Data migration system for PACS historical data migration and fusion

Abstract

The invention relates to the technical field of data processing, in particular to a data migration system for PACS historical data migration and fusion, which comprises a migration module, a creation module, a collection module, a verification module, a repair module, an adjustment module and an alarm module. According to the method, the integrity, the accuracy and the efficiency of PACS historical data migration are effectively improved through an automatic, real-time monitoring and repairing mechanism. In the migration process, the system can collect the migration speed in real time and verify the integrity and accuracy of the data, it is ensured that migration data cannot be lost or errors cannot occur, meanwhile, the system can adapt to different migration environments and data problems by dynamically adjusting the repairing threshold value and the repairing data, the stability and reliability of the migration process are optimized, and the migration efficiency is improved. The problems of data analysis errors, low migration efficiency and index failure caused by implementation differences of DICOM standards among PACS systems and incompatibility of data storage architectures are effectively solved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a data migration system for migrating and merging historical PACS data. Background Technology

[0002] With the development of medical informatization, hospital image storage and communication systems (PACS) play a vital role in clinical diagnosis and medical data management. However, with the upgrading, replacement, or integration of hospital systems, data migration between different PACS systems becomes an inevitable requirement. But due to differences in the implementation of the DICOM standard and varying storage architectures across systems, and the potential for data loss, erroneous modifications, or index failures during migration, ensuring the integrity, accuracy, and availability of historical image data has become a significant challenge for medical institutions.

[0003] Patent document CN103049582A discloses an automatic migration system and method for DICOM medical image data. The system includes a DICOM retrieval module, a DICOM acquisition module, a consistency determination module, a DICOM processing module, and a DICOM sending module. The DICOM retrieval module automatically retrieves correct patient information from the DICOM server of the old PACS according to set conditions. The DICOM acquisition module retrieves the corresponding DICOM image data file for the patient from the DICOM server of the old PACS. The consistency determination module compares the patient information in the DICOM image data file with the correct patient information retrieved from the DICOM server of the old PACS. If there is a discrepancy, the correct patient information retrieved from the DICOM server of the old PACS takes precedence. The DICOM processing module automatically modifies the patient information in the DICOM image data file. Finally, the modified DICOM image data file is automatically sent to the new PACS server via the DICOM sending module. If the patient information is consistent, the DICOM image data file retrieved by the DICOM acquisition module is directly sent to the new PACS server via the DICOM sending module.

[0004] Therefore, the aforementioned DICOM medical image data automatic migration system and method have the following problems: When inconsistencies in patient information are detected, the patient information in the DICOM image data file is directly overwritten with information from the old PACS server, resulting in the loss or incorrect modification of the data source; the migration rate may fluctuate significantly under different network environments or system loads, leading to excessively long migration times or increased failure rates; the handling of migration failures is simplistic, and when partial data loss or errors occur during the migration process, incomplete data files are stored in the new PACS system; different PACS systems may have different implementations of the DICOM standard, resulting in some image data or metadata fields being unable to be correctly parsed or being lost after migration; the old PACS and the new PACS use different data storage architectures, and direct migration may lead to missing database fields, mapping errors, or index failures. Summary of the Invention

[0005] To address this, the present invention provides a data migration system for migrating and merging historical PACS data. This system overcomes the problems of data parsing errors, low migration efficiency, and index failures caused by differences in DICOM standard implementations and incompatible data storage architectures among PACS systems in the prior art through dynamic migration rate adjustment and cross-system compatibility processing.

[0006] To achieve the above objectives, the present invention provides a data migration system for PACS historical data migration and fusion, comprising: The migration module is used to migrate patient report data from the original PACS system to the new PACS system, forming migrated data; A creation module, which is connected to the migration module, is used to create a mapping index between historical image data and migrated data in the new PACS system based on the storage address, patient identifier, examination time, and migrated data of historical image data extracted from the original PACS system; The acquisition module, which is connected to the migration module, is used to acquire the real-time migration speed of migrating patient report data from the original PACS system to the new PACS system and the real-time first speed of forming the migrated data. The verification module is connected to the migration module, the acquisition module, and the creation module respectively, and is used to verify the integrity of the migrated data based on the real-time migration speed and the real-time first speed to form a completeness, and to verify the accuracy of the migrated data based on the mapping index and the migrated data to form an accuracy. A repair module, which is connected to the verification module and the migration module respectively, is used to repair the migrated data according to the completeness, the accuracy and the preset repair threshold, to form repaired migration data; An adjustment module, connected to the repair module, is used to monitor the real-time second speed at which the repair migration data is generated, and to adjust the preset repair threshold based on the real-time second speed and the real-time migration speed, thereby forming an adjustment repair threshold. An alarm module, connected to the repair module, is used to issue alarms based on the patient report data and the repair migration data formed based on the adjusted repair threshold.

[0007] Furthermore, the migration module includes: The field extraction unit is used to extract the patient identification field, examination time field, and examination type field from the patient report data; A format acquisition unit is used to acquire the data structure format of the new PACS system; A conversion unit, which is connected to the format acquisition unit and the extraction unit respectively, is used to convert the patient identification field, examination time field and examination type field into a storage format consistent with the data structure format, forming a conversion identifier, conversion time and conversion type; The migration unit, which is connected to the conversion unit, is used to store the converted patient identifier, converted examination time, and converted examination type into the database of the new PACS system through a database insertion operation, forming the migrated data.

[0008] Furthermore, the creation module includes: An index generation unit is used to generate image index data in the database of the new PACS system based on the storage address, the patient identifier, and the examination time. An index mapping unit, connected to the index generation unit, is used to match the image index data and the migrated data according to the conversion identifier and the conversion time, and to establish an image report mapping relationship to form the mapping index.

[0009] Furthermore, the index generation unit includes: A sub-unit is established to create an image index table based on the patient identifier and the examination time; A filling subunit, which is connected to the establishing subunit, is used to fill the storage address into the image index table to generate image index data.

[0010] Furthermore, the verification module includes: The first migration fluctuation calculation unit is used to calculate the standard deviation of all the real-time migration speeds within a preset verification period to form the first migration fluctuation value. The first fluctuation calculation unit is used to calculate the standard deviation of all the real-time first velocities within the preset verification time to form the first velocity fluctuation value. A completeness calculation unit is connected to the first migration fluctuation calculation unit and the first fluctuation calculation unit, respectively, and is used to calculate the completeness based on the migration fluctuation value and the first velocity fluctuation value. An accuracy calculation unit is used to verify the accuracy of the migrated data based on the mapping index and the migrated data, and to form an accuracy.

[0011] Furthermore, the integrity calculation unit includes: The migration curve plotting subunit is used to plot the change curve of the first migration fluctuation value within the preset verification time, thereby forming a migration curve; The first curve drawing subunit is used to draw the change curve of the first speed fluctuation value within the preset verification time, forming the first curve; The integrity calculation subunit is used to calculate the cosine similarity between the migration curve and the first curve to form the integrity score.

[0012] Furthermore, the accuracy calculation unit includes: A matching record subunit is used to record the number of matches between each migrated data and its corresponding mapping index during the traversal of all the migrated data; An accuracy calculation subunit, connected to the recording subunit, is used to calculate the ratio of the number of matches to the total number of migrated data, thus forming the accuracy.

[0013] Furthermore, the repair module includes: The first deviation calculation unit is used to calculate the relative deviation between the preset completeness threshold and the completeness when the completeness is less than the preset completeness threshold, to form a completeness deviation, and to calculate the relative deviation between the preset accuracy threshold and the accuracy when the accuracy is less than the preset accuracy threshold, to form an accuracy deviation. An index calculation unit, connected to the deviation calculation unit, is used to perform a weighted summation calculation on the completeness deviation, the accuracy deviation, the preset completeness deviation weight, and the preset accuracy deviation weight to form a repair index. The second deviation calculation unit is connected to the index calculation unit and is used to calculate the relative deviation between the repair index and the preset repair threshold when the repair index is greater than the preset repair threshold, thereby forming a repair deviation. A duration recording unit, which is connected to the second deviation calculation unit, is used to record the duration when the repair deviation is less than a preset repair deviation threshold; A repair unit, connected to the duration recording unit, is used to repair the migrated data when the duration exceeds a preset repair duration, thereby forming the repaired migration data.

[0014] Furthermore, the adjustment module includes: A monitoring unit is used to monitor the real-time second speed; The second fluctuation calculation unit is connected to the monitoring unit and is used to calculate the standard deviation of the real-time second speed within a preset adjustment period to form the second speed fluctuation value. The second migration fluctuation calculation unit is used to calculate the standard deviation of the real-time migration speed within the preset adjustment period to form the second migration fluctuation value. A synchronization calculation unit, which is connected to the second fluctuation calculation unit and the second migration fluctuation calculation unit respectively, is used to calculate the relative deviation between the second speed fluctuation value and the second migration fluctuation value to form a synchronization degree; An average value calculation unit, connected to the synchronization degree calculation unit, is used to calculate the average value of the real-time second speed within the preset adjustment time when the synchronization degree is less than a preset synchronization degree threshold, to form a second average speed, and to calculate the average value of the real-time migration speed within the preset adjustment time, to form a migration average speed. An adjustment unit, connected to the average value calculation unit, is used to reduce the preset repair threshold based on the relative deviation between the average migration speed and the second average speed and a preset adjustment coefficient when the average migration speed is greater than the second average speed, thereby forming the adjustment repair threshold; and to increase the preset repair threshold based on the relative deviation between the second average speed and the average migration speed when the average migration speed is less than the second average speed, thereby forming the adjustment repair threshold.

[0015] Furthermore, the alarm module includes: A comparison unit is used to compare the integrity consistency between the patient report data and the repair migration data at the end of the migration process; A count recording unit, connected to the comparison unit, is used to record the number of comparisons when the integrity consistency is greater than a preset consistency threshold. An alarm unit, connected to the comparison unit, is used to issue an alarm when the number of comparisons exceeds a preset comparison threshold.

[0016] Compared with existing technologies, the advantages of this invention lie in its ability to effectively improve the integrity, accuracy, and efficiency of PACS historical data migration through automated, real-time monitoring and repair mechanisms. During the migration process, the system can collect migration speed data in real time and verify the integrity and accuracy of the data, ensuring that no data is lost or erroneous. Simultaneously, by dynamically adjusting repair thresholds and repair data, the system can adapt to different migration environments and data issues, reducing the need for manual intervention and optimizing the stability and reliability of the migration process. The alarm module can promptly detect potential problems, ensuring a rapid response when data deviations occur, avoiding data loss or errors during migration, improving the robustness and security of the entire system, and effectively solving the problems of data parsing errors, low migration efficiency, and index failure caused by differences in DICOM standard implementations and incompatible data storage architectures among PACS systems.

[0017] Furthermore, the standardized and automated conversion process ensured compatibility between the original PACS system data and the new system data format, improving the accuracy and efficiency of data migration. The system accurately extracted and converted key data fields, avoiding errors or omissions caused by manual intervention and guaranteeing the integrity and consistency of the migrated data. This module's efficient operation ensured a smooth transition for medical institutions during PACS system updates and data migration, significantly reducing the risks of system switching and enhancing the flexibility and security of data management.

[0018] Furthermore, by employing SQL query and hash matching technology, historical image data and migrated data can be accurately linked, ensuring data integrity and accuracy, avoiding data loss or incorrect matching, and facilitating subsequent querying, management, and maintenance, thereby improving the efficiency and accuracy of data migration.

[0019] Furthermore, by applying relational databases and standardized SQL query statements, the process of creating and populating the image index table becomes efficient and easy to manage. It can accurately match patient information with image data, improve the efficiency of data query and storage, and at the same time ensure the traceability and consistency of data, reduce errors that may be caused by manual operation, and enhance the reliability and stability of the system.

[0020] Furthermore, by calculating the fluctuations in migration speed and data rate, instability and potential problems during the data migration process can be effectively detected, ensuring that the migration process is not affected by speed fluctuations, thus preventing data loss or errors. By verifying completeness and accuracy, the migrated data is ensured to meet predetermined standards in terms of accuracy and completeness, thereby improving the reliability of the migrated data.

[0021] Furthermore, by accurately plotting the fluctuation curves during the migration process and calculating similarity, the integrity and consistency of the migrated data can be effectively determined, ensuring that no data is lost or damaged during the migration. In addition, using cosine similarity to quantify the matching degree of the fluctuation curves helps to quantify the stability and accuracy of the verification process, improving the reliability of data migration.

[0022] Furthermore, by recording the number of matches and calculating the ratio, the accuracy calculation unit can accurately assess the matching between the migrated data and the mapped index in the new PACS system, ensuring data accuracy during the migration process, improving the reliability of data migration, and ensuring that the final migrated data meets expectations.

[0023] Furthermore, by weighting the deviations in completeness and accuracy, the repair module can dynamically adjust the repair strategy to ensure that potential problems are detected and repaired in a timely manner during data migration, thereby improving the completeness and accuracy of data migration and ensuring that the quality of the migrated data meets the standards.

[0024] Furthermore, by calculating speed fluctuations and synchronization in real time, the adjustment module can intelligently adjust the repair threshold according to changes in migration speed, ensuring that the repair process matches the migration speed, thereby optimizing the timeliness and accuracy of data repair and improving the system's adaptability at different migration stages.

[0025] Furthermore, by automating comparison and monitoring to effectively monitor the integrity and consistency of the data migration process, potential problems can be detected in a timely manner and alarms can be triggered, ensuring the quality and reliability of data migration and improving system stability and data security. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the data migration system used for historical PACS data migration and fusion in this embodiment; Figure 2 This is a logic diagram for the repair module in this embodiment to determine the repair of migrated data; Figure 3 This embodiment provides a logic diagram for adjusting the preset repair threshold in the adjustment module. Figure 4 This is a logic diagram for the alarm module in this embodiment to determine when to issue an alarm. Detailed Implementation

[0027] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0028] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0029] Please see Figure 1 As shown, it is a schematic diagram of the data migration system used for PACS historical data migration and fusion in this embodiment; This embodiment provides a data migration system for PACS historical data migration and fusion, including: The migration module is used to migrate patient report data from the original PACS system to the new PACS system, forming migrated data; A creation module, which is connected to the migration module, is used to create a mapping index between historical image data and migrated data in the new PACS system based on the storage address, patient identifier, examination time, and migrated data of historical image data extracted from the original PACS system; The acquisition module, which is connected to the migration module, is used to acquire the real-time migration speed of migrating patient report data from the original PACS system to the new PACS system and the real-time first speed of forming the migrated data. The verification module is connected to the migration module, the acquisition module, and the creation module respectively, and is used to verify the integrity of the migrated data based on the real-time migration speed and the real-time first speed to form a completeness, and to verify the accuracy of the migrated data based on the mapping index and the migrated data to form an accuracy. A repair module, which is connected to the verification module and the migration module respectively, is used to repair the migrated data according to the completeness, the accuracy and the preset repair threshold, to form repaired migration data; An adjustment module, connected to the repair module, is used to monitor the real-time second speed at which the repair migration data is generated, and to adjust the preset repair threshold based on the real-time second speed and the real-time migration speed, thereby forming an adjustment repair threshold. An alarm module, connected to the repair module, is used to issue alarms based on the patient report data and the repair migration data formed based on the adjusted repair threshold.

[0030] The preset repair threshold is a standard value used to determine whether migrated data needs to be repaired. It depends on the maximum error rate or incompleteness tolerated during the data migration process and is usually set between 0% and 10%. In this embodiment, it is set to 5% to balance the speed of data migration and the need for repair, ensuring that data repair is completed within a reasonable time while avoiding unnecessary repair operations, thereby improving system efficiency and data accuracy.

[0031] The migration and fusion of historical PACS data is achieved through the collaborative work of multiple modules. First, the migration module migrates patient report data from the original PACS system to the new PACS system. The creation module establishes a mapping index between historical image data and the migrated data based on information such as the storage address and patient identification. The acquisition module monitors the migration speed in real time, and the verification module verifies data integrity and accuracy based on the real-time migration speed. If the data is incomplete or inaccurate, the repair module repairs the migrated data according to preset thresholds. The adjustment module further monitors the migration speed of the repaired data and adjusts the repair thresholds based on the real-time speed. Finally, the alarm module issues alerts based on potentially problematic data.

[0032] Through automated, real-time monitoring and repair mechanisms, the integrity, accuracy, and efficiency of PACS historical data migration are effectively improved. During the migration process, the system can collect migration speed data in real time and verify the integrity and accuracy of the data, ensuring that no data is lost or erroneous. Simultaneously, by dynamically adjusting repair thresholds and repair data, the system can adapt to different migration environments and data issues, reducing the need for manual intervention and optimizing the stability and reliability of the migration process. The alert module can promptly detect potential problems, ensuring rapid response when data deviations occur, avoiding data loss or errors during migration, improving the robustness and security of the entire system, and effectively solving problems such as data parsing errors, low migration efficiency, and index failure caused by differences in DICOM standard implementations and incompatible data storage architectures between PACS systems.

[0033] Specifically, the migration module includes: The field extraction unit is used to extract the patient identification field, examination time field, and examination type field from the patient report data; A format acquisition unit is used to acquire the data structure format of the new PACS system; A conversion unit, which is connected to the format acquisition unit and the extraction unit respectively, is used to convert the patient identification field, examination time field and examination type field into a storage format consistent with the data structure format, forming a conversion identifier, conversion time and conversion type; The migration unit, which is connected to the conversion unit, is used to store the converted patient identifier, converted examination time, and converted examination type into the database of the new PACS system through a database insertion operation, forming the migrated data.

[0034] The original PACS system supported a data interface (DICOM protocol), allowing direct extraction of required field data via an API. First, the field extraction unit extracted the patient identifier, examination time, and examination type fields from the original PACS system's patient report data. Next, the format acquisition unit obtained the data structure format of the new PACS system and converted the extracted fields into a storage format conforming to the new system through a conversion unit. Finally, the migration unit migrated the converted data to the new PACS system via database insertion, resulting in migrated data.

[0035] Through a standardized and automated conversion process, the compatibility of data formats between the original PACS system and the new system was ensured, improving the accuracy and efficiency of data migration. The system can accurately extract and convert key data fields, avoiding errors or omissions caused by manual intervention and guaranteeing the integrity and consistency of the migrated data. The efficient operation of this module ensures a smooth transition for medical institutions during PACS system updates and data migration, significantly reducing the risks of system switching and enhancing the flexibility and security of data management.

[0036] Specifically, the creation module includes: An index generation unit is used to generate image index data in the database of the new PACS system based on the storage address, the patient identifier, and the examination time. An index mapping unit, connected to the index generation unit, is used to match the image index data and the migrated data according to the conversion identifier and the conversion time, and to establish an image report mapping relationship to form the mapping index.

[0037] In the creation module, the index generation unit uses SQL queries and database management tools to generate image index data based on the storage address, patient identifier, and examination time in the new PACS system. This data undergoes data structure transformation to ensure consistency with the new system's format. Subsequently, the index mapping unit uses algorithms (such as hash function-based matching algorithms) to match the migrated patient report data with the image index data, generating a mapping relationship based on the conversion identifier and conversion time, forming a mapping index, and storing it in the database.

[0038] By employing SQL query and hash matching technology, historical image data and migrated data can be accurately linked, ensuring data integrity and accuracy, avoiding data loss or incorrect matching, and facilitating subsequent querying, management, and maintenance, thereby improving the efficiency and accuracy of data migration.

[0039] Specifically, the index generation unit includes: A sub-unit is established to create an image index table based on the patient identifier and the examination time; A filling subunit, which is connected to the establishing subunit, is used to fill the storage address into the image index table to generate image index data.

[0040] In the index generation unit, the creation sub-unit uses SQL statements in a relational database (PostgreSQL) to create an image index table in the new PACS system based on a combination of patient identification and examination time. The population sub-unit then uses SQL INSERT statements to populate the image index table with storage addresses, forming image index data and ensuring that each piece of image data can be accurately associated with the patient identification and examination time.

[0041] By applying relational databases and standardized SQL query statements, the process of creating and populating the image index table becomes efficient and easy to manage. It can accurately match patient information with image data, improve the efficiency of data query and storage, and at the same time ensure the traceability and consistency of data, reduce errors that may be caused by manual operation, and enhance the reliability and stability of the system.

[0042] Specifically, the verification module includes: The first migration fluctuation calculation unit is used to calculate the standard deviation of all the real-time migration speeds within a preset verification period to form the first migration fluctuation value. The first fluctuation calculation unit is used to calculate the standard deviation of all the real-time first velocities within the preset verification time to form the first velocity fluctuation value. A completeness calculation unit is connected to the first migration fluctuation calculation unit and the first fluctuation calculation unit, respectively, and is used to calculate the completeness based on the migration fluctuation value and the first velocity fluctuation value. An accuracy calculation unit is used to verify the accuracy of the migrated data based on the mapping index and the migrated data, and to form an accuracy.

[0043] The preset verification duration refers to the time period set during the data migration process to calculate migration fluctuations and verify data integrity. It depends on the total amount of data to be migrated, the performance of the migration system, and the required verification accuracy. It is usually set between 2 hours and 3 days. The specific value is determined according to the scale of the system and the amount of data to be migrated. In this embodiment, it is set to 6 hours, which can effectively balance verification accuracy and system operating efficiency, and ensure the stability and efficiency of the data migration process.

[0044] In the verification module, the first migration fluctuation calculation unit calculates the standard deviation of all real-time migration speeds within a preset verification period to form a first migration fluctuation value, thereby assessing the fluctuation during the data migration process. The first fluctuation calculation unit then calculates the standard deviation of the first real-time speed to form a first speed fluctuation value, further understanding the amplitude of migration speed fluctuations. The integrity calculation unit combines the fluctuation values ​​of both to calculate the integrity of the data migration and determine its stability. The accuracy calculation unit verifies the accuracy of the data by comparing the mapped index with the migrated data, ensuring the consistency between the migrated data and the original data.

[0045] By calculating the fluctuations in migration speed and data rate, instability and potential problems during data migration can be effectively detected, ensuring that the migration process is not affected by speed fluctuations, thus preventing data loss or errors. Verifying completeness and accuracy ensures that the migrated data meets predetermined standards in terms of accuracy and integrity, thereby improving the reliability of the migrated data.

[0046] Specifically, the integrity calculation unit includes: The migration curve plotting subunit is used to plot the change curve of the first migration fluctuation value within the preset verification time, thereby forming a migration curve; The first curve drawing subunit is used to draw the change curve of the first speed fluctuation value within the preset verification time, forming the first curve; The integrity calculation subunit is used to calculate the cosine similarity between the migration curve and the first curve to form the integrity score.

[0047] First, the migration curve plotting subunit plots a migration curve based on the first migration fluctuation value within a preset verification period, demonstrating the fluctuation changes during the migration process. Second, the first curve plotting subunit plots the change curve of the first velocity fluctuation value, forming the first curve. Finally, the integrity calculation subunit calculates the cosine similarity between the migration curve and the first curve to determine the integrity of the data migration, evaluating the stability and consistency of the migration process.

[0048] By accurately plotting the fluctuation curves during the migration process and calculating similarity, the integrity and consistency of the migrated data can be effectively determined, ensuring that no data is lost or damaged during migration. Furthermore, using cosine similarity to quantify the matching degree of the fluctuation curves helps to quantify the stability and accuracy of the verification process, improving the reliability of data migration.

[0049] Specifically, the accuracy calculation unit includes: A matching record subunit is used to record the number of matches between each migrated data and its corresponding mapping index during the traversal of all the migrated data; An accuracy calculation subunit, connected to the recording subunit, is used to calculate the ratio of the number of matches to the total number of migrated data, thus forming the accuracy.

[0050] First, the matching record sub-unit traverses all migrated data and records the number of matches between each migrated data and its corresponding mapping index. Then, the accuracy calculation sub-unit calculates the ratio of the number of matches to the total number of migrated data to determine the accuracy of the migrated data, reflecting the correctness of the data during the migration process.

[0051] By recording the number of matches and calculating the ratio, the accuracy calculation unit can accurately assess the matching between the migrated data and the mapped index in the new PACS system, ensuring data accuracy during the migration process, improving the reliability of data migration, and ensuring that the final migrated data meets expectations.

[0052] Please continue reading. Figure 2 As shown, this is the logic diagram for determining whether to repair migrated data in the repair module of this embodiment; The repair module includes: The first deviation calculation unit is used to calculate the relative deviation between the preset completeness threshold and the completeness when the completeness is less than the preset completeness threshold, to form a completeness deviation, and to calculate the relative deviation between the preset accuracy threshold and the accuracy when the accuracy is less than the preset accuracy threshold, to form an accuracy deviation. An index calculation unit, connected to the deviation calculation unit, is used to perform a weighted summation calculation on the completeness deviation, the accuracy deviation, the preset completeness deviation weight, and the preset accuracy deviation weight to form a repair index. The second deviation calculation unit is connected to the index calculation unit and is used to calculate the relative deviation between the repair index and the preset repair threshold when the repair index is greater than the preset repair threshold, thereby forming a repair deviation. A duration recording unit, which is connected to the second deviation calculation unit, is used to record the duration when the repair deviation is less than a preset repair deviation threshold; A repair unit, connected to the duration recording unit, is used to repair the migrated data when the duration exceeds a preset repair duration, thereby forming the repaired migration data.

[0053] The preset integrity threshold is a standard value used to judge data integrity during the data repair process. It is usually set according to the characteristics of the data and system requirements, and is typically between 90% and 95%. In this embodiment, it is set to 92%, which can balance the requirements of data integrity and repair efficiency, ensuring the necessity of repair.

[0054] The preset accuracy threshold refers to the standard value used to judge the accuracy of data during the data repair process. It depends on the system's requirements for data accuracy and is usually set between 90% and 98%. In this embodiment, it is set to 95% to ensure that the repaired data has sufficient accuracy to meet the application's needs.

[0055] The preset completeness deviation weight refers to the weight used to measure the degree of influence of completeness deviation on the repair index when calculating the repair index. It usually depends on the priority of completeness and is typically set between 0.2 and 0.5. In this embodiment, it is set to 0.3, which can balance the influence of completeness and accuracy and avoid one factor from excessively affecting the repair result.

[0056] The preset accuracy deviation weight refers to the weight used to measure the impact of accuracy deviation on the repair index when calculating the repair index. It depends on the importance of accuracy to data repair and is usually set between 0.5 and 0.8. In this embodiment, it is set to 0.7, which can more strongly consider accuracy deviation and ensure accurate data repair.

[0057] The preset repair threshold is a standard value used to determine whether repair is needed during the repair process. It depends on the tolerance and repair strategy of the data, and is usually set between 1.0 and 1.5. In this embodiment, it is set to 1.2 to ensure that the repair operation can be initiated after the repair index reaches a certain standard, avoiding unnecessary repair operations.

[0058] The preset repair duration refers to the duration recorded by the system during the data repair process when the repair deviation is less than a preset repair deviation threshold. It is typically determined based on the complexity of the data migration, the system's response time, and the stability of the data, and is usually set between 10 and 40 minutes. In this embodiment, it is set to 30 minutes, which ensures stable data repair in most data migration scenarios while avoiding excessively long waiting times that could impact system efficiency.

[0059] First, the first deviation calculation unit calculates the deviations in completeness and accuracy based on preset thresholds. Next, the index calculation unit performs a weighted summation of the deviations and their respective weights to obtain the repair index. Then, the second deviation calculation unit calculates the repair deviation based on the deviation between the repair index and the preset repair threshold. The duration recording unit records the duration when the repair deviation is less than the threshold. Finally, the repair unit determines whether to perform data repair based on a comparison between the duration and the preset repair duration.

[0060] By weighting the deviations in completeness and accuracy, the repair module can dynamically adjust the repair strategy to ensure that potential problems are detected and repaired in a timely manner during data migration, thereby improving the completeness and accuracy of data migration and ensuring that the quality of migrated data meets the standards.

[0061] Please continue reading. Figure 3 As shown, it is the logic diagram for the adjustment module to adjust the preset repair threshold in this embodiment; The adjustment module includes: A monitoring unit is used to monitor the real-time second speed; The second fluctuation calculation unit is connected to the monitoring unit and is used to calculate the standard deviation of the real-time second speed within a preset adjustment period to form the second speed fluctuation value. The second migration fluctuation calculation unit is used to calculate the standard deviation of the real-time migration speed within the preset adjustment period to form the second migration fluctuation value. A synchronization calculation unit, which is connected to the second fluctuation calculation unit and the second migration fluctuation calculation unit respectively, is used to calculate the relative deviation between the second speed fluctuation value and the second migration fluctuation value to form a synchronization degree; An average value calculation unit, connected to the synchronization degree calculation unit, is used to calculate the average value of the real-time second speed within the preset adjustment time when the synchronization degree is less than a preset synchronization degree threshold, to form a second average speed, and to calculate the average value of the real-time migration speed within the preset adjustment time, to form a migration average speed. An adjustment unit, connected to the average value calculation unit, is used to reduce the preset repair threshold based on the relative deviation between the average migration speed and the second average speed and a preset adjustment coefficient when the average migration speed is greater than the second average speed, thereby forming the adjustment repair threshold; and to increase the preset repair threshold based on the relative deviation between the second average speed and the average migration speed when the average migration speed is less than the second average speed, thereby forming the adjustment repair threshold, wherein the absolute value of the relative deviation between the second average speed and the average migration speed is positively correlated with the adjustment repair threshold.

[0062] The preset adjustment duration refers to the time period used to calculate speed fluctuations. It depends on the duration of the data migration process and the complexity of the migration task. It is usually set between 2 hours and 2 days. In this embodiment, it is set to 4 hours, which can effectively capture changes in speed fluctuations during the migration process and make timely adjustments to avoid excessive migration speed fluctuations affecting data repair.

[0063] The preset synchronization threshold is a standard for judging the degree of synchronization between migration speed and repair speed. It depends on the system's requirements for synchronization accuracy and is usually set between 0.9 and 1.0. In this embodiment, it is set to 0.95, which can balance the speed synchronization requirements and the flexibility of the repair process, and ensure the response speed and accuracy when adjusting the repair threshold.

[0064] The preset adjustment coefficient is a parameter that adjusts the magnitude of the change in the repair threshold. It depends on the stability of the migration process and the tolerance for repair time. It is usually set between 0.1 and 0.5. In this embodiment, it is set to 0.3, which helps to adjust the repair threshold appropriately, avoid over-correction or slow response, and improve the overall migration and repair efficiency.

[0065] First, the second fluctuation calculation unit and the second migration fluctuation calculation unit calculate the standard deviation of the real-time second velocity and the real-time migration velocity within a preset adjustment period, respectively, to form the second velocity fluctuation value and the second migration fluctuation value. Next, the synchronization calculation unit calculates the relative deviation based on these two fluctuation values ​​to obtain the synchronization degree. Then, the average value calculation unit calculates the average value of the real-time second velocity and the migration velocity. Finally, the adjustment unit dynamically adjusts the repair threshold based on the difference in average values ​​and a preset adjustment coefficient.

[0066] By calculating speed fluctuations and synchronization in real time, the adjustment module can intelligently adjust the repair threshold according to changes in migration speed, ensuring that the repair process matches the migration speed, thereby optimizing the timeliness and accuracy of data repair and improving the system's adaptability at different migration stages.

[0067] Please continue reading. Figure 4 As shown, this is the logic diagram for the alarm module to determine when to issue an alarm in this embodiment; The alarm module includes: A comparison unit is used to compare the integrity consistency between the patient report data and the repair migration data at the end of the migration process; A count recording unit, connected to the comparison unit, is used to record the number of comparisons when the integrity consistency is greater than a preset consistency threshold. An alarm unit, connected to the comparison unit, is used to issue an alarm when the number of comparisons exceeds a preset comparison threshold.

[0068] The preset consistency threshold is set according to the consistency requirements during the data migration process. It depends on the required level of accuracy and is usually set between 90% and 99.99%. In this embodiment, it is set to 99.9% to ensure a high degree of consistency in the migrated data.

[0069] The preset comparison threshold is determined based on the cumulative reliability of the comparison count, and is usually set between 2 and 4 times. In this embodiment, it is set to 3 times to ensure that the consistency of data integrity is fully verified and to prevent missing alarms due to occasional low consistency.

[0070] The alarm module compares the integrity and consistency of patient report data and repaired migration data at the end of the migration process using a comparison unit. If the consistency is greater than a preset consistency threshold, the comparison count is recorded by the count recording unit. When the number of comparisons exceeds a preset comparison count threshold, the alarm unit triggers an alarm to alert the system administrator to the data integrity issue.

[0071] By automating comparison and monitoring, the integrity and consistency of the data migration process can be effectively monitored, potential problems can be detected in a timely manner and alarms can be triggered, ensuring the quality and reliability of data migration and improving system stability and data security.

[0072] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A data migration system for migrating and merging historical PACS data, characterized in that, include: The migration module is used to migrate patient report data from the original PACS system to the new PACS system, forming migrated data; A creation module, which is connected to the migration module, is used to create a mapping index between historical image data and migrated data in the new PACS system based on the storage address, patient identifier, examination time, and migrated data of historical image data extracted from the original PACS system; The acquisition module, which is connected to the migration module, is used to acquire the real-time migration speed of migrating patient report data from the original PACS system to the new PACS system and the real-time first speed of forming the migrated data. The verification module is connected to the migration module, the acquisition module, and the creation module respectively, and is used to verify the integrity of the migrated data based on the real-time migration speed and the real-time first speed to form a completeness, and to verify the accuracy of the migrated data based on the mapping index and the migrated data to form an accuracy. A repair module, which is connected to the verification module and the migration module respectively, is used to repair the migrated data according to the completeness, the accuracy and the preset repair threshold, to form repaired migration data; An adjustment module, connected to the repair module, is used to monitor the real-time second speed at which the repair migration data is generated, and to adjust the preset repair threshold based on the real-time second speed and the real-time migration speed, thereby forming an adjustment repair threshold. An alarm module, connected to the repair module, is used to issue alarms based on the patient report data and the repair migration data formed based on the adjusted repair threshold.

2. The data migration system for PACS historical data migration and fusion according to claim 1, characterized in that, The migration module includes: The field extraction unit is used to extract the patient identification field, examination time field, and examination type field from the patient report data; A format acquisition unit is used to acquire the data structure format of the new PACS system; A conversion unit, which is connected to the format acquisition unit and the extraction unit respectively, is used to convert the patient identification field, examination time field and examination type field into a storage format consistent with the data structure format, forming a conversion identifier, conversion time and conversion type; The migration unit, which is connected to the conversion unit, is used to store the converted patient identifier, converted examination time, and converted examination type into the database of the new PACS system through a database insertion operation, forming the migrated data.

3. The data migration system for PACS historical data migration and fusion according to claim 2, characterized in that, The creation module includes: An index generation unit is used to generate image index data in the database of the new PACS system based on the storage address, the patient identifier, and the examination time. An index mapping unit, connected to the index generation unit, is used to match the image index data and the migrated data according to the conversion identifier and the conversion time, and to establish an image report mapping relationship to form the mapping index.

4. The data migration system for PACS historical data migration and fusion according to claim 3, characterized in that, The index generation unit includes: A sub-unit is established to create an image index table based on the patient identifier and the examination time; A filling subunit, which is connected to the establishing subunit, is used to fill the storage address into the image index table to generate image index data.

5. The data migration system for PACS historical data migration and fusion according to claim 4, characterized in that, The verification module includes: The first migration fluctuation calculation unit is used to calculate the standard deviation of all the real-time migration speeds within a preset verification period to form the first migration fluctuation value. The first fluctuation calculation unit is used to calculate the standard deviation of all the real-time first velocities within the preset verification time to form the first velocity fluctuation value. A completeness calculation unit is connected to the first migration fluctuation calculation unit and the first fluctuation calculation unit, respectively, and is used to calculate the completeness based on the migration fluctuation value and the first velocity fluctuation value. An accuracy calculation unit is used to verify the accuracy of the migrated data based on the mapping index and the migrated data, and to form an accuracy.

6. The data migration system for PACS historical data migration and fusion according to claim 5, characterized in that, The integrity calculation unit includes: The migration curve plotting subunit is used to plot the change curve of the first migration fluctuation value within the preset verification time, thereby forming a migration curve; The first curve drawing subunit is used to draw the change curve of the first speed fluctuation value within the preset verification time, forming the first curve; The integrity calculation subunit is used to calculate the cosine similarity between the migration curve and the first curve to form the integrity score.

7. The data migration system for PACS historical data migration and fusion according to claim 5, characterized in that, The accuracy calculation unit includes: A matching record subunit is used to record the number of matches between each migrated data and its corresponding mapping index during the traversal of all the migrated data; An accuracy calculation subunit, connected to the recording subunit, is used to calculate the ratio of the number of matches to the total number of migrated data to form the accuracy.

8. The data migration system for PACS historical data migration and fusion according to claim 7, characterized in that, The repair module includes: The first deviation calculation unit is used to calculate the relative deviation between the preset completeness threshold and the completeness when the completeness is less than the preset completeness threshold, to form a completeness deviation, and to calculate the relative deviation between the preset accuracy threshold and the accuracy when the accuracy is less than the preset accuracy threshold, to form an accuracy deviation. An index calculation unit, connected to the deviation calculation unit, is used to perform a weighted summation calculation on the completeness deviation, the accuracy deviation, the preset completeness deviation weight, and the preset accuracy deviation weight to form a repair index. The second deviation calculation unit is connected to the index calculation unit and is used to calculate the relative deviation between the repair index and the preset repair threshold when the repair index is greater than the preset repair threshold, thereby forming a repair deviation. A duration recording unit, which is connected to the second deviation calculation unit, is used to record the duration when the repair deviation is less than a preset repair deviation threshold; A repair unit, connected to the duration recording unit, is used to repair the migrated data when the duration exceeds a preset repair duration, thereby forming the repaired migration data.

9. The data migration system for PACS historical data migration and fusion according to claim 8, characterized in that, The adjustment module includes: A monitoring unit is used to monitor the real-time second speed; The second fluctuation calculation unit is connected to the monitoring unit and is used to calculate the standard deviation of the real-time second speed within a preset adjustment period to form the second speed fluctuation value. The second migration fluctuation calculation unit is used to calculate the standard deviation of the real-time migration speed within the preset adjustment period to form the second migration fluctuation value. A synchronization calculation unit, which is connected to the second fluctuation calculation unit and the second migration fluctuation calculation unit respectively, is used to calculate the relative deviation between the second speed fluctuation value and the second migration fluctuation value to form a synchronization degree; An average value calculation unit, connected to the synchronization degree calculation unit, is used to calculate the average value of the real-time second speed within the preset adjustment time when the synchronization degree is less than a preset synchronization degree threshold, to form a second average speed, and to calculate the average value of the real-time migration speed within the preset adjustment time, to form a migration average speed. An adjustment unit, connected to the average value calculation unit, is used to reduce the preset repair threshold based on the relative deviation between the average migration speed and the second average speed and a preset adjustment coefficient when the average migration speed is greater than the second average speed, thereby forming the adjustment repair threshold; and to increase the preset repair threshold based on the relative deviation between the second average speed and the average migration speed when the average migration speed is less than the second average speed, thereby forming the adjustment repair threshold.

10. The data migration system for PACS historical data migration and fusion according to claim 9, characterized in that, The alarm module includes: A comparison unit is used to compare the integrity consistency between the patient report data and the repair migration data at the end of the migration process; A count recording unit, connected to the comparison unit, is used to record the number of comparisons when the integrity consistency is greater than a preset consistency threshold. An alarm unit, connected to the comparison unit, is used to issue an alarm when the number of comparisons exceeds a preset comparison threshold.

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