen container obtained after container detection of the target specimen container. The target container capacity refers to the container capacity of the target specimen container obtained after container detection of the target specimen container.

[0162] S7, if the target specimen container does not meet the specimen collection requirement, the detection process is terminated, and a preset second abnormal handling scheme is triggered, if the target specimen container meets the specimen collection requirement, specimen collection is performed on the target patient, specimen collection information is recorded, the specimen collection information is uploaded to the hospital information system, and specimen container intelligent checking based on medical order matching is completed.

[0163] It can be understood that the second abnormal handling scheme refers to an artificial pre-set abnormal handling process triggered when the target specimen container does not meet the specimen collection requirement. Specimen collection refers to collecting specimen from the target patient and storing it in the target specimen container. Specimen collection information refers to the collection information recorded during specimen collection, such as collection time, specimen type, etc.

[0164] Further, when the second abnormality processing scheme is triggered, the abnormality is recorded, including: specimen container information, patient identity information, trigger cause of abnormality phenomenon, etc. Then, the hospital information system issues a warning to prohibit the use of the target specimen container for specimen collection, and notifies the relevant medical staff to replace the container or manually check.

[0165] In detail, the specimen collection information includes:

[0166] According to the specimen type information, the corresponding sampling tool is obtained;

[0167] The target patient is collected by the sampling tool to obtain the target specimen;

[0168] The target specimen is stored in the target specimen container, and the specimen storage time is recorded;

[0169] Based on the specimen type information, the specimen category identifier is obtained;

[0170] The target specimen container is marked and detected to obtain specimen container marking information, wherein the specimen container marking information refers to the completeness and clarity of the marking of the target specimen container;

[0171] The specimen collection amount, specimen storage time, specimen category identifier, and specimen container marking information are integrated to obtain the specimen collection information.

[0172] It should be understood that the sampling tool refers to a special instrument for collecting specimens from the target patient, such as a blood collection needle, a blood collection tube, a urine collection cup, etc. The target specimen refers to the specimen collected from the target patient. The specimen storage time refers to the specific time when the collected target specimen is stored in the target specimen container. The specimen category identifier refers to a code or label used to identify the specimen category, such as "BLD" for blood and "UR" for urine. Marking detection refers to detecting and evaluating the completeness and clarity of the surface marking (such as labels, warning signs, etc.) of the target specimen container through image recognition technology.

[0173] For example, the specimen type of a certain target specimen is blood, the specimen category identifier is "BLD", the specimen collection amount is 5mL, the specimen storage time is April 9, 2025, 14:25:24, the specimen container marking is clear, and the marking content is complete. After integrating the above information, the specimen collection information of the target specimen is obtained, and the specimen collection information is uploaded to the hospital information system to complete the specimen container check of the specimen.

[0174] The present application is to solve the problems described in the background art. The present application receives patient checking instructions, determines a checking environment according to the patient checking instructions, wherein the checking environment includes a patient to be checked, a hospital information system, and a mobile data terminal. The hospital information system is used to obtain medical order information, which is the core basis for specimen collection and includes patient identity information, specimen container information, and specimen type information. The patient identity information is used to check the identity of the patient using the mobile data terminal. The target patient identity information is obtained by scanning the patient's identity, and the target patient is determined. Then, the specimen container set is obtained, and each specimen container in the specimen container set is checked. First, the container barcode on the specimen container is scanned to obtain container identification information. Then, the image of each specimen container is collected to obtain container appearance information. The container identification information and the container appearance information are compared with the specimen container information based on a predetermined container matching rule. Because the specimen container information includes the target container identification information and the target container appearance information, it can be determined whether there is a specimen container that matches the medical order information by comparing the specimen container information with the container identification information and the container appearance information. If no specimen container that matches the specimen container information is found, the matching process will be terminated, and a predetermined first abnormal handling scheme will be triggered. If there is a specimen container that matches the specimen container information, the specimen container is confirmed as the target specimen container. Finally, after the target specimen container is confirmed, further detection of the target specimen container is required based on the specimen type information to determine whether it meets the predetermined specimen collection requirements. This step ensures that the target specimen container not only matches the medical order in terms of identification and appearance, but also meets the standard and standard of specimen collection. If the target specimen container does not meet the specimen collection requirements, the detection process will be terminated, and a predetermined second abnormal handling scheme will be triggered to prevent incorrect specimen collection operations. If the target specimen container meets the specimen collection requirements, specimen collection operations can be performed, the medical staff collects specimens from the target patient, records specimen collection information, uploads the specimen collection information to the hospital information system, and completes the entire specimen container intelligent checking process based on medical order matching. Therefore, the present application can solve the problem of insufficient accuracy in the current specimen container checking process.

[0175] As Figure 2 shown, it is a functional module diagram of the specimen container intelligent checking system based on medical order matching provided by an embodiment of the present application.

[0176] The specimen container intelligent checking system 100 based on order matching can be installed in an electronic device. According to the functions to be realized, the specimen container intelligent checking system 100 based on order matching can include a checking instruction receiving module 101, an order information obtaining module 102, a specimen container matching module 103, and a specimen collection matching module 104. The modules in the present application can also be referred to as units, which refer to a series of computer program segments that can be executed by an electronic device processor and can complete a fixed function, and are stored in the memory of the electronic device.

[0177] The checking instruction receiving module 101 is configured to receive a patient checking instruction, and determine a checking environment according to the patient checking instruction, wherein the checking environment includes a patient to be checked, a hospital information system, and a mobile data terminal.

[0178] The order information obtaining module 102 is configured to obtain order information based on the hospital information system, wherein the order information includes patient identity information, specimen container information, and specimen type information. Based on the patient identity information, the patient is checked for identity by using the mobile data terminal, and a target patient is determined.

[0179] The specimen container matching module 103 is configured to obtain a specimen container set, and perform the following operations on each specimen container in the specimen container set: scanning a preset container barcode on the specimen container to obtain container identification information, collecting an image of the specimen container to obtain container appearance information, comparing the container identification information and the container appearance information with the specimen container information based on a preset container matching rule, determining whether there is a specimen container matching the specimen container information, if there is no specimen container matching the specimen container information, terminating the matching process and triggering a preset first exception handling scheme, and if there is a specimen container matching the specimen container information, confirming the specimen container as a target specimen container.

[0180] The specimen collection matching module 104 is configured to detect the target specimen container according to the specimen type information, determine whether the target specimen container meets a preset specimen collection requirement, if the target specimen container does not meet the specimen collection requirement, terminate the detection process and trigger a preset second exception handling scheme, if the target specimen container meets the specimen collection requirement, collect a specimen from the target patient, record specimen collection information, and upload the specimen collection information to the hospital information system.

[0181] In detail, the modules in the specimen container intelligent checking system 100 based on order matching in the embodiments of the present application use the same technical means as the specimen container intelligent checking method based on order matching in the above Figure 1 , and can produce the same technical effects, which will not be described here again.

[0182] As Figure 3 shown is a structural schematic diagram of an electronic device for implementing the specimen container intelligent checking method based on order matching according to an embodiment of the present application.

[0183] The electronic device 1 can include a processor 10, a memory 11 and a bus 12, and can further include a computer program stored in the memory 11 and executable on the processor 10, such as a specimen container intelligent checking method program based on order matching.

[0184] The memory 11 includes at least one type of readable storage medium, such as flash memory, mobile hard disk, multimedia card, card-type memory (e.g. SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 can also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on the electronic device 1. Further, the memory 11 includes both the internal storage unit and the external storage device of the electronic device 1. The memory 11 can be used not only to store application software and various data installed on the electronic device 1, such as the code of the specimen container intelligent checking method program based on order matching, but also to temporarily store data that has been output or will be output.

[0185] The processor 10 can be composed of integrated circuits in some embodiments, such as a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more combinations of central processing units (CPU), microprocessors, digital processing chips, graphics processors and various control chips, etc. The processor 10 is the control unit of the electronic device, which connects various components of the entire electronic device through various interfaces and lines, executes or runs programs or modules stored in the memory 11 (such as the specimen container intelligent checking method program based on order matching, etc.), and calls data stored in the memory 11 to perform various functions and process data of the electronic device 1.

[0186] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to enable connection and communication between the memory 11, the at least one processor 10, etc.

[0187] Figure 3 Only the electronic device with components is shown, and those skilled in the art can understand that, Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and can include fewer or more components than shown, or combine certain components, or different component arrangements.

[0188] For example, although not shown, the electronic device 1 can also include a power supply (such as a battery) to power each component. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, so that the power management device can implement functions such as charge management, discharge management, and power consumption management. The power supply can also include one or more direct current or alternating current power supplies, recharging devices, power supply fault detection circuits, power supply converters or inverters, power supply status indicators, etc. The electronic device 1 can also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which are not described here.

[0189] Further, the electronic device 1 can also include a network interface, which can optionally include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), and is typically used to establish a communication connection between the electronic device 1 and other electronic devices.

[0190] Optionally, the electronic device 1 can also include a user interface, which can be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally a standard wired interface, a wireless interface. Optionally, in some embodiments, the display can be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch, etc. The display can also be appropriately referred to as a display screen or a display unit, and is used to display information processed in the electronic device 1 and to display a visualized user interface.

[0191] The specimen container intelligent checking method program stored in the memory 11 in the electronic device 1 is a combination of multiple instructions, which, when running in the processor 10, can realize:

[0192] receiving a patient checking instruction, and determining a checking environment according to the patient checking instruction, wherein the checking environment includes a patient to be checked, a hospital information system, and a mobile data terminal;

[0193] obtaining order information based on the hospital information system, wherein the order information includes patient identity information, specimen container information, and specimen type information;

[0194] checking the identity of the patient based on the patient identity information by using the mobile data terminal, and determining a target patient;

[0195] obtaining a set of specimen containers, and performing the following operations on each specimen container in the set of specimen containers:

[0196] scanning a preset container barcode on the specimen container to obtain container identification information;

[0197] performing image acquisition on the specimen container to obtain container appearance information;

[0198] comparing the container identification information and the container appearance information with the specimen container information based on a preset container matching rule, and determining whether there is a specimen container matching the specimen container information;

[0199] if there is no specimen container matching the specimen container information, terminating the matching process and triggering a preset first exception processing scheme;

[0200] if there is a specimen container matching the specimen container information, confirming the specimen container as a target specimen container;

[0201] detecting the target specimen container according to the specimen type information, and determining whether the target specimen container meets a preset specimen collection requirement;

[0202] if the target specimen container does not meet the specimen collection requirement, terminating the detection process and triggering a preset second exception processing scheme;

[0203] if the target specimen container meets the specimen collection requirement, collecting a specimen from the target patient and recording specimen collection information;

[0204] uploading the specimen collection information to the hospital information system, and completing the intelligent checking of the specimen container based on the order matching.

[0205] Specifically, the processor 10 can refer to the specific implementation method of the above instructions Figures 1 to 3The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0206] Further, the modules / units integrated in the electronic device 1, if implemented in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. The computer readable storage medium can be volatile or non-volatile. For example, the computer readable medium can include any entity or device capable of carrying the computer program code, a recording medium, a U disk, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM).

[0207] The application further provides a computer readable storage medium, which stores a computer program, and the computer program can realize the following when executed by a processor of an electronic device:

[0208] receiving a patient checking instruction, and determining a checking environment according to the patient checking instruction, wherein the checking environment includes a patient to be checked, a hospital information system, and a mobile data terminal;

[0209] obtaining medical order information based on the hospital information system, wherein the medical order information includes patient identity information, specimen container information, and specimen type information;

[0210] checking the identity of the patient based on the patient identity information by using the mobile data terminal, and determining a target patient;

[0211] obtaining a set of specimen containers, and performing the following operations on each specimen container in the set of specimen containers:

[0212] scanning a preset container barcode on the specimen container to obtain container identification information;

[0213] performing image acquisition on the specimen container to obtain container appearance information;

[0214] comparing the container identification information and the container appearance information with the specimen container information based on a preset container matching rule, and determining whether there is a specimen container that matches the specimen container information;

[0215] if there is no specimen container that matches the specimen container information, terminating the matching process and triggering a preset first exception processing scheme;

[0216] if there is a specimen container that matches the specimen container information, confirming the specimen container as a target specimen container;

[0217] detecting the target specimen container according to the specimen type information, and determining whether the target specimen container meets a preset specimen collection requirement;

[0218] If the target specimen container does not meet the specimen collection requirements, terminate the detection process, and trigger a preset second exception processing scheme;

[0219] If the target specimen container meets the specimen collection requirements, perform specimen collection on the target patient, and record specimen collection information;

[0220] Upload the specimen collection information to the hospital information system, and complete specimen container intelligent checking based on order matching.

[0221] In several embodiments provided in the present application, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the above-described system embodiments are only illustrative, and actual implementation can have other division ways.

[0222] The modules described as separate components can or can not be physically separated, and the components displayed as modules can or can not be physical units, that is, they can be located in one place, or distributed to multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment according to actual needs.

[0223] In addition, the functional modules in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically independently, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware, or in the form of hardware plus software functional modules.

[0224] It is obvious for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application.

[0225] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A method for intelligent verification of specimen containers based on medical order matching, characterized in that: The method comprises: receiving a patient verification instruction, and determining a verification environment according to the patient verification instruction, wherein the verification environment includes: a patient to be verified, a hospital information system, and a mobile data terminal; Obtaining medical order information based on the hospital information system, wherein the medical order information includes: patient identity information, specimen container information, and specimen type information; Based on the patient's identity information, use mobile data terminals to verify the patient's identity and identify the target patient; Obtain a specimen container set, and perform the following operations on each specimen container in the specimen container set: Scan the preset container barcode on the specimen container to obtain the container identification information; Capturing an image of the specimen container to obtain container appearance information; Based on a preset container matching rule, the container identification information and the container appearance information are compared with the specimen container information to determine whether there is a specimen container that matches the specimen container information; If there is no specimen container matching the specimen container information, the matching process is terminated and a preset first exception handling solution is triggered; If there is a specimen container that matches the specimen container information, the specimen container is confirmed as the target specimen container; Detecting the target specimen container according to the specimen type information to determine whether the target specimen container meets the preset specimen collection requirements; If the target specimen container does not meet the specimen collection requirements, the detection process is terminated and the preset second abnormality handling plan is triggered; If the target specimen container meets the specimen collection requirements, the specimen is collected from the target patient and the specimen collection information is recorded; The specimen collection information is uploaded to the hospital information system to complete the intelligent verification of the specimen container based on the medical order matching.

2. The method for intelligent specimen container verification based on medical order matching according to claim 1, characterized in that: The obtaining of medical order information based on the hospital information system includes: Obtaining patient diagnostic information, uploading the patient diagnostic information to a hospital information system, and obtaining electronic diagnostic information; determining patient identification information based on the electronic diagnostic information; extracting disease test items of the patient from the electronic diagnostic information; Based on the disease test items, the hospital information system is used to obtain specimen container information and specimen type information from a preset database; The patient identity information is integrated with the specimen container information and the specimen type information to obtain medical order information.

3. The method for intelligent specimen container verification based on medical order matching according to claim 2, characterized in that: The use of a mobile data terminal to verify the patient's identity and determine the target patient includes: Obtaining a patient identification identifier, wherein the patient identification identifier refers to a unique identifier that can represent the patient's identity information; Scanning the patient identification using the mobile data terminal to obtain the target patient's identity information; The target patient is determined according to the target patient identity information.

4. The method for intelligent specimen container verification based on medical order matching according to claim 3, characterized in that: The step of collecting an image of the specimen container to obtain container appearance information includes: Using a mobile data terminal to collect an image of the specimen container to obtain an image of the specimen container; Performing grayscale processing on the specimen container image to obtain a container grayscale image; A pre-built Gaussian filtering algorithm is used to perform image noise reduction on the grayscale image of the container to obtain a pre-processed container image, wherein the Gaussian filtering algorithm is as follows: G=H(I,(k,k),σ) Wherein, G represents the preprocessed container image, H() represents the Gaussian blur formula, I represents the grayscale image, σ represents the standard deviation of the Gaussian blur formula, (k, k) represents the convolution kernel of the Gaussian blur formula, and the size of the convolution kernel is k×k; Feature extraction is performed on the preprocessed container image to obtain container appearance information.

5. The method for intelligent specimen container verification based on medical order matching according to claim 4, characterized in that: The determining whether there is a specimen container matching the specimen container information includes: Using a mobile data terminal, retrieve the specimen container information from a hospital information system, wherein the specimen container information includes: target container identification information and target container appearance information; Summarizing the container identification information to obtain a container identification information set; Compare the target container identification information with each container identification information in the container identification information set, and determine whether the container identification information and the target container identification information are consistent; If there is no container identification information that is consistent with the target container identification information, it is determined that there is no specimen container whose specimen container information matches; If the container identification information is consistent with the target container identification information, then a feature comparison is performed on the container appearance information and the target container appearance information to obtain feature similarity, wherein the feature similarity includes: color similarity and contour similarity; When the feature similarity meets a preset similarity standard, it is determined that there is a specimen container that matches the specimen container information.

6. The method for intelligent specimen container verification based on medical order matching according to claim 5, characterized in that: The comparing the features of the container appearance information with the target container appearance information to obtain feature similarity includes: The container color histogram and the target container color histogram are obtained according to the container appearance information and the target container appearance information, and the color similarity is calculated using the following formula: Among them, S c Indicates color similarity, H 1，i Indicates the value of the container color histogram in the i-th bin, H 2，i Indicates the value of the target container color histogram in the i-th bin, N indicates the number of bins of the container color histogram and the target container color histogram, min(H 1，i , H 2，i ) indicates H 1，i and H 2，i The minimum value in max(H 1，i , H 2，i ) indicates H 1，i and H 2，i The maximum value in ; Perform contour comparison on the container appearance information and the target container appearance information to obtain contour similarity; The color similarity and the outline similarity are integrated to obtain feature similarity.

7. The method for intelligent specimen container verification based on medical order matching according to claim 6, characterized in that: Comparing the outlines of the container appearance information and the target container appearance information to obtain outline similarity includes: Performing contour detection on the container appearance information and the target container appearance information to obtain a container contour point set and a target container contour point set; Normalizing the container contour point set and the target container contour point set to obtain a standard container contour point set and a standard target container contour point set; Encode the standard container contour point set and the standard target container contour point set using a preset chain code algorithm to obtain the container chain code and the target container chain code; According to the container chain code and the target container chain code, the contour similarity between the container appearance information and the target container appearance information is calculated using a pre-built edge contour formula, wherein the edge contour formula is as follows: Among them, S e Represents the contour similarity, C1 and C2 are respectively the container chain code and the target container chain code, D e (C1, C2) represents the edit distance between the container chain code and the target container chain code, len(C1) represents the length of the container chain code, len(C2) represents the length of the target container chain code, and max(len(C1), len(C2)) represents the maximum value of len(C1) and len(C2).

8. The method for intelligent specimen container verification based on medical order matching according to claim 7, characterized in that: The detecting of the target specimen container according to the specimen type information to determine whether the target specimen container meets the preset specimen collection requirements includes: Using a mobile data terminal, the specimen type information is retrieved from a hospital information system, wherein the specimen type information includes: specimen type and specimen collection amount; Based on the specimen type, a standard container type is obtained from the hospital information system; Performing container detection on a target specimen container to obtain a target container type and a target container capacity; Compare the target container type with the standard container type; If the target container type is inconsistent with the standard container type, it is determined that the target specimen container does not meet the specimen collection requirements; If the target container type is consistent with the standard container type, the target container capacity is further compared with the specimen collection volume; If the target container capacity is smaller than the specimen collection volume, it is determined that the target specimen container does not meet the specimen collection requirements; If the target container capacity is not less than the specimen collection volume, the target specimen container is determined to meet the specimen collection requirements.

9. The method for intelligent specimen container verification based on medical order matching according to claim 8, characterized in that: The sample collection from the target patient and the recording of the sample collection information include: Obtain the corresponding sampling tool according to the specimen type information; Using the sampling tool to collect specimens from a target patient to obtain a target specimen; Store the target specimen in the target specimen container and record the specimen storage time; Based on the specimen type information, obtaining a specimen type identification; Performing label detection on the target specimen container to obtain specimen container label information, wherein the specimen container label information refers to the integrity and clarity of the label on the target specimen container; The specimen collection amount, specimen storage time, specimen type identification, and specimen container marking information are integrated to obtain specimen collection information.

10. A specimen container intelligent verification system based on medical order matching, characterized in that: The system comprises: A verification instruction receiving module is used to receive a patient verification instruction and determine a verification environment according to the patient verification instruction, wherein the verification environment includes: a patient to be verified, a hospital information system, and a mobile data terminal; The medical order information acquisition module is used to obtain medical order information based on the hospital information system. The medical order information includes: patient identity information, specimen container information, and specimen type information. Based on the patient identity information, the mobile data terminal is used to verify the patient's identity and determine the target patient; a specimen container matching module, configured to obtain a specimen container set, and perform the following operations on each specimen container in the specimen container set: scanning a preset container barcode on the specimen container to obtain container identification information, performing image capture on the specimen container to obtain container appearance information, and comparing the container identification information and the container appearance information with the specimen container information based on a preset container matching rule to determine whether there is a specimen container that matches the specimen container information; if no specimen container that matches the specimen container information exists, terminating the matching process and triggering a preset first exception handling solution; if there is a specimen container that matches the specimen container information, confirming the specimen container as a target specimen container; The specimen collection matching module is used to detect the target specimen container according to the specimen type information and determine whether the target specimen container meets the preset specimen collection requirements. If the target specimen container does not meet the specimen collection requirements, the detection process is terminated and the preset second abnormality handling plan is triggered. If the target specimen container meets the specimen collection requirements, the specimen is collected from the target patient, and the specimen collection information is recorded and uploaded to the hospital information system.

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