Iconography data analysis method and system for pulmonary arterial hypertension intervention

Abstract

The invention discloses an imaging data analysis method and system for pulmonary arterial hypertension intervention, and relates to the technical field of imaging data analysis of pulmonary arterial hypertension intervention. The imaging data analysis method for pulmonary arterial hypertension intervention comprises the following steps of data processing, transmission evaluation, data verification and grading. According to the method, the original data of the computed tomography pulmonary arteriography equipment is collected, preprocessed and then transmitted through the main network, and evaluation is performed according to the data transmission condition of the main network to obtain the main network transmission evaluation index; hash operation and data verification are carried out on the received original data to obtain a data integrity evaluation index and grade division is carried out, so that the effect of improving the accuracy of imaging data analysis of pulmonary arterial hypertension intervention is achieved; the problem that in the prior art, data transmission is not accurate in imaging data analysis of pulmonary arterial hypertension intervention is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of imaging data analysis for pulmonary hypertension intervention, and in particular to an imaging data analysis method and system for pulmonary hypertension intervention. Background Art

[0002] With the continuous development of medical imaging technology and the improvement of computer processing capabilities, the diagnosis and treatment strategies in the field of pulmonary hypertension are also constantly updated. The imaging data analysis system can assist clinical decision-making to a great extent and improve the diagnosis and treatment effects of pulmonary hypertension. For the diagnosis and treatment of patients with pulmonary hypertension, accurate imaging data analysis is required to evaluate the status of the pulmonary artery and heart and guide interventional treatment. The accurate analysis and efficient transmission of imaging data are of great significance for diagnosis, treatment planning and follow-up.

[0003] Existing imaging data analysis methods and systems for disease treatment integrate multimodal imaging technology, combine advanced data analysis algorithms to build and train imaging analysis models, collect a large amount of labeled clinical imaging data, and conduct model training and verification, thus realizing the intelligence and automation of imaging data analysis methods and systems.

[0004] For example, the invention patent with announcement number: CN109522974B discloses a method for selecting a lesion level for improving the positive rate of puncture biopsy, including: a data acquisition module, an image scanning module, an image processing module, a data analysis module and a storage module, and the selection method is as follows: collecting training data; outlining the sample lesion level ROI according to the training data; establishing a positive rate prediction model; obtaining prediction parameters according to the positive rate prediction model; fitting the obtained prediction parameters to obtain final prediction data; outlining the patient lesion level ROI according to the final prediction data and obtaining patient characteristics; obtaining a positive rate prediction value according to the patient lesion level ROI and patient characteristics; and selecting the lesion level ROI.

[0005] For example, a patent application with publication number: CN115410006A discloses a method for correlation analysis of ultra-high-dimensional feature data of breast ultrasound imaging genomics, including: storing massive ultra-high-dimensional breast ultrasound image feature data in a distributed file system; calculating the sum and square sum of each feature data in the cluster node; using the data to estimate the correlation between each feature and output it; if it cannot be estimated, calculating its mean and standard deviation, and continuing to perform distributed computing; each node calculates the correlation coefficient between the features that cannot be estimated based on the mean and standard deviation; summarizing the results and calculating the mean to obtain the correlation between the overall features.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the prior art, since medical imaging data contains a large amount of sensitive information, the data is easily tampered with or damaged during transmission, and even data transmission failure may occur. There is a problem of inaccurate data transmission in the imaging data analysis of pulmonary hypertension intervention. Summary of the invention

[0008] The embodiments of the present application solve the problem of inaccurate data transmission in the imaging data analysis of pulmonary hypertension intervention in the prior art by providing an imaging data analysis method and system for pulmonary hypertension intervention, thereby improving the accuracy of imaging data analysis of pulmonary hypertension intervention.

[0009] The embodiment of the present application provides an imaging data analysis method for pulmonary hypertension intervention, comprising the following steps: S1, collecting raw data from a computed tomography pulmonary angiography device, and transmitting the raw data to a pulmonary hypertension intervention imaging monitoring platform through a main network after preprocessing the raw data, wherein the raw data is used to describe the data generated during the operation of the computed tomography pulmonary angiography device; S2, obtaining the main network transmission evaluation data of the main network within a preset time interval, and evaluating the data transmission status of the main network within the preset time interval according to the main network transmission evaluation data to obtain a main network transmission evaluation index; if the main network transmission evaluation index is within a preset threshold range, continue to transmit; otherwise, switch to the backup network for transmission, and according to A comprehensive evaluation is performed on the main network transmission evaluation index and the data transmission situation to obtain a comprehensive evaluation result, wherein the main network transmission evaluation data includes data packet transmission data, sent data packet data, lost data packet data and bandwidth utilization data, and the main network transmission evaluation index is used to describe the transmission efficiency of the main network, and the comprehensive evaluation result is used to visualize the data transmission situation; S3, hash operation and data verification are performed on the original data received by the pulmonary hypertension interventional imaging monitoring platform to obtain a data integrity evaluation index, and the data integrity evaluation index is used to comprehensively quantify the data integrity situation detected by hash verification; S4, grading is performed according to the data integrity evaluation index to obtain a grading result and feedback is given in the form of a chart.

[0010] Furthermore, the specific steps for collecting the original data of the computed tomography pulmonary angiography device are as follows: obtaining the pulmonary artery angiography image and the corresponding image data generated by the computed tomography pulmonary angiography device, the image data including the image unique identifier, image resolution, scanning mode and scanning parameters, the scanning parameters including current, voltage and rotation speed; obtaining the type, dosage and injection time of the contrast agent used by the computed tomography pulmonary angiography device during the scanning process.

[0011] Furthermore, the specific steps of preprocessing the original data and transmitting it to the pulmonary hypertension interventional imaging supervision platform through the main network are as follows: perform SHA-256 hash operation on the collected original data to generate a hash value, perform BZ IP2 lossless compression on the generated hash value and the original data, and simultaneously perform AES symmetric encryption on the compressed hash value and the original data to obtain an encrypted hash value; transmit the encrypted hash value and the original data to the pulmonary hypertension interventional imaging supervision platform through the HTTPS protocol of the main network.

[0012] Furthermore, a specific method for obtaining the transmission evaluation index of the main network is as follows: obtaining data packet transmission data according to the data transmission situation of the main network within a preset time interval, the data packet transmission data including first transmission data and second transmission data, the first transmission data being used to describe the transmission situation of the data packet of the main network within the preset time interval under a preset normal state, the first transmission data including a first sending time and a first receiving time, the second transmission data being used to describe the transmission situation of the data packet of the main network within the preset time interval under a congested state, the second transmission data including a second sending time and a second receiving time; obtaining sent data packet data and lost data packet data according to the data packet sending situation and loss situation of the main network within the preset time interval, and obtaining bandwidth utilization data, the sent data packet data including first sent data packet data and second sent data packet data, the first sent data packet data being used to describe the total number of data packets sent by the main network within the preset time interval under a preset normal state, the second sent data packet data being used to describe the total number of data packets sent by the main network within the preset time interval under a congested state, the lost data packet data being used to describe the total number of data packets sent by the main network within the preset time interval under a congested state, The lost data packet data includes first lost data packet data and second lost data packet data, the first lost data packet data is used to describe the total number of data packets lost by the primary network within a preset time interval under a preset normal state, and the second lost data packet data is used to describe the total number of data packets lost by the primary network within a preset time interval under a congested state, the bandwidth utilization data includes first bandwidth utilization and second bandwidth utilization, the first bandwidth utilization is used to describe the flow information of data packets transmitted by the primary network within a preset time interval under a preset normal state, and the second bandwidth utilization is used to describe the flow information of data packets transmitted by the primary network within a preset time interval under a congested state; a first transmission delay is obtained according to a first receiving time and a first sending time, a second transmission delay is obtained according to a second receiving time and a second sending time, and a primary network transmission evaluation index is obtained by combining the first transmission delay reference deviation, the second transmission delay reference deviation, the first bandwidth utilization reference deviation, and the second bandwidth utilization reference deviation with evaluation weights obtained from a preset database, the evaluation weights include an average transmission delay weight, a packet loss rate weight, and a bandwidth utilization weight.

[0013] Furthermore, the main network transmission evaluation index is calculated using the following formula:

[0014]

[0015] In the formula, I represents the primary network transmission evaluation index, M represents the first transmission delay, m represents the second transmission delay, ΔM represents the first transmission delay reference deviation, Δm represents the second transmission delay reference deviation, h represents the second lost data packet data, g represents the second sent data packet data, H represents the first lost data packet data, G represents the first sent data packet data, r represents the second bandwidth utilization, Δr represents the second bandwidth utilization reference deviation, R represents the first bandwidth utilization, ΔR represents the first bandwidth utilization reference deviation, c1 represents the average transmission delay weight, c2 represents the packet loss rate weight, and c3 represents the bandwidth utilization weight.

[0016] Furthermore, the specific steps of performing a comprehensive evaluation based on the main network transmission evaluation index and data transmission conditions to obtain a comprehensive evaluation result are as follows: visually displaying the original data in the transmission process through Grafana, and obtaining the number of times the transmission is switched to the backup network according to the main network transmission evaluation index; performing a comprehensive evaluation based on the main network transmission evaluation index and the number of times the transmission is switched to the backup network to obtain a comprehensive evaluation result, if the number of times the transmission is switched to the backup network exceeds a preset number, the main network transmission evaluation index and the original data are fed back and recorded as unqualified for the main network transmission; otherwise, the main network transmission evaluation index and the original data are uploaded to the database and recorded as qualified for the main network transmission.

[0017] Furthermore, a specific method for obtaining the data integrity assessment index is as follows: re-performing a SHA-256 hash operation on the data packet in the original data received by the pulmonary arterial hypertension interventional imaging monitoring platform to obtain a verification hash value and compare it with the encrypted hash value; if the recalculated verification hash value is equal to the encrypted hash value, it is recorded as a matching data packet; the data integrity assessment index is obtained by the number of matching data packets in the total data packets sent and the hash algorithm strength weight obtained from a preset database.

[0018] Furthermore, the data integrity evaluation index is calculated using the following formula:

[0019]

[0020] Where J represents the data integrity evaluation index, K represents the total number of data packets sent during the primary network transmission process, L represents the number of matching data packets, β represents the hash algorithm strength weight, and w represents the hash collision probability.

[0021] Furthermore, the specific process of performing grading according to the data integrity evaluation index to obtain a grading result is as follows: obtaining the data integrity evaluation index and the corresponding preset threshold, performing grading according to the data integrity evaluation index to obtain a grading result, and drawing the grading result into a grading result chart, wherein the grading result is used to visualize the data integrity evaluation index, and the grading result chart includes a stacked column chart, a pie chart and a bar chart, wherein the stacked column chart is used to describe the data level distribution in different groups, the pie chart is used to describe the proportion of data of each level, and the bar chart is used to compare the amount of data of different levels; the method for obtaining the grading result is: if the data integrity evaluation index is lower than the preset threshold, it is recorded as a data missing level; if the data integrity evaluation index is equal to the preset threshold, it is recorded as a normal data level; if the data integrity evaluation index is higher than the preset threshold, it is recorded as a good data level.

[0022] The embodiment of the present application provides an imaging data analysis system for pulmonary hypertension intervention, including: a data processing module, a transmission evaluation module, a data verification module, and a level classification module; the data processing module is used to collect raw data from a computed tomography pulmonary angiography device, and transmit the raw data to a pulmonary hypertension intervention imaging supervision platform through a main network after preprocessing the raw data, wherein the raw data is used to describe the data generated during the operation of the computed tomography pulmonary angiography device; the transmission evaluation module is used to obtain a main network transmission evaluation index by evaluating the data transmission status of the main network within a preset time interval, and if the main network transmission evaluation index is within a preset threshold range, the transmission continues. transmission, otherwise, switch to the backup network transmission, and perform a comprehensive evaluation based on the main network transmission evaluation index and the data transmission situation to obtain a comprehensive evaluation result, wherein the main network transmission evaluation index is used to describe the transmission efficiency of the main network, and the comprehensive evaluation result is used to visualize the data transmission situation; the data verification module is used to perform hash operation and data verification on the original data received by the pulmonary hypertension interventional imaging supervision platform to obtain a data integrity evaluation index, and the data integrity evaluation index is used to comprehensively quantify the data integrity situation detected by hash verification; the grading module is used to perform grading based on the data integrity evaluation index to obtain a grading result and provide feedback in the form of a chart.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0024] 1. The original data of the computed tomography pulmonary angiography device is collected and preprocessed, and then transmitted to the pulmonary hypertension interventional imaging supervision platform through the main network. Then, the data transmission of the main network is evaluated to obtain the main network transmission evaluation index. Then, the received original data is hashed and verified to obtain the data integrity evaluation index and graded to obtain the graded results, thereby improving the evaluation of data transmission accuracy in the imaging data analysis of pulmonary hypertension intervention, and then achieving the improvement of the accuracy of data analysis in the imaging data analysis of pulmonary hypertension intervention, and effectively solving the problem of inaccurate data transmission in the imaging data analysis of pulmonary hypertension intervention in the prior art.

[0025] 2. The main network transmission evaluation index is obtained by evaluating the data transmission status of the main network within a preset time interval. If the main network transmission evaluation index is within the preset threshold range, the transmission continues; otherwise, the transmission is switched to the backup network, thereby improving the stability of the data transmission process and achieving a more accurate evaluation of the data transmission efficiency.

[0026] 3. The data integrity evaluation index is used to perform grading to obtain the grading results, and the grading results are plotted into a grading result chart, thereby realizing the visualization of the degree of data transmission integrity, and further realizing a more accurate evaluation of the degree of data transmission integrity. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A flow chart of the imaging data analysis method for pulmonary hypertension intervention provided in an embodiment of the present application;

[0028] Figure 2 A graph showing changes in the data integrity assessment index provided in an embodiment of the present application;

[0029] Figure 3 A schematic diagram of the structure of an imaging data analysis system for pulmonary hypertension intervention provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] The embodiments of the present application solve the problem of inaccurate data transmission in the imaging data analysis of pulmonary hypertension intervention in the prior art by providing an imaging data analysis method and system for pulmonary hypertension intervention. The original data of the computed tomography pulmonary angiography device is collected, and the original data is pre-processed and transmitted to the pulmonary hypertension intervention imaging monitoring platform through the main network. Then, the data transmission status of the main network within a preset time interval is evaluated to obtain the main network transmission evaluation index. Subsequently, hash operations and data verification are performed on the original data received by the pulmonary hypertension intervention imaging monitoring platform to obtain the data integrity evaluation index. Finally, the data integrity evaluation index is used to perform grading to obtain the grading result and the grading result is fed back in the form of a chart, thereby improving the accuracy of the imaging data analysis of pulmonary hypertension intervention.

[0031] The technical solution in the embodiment of the present application is to solve the problem of inaccurate data transmission in the imaging data analysis of pulmonary hypertension intervention mentioned above. The overall idea is as follows:

[0032] The original data of the computed tomography pulmonary angiography device is collected, and after hashing the original data, the encrypted hash value and the original data are transmitted to the pulmonary hypertension interventional imaging supervision platform through the main network. The data transmission of the main network is evaluated to obtain the main network transmission evaluation index. If it exceeds the preset threshold range, it is switched to the backup network. Then, the received original data is hashed and verified to obtain the data integrity evaluation index and grade it, thereby achieving the effect of improving the accuracy of imaging data analysis for pulmonary hypertension intervention.

[0033] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0034] like Figure 1As shown, it is a flow chart of the imaging data analysis method for pulmonary hypertension intervention provided by an embodiment of the present application, and the method includes the following steps: S1, collecting raw data of a computed tomography pulmonary angiography device, and transmitting the raw data to a pulmonary hypertension intervention imaging monitoring platform through a main network after preprocessing the raw data, wherein the raw data is used to describe the data generated during the operation of the computed tomography pulmonary angiography device; S2, obtaining the main network transmission evaluation data of the main network within a preset time interval, and evaluating the data transmission status of the main network within the preset time interval according to the main network transmission evaluation data to obtain a main network transmission evaluation index; if the main network transmission evaluation index is within a preset threshold range, continue to transmit, otherwise, switch to the backup Network transmission, and conduct a comprehensive evaluation based on the main network transmission evaluation index and data transmission status to obtain a comprehensive evaluation result. The main network transmission evaluation data includes data packet transmission data, sent data packet data, lost data packet data and bandwidth utilization data. The main network transmission evaluation index is used to describe the transmission efficiency of the main network, and the comprehensive evaluation result is used to visualize the data transmission status; S3, perform hash operation and data verification on the original data received by the pulmonary arterial hypertension interventional imaging monitoring platform to obtain a data integrity evaluation index. The data integrity evaluation index is used to comprehensively quantify the data integrity detected by hash verification; S4, perform grading based on the data integrity evaluation index to obtain the grading result and provide feedback in the form of a chart.

[0035] In this embodiment, since medical imaging data contains a large amount of sensitive information, the data is prone to being tampered with or damaged during transmission. The original data can be initially protected through preprocessing. Preprocessing means generating a data check code by using a SHA-256 hash operation on the original data to obtain an encrypted hash value; when the amount of data is large, the data is divided into a preset number of data packets to obtain the total number of data packets sent, and a hash function is used independently for each data packet to generate its own hash value; then the hash values ​​obtained after the hash function calculation of each data packet are connected in series or aggregated to form an encrypted hash value of the overall data, and the encrypted hash value is attached to the transmission or storage of the original data; thereby achieving improved accuracy in imaging data analysis for pulmonary hypertension intervention.

[0036] Furthermore, the specific steps for collecting the original data of the computed tomography pulmonary angiography device are as follows: obtain the pulmonary angiography image and the corresponding image data generated by the computed tomography pulmonary angiography device, the image data including the image unique identifier, image resolution, scanning mode and scanning parameters, and the scanning parameters including current, voltage and rotation speed; obtain the type, dosage and injection time of the contrast agent used by the computed tomography pulmonary angiography device during the scanning process.

[0037] In this embodiment, a pulmonary artery angiography image generated by a computed tomography pulmonary artery angiography device and corresponding image data are obtained, the pulmonary artery angiography image generated by the computed tomography pulmonary artery angiography device is stored in a DICOM (Digital Imaging and Communications in Medicine) format, and a DICOM viewer or a dedicated software tool, such as OsiriX, RadiAnt, 3D Slicer, etc., is used to view and extract image data in the DICOM file, wherein the image unique identifier is used to uniquely identify each image, the image resolution is used to describe the number of pixels and clarity of the image, and the scanning mode is a specific scanning mode used by a specified scanning device, such as spiral scanning and layer-by-layer scanning; the current of the scanning parameter refers to the setting of the X-ray tube current, which is used to describe the quality and radiation dose of imaging, the voltage of the scanning parameter refers to the setting of the X-ray tube voltage, which is used to describe the contrast and energy distribution of imaging, and the rotation speed of the scanning parameter refers to the speed of rotation of the scanning device, which is used to describe the time and quality of image reconstruction; the concretization of imaging data for pulmonary hypertension intervention is achieved.

[0038] Furthermore, the specific steps for preprocessing the original data and transmitting it to the pulmonary hypertension interventional imaging supervision platform through the main network are as follows: perform SHA-256 hash operation on the collected original data to generate a hash value, perform BZIP2 lossless compression on the generated hash value and the original data, and simultaneously perform AES symmetric encryption on the compressed hash value and the original data to obtain an encrypted hash value; transmit the encrypted hash value and the original data to the pulmonary hypertension interventional imaging supervision platform through the HTTPS protocol of the main network.

[0039] In this embodiment, the generated hash value and the original data are subjected to BZIP2 lossless compression. First, the input data is subjected to Burrows-Wheeler transformation, and the original data is reordered so that similar bytes are adjacent. Specifically, all cyclic shifts of the input string can be generated, and all the generated cyclic shifts are sorted in lexicographic order. The last column of characters is extracted from the sorted cyclic shifts to form a new string. Then, Move-To-Front encoding is applied to the transformed data, and the encoded data is encoded again using Huffman encoding. Finally, bit operation processing is performed on the Huffman encoded data. The compressed hash value and the original data are encrypted after generating the round keys required for multi-round encryption according to the selected key length (128 bits, 192 bits or 256 bits). During the transmission process, a secure connection is established using the HyperText TransferProtocol Secure protocol. Improvement of data quality during transmission is achieved.

[0040] Furthermore, a specific method for obtaining the transmission evaluation index of the main network is as follows: data packet transmission data is obtained according to the data transmission situation of the main network within a preset time interval, the data packet transmission data includes first transmission data and second transmission data, the first transmission data is used to describe the transmission situation of the data packet of the main network within the preset time interval under a preset normal state, the first transmission data includes a first sending time and a first receiving time, the second transmission data is used to describe the transmission situation of the data packet of the main network within the preset time interval under a congested state, the second transmission data includes a second sending time and a second receiving time; according to the data packet sending situation and loss situation of the main network within the preset time interval, the sent data packet data and the lost data packet data are obtained, and the bandwidth utilization data is obtained, the sent data packet data includes first sent data packet data and second sent data packet data, the first sent data packet data is used to describe the total number of data packets sent by the main network within the preset time interval under a preset normal state, the second sent data packet data is used to describe the total number of data packets sent by the main network within the preset time interval under a congested state, and the number of lost data packets is The data includes first lost data packet data and second lost data packet data, the first lost data packet data is used to describe the total number of data packets lost by the main network in a preset time interval under a preset normal state, and the second lost data packet data is used to describe the total number of data packets lost by the main network in a preset time interval under a congested state, and the bandwidth utilization data includes first bandwidth utilization and second bandwidth utilization, the first bandwidth utilization is used to describe the flow information of data packets transmitted by the main network in a preset time interval under a preset normal state, and the second bandwidth utilization is used to describe the flow information of data packets transmitted by the main network in a preset time interval under a congested state; a first transmission delay is obtained according to the first receiving time and the first sending time, and a second transmission delay is obtained according to the second receiving time and the second sending time, and a main network transmission evaluation index is obtained by combining the first transmission delay reference deviation, the second transmission delay reference deviation, the first bandwidth utilization reference deviation and the second bandwidth utilization reference deviation with evaluation weights obtained from a preset database, and the evaluation weights include average transmission delay weight, packet loss rate weight and bandwidth utilization weight.

[0041] In this embodiment, Nagi os is used to obtain the data packet sending and loss conditions within a preset time interval to obtain the sending data packet data and the lost data packet data, and the Wi reshark network traffic monitoring tool is used to obtain the bandwidth utilization data of the main network within the preset time interval; the first transmission delay is the difference between the first receiving time and the first sending time, and the second transmission delay is the difference between the second receiving time and the second sending time; wherein, the average transmission delay weight is used to describe the influence of the average transmission delay on the main network transmission evaluation index, specifically, the average transmission delay weight is obtained from a preset database, and in a specific embodiment, a fitting curve is obtained by the relationship between the network load, the corresponding network working time, the data packet size, the link bandwidth and the main network transmission evaluation index in a historical time period, and the average transmission delay weight corresponding to the real-time transmitted data packet is obtained according to the fitting curve; the packet loss rate weight is used to describe the influence of the packet loss rate on the main network transmission evaluation index, Specifically, the packet loss rate weight is obtained from a preset database. In a specific embodiment, a fitting curve is obtained by the relationship between the network load, the corresponding network working time, the link quality, the network delay and the main network transmission evaluation index in a historical time period, and the packet loss rate weight corresponding to the real-time transmitted data packet is obtained according to the fitting curve; the bandwidth utilization weight is used to describe the influence of bandwidth utilization on the main network transmission evaluation index. Specifically, the bandwidth utilization weight is obtained from a preset database. In a specific embodiment, a fitting curve is obtained by the relationship between the network load, the data packet size, the network traffic intensity, the network delay and the main network transmission evaluation index in a historical time period, and the bandwidth utilization weight corresponding to the real-time transmitted data packet is obtained according to the fitting curve; a more accurate evaluation of the main network transmission is achieved.

[0042] Furthermore, the main network transmission evaluation index is calculated using the following formula:

[0043]

[0044] In the formula, I represents the primary network transmission evaluation index, M represents the first transmission delay, m represents the second transmission delay, ΔM represents the first transmission delay reference deviation, Δm represents the second transmission delay reference deviation, h represents the second lost data packet data, g represents the second sent data packet data, H represents the first lost data packet data, G represents the first sent data packet data, r represents the second bandwidth utilization, Δr represents the second bandwidth utilization reference deviation, R represents the first bandwidth utilization, ΔR represents the first bandwidth utilization reference deviation, c1 represents the average transmission delay weight, c2 represents the packet loss rate weight, and c3 represents the bandwidth utilization weight.

[0045] In this embodiment, assuming that the average transmission delay weight, packet loss rate weight, and bandwidth utilization weight are all 1, the second lost data packet data is 5 bytes, the second sent data packet data is 100 bytes, the first lost data packet data is 4 bytes, and the first sent data packet data is 100 bytes, the primary network transmission evaluation index can be calculated by the above method, and the change statistics of the primary network transmission evaluation index are shown in Table 1:

[0046] Table 1 Statistics of changes in the main network transmission evaluation index

[0047]

[0048]

[0049] The main network transmission evaluation index can be used to quantify the transmission efficiency of the main network. A main network transmission evaluation index within the preset threshold range indicates that the transmission of the main network is relatively good. A main network transmission evaluation index outside the range indicates that there are abnormalities in the transmission process of the main network, which requires further inspection or switching to the backup network transmission. The preset threshold range is set by professionals according to standards in the field, realizing the numerical evaluation of the main network transmission.

[0050] Furthermore, the specific steps for conducting a comprehensive evaluation based on the main network transmission evaluation index and data transmission to obtain a comprehensive evaluation result are as follows: using Grafana to visualize the original data in the transmission process, and obtaining the number of times the transmission is switched to the backup network according to the main network transmission evaluation index; conducting a comprehensive evaluation based on the main network transmission evaluation index and the number of times the transmission is switched to the backup network to obtain a comprehensive evaluation result. If the number of times the transmission is switched to the backup network exceeds a preset number, the main network transmission evaluation index and the original data are fed back and recorded as unqualified for the main network transmission; otherwise, the main network transmission evaluation index and the original data are uploaded to the database and recorded as qualified for the main network transmission.

[0051] In this embodiment, a time series graph is created through Grafana to visualize the original data. Specifically, by adding the original data as a data source, a dynamic and interactive dashboard is created for data visualization analysis. In addition, it can be used in conjunction with Prometheus for monitoring and alarming. When the number of switches to the backup network exceeds the preset number, feedback will be given. The original data and the main network transmission evaluation index and the number of switches to the backup network transmission are stored. The specific storage methods include relational databases and cloud storage. The visualization of the results of the main network transmission is achieved.

[0052] Furthermore, a specific method for obtaining the data integrity assessment index is as follows: re-performing SHA-256 hash operations on the data packets in the original data received by the pulmonary hypertension interventional imaging monitoring platform to obtain a verification hash value and compare it with the encrypted hash value; if the recalculated verification hash value is equal to the encrypted hash value, it is recorded as a matching data packet; the data integrity assessment index is obtained by the number of matching data packets in the total number of data packets sent and the hash algorithm strength weight obtained from the preset database.

[0053] In this embodiment, the SHA-256 hash operation is re-performed on the data packet in the original data received by the pulmonary arterial hypertension interventional imaging monitoring platform, and the content of the data packet is converted into a 256-bit hash value to obtain a verification hash value. If the verification hash value is equal to the encrypted hash value, it indicates that the data packet has not been tampered with or damaged during transmission; the hash algorithm strength weight is used to describe the degree of influence of the hash algorithm strength on the data integrity evaluation index. Specifically, the hash algorithm strength weight is obtained from a preset database. In a specific embodiment, a fitting curve is obtained by the relationship between the hash algorithm's anti-second pre-image attack capability, pre-image attack capability, time complexity, and space complexity of the hash algorithm and the data integrity evaluation index in historical time, and the hash algorithm strength weight corresponding to the input hash algorithm's anti-second pre-image attack capability, pre-image attack capability, time complexity, and space complexity is obtained according to the fitting curve, thereby achieving a more accurate evaluation of data integrity.

[0054] Furthermore, the data integrity evaluation index is calculated using the following formula:

[0055]

[0056] Where J represents the data integrity evaluation index, K represents the total number of data packets sent during the primary network transmission process, L represents the number of matching data packets, β represents the hash algorithm strength weight, and w represents the hash collision probability.

[0057] In this embodiment, the hash collision probability refers to the probability that different inputs may produce the same output (collision) under a specific hash function. When the number of packets is known, the hash collision probability can be recorded as a constant (w = K 2 / 2 256 ),like Figure 2As shown, it is a data integrity evaluation index variation diagram provided in an embodiment of the present application. When the hash algorithm strength weight is set to 1, a comprehensive analysis shows that there is a correlation between the number of matching data packets in the data integrity evaluation index and the total number of data packets sent during the main network transmission. Since w is proportional to the square of K and divided by a large constant, the value of w is very small. As K increases, the value of w also increases, but remains within a very small range; as the total number of data packets sent and the number of matching data packets increase during the main network transmission, the data integrity evaluation index will gradually increase, and when the total number of data packets sent is constant, as the number of matching data packets increases, the data integrity evaluation index will also gradually increase. Therefore, by establishing a mathematical form for precise analysis, the digitization of data integrity evaluation is achieved.

[0058] Furthermore, the specific process of obtaining the grading result by grading according to the data integrity assessment index is as follows: obtain the data integrity assessment index and the corresponding preset threshold, perform grading according to the data integrity assessment index to obtain the grading result, and draw the grading result into a grading result chart, the grading result is used to visualize the data integrity assessment index, the grading result chart includes stacked column chart, pie chart and bar chart, the stacked column chart is used to describe the data level distribution in different groups, the pie chart is used to describe the proportion of data of each level, and the bar chart is used to compare the amount of data of different levels; the method for obtaining the grading result is: if the data integrity assessment index is lower than the preset threshold, it is recorded as the data missing level; if the data integrity assessment index is equal to the preset threshold, it is recorded as the data normal level; if the data integrity assessment index is higher than the preset threshold, it is recorded as the data good level.

[0059] In this embodiment, the preset threshold is set by professionals according to the standards in the field; the stacked column chart is used to describe the distribution of data levels in different groups, the pie chart is used to describe the proportion of data at each level, and the bar chart is used to compare the amount of data at different levels; software tools (such as the Matplotlib library in Python) are used to draw stacked column charts, pie charts and bar charts, wherein each column in the stacked column chart represents a group, the height of the column represents the number of each level in the group, and the stacking effect shows the proportion of each level in the total; each sector in the pie chart represents a level, and its area or angle represents the proportion of the level in the total; each bar in the bar chart represents a level, and the length of the bar represents the amount of data at the level, and the height of the bar can be used to quickly compare the quantity differences between the levels; the level visualization of data integrity assessment is achieved.

[0060] like Figure 3As shown, it is a structural schematic diagram of the imaging data analysis system for pulmonary hypertension intervention provided in an embodiment of the present application. The imaging data analysis system for pulmonary hypertension intervention provided in an embodiment of the present application includes: a data processing module, a transmission evaluation module, a data verification module, and a classification module; wherein the data processing module is used to collect raw data of a computed tomography pulmonary angiography device, and transmit the raw data to the pulmonary hypertension intervention imaging supervision platform through a main network after pre-processing the raw data, and the raw data is used to describe the data generated during the operation of the computed tomography pulmonary angiography device; the transmission evaluation module is used to obtain a main network transmission evaluation index by evaluating the data transmission status of the main network within a preset time interval, if If the main network transmission evaluation index is within the preset threshold range, transmission will continue; otherwise, transmission will be switched to the backup network, and a comprehensive evaluation will be performed based on the main network transmission evaluation index and data transmission status to obtain a comprehensive evaluation result. The main network transmission evaluation index is used to describe the transmission efficiency of the main network, and the comprehensive evaluation result is used to visualize the data transmission status; the data verification module is used to perform hash operations and data verification on the original data received by the pulmonary hypertension interventional imaging monitoring platform to obtain a data integrity evaluation index, and the data integrity evaluation index is used to comprehensively quantify the data integrity status detected by hash verification; the grading module is used to perform grading based on the data integrity evaluation index to obtain the grading result and provide feedback in the form of a chart.

[0061] In this embodiment, the data processing module includes a data acquisition unit, a preprocessing unit and a main network transmission unit to meet the needs of transmission and subsequent processing; the transmission evaluation module includes a backup network switching unit and a comprehensive evaluation unit to ensure the continuity of the data transmission process; the data verification module includes a hash operation unit, a data verification unit and a data integrity evaluation unit, which are used to calculate the data integrity evaluation index based on the hash verification result, which is used to quantify the integrity of the data; the level division module includes a level division unit and a chart feedback unit to generate a chart according to the level division result to feedback the result of the data integrity evaluation; a more accurate evaluation of the reliability during the data transmission process is achieved.

[0062] To summarize, the embodiment of the present application collects the original data of the computed tomography pulmonary angiography device and transmits it to the pulmonary hypertension interventional imaging supervision platform through the main network after preprocessing, and then evaluates the data transmission status of the main network to obtain the main network transmission evaluation index, and then performs hash operation and data verification on the received original data to obtain the data integrity evaluation index and classifies the data to obtain the classification result, thereby improving the accurate evaluation of data transmission accuracy in the imaging data analysis of pulmonary hypertension intervention, and further achieving the improvement of the accuracy of data analysis in the imaging data analysis of pulmonary hypertension intervention, and effectively solving the problem of inaccurate data transmission in the imaging data analysis of pulmonary hypertension intervention in the prior art.

[0063] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0064] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0065] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0066] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0067] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0068] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An imaging data analysis method for pulmonary hypertension intervention, characterized in that: The following steps are involved: S1, collecting raw data of a computed tomography pulmonary angiography device, and transmitting the raw data to a pulmonary hypertension interventional imaging monitoring platform through a main network after preprocessing the raw data, wherein the raw data is used to describe data generated during the operation of the computed tomography pulmonary angiography device; S2, obtaining the main network transmission evaluation data of the main network within a preset time interval, evaluating the data transmission situation of the main network within the preset time interval according to the main network transmission evaluation data to obtain a main network transmission evaluation index, if the main network transmission evaluation index is within a preset threshold range, continue to transmit, otherwise, switch to the backup network transmission, and perform a comprehensive evaluation based on the main network transmission evaluation index and the data transmission situation to obtain a comprehensive evaluation result, the main network transmission evaluation data includes data packet transmission data, sent data packet data, lost data packet data and bandwidth utilization data, the main network transmission evaluation index is used to describe the transmission efficiency of the main network, and the comprehensive evaluation result is used to visualize the data transmission situation; S3, performing hash operation and data verification on the original data received by the pulmonary hypertension interventional imaging monitoring platform to obtain a data integrity evaluation index, wherein the data integrity evaluation index is used to comprehensively quantify the data integrity detected by the hash verification method; S4, classify the data according to the data integrity evaluation index to obtain the classification results and provide feedback in the form of charts.

2. The imaging data analysis method for pulmonary hypertension intervention as claimed in claim 1, characterized in that: The specific steps of collecting raw data of the computer tomography pulmonary artery angiography device are as follows: Acquire a pulmonary artery angiography image generated by a computed tomography pulmonary artery angiography device and corresponding image data, wherein the image data includes an image unique identifier, image resolution, scanning mode and scanning parameters, wherein the scanning parameters include current, voltage and rotation speed; Obtain the type, dose, and injection time of contrast agent used during the computed tomography pulmonary angiography scan.

3. The imaging data analysis method for pulmonary hypertension intervention according to claim 1, characterized in that: The specific steps of pre-processing the raw data and transmitting it to the pulmonary hypertension interventional imaging monitoring platform through the main network are as follows: Perform SHA-256 hash operation on the collected original data to generate a hash value, perform BZIP2 lossless compression on the generated hash value and the original data, and perform AES symmetric encryption on the compressed hash value and the original data to obtain an encrypted hash value; The encrypted hash value and original data are transmitted to the pulmonary arterial hypertension interventional imaging monitoring platform through the HTTPS protocol of the main network.

4. The imaging data analysis method for pulmonary hypertension intervention according to claim 1, characterized in that: The specific method for obtaining the main network transmission evaluation index is as follows: The data packet transmission data is obtained according to the data transmission situation of the primary network within the preset time interval, and the data packet transmission data includes first transmission data and second transmission data. The first transmission data is used to describe the transmission situation of the data packet of the primary network within the preset time interval under a preset normal state, and the first transmission data includes a first sending time and a first receiving time. The second transmission data is used to describe the transmission situation of the data packet of the primary network within the preset time interval under a congested state, and the second transmission data includes a second sending time and a second receiving time. According to the data packet sending and loss conditions of the primary network within a preset time interval, the sent data packet data and the lost data packet data are obtained, and the bandwidth utilization data is obtained, the sent data packet data includes first sent data packet data and second sent data packet data, the first sent data packet data is used to describe the total number of data packets sent by the primary network within the preset time interval under a preset normal state, and the second sent data packet data is used to describe the total number of data packets sent by the primary network within the preset time interval under a congestion state, the lost data packet data includes first lost data packet data and second lost data packet data, the first lost data packet data is used to describe the total number of data packets lost by the primary network within the preset time interval under a preset normal state, and the second lost data packet data is used to describe the total number of data packets lost by the primary network within the preset time interval under a congestion state, the bandwidth utilization data includes first bandwidth utilization and second bandwidth utilization, the first bandwidth utilization is used to describe the flow information of data packets transmitted by the primary network within the preset time interval under a preset normal state, and the second bandwidth utilization is used to describe the flow information of data packets transmitted by the primary network within the preset time interval under a congestion state; A first transmission delay is obtained according to a first receiving time and a first sending time, a second transmission delay is obtained according to a second receiving time and a second sending time, and a primary network transmission evaluation index is obtained by combining the first transmission delay reference deviation, the second transmission delay reference deviation, the first bandwidth utilization reference deviation and the second bandwidth utilization reference deviation with evaluation weights obtained from a preset database, wherein the evaluation weights include an average transmission delay weight, a packet loss rate weight and a bandwidth utilization weight.

5. The imaging data analysis method for pulmonary hypertension intervention as claimed in claim 4, characterized in that: The main network transmission evaluation index is calculated using the following formula: In the formula, I represents the primary network transmission evaluation index, M represents the first transmission delay, m represents the second transmission delay, ΔM represents the first transmission delay reference deviation, Δm represents the second transmission delay reference deviation, h represents the second lost data packet data, g represents the second sent data packet data, H represents the first lost data packet data, G represents the first sent data packet data, r represents the second bandwidth utilization, Δr represents the second bandwidth utilization reference deviation, R represents the first bandwidth utilization, ΔR represents the first bandwidth utilization reference deviation, c1 represents the average transmission delay weight, c2 represents the packet loss rate weight, and c3 represents the bandwidth utilization weight.

6. The imaging data analysis method for pulmonary hypertension intervention according to claim 5, characterized in that: The specific steps of performing a comprehensive evaluation based on the main network transmission evaluation index and data transmission status to obtain a comprehensive evaluation result are as follows: Use Grafana to visualize the raw data during the transmission process, and obtain the number of times the transmission is switched to the backup network based on the main network transmission evaluation index. A comprehensive evaluation result is obtained by performing a comprehensive evaluation based on the main network transmission evaluation index and the number of times the transmission is switched to the backup network. If the number of times the transmission is switched to the backup network exceeds the preset number, the main network transmission evaluation index and the original data will be fed back and recorded as the main network transmission is unqualified. Otherwise, the main network transmission evaluation index and the original data will be uploaded to the database and recorded as the main network transmission is qualified.

7. The imaging data analysis method for pulmonary hypertension intervention according to claim 1, characterized in that: The specific method for obtaining the data integrity assessment index is as follows: The SHA-256 hash operation is performed again on the data packets in the original data received by the pulmonary hypertension interventional imaging monitoring platform to obtain the verification hash value and compare it with the encrypted hash value. If the recalculated verification hash value is equal to the encrypted hash value, it is recorded as a matching data packet; The data integrity evaluation index is obtained by the number of matching data packets in the total sent data packets and the hash algorithm strength weight obtained from the preset database.

8. The imaging data analysis method for pulmonary hypertension intervention as claimed in claim 7, characterized in that: The data integrity assessment index is calculated using the following formula: Where J represents the data integrity evaluation index, K represents the total number of data packets sent during the primary network transmission process, L represents the number of matching data packets, β represents the hash algorithm strength weight, and w represents the hash collision probability.

9. The imaging data analysis method for pulmonary hypertension intervention according to claim 8, characterized in that: The specific process of obtaining the grading result by grading according to the data integrity evaluation index is as follows: Obtaining a data integrity assessment index and a corresponding preset threshold, performing grading according to the data integrity assessment index to obtain a grading result, and drawing the grading result into a grading result chart, wherein the grading result is used to visualize the data integrity assessment index, and the grading result chart includes a stacked column chart, a pie chart, and a bar chart; The method for obtaining the grading result is: If the data integrity assessment index is lower than the preset threshold, it is recorded as the data missing level; If the data integrity assessment index is equal to the preset threshold, it is recorded as the normal level of data; If the data integrity assessment index is higher than the preset threshold, it is recorded as a good data level.

10. An imaging data analysis system for interventional treatment of pulmonary hypertension, characterized in that: include: Data processing module, transmission evaluation module, data verification module, and grading module: The data processing module is used to collect raw data from the computed tomography pulmonary angiography device, and transmit the raw data to the pulmonary hypertension interventional imaging monitoring platform through the main network after pre-processing the raw data, and the raw data is used to describe the data generated during the operation of the computed tomography pulmonary angiography device; The transmission evaluation module is used to obtain the main network transmission evaluation data of the main network within a preset time interval, and evaluate the data transmission situation of the main network within the preset time interval according to the main network transmission evaluation data to obtain the main network transmission evaluation index. If the main network transmission evaluation index is within the preset threshold range, the transmission continues; otherwise, the backup network transmission is switched to obtain a comprehensive evaluation result based on the main network transmission evaluation index and the data transmission situation. The main network transmission evaluation data includes data packet transmission data, sent data packet data, lost data packet data and bandwidth utilization data. The main network transmission evaluation index is used to describe the transmission efficiency of the main network, and the comprehensive evaluation result is used to visualize the data transmission situation. The data verification module is used to perform hash operation and data verification on the original data received by the pulmonary hypertension interventional imaging monitoring platform to obtain a data integrity evaluation index, and the data integrity evaluation index is used to comprehensively quantify the data integrity detected by the hash verification method; The grading module is used to perform grading according to the data integrity evaluation index to obtain grading results and provide feedback in the form of charts.

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