Data adaptive analysis method, system, device and equipment for medical teaching assessment
By adaptively parsing DICOM data generated by medical imaging equipment, the problem of poor data interoperability between various devices is solved, enabling efficient and secure assessment and evaluation, and enhancing the system's compatibility and security.
Patent Information
- Application Number
- CN202510519213.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-23
- Publication Date
- 2025-10-24
AI Technical Summary
Existing technologies cannot effectively support adaptive parsing of DICOM data from a variety of medical imaging devices, resulting in poor data interoperability between devices in medical teaching and assessment, and a lack of security and privacy protection measures.
By acquiring DICOM medical data generated by operators operating medical imaging equipment, adaptive parsing is performed based on target parsing rules to generate target-approved data sequences, which are then evaluated to obtain assessment results. Encryption measures are used to ensure data security.
It enables automated processing of data from different medical imaging devices, improves analysis efficiency and accuracy, enhances system compatibility and adaptability, and ensures data security and privacy protection.
Smart Images
Figure CN120833239A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of medical equipment examination, and in particular to a data adaptive analysis method, system, device and equipment for medical teaching examination. BACKGROUND
[0002] In the medical teaching process, in order to check the proficiency of students in operating medical equipment, the operation skills of students need to be examined. The traditional medical imaging equipment teaching examination method is more that teachers teach students the operation method of the equipment, and examinees answer questions with paper answer sheets, and the answers are evaluated manually to determine the proficiency of examinees in operating the imaging equipment.
[0003] In the related art, attribute information of a medical image file is extracted to construct a multi-dimensional binary tree to achieve fast retrieval, but it cannot support adaptive analysis of DICOM data of multiple devices. Therefore, a new data adaptive analysis method for medical teaching examination is needed. SUMMARY
[0004] The embodiments of the present specification aim to solve at least one of the technical problems in the related art to some extent. To this end, the embodiments of the present specification propose a data adaptive analysis method, system, device and equipment for medical teaching examination.
[0005] The embodiments of the present specification provide a data adaptive analysis method for medical teaching examination, the method comprising:
[0006] obtaining DICOM medical data, wherein the DICOM medical data is generated based on output data of an operator operating a medical imaging device;
[0007] adaptively analyzing the DICOM medical data based on a target analysis rule corresponding to the medical imaging device to obtain a target approved data sequence;
[0008] evaluating the target approved data sequence to obtain an examination evaluation result of the operator.
[0009] In one of the embodiments, before obtaining the DICOM medical data, the method further comprises:
[0010] determining a data return path and a data naming rule corresponding to the medical imaging device based on an examination related parameter corresponding to a sample, wherein the sample includes content description for indicating the operator operating the medical imaging device, and the examination related parameter includes a sample identifier;
[0011] obtaining the output data, and storing the output data based on the data return path and the data naming rule corresponding to the medical imaging device.
[0012] In one of the embodiments, the DICOM medical data is adaptively parsed based on the target parsing rule corresponding to the medical imaging device to obtain a target approved data sequence, including:
[0013] The data return path and data naming rule corresponding to the medical imaging device are obtained through a non-encrypted access mode;
[0014] The target medical data is extracted from the DICOM medical data based on the data return path and data naming rule corresponding to the medical imaging device;
[0015] The target parsing rule is determined in combination with the data return path and the data naming rule;
[0016] The target medical data is adaptively parsed based on the target parsing rule to extract metadata, and the target approved data sequence is obtained.
[0017] In one of the embodiments, the method further includes:
[0018] The data return path and data naming rule corresponding to the medical imaging device are pre-configured;
[0019] The target parsing rule corresponding to the medical imaging device is configured based on the data return path and the data naming rule.
[0020] In one of the embodiments, the target approved data sequence includes a parsed TAG group, the parsed TAG group is a digital expression of a parsed TAG element, and the operation personnel's examination evaluation result is obtained by evaluating the target approved data sequence, including:
[0021] The examination point and element correspondence relationship is obtained through an encrypted access mode;
[0022] The target examination point identifier corresponding to the target approved data sequence is determined based on the examination point and element correspondence relationship, wherein the examination point and element correspondence relationship includes an examination point TAG group and / or an examination point TAG element;
[0023] The target answer is determined from an examination point data sequence based on the target examination point identifier;
[0024] The target answer is compared with a to-be-approved answer in the target approved data sequence to obtain the operation personnel's examination evaluation result, wherein the to-be-approved answer is actual operation content obtained by the operation personnel operating the medical imaging device.
[0025] In one of the embodiments, the method further includes:
[0026] The configuration operation is performed on the management check list to convert the simulated patient parameters into patient information;
[0027] The patient information is sent to the medical imaging device for the medical imaging device to verify the patient information.
[0028] The present specification embodiment provides a data adaptive analysis system for medical teaching examination, the device comprises:
[0029] The system comprises:
[0030] An examination system client is configured to acquire DICOM medical data, perform adaptive analysis on the DICOM medical data based on target analysis rules corresponding to a medical imaging device to obtain a target approved data sequence, evaluate the target approved data sequence, and obtain an examination evaluation result of an operator, wherein the DICOM medical data is generated based on output data of the operator operating the medical imaging device;
[0031] A medical imaging device is configured to generate the output data based on the operation of the operator.
[0032] The present specification embodiment provides a data adaptive analysis device for medical teaching examination, the device comprises:
[0033] A medical data acquisition module is configured to acquire DICOM medical data, wherein the DICOM medical data is generated based on output data of an operator operating a medical imaging device;
[0034] A medical data analysis module is configured to perform adaptive analysis on the DICOM medical data based on target analysis rules corresponding to the medical imaging device to obtain a target approved data sequence;
[0035] An approved data evaluation module is configured to evaluate the target approved data sequence to obtain an examination evaluation result of the operator.
[0036] The present specification embodiment provides a computer device, comprising a memory and one or more processors in communication connection with the memory; the memory stores instructions executable by the one or more processors, and the instructions are executed by the one or more processors to enable the one or more processors to implement the steps of the method of any one of the above embodiments.
[0037] The present specification embodiment provides a computer readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the steps of the method of any one of the above embodiments.
[0038] The embodiments of the present specification provide a computer program product comprising instructions, which, when executed by a processor of a computer device, enable the computer device to perform the steps of the method according to any one of the above embodiments.
[0039] In the above embodiments of the present specification, first, the DICOM medical data generated based on the output data of the operation of the medical imaging device by the operator is acquired. Then, the DICOM medical data is adaptively parsed based on the target parsing rule corresponding to the medical imaging device to adapt to the data format difference or complexity generated by different medical imaging devices, so as to avoid parsing errors caused by format problems, and obtain the target approved data sequence. Finally, the target approved data sequence is evaluated to obtain the evaluation result of the operator, so as to more truly reflect the technical level and device operation ability of the operator. By adaptively parsing the DICOM medical data returned by different medical imaging devices, automatic processing can be realized, manual intervention is avoided, the efficiency and accuracy of data parsing are improved, and the compatibility and adaptability of the system are enhanced. BRIEF DESCRIPTION OF DRAWINGS
[0040] Figure 1 A flowchart of a data adaptive parsing method for medical teaching examination provided by the embodiments of the present specification is provided.
[0041] Figure 2 A flowchart of acquiring output data provided by the embodiments of the present specification is provided.
[0042] Figure 3 A flowchart of obtaining a target approved data sequence provided by the embodiments of the present specification is provided.
[0043] Figure 4 A flowchart of configuring a target parsing rule corresponding to a medical imaging device provided by the embodiments of the present specification is provided.
[0044] Figure 5 A flowchart of obtaining an evaluation result of an operator provided by the embodiments of the present specification is provided.
[0045] Figure 6 A flowchart of a medical imaging device verifying patient information provided by the embodiments of the present specification is provided.
[0046] Figure 7 A general framework diagram of a data adaptive parsing system for medical teaching examination provided by the embodiments of the present specification is provided.
[0047] Figure 8 A schematic diagram of a data adaptive parsing device for medical teaching examination provided by the embodiments of the present specification is provided.
[0048] Figure 9 An internal structure diagram of a computer device is provided for the embodiments of the present specification. DETAILED DESCRIPTION
[0049] Embodiments of the present application are described in detail below with reference to examples thereof illustrated in the accompanying drawings, in which like or similar elements are denoted throughout by like reference numerals, and which are meant to be exemplary, not limiting, of the present application.
[0050] Medical colleges often need to purchase multiple types of teaching equipment for training machines. However, the DICOM data files generated by these devices are not uniform in terms of storage path, file name, and private data definition. In particular, the DICOM private data of different device manufacturers differ in the correspondence with the test sites and the specific parsing format, and the parsing standards of these private data usually need to be kept secret.
[0051] In related technologies, a medical image device teaching examination system can usually only identify the data parsing format of a single device. When the DICOM data files generated by different devices have the same TAG but different meanings, or the same meaning but different parsing formats, the system in related technologies often cannot adaptively parse these data.
[0052] In related technologies, by obtaining DICOM medical image data, key elements are mined and analyzed, and finally an optimized medical reconstruction image result is obtained.
[0053] In related technologies, the parsing module is responsible for receiving and archiving DICOM data, files and other related data of medical techniques; the management storage module stores the DICOM data, files and other data in association; the query service module retrieves the corresponding information from the management storage module according to the query request of the terminal, and classifies and stores on the basis of integrated management of DICOM data, files and other data.
[0054] In related technologies, first, the patient is CT scanned and three-dimensional reconstruction is performed; then the image data after three-dimensional reconstruction is uploaded to the cloud; the terminal device downloads the image data from the cloud and performs DICOM parsing to generate a data linked list; according to the data linked list, the film reading operation is performed and a diagnosis report is formed, and finally the diagnosis report is uploaded to the cloud; the PC of the vehicle-mounted CT downloads the diagnosis report from the cloud for reference.
[0055] In related technologies, a medical data information digital image data cloud storage method includes the following steps: data identification, data screening, data acquisition, data upload, data release, patient data matching and data pushing. This method is mainly used for cloud storage of digital image data.
[0056] In the related art, a terminal extracts multiple frames of medical images corresponding to a Digital Imaging and Communications in Medicine (DICOM) file by parsing the DICOM file, and encodes the images using a preset encoding rule to generate a universal play list file corresponding to the DICOM file.
[0057] In the related art, attribute information of a medical image file conforming to a Digital Imaging and Communications in Medicine (DICOM) standard is extracted, and a multi-dimensional binary tree is constructed according to the attribute information, so as to realize fast response to a search request. However, this method has a limitation that it cannot support adaptive parsing of multiple image devices. In particular, in a medical college or a medical device use training institution, if multiple medical image devices need to communicate, the method can only generate multiple independent examination systems and interact with the corresponding devices.
[0058] In the related art, a complete file is established for a patient by an identity information storage unit and a medical information unit, and is stored in a cloud server. The system realizes real-time retrieval of the patient file from the cloud by an identity recognition unit, and generates an access link, a medical information two-dimensional code or a propagation interface medium for propagation and access. Users can view the medical information of the patient in real time through the access link, scan the medical information two-dimensional code or through the propagation interface medium, while supporting information exchange between multiple users in the information interaction unit.
[0059] In the related art, first, medical images of the same sequence are acquired and parsed, image data is extracted, and a volume data field is constructed based on the image data; if the obtained medical images are not symmetric images, a three-dimensional model of the head skin is further constructed according to the image data; then, a three-dimensional contour is extracted from the three-dimensional model of the head skin according to the volume data field; then, the three-dimensional contour is converted into a symmetric two-dimensional contour, and a base curve parameter is measured on the two-dimensional contour; finally, a base curve value is calculated according to the measured base curve parameter.
[0060] In the related art, an image important data priority encoding method is adopted. A client dynamically and adaptively adjusts the extraction and display of images in real time according to the current network bandwidth resources, image browsing layout and operation information of a clinician, so as to optimize the image transmission efficiency and display effect. This method ensures that the clinician can quickly and clearly browse images in a step-by-step and efficient manner, and improves the clinical operation experience.
[0061] The related art has the following disadvantages: the tools such as WorkList, CT / MR image teaching equipment, main console software, and PACS (Picture Archiving and Communication System) are not fully utilized to simulate and simulate the whole process information of patient examination, and a complete scheme for medical teaching and examination cannot be realized. In addition, the related art does not support adaptive parsing of DICOM data of multiple medical teaching equipment, resulting in poor data interoperability between different devices. During the DICOM data file parsing process, there is a lack of support for key security and privacy protection measures such as device usage authorization, configuration file encryption, and database isolation.
[0062] Therefore, the embodiments of the present specification provide a data adaptive parsing method for medical teaching and examination. First, DICOM medical data generated based on output data of a medical imaging device operated by an operator is obtained. Then, the DICOM medical data is adaptively parsed based on a target parsing rule corresponding to the medical imaging device to adapt to the data format difference or complexity generated by different medical imaging devices, thereby avoiding parsing errors caused by format problems, and obtaining a target approved data sequence. Finally, the target approved data sequence is evaluated to obtain an examination evaluation result of the operator, so as to more truly reflect the technical level and equipment operation ability of the operator. By adaptively parsing the DICOM medical data returned by different medical imaging devices, automatic processing can be realized, manual intervention is avoided, the efficiency and accuracy of data parsing are improved, and the compatibility and adaptability of the system are enhanced.
[0063] The embodiments of the present specification provide a data adaptive parsing method for medical teaching and examination. Please refer to Figure 1 The data adaptive parsing method for medical teaching and examination can include the following steps:
[0064] S110, obtaining DICOM medical data.
[0065] S120, adaptively parsing the DICOM medical data based on a target parsing rule corresponding to the medical imaging device to obtain a target approved data sequence.
[0066] S130, evaluating the target approved data sequence to obtain an examination evaluation result of the operator.
[0067] The DICOM medical data is generated based on output data of a medical imaging device operated by an operator.
[0068] Specifically, when operating a medical imaging device (such as an X-ray, CT, nuclear magnetic resonance, ultrasound, etc.) for imaging operation, an operator needs to set a series of parameters and select a suitable imaging mode in advance according to specific clinical needs and device characteristics. After receiving the operation instruction, the device will generate output data according to the parameters and mode. Then, DICOM medical data is generated based on the output data.
[0069] Due to the differences or complexities in the data formats generated by different medical imaging devices, to ensure the accuracy of data analysis, the examination system client performs adaptive analysis on the DICOM medical data using the target analysis rules corresponding to the medical imaging device after obtaining the DICOM medical data, thereby avoiding analysis errors caused by format problems and obtaining the target approved data sequence. Then, the target approved data sequence is evaluated for accuracy using pre-set answers to obtain the operator's examination evaluation results, helping to evaluate the operator's technical level in the medical imaging device operation process. Through the examination evaluation results, the operator's performance in actual operation can be truly reflected, thereby providing a basis for subsequent training and technical improvement.
[0070] In the above embodiment, first, DICOM medical data generated based on output data of an operator operating a medical imaging device is obtained. Then, the DICOM medical data is adaptively analyzed based on target analysis rules corresponding to the medical imaging device to adapt to the differences or complexities in the data formats generated by different medical imaging devices, thereby avoiding analysis errors caused by format problems and obtaining the target approved data sequence. Finally, the target approved data sequence is evaluated to obtain the operator's examination evaluation results, so as to more truly reflect the operator's technical level and device operation ability. By adaptively analyzing the DICOM medical data returned by different medical imaging devices, automatic processing can be achieved, avoiding manual intervention, improving the efficiency and accuracy of data analysis, and enhancing the compatibility and adaptability of the system.
[0071] It should be noted that the entire process of the data adaptive analysis system for medical teaching examination adopts login password encryption and software authorization code to prevent unauthorized devices from using the system. The message channel registration and access function subscription of the examination system client and server are adopted to prevent unauthorized client access. The system also involves access limiting methods to protect the examination point and element comparison relationship to ensure that sensitive data is not accessed by unauthorized users.
[0072] Exemplarily, the main console of the medical imaging device contains a dongle for ensuring security and authorization management of the device. A general user cannot log in to the server system using the system administrator permission, and software login in the data server adopts MD5 encryption (non-plain storage) to ensure the security of data transmission and storage. The MD5 (Message-Digest Algorithm 5) is a widely used hash algorithm that can generate a 128-bit (16-byte) hash value for verifying the integrity and consistency of information.
[0073] The test system client (including the configuration module and the test module) needs to be registered on the server through the Remoting framework when running, so as to ensure the security and stability of the system. The Remoting framework provides an object interaction mechanism across application domains, and realizes communication between application domains through channels. After the data calling method is registered on the channel, the remote object code can run on the server side, so as to realize the interaction between the client and the server.
[0074] In addition, the test module configuration file in the test system client adopts encryption measures (system running file encryption uses DES algorithm, and test module uses authorized registration code). The DES (Data Encryption Standard) is a block algorithm using key encryption. The test module uses the environment configuration in the form of an encrypted file, and in this way, the use of the system by unauthorized devices can be effectively controlled.
[0075] In some embodiments, referring to Figure 2 Before acquiring the DICOM medical data, the method can further include the following steps:
[0076] S210, determining a data return path and a data naming rule corresponding to the medical imaging device based on the examination related parameters corresponding to the sample.
[0077] S220, acquiring output data and storing the output data based on the data return path and the data naming rule corresponding to the medical imaging device.
[0078] The sample includes a content description for instructing an operator to operate the medical imaging device, and the examination related parameters include a sample identifier. The sample identifier is a description of the sample type.
[0079] Specifically, the examination related parameters include a sample identifier. The examination system client queries and matches the data return path and data naming rules corresponding to the medical imaging device corresponding to the sample based on the sample identifier corresponding to the sample from the server side. After completing the matching of the data return path and the data naming rules, the examination system client extracts the data return path and the data naming rules corresponding to the medical imaging device corresponding to the sample, so as to ensure that the image data can be stored and managed according to a unified standard format. The operator selects the corresponding patient information according to the sample (the sample includes a content description for instructing the operator to operate the medical imaging device) through the medical imaging device host console software, and enters the examination protocol and device parameters according to the requirements. The medical imaging device simulates the patient examination process according to the content entered by the operator, and simulates the generation of corresponding output data on the medical imaging device. The examination system client integrates the PACS system function. The output data is returned to the PACS system using the DICOM protocol. The PACS system receives the output data returned by the medical imaging device, stores the output data according to the data return path and the data naming rules corresponding to the medical imaging device, ensures that the file returned by the medical imaging device is stored in a unified standard format, and obtains DICOM medical data. The output data can include a study identifier (StudyInstanceUID), a sequence identifier (SeriesInstanceUID), an operation object instance identifier (SOPInstanceUID), and an image sequence number.
[0080] Exemplarily, the data structure form of the examination related parameters can be {serial number, description, sample identifier}, and the data sample is as follows: {1, “CT examination”, CT}, {2, “MR examination”, MR}, and {3, “DR examination”, DR}.
[0081] In some embodiments, the sample can be dynamically set according to the input examination related parameters and input data, and at this time, the examination point data sequence needs to be configured. The configured sample and examination point data sequence are stored to the server side.
[0082] In some embodiments, the sample can be dynamically set according to the input examination related parameters and input data, and at this time, the examination point data sequence needs to be configured. The configured sample and examination point data sequence are stored to the server side.
[0083] In the above embodiments, the data return path and the data naming rules corresponding to the medical imaging device are determined based on the examination related parameters corresponding to the sample, the output data is obtained, and the output data is stored based on the data return path and the data naming rules corresponding to the medical imaging device, so as to avoid data confusion and provide a basis for subsequent adaptive analysis.
[0084] In some embodiments, please refer toFigure 3 The adaptive parsing of the DICOM medical data based on the target parsing rule corresponding to the medical imaging device obtains a target approved data sequence, which can include the following steps:
[0085] S310, obtaining the data return path and data naming rule corresponding to the medical imaging device through a non-encrypted access mode.
[0086] S320, extracting target medical data from the DICOM medical data based on the data return path and data naming rule corresponding to the medical imaging device.
[0087] S330, determining the target parsing rule in combination with the data return path and data naming rule.
[0088] S340, adaptive parsing of the target medical data based on the target parsing rule, extracting metadata, and obtaining a target approved data sequence.
[0089] Specifically, according to the sample identification, the examination system client communicates with the server side through a non-encrypted access mode, queries and matches the data return path and data naming rule corresponding to the current sample corresponding to the medical imaging device in the server side. After completing the matching of the data return path and the data naming rule, the examination system client extracts the data return path and the data naming rule, and then locates the file storage location storing the DICOM medical data according to the data return path. Then, the required medical data required by the current sample is filtered and extracted from the DICOM medical data by using the data naming rule, and the target medical data is obtained. After determining the data return path and the data naming rule, the examination system client communicates with the server side, queries the information stored in the server side, and matches and obtains the corresponding target parsing rule from the server side in combination with the data return path and the data naming rule. The target parsing rule will guide how to extract the required metadata from the target medical data. Based on the target parsing rule, the examination system client adaptively parses the target medical data. Adaptive parsing means that the parsing process can automatically adjust the parsing strategy according to the characteristics and needs of the data. The metadata extracted by adaptive parsing will be organized into a target approved data sequence, which contains the approved answers of the sample, so as to be analyzed and evaluated subsequently.
[0090] In the above embodiments, the data return path and data naming rules corresponding to the medical imaging device are obtained through a non-encrypted access mode, the target medical data is extracted from the DICOM medical data based on the data return path and data naming rules corresponding to the medical imaging device, the target parsing rule is determined in combination with the data return path and data naming rules, the target medical data is adaptively parsed based on the target parsing rule, the metadata is extracted, and the target approved data sequence is obtained. This can realize automatic processing, avoid manual intervention, improve the efficiency and accuracy of data parsing, and enhance the compatibility and adaptability of the system.
[0091] In some embodiments, referring to Figure 4 The method can further include the following steps:
[0092] S410, pre-configure the data return path and data naming rules corresponding to the medical imaging device.
[0093] S420, configure the target parsing rule corresponding to the medical imaging device based on the data return path and data naming rules.
[0094] Specifically, due to the diversity and complexity of medical imaging devices, different types of devices (such as CT, MRI, X-ray, ultrasound, etc.) may generate data in different formats. Therefore, each device needs to be configured to ensure the accuracy of data storage and parsing.
[0095] According to the type and function of the medical imaging device, a specific data return path is configured for it. This path is used to store the output data of the medical imaging device, ensuring that the data can be uniformly managed and accessed.
[0096] Since the output data of the medical imaging device may contain multiple categories (such as head scan, chest scan, etc.), a unified naming rule needs to be defined for each category to facilitate the classification and management of data. The naming rule can include the examination date, patient information, examination type, device type, etc.
[0097] Since the output data formats of different medical imaging devices are different, the data formats stored in the DICOM files of different examination points are different, the data feature values are different, and the parsing formats are different, the target parsing rule corresponding to each medical imaging device is configured based on the data return path and naming rule. The target parsing rule is used to parse the stored output data of the medical imaging device it matches, ensuring that the data can be correctly parsed to obtain subsequent data for evaluation. After configuring the data return path, data naming rules corresponding to the medical imaging device and the target parsing rule corresponding to the medical imaging device, these configuration information will be stored on the server side, so that the subsequent examination system client can query and call.
[0098] In the above embodiments, the data return path and the data naming rule corresponding to the medical imaging device are pre-configured, and the target analysis rule corresponding to the medical imaging device is configured based on the data return path and the data naming rule, so as to adapt to the data format difference or complexity generated by different medical imaging devices, thereby avoiding analysis errors caused by format problems.
[0099] In some embodiments, referring to Figure 5 The target approved data sequence includes an analysis TAG group, the analysis TAG group is a digital expression of the analysis TAG element, and the target approved data sequence is evaluated to obtain the assessment result of the operator. The assessment result can include the following steps:
[0100] S510, obtaining the examination point and element correspondence relationship through an encrypted access mode.
[0101] S520, determining the target examination point identifier corresponding to the target approved data sequence based on the examination point and element correspondence relationship.
[0102] The examination point and element correspondence relationship includes an examination point TAG group and / or an examination point TAG element.
[0103] Specifically, the assessment system client determines an encrypted access mode according to the sample identifier, then communicates with the server side through the encrypted access mode, and queries and matches the examination point and element correspondence relationship corresponding to the current sample in the server side. In some embodiments, the examination point and element correspondence relationship includes an examination point TAG group. The target approved data sequence includes an analysis TAG group. After matching the examination point and element correspondence relationship corresponding to the current sample, the assessment system client searches in the examination point and element correspondence relationship based on the analysis TAG group included in the target approved data sequence, and determines whether there is an examination point TAG group matching the analysis TAG group in the examination point and element correspondence relationship. If there is a matching item, in the examination point and element correspondence relationship, the examination point identifier corresponding to the examination point TAG group matching the analysis TAG group included in the target approved data sequence is taken as the target examination point identifier corresponding to the target approved data sequence.
[0104] In some embodiments, the point-element correspondence relationship comprises a point TAG element. The target approved data sequence comprises a parsed TAG group and a parsed TAG element, wherein the parsed TAG group is a digital representation of the parsed TAG element. After completing the matching of the point-element correspondence relationship corresponding to the current sample, the examination system client searches in the point-element correspondence relationship based on the parsed TAG element included in the target approved data sequence, and determines whether there is a point TAG element in the point-element correspondence relationship that matches the parsed TAG element. If there is a matching item, the point identification corresponding to the point TAG element in the point-element correspondence relationship that matches the parsed TAG element included in the target approved data sequence is taken as the target point identification corresponding to the target approved data sequence.
[0105] In some embodiments, the point-element correspondence relationship comprises a point TAG element. The target approved data sequence comprises a parsed TAG group and a parsed TAG element, wherein the parsed TAG group is a digital representation of the parsed TAG element. After completing the matching of the point-element correspondence relationship corresponding to the current sample, the examination system client searches in the point-element correspondence relationship based on the parsed TAG element included in the target approved data sequence, and determines whether there is a point TAG element in the point-element correspondence relationship that matches the parsed TAG element. If there is a matching item, the point identification corresponding to the point TAG element in the point-element correspondence relationship that matches the parsed TAG element included in the target approved data sequence is taken as the target point identification corresponding to the target approved data sequence.
[0106] Exemplarily, the data structure form of the point-element correspondence relationship can be {serial number, group number, point TAG group, point TAG element, point identification}, and the data sample is as follows: {1, Group_01, (0010, 0020), patient identification, PatientID}, {2, Group_01, (0010, 0010), patient name, PatientName}, {3, Group_01, (0010, 0040), patient gender, PatientSex}, ….
[0107] S530, determining the target answer from the point data sequence based on the target point identification.
[0108] Specifically, the examination point data sequence includes an examination point identifier, an answer, an examination point TAG group and / or an examination point TAG element. The examination system client communicates with the server, queries and matches the examination point data sequence corresponding to the current sample according to the sample identifier. After completing the matching of the examination point data sequence corresponding to the current sample, the examination system client extracts the examination point data sequence, and then searches in the examination point data sequence corresponding to the current sample according to the target examination point identifier to determine whether there is an examination point identifier matching the target examination point identifier in the examination point data sequence corresponding to the current sample. If there is a matching item, the answer corresponding to the target examination point identifier in the examination point data sequence corresponding to the current sample is determined as the target answer.
[0109] Exemplarily, the data structure form of the examination point data sequence can be {serial number, sample identifier, examination point TAG element, answer, examination point identifier}, and the data sample is as follows: {1, CT, patient identifier, P-202501010001, PatientID}, {2, CT, patient name, Zhang San, PatientName}, {3, CT, patient gender, male, PatientSex}, ….
[0110] S540, comparing the target answer with the to-be-approved answer in the target approved data sequence to obtain an examination evaluation result of the operator.
[0111] The to-be-approved answer is based on actual operation content obtained by the operator operating the medical imaging device.
[0112] Specifically, the target approved data sequence includes a to-be-approved answer, and the to-be-approved answer is based on actual operation content obtained by the operator operating the medical imaging device, so it is necessary to judge its accuracy. The examination system client compares the target answer with the to-be-approved answer in the target approved data sequence. When the target answer is consistent with the to-be-approved answer in the target approved data sequence, it is determined that the target approved data sequence is accurate. When the target answer is inconsistent with the to-be-approved answer in the target approved data sequence, it is determined that the target approved data sequence is inaccurate. Then, based on the results of all target approved data sequences, the examination evaluation result of the operator is obtained.
[0113] It should be noted that the assessment results of the operator will be stored in the server side, and the assessment results and related examples will be retained for subsequent review. Specifically, the examples and assessment results will not be encrypted, so that the operator and the teacher can access and query the relevant data at any time. In addition, the examination point data sequence (including example identification, examination point TAG element, answer, and examination point identification) will be open to the operator for query after the evaluation is completed. This data storage and query mechanism aims to facilitate the operator and the teacher to view the historical assessment records at any time, and to ensure the transparency and traceability of the assessment process. The operator can view the detailed content of the historical assessment, including but not limited to the assessment examples, the assessment results, the answers, etc.
[0114] In the above embodiment, the examination point and element correspondence relationship is obtained through an encrypted access mode, enhancing data security. Based on the examination point and element correspondence relationship, the target examination point identification corresponding to the target approved data sequence is determined, the target answer is determined from the examination point data sequence based on the target examination point identification, the target answer is compared with the to-be-approved answer in the target approved data sequence, the operator's assessment result is obtained through an automatic assessment system, and the evaluation efficiency is improved.
[0115] In some embodiments, referring to Figure 6 The method can further include the following steps:
[0116] S610, the configuration operation is performed on the management check list to convert the simulated patient parameters into patient information.
[0117] S620, the patient information is sent to the medical imaging device, so that the medical imaging device checks the patient information.
[0118] Specifically, when the operator starts answering the questions, the operator first performs a configuration operation on the worklist on the test system client, and communicates with the main console software of the medical imaging device after setting the specific address (IP) and port parameters. In different embodiments, the operator also needs to set the AE title (application entity title) for identifying one or more DICOM services. The test system client can use the DICOM protocol to convert the patient personal information and examination information registered after simulating the hospital patient registration, i.e., the simulated patient parameters, into the patient information required for medical imaging device examination, wherein the patient information includes the worklist patient information list. Through the patient information, medical workers can better organize and manage work and ensure that patients receive timely and accurate medical services. At the same time, the patient information can also help medical workers better understand the patient's condition in order to make more accurate diagnoses and treatments. Then the test system client sends the patient information to the medical imaging device. After receiving the patient information, the medical imaging device will verify it according to the unique identifier (study instance UID) in the patient information. After the verification is successful, the operator can perform operations on the medical imaging device. It should be noted that the magnetic resonance imaging device needs to be verified, and the computed tomography scanner does not need to be verified.
[0119] In the above embodiment, the simulated patient parameters are converted into patient information by performing a configuration operation on the worklist, the patient information is sent to the medical imaging device, and the medical imaging device verifies the patient information, so as to ensure that it is suitable for different medical imaging devices.
[0120] The embodiments of the present specification provide a data self-adaptive analysis system for medical teaching examination, the system comprises:
[0121] The test system client is configured to obtain DICOM medical data, perform self-adaptive analysis on the DICOM medical data based on a target analysis rule corresponding to the medical imaging device, obtain a target approved data sequence, evaluate the target approved data sequence, and obtain an examination evaluation result of the operator, wherein the DICOM medical data is generated based on output data of the operator operating the medical imaging device;
[0122] The medical imaging device is configured to generate output data based on the operation of the operator.
[0123] In some embodiments, the medical teaching examination data adaptive analysis system can be developed in C# language. The system is based on the Net Remoting framework, which is a communication mechanism across application domains and networks, and can realize object interaction between different application domains, support message channel registration and function subscription. The system uses the DICOM (Digital Imaging and Communications in Medicine) protocol, which is an international standard (ISO 12052) that defines a medical image format that meets clinical needs and is widely used in radiology, cardiovascular imaging, and data exchange of various imaging devices (such as X-ray, CT, nuclear magnetic resonance, ultrasound, etc.).
[0124] The medical teaching examination data adaptive analysis system provided by the embodiments of the present specification provides a general framework diagram, please refer to Figure 7 The system includes an examination system client, an examination system server, a WorkList server, a PACS server, a CT\MR image teaching device, and a main console software. The system can simulate the whole process of examination operation in the radiology department of a hospital and support the transmission of DICOM data files.
[0125] Specifically, the configuration operation is performed through the WorkList function to convert the simulated patient parameters into patient information, and the patient information is sent to the medical imaging device for verification. After successful verification, the operator performs operations through the CT\MR image teaching device and the main console software, obtains output data, and then uses the DICOM protocol to return the output data to the PACS system. The PACS system receives the output data and stores the output data according to the data return path and data naming rules corresponding to the CT\MR image teaching device to obtain DICOM medical data. Then, the examination system client performs adaptive analysis on the DICOM medical data based on the target analysis rules corresponding to the CT\MR image teaching device to obtain a target approved data sequence. Finally, the target approved data sequence is evaluated based on the examination point and element correspondence relationship to obtain the examination and evaluation result of the operator.
[0126] Among them, the examination system client can obtain the data return path and data naming rules corresponding to the CT\MR image teaching device from the non-encrypted area of the data server through a non-encrypted access method. The examination point and element correspondence relationship is obtained from the encrypted area of the data server through an encrypted access method.
[0127] The medical teaching examination data adaptive analysis system provided by the embodiments of the present specification provides a general framework diagram, please refer to Figure 8The data adaptive analysis device 800 for medical teaching assessment includes: a medical data acquisition module 810, a medical data analysis module 820, and an approval data evaluation module 830.
[0128] A medical data acquisition module 810 is configured to acquire DICOM medical data, wherein the DICOM medical data is generated based on output data of a medical imaging device operated by an operator;
[0129] A medical data parsing module 820 is configured to adaptively parse the DICOM medical data based on target parsing rules corresponding to the medical imaging device to obtain a target approved data sequence;
[0130] The approval data evaluation module 830 is used to evaluate the target approval data sequence and obtain the assessment result of the operator.
[0131] For a detailed description of the data adaptive analysis device for medical teaching assessment, please refer to the description of the data adaptive analysis method for medical teaching assessment above, which will not be repeated here.
[0132] In some embodiments, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 9 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a data adaptive parsing method for medical teaching assessment is implemented. The display screen of the computer device can be a liquid crystal display or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.
[0133] Those skilled in the art will understand that Figure 9 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution disclosed in this specification, and does not constitute a limitation on the computer device to which the solution disclosed in this specification is applied. Specifically, the computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.
[0134] In some embodiments, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the method steps of the above embodiments when executing the computer program.
[0135] One embodiment of the present specification provides a computer readable storage medium having stored therein a computer program, the computer program, when executed by a processor, implementing the steps of the method in any of the above embodiments.
[0136] One embodiment of the present specification provides a computer program product comprising instructions, which, when executed by a processor of a computer device, enable the computer device to perform the steps of the method of any of the above embodiments.
[0137] It should be noted that the logic and / or steps represented in the flowcharts and / or otherwise described herein, for example, can be considered as a sequence of executable instructions stored in any computer readable medium, which can be interpreted by an instruction execution system, apparatus or device, such as a computer-based system, a processor-based system, or other system that can fetch the instructions from the instruction execution system, apparatus or device and execute the instructions, or in conjunction with the instruction execution system, apparatus or device. For the purposes of this specification, a "computer readable medium" can be any apparatus that can contain, store, communicate, propagate or transport the program for use by or in connection with the instruction execution system, apparatus or device. More specific examples (a non-exhaustive list) of the computer readable medium include the following: an electrical connection having one or more wires (electrical apparatus), a portable computer diskette (magnetic apparatus), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber (optical apparatus), and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium can even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example, by optically scanning the paper or other suitable medium, then electronically converted into a form that can be edited, compiled or interpreted for execution by a computer.
Claims
1. A data self-adaptive analysis method for medical teaching examination, characterized in that, The method comprises: acquiring DICOM medical data, wherein the DICOM medical data is generated based on output data of an operator operating a medical imaging device; performing adaptive analysis on the DICOM medical data based on a target analysis rule corresponding to the medical imaging device to obtain a target approved data sequence; evaluating the target approved data sequence to obtain an evaluation result of the operator.
2. The method of claim 1, wherein, Before acquiring the DICOM medical data, the method further comprises: determining a data return path and a data naming rule corresponding to the medical imaging device based on an evaluation related parameter corresponding to a sample, wherein the sample comprises a content description for instructing the operator to operate the medical imaging device, and the evaluation related parameter comprises a sample identifier; acquiring the output data and storing the output data based on the data return path and the data naming rule corresponding to the medical imaging device.
3. The method of claim 1, wherein, The adaptive analysis on the DICOM medical data based on the target analysis rule corresponding to the medical imaging device to obtain the target approved data sequence comprises: acquiring the data return path and the data naming rule corresponding to the medical imaging device through a non-encrypted access mode; extracting target medical data from the DICOM medical data based on the data return path and the data naming rule corresponding to the medical imaging device; determining a target analysis rule in combination with the data return path and the data naming rule; performing adaptive analysis on the target medical data based on the target analysis rule to extract metadata to obtain the target approved data sequence.
4. The method of claim 3, wherein, The method further comprises: pre-configuring the data return path and the data naming rule corresponding to the medical imaging device; configuring a target analysis rule corresponding to the medical imaging device based on the data return path and the data naming rule.
5. The method of claim 1, wherein, The target approved data sequence comprises an analysis TAG group, which is a digital expression of an analysis TAG element, and the evaluation of the target approved data sequence to obtain the evaluation result of the operator comprises: acquiring a test point and element correspondence relationship through an encrypted access mode; determining a target test point identifier corresponding to the target approved data sequence based on the test point and element correspondence relationship, wherein the test point and element correspondence relationship comprises a test point TAG group and / or a test point TAG element; determining a target answer from a test point data sequence based on the target test point identifier; comparing the target answer with a to-be-approved answer in the target approved data sequence to obtain the evaluation result of the operator, wherein the to-be-approved answer is based on actual operation content obtained by the operator operating the medical imaging device.
6. The method of claim 1, wherein, The method further comprises: transforming a simulated patient parameter into patient information by performing a configuration operation on a management check list; sending the patient information to the medical imaging device so that the medical imaging device verifies the patient information.
7. A data self-adaptive analysis system for medical teaching examination, characterized in that, The system comprises: The examination system client is used for acquiring DICOM medical data, adaptively analyzing the DICOM medical data based on a target analysis rule corresponding to a medical imaging device to obtain a target approved data sequence, evaluating the target approved data sequence, and obtaining an examination evaluation result of an operator, wherein the DICOM medical data is generated based on output data of the operator operating the medical imaging device; The medical imaging device is used for generating the output data based on an operation of an operator.
8. A data self-adaptive analysis device for medical teaching examination, characterized in that, The device comprises: a medical data acquisition module configured to acquire DICOM medical data, wherein the DICOM medical data is generated based on output data of an operator operating a medical imaging device; a medical data analysis module configured to adaptively analyze the DICOM medical data based on a target analysis rule corresponding to the medical imaging device to obtain a target approved data sequence; an approved data evaluation module configured to evaluate the target approved data sequence to obtain an examination evaluation result of the operator. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor executes the computer program to implement the steps of the method in any one of claims 1 to 6.
10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method in any one of claims 1 to 6.