Remote control CT machine detection method and device, computer equipment and storage medium
By obtaining patient information in a remote remote control CT machine and pre-processing CT images, the problem of low diagnostic efficiency caused by low CT image clarity is solved, and a more accurate and efficient diagnosis of the disease is achieved.
Patent Information
- Application Number
- CN202411694834.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-25
- Publication Date
- 2025-02-28
AI Technical Summary
When processing CT images, existing remote remote control CT machines are difficult to generate accurate patient condition information, which leads to doctors being unable to correctly and promptly determine the condition, affecting diagnostic efficiency.
By obtaining patient information, generating remote remote control CT machine work information, obtaining CT image information and generating CT image analysis and processing instructions, performing CT image preprocessing, generating CT image processing results, initially diagnosing the disease and generating hierarchical diagnosis information.
It improves the unity between CT machine processing CT images and identifying the disease, ensures the accuracy and efficiency of diagnosis, reduces the waiting time of patients, and expands the coverage of medical services.
Smart Images
Figure CN119523508A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of remote control CT machines, and in particular to a remote control CT machine detection method, device, computer equipment and storage medium. Background Art
[0002] With the continuous development of medical technology, remote control technology has gradually become an important application in the medical field. Among them, remote control technology can enable expert doctors to control CT machines in real time and accurately scan patients. Through high-definition cameras and sensors, remote doctors can obtain the same image information as on-site doctors, so as to make more accurate diagnoses. In addition, remote control technology can also enable doctors in multiple locations to consult together, brainstorm, and further improve the accuracy of diagnosis. Secondly, the remote control CT machine detection system also has a significant effect in improving work efficiency. Traditional CT detection requires doctors to operate on-site, while remote control technology allows doctors to control CT machines in the office or at home. This not only reduces the time cost of doctors' on-site operation, but also allows detection anytime and anywhere, greatly improving work efficiency. In addition, through automated and intelligent technical means, the remote control CT machine detection system can also realize functions such as automatic scanning and automatic film reading, further improving work efficiency.
[0003] With respect to the above-mentioned related technologies, the existing remote-controlled CT machine is used to examine the patient. The doctor obtains the CT image by controlling the CT machine. At the same time, the CT machine automatically generates corresponding patient condition information according to the CT image. The doctor can make a graded judgment based on the obtained patient condition information. Although the doctor can work conveniently and quickly through the remote-controlled CT machine, when the obtained CT image has low clarity, it is difficult for the CT machine to generate accurate patient condition information, which results in the doctor being unable to make a correct and timely judgment on the patient's condition based on the patient's condition information, thereby affecting the diagnostic efficiency of the condition. Summary of the invention
[0004] In order to improve the consistency of the CT machine in processing CT images, identifying disease conditions and storing patient information, the present application provides a remote control CT machine detection method, device, computer equipment and storage medium.
[0005] The above-mentioned invention objective of the present application is achieved through the following technical solutions: A remote control CT machine detection method, the remote control CT machine detection method comprising: Acquire patient information, generate remote control CT machine working information according to the patient information, acquire CT image information from the remote control CT machine working information, and generate an instruction for analyzing and processing CT images, wherein the instruction for analyzing and processing CT images is used to analyze and process the CT image information to generate a CT image preprocessing result; Acquiring a CT standard image format and protocol, wherein the CT standard image format and protocol are used to modulate the CT image preprocessing result to generate a CT image processing result; Generate a preliminary disease diagnosis result according to the CT image processing result, and generate graded diagnosis information according to the preliminary disease diagnosis result; CT image compression information is generated according to the CT image imaging result, and CT image cloud storage information is generated according to the CT image compression information.
[0006] By adopting the above technical solution, the remote control CT machine can realize the sharing and utilization of medical resources through the Internet. Even in areas with insufficient medical resources, professional medical image detection services can be obtained through remote control technology to improve the utilization efficiency of medical resources. The remote control CT machine can make the medical service coverage wider, and can provide medical image detection services for remote areas, areas with insufficient medical resources and areas with limited medical conditions, alleviating the problem of uneven distribution of medical resources. Traditional CT detection requires patients to go to hospitals or clinics to wait in line, while the remote control CT machine can perform remote diagnosis by appointment, effectively reducing the waiting time of patients and improving the efficiency of patients' medical treatment. The remote control CT machine can realize instant diagnosis and remote consultation. Doctors can monitor and diagnose patients in real time through remote control technology, which helps to improve the efficiency and accuracy of diagnosis. The remote control CT machine can upload medical image data to the cloud for storage and management. Doctors can obtain patients' medical image data anytime and anywhere, and perform diagnosis and analysis, which greatly facilitates the work of doctors.
[0007] In a preferred example, the present application may be further configured as follows: the patient information is obtained, remote control CT machine working information is generated according to the patient information, CT image information is obtained from the remote control CT machine working information, and an instruction for analyzing and processing CT images is generated, wherein the instruction for analyzing and processing CT images is used to analyze and process the CT image information to generate a CT image preprocessing result, specifically including: Generate a CT scan type according to the patient information, and obtain the CT machine working information from the CT scan type; Generate remote login information according to the CT machine working information, and generate remote control CT machine working information according to the remote login information; Acquire CT image information from the remote control CT machine working information, and generate instructions for analyzing and processing CT images according to the CT image information; The CT image information is subjected to CT image processing by the CT image analysis and processing instruction to generate the CT image preprocessing result.
[0008] By adopting the above technical solution, by obtaining the patient's clinical information from the patient information, a personalized CT scan type can be generated according to the patient's specific situation, which is helpful for a more accurate diagnosis according to the patient's needs and disease characteristics. According to the CT scan type, the corresponding CT machine working information can be automatically generated, and the CT machine working information includes scanning mode, scanning parameters, etc., which not only improves the degree of automation of the operation, but also reduces the potential errors of manual settings. When the CT machine is working, by generating remote login information, the doctor or technician can remotely log in to the CT machine system. By obtaining remote setting adjustment information from the remote control CT machine working information, the CT scanning parameters can be adjusted in real time to realize remote control of the CT machine. At the same time, the doctor or technician can adjust the CT scanning parameters in real time according to the actual situation of the patient to ensure that high-quality CT images are obtained. By automatically generating CT machine working information and remote control, the reduction of CT machine scanning accuracy caused by human operation can be avoided as much as possible, which is important for improving the accuracy and safety of CT scanning. At the same time, doctors or technicians do not need to go to the CT machine site in person. Doctors or technicians can log in remotely and adjust the settings, making the entire process more efficient and convenient, which has a positive impact on improving the efficiency and flexibility of medical services.
[0009] In a preferred example, the present application may be further configured as follows: the step of acquiring CT image information from the remote control CT machine working information and generating instructions for analyzing and processing CT images according to the CT image information specifically includes: Acquire scanning mode and region information from the remote control CT machine working information, and generate the CT image information according to the scanning mode and region information; CT image preprocessing information is generated according to the CT image information, and the CT image analysis and processing instruction is obtained from the CT image preprocessing information.
[0010] By adopting the above technical solution, the scanning mode and area information in the remote control CT machine working information can be used to obtain the specific parameter settings of the CT scan in real time, which helps to understand the key parameters in the scanning process. The key parameters in the scanning process include scanning methods such as spiral scanning, static scanning, and scanning areas. Based on the acquired scanning mode and area information, corresponding CT image information can be generated. The CT image information includes a cross-sectional CT image of the patient's body, showing the anatomical structure of a specific area. The quality and contrast of the CT image can be improved by performing CT image preprocessing on the CT image information. The CT image preprocessing includes operations such as denoising, enhancement, and filtering. Based on the CT image information that has undergone CT image preprocessing, instructions for analyzing and processing CT images can be generated. In a preferred example, the present application may be further configured as follows: the acquiring of the CT standard image format and protocol, the CT standard image format and protocol being used for the CT image preprocessing result to generate the CT image processing result, specifically including: A CT standard image comparison is performed with the CT standard image format and protocol and the CT image preprocessing result to generate the CT image processing result.
[0011] By adopting the above technical solutions, the remote control CT machine can compare with the preprocessing results through standard image formats and protocols, thereby improving the accuracy of diagnosis. Doctors can use standardized image comparison methods to make accurate diagnoses and reduce diagnostic errors. The remote control CT machine can realize real-time connection between doctors and equipment. Doctors can quickly obtain CT images and make comparison diagnoses, shortening the diagnosis time. This is especially important for patients who need emergency treatment or rapid treatment, and treatment plans can be quickly formulated. Through the remote control CT machine, doctors can transcend geographical restrictions, remotely manage multiple devices, and make full use of medical resources. This helps to reduce the idle time of equipment and improve the efficiency of medical equipment use.
[0012] In a preferred example, the present application may be further configured as follows: generating a preliminary disease diagnosis result according to the CT image processing result, and generating graded diagnosis information according to the preliminary disease diagnosis result, specifically including: Acquiring individual characteristics and historical diagnosis information of the patient, and generating the preliminary disease diagnosis result by combining the CT image processing result with the individual characteristics and historical diagnosis information of the patient; The severity information of the disease is obtained from the preliminary disease diagnosis result, and the graded diagnosis information is generated according to the severity information of the disease.
[0013] By adopting the above technical solution, personalized diagnosis can be achieved by obtaining the individual characteristics and historical diagnosis information of the patient and combining it with the CT image processing results. Doctors can formulate treatment plans that better meet the needs of patients based on the characteristics and historical medical history of the patients, thereby improving the treatment effect. Remote control of CT machines can achieve real-time connection between doctors and patients without the need for both parties to be in the same location. This means that even if the patient and the doctor are in different regions, the doctor can still obtain the individual characteristics and historical diagnosis information of the patient remotely for diagnosis. Remote control of CT machines can speed up the diagnosis and treatment process. Doctors can quickly obtain patient information and make diagnoses based on the CT image processing results, thereby formulating treatment plans faster and improving treatment efficiency.
[0014] In a preferred example, the present application may be further configured as follows: generating CT image compression information according to the CT image imaging result, and generating CT image cloud storage information according to the CT image compression information specifically includes: generating CT image quality control and verification information according to the CT image imaging result, and generating the CT image compression information according to the CT image quality control and verification information; Acquire a CT image compression result according to the CT image compression information, and store the CT image compression result; By adopting the above technical solution, by generating CT image quality control and verification information, the quality of remotely acquired CT images can be monitored and verified in real time. This helps to ensure the accuracy and reliability of remote diagnosis and improve the credibility of the remote control CT machine detection method. By generating CT image compression information, the storage and transmission process of CT images can be optimized, and the data transmission cost and storage space occupation can be reduced. This helps to improve the efficiency and economy of the remote control CT machine detection method. By controlling and verifying the resolution, contrast and noise level of CT images, it can be ensured that the images acquired by the remote control CT machine at different times and locations have consistent imaging quality, and improve the consistency and stability of diagnosis. By storing CT images in the cloud, doctors can access and view patients' CT images anytime and anywhere, thereby enhancing remote diagnosis capabilities. This helps doctors make diagnosis and treatment decisions more timely and improves the practicality and convenience of the remote control CT machine detection method.
[0015] In a preferred example, the present application may be further configured as follows: obtaining a CT image compression result according to the CT image compression information, and storing the CT image compression result, specifically including: Acquire a CT image compression algorithm from the CT image compression information, acquire a CT image compression ratio standard, a CT image distortion standard, and a CT image file size standard, wherein the CT image compression ratio standard, the CT image distortion standard, and the CT image file size standard are used for CT image compression control to generate the image quality control index information; According to the CT image compression result, the CT image compression result is stored.
[0016] By adopting the above technical solution, by obtaining the CT image compression algorithm, compression ratio standard, distortion standard and file size standard, effective compression and control of CT images can be achieved, thereby optimizing storage management. This helps to reduce storage space occupancy, improve storage efficiency, and provide a more efficient data management solution for the remote control CT machine detection method. By generating storage location information, CT images can be stored in a suitable location to ensure the security and integrity of data. This helps to avoid data loss or damage and ensure the reliability and accuracy of remote diagnosis. By optimizing the management of compression control and storage location of CT images, storage efficiency can be improved and storage costs can be reduced. This helps to reduce the operating cost of the remote control CT machine detection method and improve resource utilization. By storing CT images in the cloud, remote access and sharing of data can be achieved, and doctors can obtain and view patients' CT images anytime and anywhere, thereby simplifying the data access process and improving the efficiency and convenience of medical services. By generating image quality control indicator information, the quality of CT images can be effectively monitored and managed to ensure the accuracy and credibility of the images. This helps to improve the diagnostic effect and data management capabilities of the remote control CT machine detection method.
[0017] The second object of the invention is achieved by the following technical solutions: A remote control CT machine detection device, the remote control CT machine detection device comprising: A CT image acquisition module, used to acquire patient information, generate remote control CT machine working information according to the patient information, acquire CT image information from the remote control CT machine working information, and generate an analysis and processing CT image instruction, wherein the analysis and processing CT image instruction is used to analyze and process the CT image information to generate a CT image preprocessing result; A CT image processing module, used for acquiring a CT standard image format and protocol, wherein the CT standard image format and protocol are used for the CT image preprocessing result to generate a CT image processing result; A diagnosis information generating module, used to generate a preliminary disease diagnosis result according to the CT image processing result, and to generate graded diagnosis information according to the preliminary disease diagnosis result; The CT image compression module is used to generate CT image compression information according to the CT image imaging result, and generate CT image cloud storage information according to the CT image compression information.
[0018] By adopting the above technical solution, the remote control CT machine can realize the sharing and utilization of medical resources through the Internet. Even in areas with insufficient medical resources, professional medical image detection services can be obtained through remote control technology to improve the utilization efficiency of medical resources. The remote control CT machine can make the medical service coverage wider, and can provide medical image detection services for remote areas, areas with insufficient medical resources and areas with limited medical conditions, alleviating the problem of uneven distribution of medical resources. Traditional CT detection requires patients to go to hospitals or clinics to wait in line, while the remote control CT machine can perform remote diagnosis by appointment, effectively reducing the waiting time of patients and improving the efficiency of patients' medical treatment. The remote control CT machine can realize instant diagnosis and remote consultation. Doctors can monitor and diagnose patients in real time through remote control technology, which helps to improve the efficiency and accuracy of diagnosis. The remote control CT machine can upload medical image data to the cloud for storage and management. Doctors can obtain patients' medical image data anytime and anywhere, and perform diagnosis and analysis, which greatly facilitates the work of doctors.
[0019] The third objective of the present application is achieved through the following technical solutions: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned remote control CT machine detection method are implemented.
[0020] The fourth objective of the present application is achieved through the following technical solutions: A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the remote control CT machine detection method are implemented.
[0021] In summary, the present application includes at least one of the following beneficial technical effects: 1. Remote control CT machines can realize the sharing and utilization of medical resources through the Internet. Even in areas with insufficient medical resources, professional medical image detection services can be obtained through remote control technology to improve the utilization efficiency of medical resources. Remote control CT machines can make medical services cover a wider range, and can provide medical image detection services for remote areas, areas with insufficient medical resources, and areas with limited medical conditions, alleviating the problem of uneven distribution of medical resources. Traditional CT tests require patients to go to hospitals or clinics to wait in line, while remote control CT machines can perform remote diagnosis through appointments, effectively reducing patients' waiting time and improving patients' medical treatment efficiency. Remote control CT machines can realize instant diagnosis and remote consultation. Doctors can monitor and diagnose patients in real time through remote control technology, which helps to improve diagnostic efficiency and accuracy. Remote control CT machines can upload medical imaging data to the cloud for storage and management. Doctors can obtain patients' medical imaging data anytime and anywhere, and perform diagnosis and analysis, which greatly facilitates the doctor's work; 2. By obtaining the patient's clinical information from the patient information, a personalized CT scan type can be generated according to the patient's specific situation, which helps to make a more accurate diagnosis according to the patient's needs and disease characteristics. According to the CT scan type, the corresponding CT machine working information can be automatically generated. The CT machine working information includes scanning mode, scanning parameters, etc., which not only improves the degree of automation of the operation, but also reduces the potential errors of manual settings. When the CT machine is working, by generating remote login information, doctors or technicians can remotely log in to the CT machine system. By obtaining remote setting adjustment information from the remote control CT machine working information, the CT scanning parameters can be adjusted in real time to achieve remote control of the CT machine. At the same time, doctors or technicians can adjust the CT scanning parameters in real time according to the actual situation of the patient to ensure that high-quality CT images are obtained. By automatically generating CT machine working information and remote control, the reduction of CT machine scanning accuracy caused by human operation can be avoided as much as possible, which is important for improving the accuracy and safety of CT scanning. At the same time, doctors or technicians do not need to go to the CT machine site in person. Doctors or technicians can log in remotely and adjust the settings, making the entire process more efficient and convenient, which has a positive impact on improving the efficiency and flexibility of medical services; 3. By obtaining the CT image compression algorithm, compression ratio standard, distortion standard and file size standard, effective compression and control of CT images can be achieved, thereby optimizing storage management. This helps to reduce storage space occupation, improve storage efficiency, and provide a more efficient data management solution for the remote control CT machine detection method. By generating storage location information, CT images can be stored in a suitable location to ensure the security and integrity of the data. This helps to avoid data loss or damage and ensure the reliability and accuracy of remote diagnosis. By optimizing the management of compression control and storage location of CT images, storage efficiency can be improved and storage costs can be reduced. This helps to reduce the operating cost of the remote control CT machine detection method and improve resource utilization. By storing CT images in the cloud, remote access and sharing of data can be achieved, and doctors can obtain and view patients' CT images anytime and anywhere, thereby simplifying the data access process and improving the efficiency and convenience of medical services. By generating image quality control indicator information, the quality of CT images can be effectively monitored and managed to ensure the accuracy and credibility of the images. This helps to improve the diagnostic effect and data management capabilities of the remote control CT machine detection method. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] Figure 1 This is a flow chart of detection by remote control of a CT machine in one embodiment of the present application; Figure 2 This is a flowchart of implementing step S10 in remote control of a CT machine in one embodiment of the present application; Figure 3 This is a flowchart for implementing step S13 in remote control of a CT machine in one embodiment of the present application; Figure 4 This is a flowchart for implementing step S20 in remote control of a CT machine in one embodiment of the present application; Figure 5 This is a flowchart for implementing step S30 in remote control of a CT machine in one embodiment of the present application; Figure 6 This is a flowchart of implementing step S40 in remote control of a CT machine in one embodiment of the present application; Figure 7 This is a flowchart of implementing step S42 in remote control of a CT machine in one embodiment of the present application; Figure 8 This is a principle block diagram of detection by remote control of a CT machine in one embodiment of the present application; Fig. 9 It is a schematic diagram of a device in an embodiment of the present application. DETAILED DESCRIPTION
[0023] The present application is further described in detail below in conjunction with the accompanying drawings.
[0024] In one embodiment, if Figure 1 As shown, the present application discloses a remote control CT machine detection method, which specifically includes the following steps: S10: Acquire patient information, generate remote-controlled CT machine working information according to the patient information, acquire CT image information from the remote-controlled CT machine working information, and generate instructions for analyzing and processing CT images, wherein the instructions for analyzing and processing CT images are used to analyze and process the CT image information to generate CT image preprocessing results.
[0025] In this embodiment, patient information refers to clinical information related to patient baseline information and patient medical history. Remote control CT machine operation information refers to the CT machine being remotely adjusted and used after the CT machine is in operation. CT image information refers to real-time capture of CT images generated by the remote control CT machine. Analysis and processing of CT images instructions refers to analysis and processing of captured CT images. CT image preprocessing results refer to preprocessing results generated after analyzing the CT images.
[0026] Specifically, through patient information collection, the basic information of the patient is collected, including name, gender, age, height and weight. In addition, it is necessary to obtain information about the patient's medical history, clinical symptoms and allergic reactions. At the same time, the patient's clinical information is analyzed to determine the purpose and scope of the CT scan. According to the patient's symptoms and the doctor's requirements, the scanning area, scanning method and required CT image resolution and other parameters are determined. According to the analysis of clinical information, the appropriate CT scan type is determined, such as abdominal CT, head CT and chest CT. According to the determined scan type, the parameters of the CT machine are configured, including X-ray tube current, voltage, scanning speed and slice thickness. After adjusting the CT machine parameters, the CT machine is adjusted to work, and at the same time, it is ensured that the CT machine network connection is completed and there is no abnormality, so that the CT machine is remotely controlled, and the image information of the CT machine is obtained in real time through remote control, and the CT image analysis and processing instructions are obtained, and the image information of the CT machine is processed: after analysis and processing, the preprocessing result of the CT image is generated.
[0027] S20: Acquire a CT standard image format and protocol, where the CT standard image format and protocol are used to modulate the CT image preprocessing result to generate a CT image processing result.
[0028] In this embodiment, the CT standard image format and protocol refer to the standard format and communication protocol used to represent and transmit CT image data in the field of medical imaging. The CT image processing result refers to the processing result obtained by performing image enhancement, denoising, segmentation, feature extraction, reconstruction and other operations on the CT image preprocessing result.
[0029] Specifically, the preprocessed CT image data is processed and converted according to the CT standard image format and protocol, the processed image data is converted into DICOM format, the DICOM format image is transmitted, and the CT image is enhanced, segmented and feature extracted to obtain the CT image processing result.
[0030] It can be understood that the DICOM format refers to a CT image format determined by a CT standard image format and protocol.
[0031] S30: Generate a preliminary disease diagnosis result according to the CT image processing result, and generate graded diagnosis information according to the preliminary disease diagnosis result.
[0032] In this embodiment, the preliminary diagnosis result refers to the preliminary judgment of the possible diseases and conditions of the patient by CT based on the examination results and medical history information. The graded diagnosis information refers to the graded diagnosis of different doctors according to the condition.
[0033] Specifically, based on the CT image processing results, the CT machine identifies the preliminary condition, and the image information generated by the CT machine is transmitted to the attending physician. Based on the results of the CT image analysis, the corresponding diagnostic information is generated, and the diagnostic information includes information such as the type, location, size, and severity of the lesion. Based on the generated diagnostic information, a graded diagnosis is performed to classify the lesions into different categories or determine the severity of the lesions, and the results of the graded diagnosis are presented to the doctor in the form of CT images and reports.
[0034] S40: Generate CT image compression information according to the CT image imaging result, and generate CT image cloud storage information according to the CT image compression information.
[0035] In this embodiment, the CT image compression information refers to the Huffman coding lossless compression of the CT image. The CT image cloud storage information refers to the storage of the diagnosis result.
[0036] Specifically, the CT image is preprocessed by denoising, enhancing and segmenting. The processed CT image is compressed using the Huffman coding algorithm. First, the frequency of occurrence of each pixel value in the image needs to be counted and a Huffman tree needs to be constructed. Then, a corresponding Huffman code is assigned to each pixel value according to the Huffman tree. Finally, the original image data is replaced with the Huffman-coded data, and the compressed data is stored. After the compression is completed, the CT image compression information is generated, and the compressed CT image data and its corresponding compression information are uploaded to the cloud storage space.
[0037] In one embodiment, if Figure 2As shown, in step S10, patient information is obtained, remote control CT machine working information is generated according to the patient information, CT image information is obtained from the remote control CT machine working information, and CT image analysis and processing instructions are generated. The CT image analysis and processing instructions are used to analyze and process the CT image information to generate a CT image preprocessing result, which specifically includes: S11: Generate a CT scan type according to the patient information, and obtain the CT machine working information from the CT scan type.
[0038] In this embodiment, the CT scanning type refers to using different scanning types according to different patient conditions.
[0039] Specifically, the patient information includes name, age, gender, symptoms and medical history of the patient, etc. The key diagnosis or symptom features are extracted from the patient's clinical information to determine the applicable CT scan type. Based on the parsed clinical information, the applicable CT scan type is determined. Based on the determined CT scan type, the corresponding CT machine working information is queried from the CT machine database or configuration file. The CT machine working information includes scanning parameters, scanning mode and radiation dose, etc. The patient information, clinical information, CT scan type and CT machine working information are integrated so that the CT machine can work.
[0040] S12: Generate remote login information according to the CT machine working information, and generate remote control CT machine working information according to the remote login information.
[0041] In this embodiment, the remote login information refers to the information required to log in when remotely controlling the operation of the CT machine. The remote control operation information of the CT machine refers to the adjustment of the operation of the CT machine by remote means.
[0042] Specifically, the device identification, connection protocol, network address, and control command support are extracted from the CT machine working information. The remote login information is generated and the parsed CT machine working information is used. The information for remote login is constructed, and the remote login information includes the device identification, connection credentials, and security authentication, etc., to ensure that the generated information meets the security requirements of remote login. At the same time, the remote login process is designed and implemented, and the remote login process includes steps such as user identity authentication and security encryption to ensure that only authorized users can log in remotely. Once the remote login is successful, the setting parameters of the current device are obtained by communicating with the CT machine, and the setting parameters include scanning mode, radiation dose, and CT image quality. At the same time, a user interaction interface is provided so that the remote user can easily adjust the settings of the CT machine. The user interaction interface includes a graphical user interface or a command line interface, allowing the user to flexibly adjust the settings. According to the user's input in the interaction interface, the corresponding setting adjustment command is generated, and the setting adjustment command is used to adjust the various parameters of the CT machine. Combined with the remote login information and the setting adjustment command, a complete remote control CT machine working information is generated.
[0043] S13: Acquire the CT image information from the remote control CT machine working information, and generate the CT image analysis and processing instruction according to the CT image information.
[0044] Specifically, the CT machine is operated by remote control, and the required CT image information is extracted from the parsed work information. The CT image information includes the patient's identity information, such as the scanning area, scanning layer thickness, scanning interval, and scanning mode. According to the extracted CT image information, the image processing and analysis required are determined, and the image processing and analysis include: image denoising, enhancement, segmentation, and feature extraction. According to the determined image processing requirements, the corresponding analysis and processing instructions for CT images are generated. For example, if image denoising is required, the corresponding denoising algorithm and parameter setting instructions are generated; if image segmentation is required, the corresponding segmentation algorithm and parameter setting instructions are generated.
[0045] S14: performing CT image processing on the CT image information through the CT image analysis and processing instruction to generate the CT image preprocessing result.
[0046] Specifically, according to the instructions for analyzing and processing CT images, corresponding image processing operations are performed. Image processing operations include denoising, enhancement, segmentation, registration and other operations. When denoising is required, the Gaussian excitation method is applied to reduce the noise in the image. When the visual effect of the image is enhanced, the histogram equalization method is used to achieve the enhanced visual effect of the image.
[0047] It can be understood that the Gaussian excitation method refers to image denoising by applying the surface clarity of the Gaussian function. The histogram equalization method refers to redistributing the pixel values of the image so that the histogram of the image is evenly distributed in the entire grayscale range, thereby enhancing the overall restoration of the image.
[0048] In one embodiment, if Figure 3 As shown, in step S13, that is, obtaining CT image information from the remote control CT machine working information, and generating analysis and processing CT image instructions according to the CT image information, specifically includes: S131: Obtain scanning mode and region information from the remote control CT machine working information, and generate CT image information according to the scanning mode and region information.
[0049] In this embodiment, the scanning mode and area information refers to the scanning mode and area used to treat the patient's condition.
[0050] Specifically, by parsing the CT machine working information obtained from the remote, the CT machine working information includes scanning mode and area information, and by parsing the received data packet, the scanning mode is extracted from the parsed information, and the scanning mode includes spiral scanning and static scanning, etc., as well as the scanning area, and the scanning area includes parameters such as head, chest and abdomen. According to the extracted scanning mode and area information, the parameters required for generating CT images are constructed, and the parameters required for CT images include scanning speed, layer thickness and radiation dose, etc. The generated CT image parameters are used to call the scanning function of the CT machine through the remote connection, including sending corresponding control instructions to start, stop or adjust the CT scan, and at the same time, the scanning progress is monitored in real time during the scanning process to ensure that the scanning is carried out according to the set mode and area, and the scanned image data is obtained in time. By receiving the raw data obtained by the scan, CT image processing and reconstruction are performed to generate the final CT image, and the CT image processing and reconstruction include denoising, filtering and CT image reconstruction algorithm, etc. Finally, the generated CT image is transmitted back to the remote operator or stored in a specific location for further analysis, diagnosis or storage.
[0051] S132: Generate CT image preprocessing information according to the CT image information, and obtain the CT image analysis and processing instruction from the CT image preprocessing information.
[0052] In this embodiment, the CT image preprocessing information refers to preprocessing of the CT image.
[0053] Specifically, the CT image size, pixel value range, and CT image format are parsed from the received CT image information. According to the requirements for analyzing and processing the CT image, the CT image preprocessing operations to be performed are determined, and the CT image preprocessing operations include denoising, enhancement, contrast adjustment, and smoothing. According to the requirements for CT image preprocessing, CT image preprocessing information is generated, and the CT image preprocessing information includes the required preprocessing algorithm, parameter settings, etc. The generated CT image preprocessing information is transmitted to the CT machine or CT image processing device to perform the corresponding CT image preprocessing operations. The received CT image preprocessing information is executed on the CT machine or CT image processing device to perform corresponding processing on the CT image, and the CT image processing includes calling a specific CT image processing algorithm and setting parameters, etc. The preprocessed CT data is obtained from the CT machine or CT image processing device to ensure that the data is accurately transmitted and meets the expected preprocessing effect. According to the preprocessed CT image data, an instruction for analyzing and processing the CT image is generated, and the CT image instruction includes a specific CT image analysis algorithm, measurement operation, and region marking, etc. The generated instruction for analyzing and processing the CT image is transmitted back to the CT machine or related equipment to perform subsequent CT image analysis and processing steps.
[0054] It can be understood that the preprocessing requirement refers to the requirement generated by preprocessing the CT image.
[0055] In one embodiment, if Figure 4 As shown, in step S20, that is, the acquisition of the CT standard image format and protocol, the CT standard image format and protocol are used for the CT image preprocessing result to generate the CT image processing result, specifically including: S21: performing a CT standard image comparison with the CT image preprocessing result through the CT standard image format and protocol to generate the CT image processing result.
[0056] In this embodiment, the CT standard image format and protocol refers to the DICOM standard protocol, which is a standard format and communication protocol for storing and transmitting CT scan image data, ensuring interoperability between different devices and software.
[0057] Specifically, by obtaining a CT scan image in DICOM format and an original CT image, the two images are compared and the structural similarity index method is used to compare and generate a comparison result. When the original CT image has a high image similarity, the original CT image is retained to generate a CT image processing result. If the original CT image does not meet the standard, the image is filtered, segmented, and feature extracted, and compared again with the DICOM standard protocol. When the image meets the standard, a CT image processing result is generated.
[0058] It can be understood that the structural similarity index method measures the similarity of the brightness or grayscale distribution of the image between two images by comparing the brightness similarity. Contrast similarity measures the similarity of the image contrast between two images. Structural similarity measures the similarity of the image structure between two images, that is, the texture and edge details in the image.
[0059] In one embodiment, if Figure 5 As shown, in step S30, that is, generating a preliminary disease diagnosis result according to the CT image processing result, generating graded diagnosis information according to the preliminary disease diagnosis result specifically includes: S31: Acquire the individual characteristics and historical diagnosis information of the patient, and generate the preliminary disease diagnosis result by combining the CT image processing result with the individual characteristics and historical diagnosis information of the patient.
[0060] In this embodiment, the patient's individual characteristics and historical diagnosis information refers to the record of the patient's personal characteristics, medical history, and clinical diagnosis.
[0061] Specifically, the individual characteristics and historical diagnosis information of the patient are obtained from the patient's medical record system or medical information system. The individual characteristics and historical diagnosis information of the patient involve extracting information such as age, gender, past medical history, drug allergy history, family history, etc. The CT image processing results are obtained by preprocessing and analyzing the patient's CT scan image. This may include steps such as image enhancement, segmentation, and feature extraction. The obtained individual characteristics and historical diagnosis information of the patient are combined with the CT image processing results. By taking the individual characteristics and historical diagnosis information as input and associating them with the CT image processing results, the patient's data is analyzed based on the combined data to generate a preliminary diagnosis result of the disease. S32: Acquire disease severity information from the preliminary disease diagnosis result, and generate the graded diagnosis information according to the disease severity information.
[0062] In this embodiment, the disease severity information refers to information about the severity of the patient's disease state.
[0063] Specifically, the patient's condition is initially determined to determine the severity of the condition, and corresponding graded diagnosis information is generated according to the determined severity of the condition. The patient's CT image is transmitted to different doctors, such as the attending doctor and the deputy attending doctor, who determine the condition and confirm the cause of the condition.
[0064] In one embodiment, if Figure 6 As shown, in step S40, that is, generating CT image compression information according to the CT image imaging result, and generating CT image cloud storage information according to the CT image compression information, specifically includes: S41: Generate CT image quality control and verification information according to the CT image imaging result, and generate the CT image compression information according to the CT image quality control and verification information.
[0065] In this embodiment, the CT image quality control and verification information refers to information used to evaluate and ensure the quality of CT scan images.
[0066] Specifically, record the radiation dose of each scan, including CTDI and DLP values, record slice thickness, slice spacing, and the position and direction of the scanning plane, evaluate the noise level and contrast of the image, ensure that the image quality is good enough, identify any existing artifacts, and record the correction measures, record the image reconstruction algorithm and parameter settings used, record the regular calibration and quality control test results of the CT equipment, and verify whether the CT image meets the clinical application requirements, such as diagnosis and treatment planning. When the clinical application requirements are met, compress the CT image.
[0067] S42: Obtaining a CT image compression result according to the CT image compression information, and storing the CT image compression result.
[0068] In this embodiment, the CT image compression result refers to compressed image data.
[0069] Specifically, the CT image is compressed by the Huffman coding lossless compression algorithm to obtain a CT image compression result, and after applying the compression algorithm, compressed image data is generated. The CT image is stored through a connection network.
[0070] In one embodiment, if Figure 7 As shown, in step S42, that is, obtaining a CT image compression result according to the CT image compression information and storing the CT image compression result, specifically includes: S421: Obtain a CT image compression algorithm from the CT image compression information, obtain a CT image compression ratio standard, a CT image distortion standard, and a CT image file size standard, the CT image compression ratio standard, the CT image distortion standard, and the CT image file size standard are used for CT image compression control to generate the CT image compression result, and store the CT image compression result according to the CT image compression result.
[0071] In this embodiment, the CT image compression algorithm refers to the Huffman coding lossless compression algorithm. The CT image compression ratio standard refers to an indicator for measuring the compression effect. The CT image distortion standard refers to the distortion measurement standard used when evaluating CT images. The CT image file size standard refers to the size limit of the CT image file.
[0072] Specifically, parameters such as lossless predictive coding algorithm, compression ratio standard, distortion standard and file size standard are extracted from CT image compression information. The CT image is compressed using the Huffman coding lossless compression algorithm. According to the compression ratio standard, distortion standard and file size standard, the parameter settings in the compression process are controlled to ensure that the compressed image data meets the specified compression effect and file size requirements. The compressed image is evaluated according to the distortion standard to ensure that the compression process does not introduce too much distortion. The compressed image data is stored in the CT image storage database to ensure that the file size meets the file size standard.
[0073] It can be understood that the CT image storage database refers to a database set up to store CT images.
[0074] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.
[0075] In one embodiment, a remote control CT machine detection device is provided, and the remote control CT machine detection device corresponds to the remote control CT machine detection method in the above embodiment. Figure 8 As shown, the remote control CT machine detection device includes a control CT image acquisition module, a CT image processing module, a diagnostic information generation module and a CT image compression module. The detailed description of each functional module is as follows: A CT image acquisition module, used to acquire patient information, generate remote control CT machine working information according to the patient information, acquire CT image information from the remote control CT machine working information, and generate an analysis and processing CT image instruction, wherein the analysis and processing CT image instruction is used to analyze and process the CT image information to generate a CT image preprocessing result; A CT image processing module, used for acquiring a CT standard image format and protocol, wherein the CT standard image format and protocol are used for the CT image preprocessing result to generate a CT image processing result; The diagnosis information generation module is used to generate a preliminary disease diagnosis result according to the CT image processing result, and generate graded diagnosis information according to the preliminary disease diagnosis result.
[0076] The CT image compression module is used to generate CT image compression information according to the CT image imaging result, and generate CT image cloud storage information according to the CT image compression information.
[0077] Optionally, the CT machine control working module includes: A CT machine working submodule, used for generating a CT scan type according to the patient information, and obtaining the CT machine working information from the CT scan type; A remote control submodule, used to generate remote login information according to the CT machine working information, and generate remote control CT machine working information according to the remote login information; An image processing submodule, used for acquiring CT image information from the remote control CT machine working information, and generating instructions for analyzing and processing CT images according to the CT image information; The CT image preprocessing result submodule is used to perform CT image processing on the CT image information through the CT image analysis and processing instruction to generate the CT image preprocessing result.
[0078] Optionally, the image processing submodule includes: A CT image region confirmation unit, used to obtain scanning mode and region information from the remote control CT machine working information, and generate the CT image information according to the scanning mode and region information; The CT image preprocessing unit is used to generate CT image preprocessing information according to the CT image information, and obtain the CT image analysis and processing instructions from the CT image preprocessing information.
[0079] Optionally, the CT image processing module includes: The CT image processing result submodule is used to perform CT standard image comparison with the CT image preprocessing result through the CT standard image format and protocol to generate the CT image processing result.
[0080] Optionally, the diagnostic information generation module includes: A preliminary disease diagnosis result submodule is used to obtain individual characteristics and historical diagnosis information of the patient, and generate the preliminary disease diagnosis result by combining the CT image processing result with the individual characteristics and historical diagnosis information of the patient; The graded diagnosis submodule is used to obtain the disease severity information from the preliminary disease diagnosis result and generate the graded diagnosis information according to the disease severity information.
[0081] Optionally, the CT image compression module includes: A CT image quality control and verification submodule, used to generate CT image quality control and verification information according to the CT image imaging result, and to generate the CT image compression information according to the CT image quality control and verification information; The CT image compression result submodule is used to obtain the CT image compression result according to the CT image compression information, and store the CT image compression result.
[0082] Optionally, the CT image compression result submodule includes: The CT image storage unit is used to obtain a CT image compression algorithm from the CT image compression information, obtain a CT image compression ratio standard, a CT image distortion standard and a CT image file size standard, wherein the CT image compression ratio standard, the CT image distortion standard and the CT image file size standard are used for CT image compression control to generate the CT image compression result, and store the CT image compression result according to the CT image compression result.
[0083] For the specific definition of the remote control CT machine detection device, please refer to the definition of the remote control CT machine detection method above, which will not be repeated here. Each module in the above remote control CT machine detection device can be implemented in whole or in part by software, hardware and combination. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.
[0084] In one embodiment, a computer device is provided. The computer device may be a server, and the internal structure diagram may be as follows: Fig. 9 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. In, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used for CT image storage database. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a remote control CT machine detection method is implemented.
[0085] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: Acquire patient information, generate remote control CT machine working information according to the patient information, acquire CT image information from the remote control CT machine working information, generate analysis and processing CT image instructions, and the analysis and processing CT image instructions are used to analyze and process the CT image information to generate CT image preprocessing results; Acquire a CT standard image format and protocol, wherein the CT standard image format and protocol are used to modulate a CT image preprocessing result to generate a CT image processing result; Generate a preliminary disease diagnosis result according to the CT image processing result, and generate graded diagnosis information according to the preliminary disease diagnosis result; CT image compression information is generated according to the CT image imaging result, and CT image cloud storage information is generated according to the CT image compression information.
[0086] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Acquire patient information, generate remote control CT machine working information according to the patient information, acquire CT image information from the remote control CT machine working information, generate analysis and processing CT image instructions, and the analysis and processing CT image instructions are used to analyze and process the CT image information to generate CT image preprocessing results; Acquire a CT standard image format and protocol, wherein the CT standard image format and protocol are used to modulate a CT image preprocessing result to generate a CT image processing result; Generate a preliminary disease diagnosis result according to the CT image processing result, and generate graded diagnosis information according to the preliminary disease diagnosis result; CT image compression information is generated according to the CT image imaging result, and CT image cloud storage information is generated according to the CT image compression information.
[0087] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.
[0088] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.
[0089] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.
Claims
1. A remote control CT machine detection method, characterized in that: The remote control CT machine detection method comprises: Acquire patient information, generate remote control CT machine working information according to the patient information, acquire CT image information from the remote control CT machine working information, and generate an instruction for analyzing and processing CT images, wherein the instruction for analyzing and processing CT images is used to analyze and process the CT image information to generate a CT image preprocessing result; Acquiring a CT standard image format and protocol, wherein the CT standard image format and protocol are used to modulate the CT image preprocessing result to generate a CT image processing result; Generate a preliminary disease diagnosis result according to the CT image processing result, and generate graded diagnosis information according to the preliminary disease diagnosis result; CT image compression information is generated according to the CT image imaging result, and CT image cloud storage information is generated according to the CT image compression information.
2. The remote control CT machine detection method according to claim 1, characterized in that: The step of acquiring patient information, generating remote control CT machine working information according to the patient information, acquiring CT image information from the remote control CT machine working information, and generating an instruction for analyzing and processing CT images, wherein the instruction for analyzing and processing CT images is used to analyze and process the CT image information to generate a CT image preprocessing result, specifically includes: Generate a CT scan type according to the patient information, and obtain the CT machine working information from the CT scan type; Generate remote login information according to the CT machine working information, and generate remote control CT machine working information according to the remote login information; Acquire CT image information from the remote control CT machine working information, and generate instructions for analyzing and processing CT images according to the CT image information; The CT image information is subjected to CT image processing by the CT image analysis and processing instruction to generate the CT image preprocessing result.
3. The remote-controlled CT machine detection method according to claim 2, characterized in that the step of acquiring CT image information from the remote-controlled CT machine working information and generating an instruction for analyzing and processing CT images according to the CT image information specifically comprises: Acquire scanning mode and region information from the remote control CT machine working information, and generate the CT image information according to the scanning mode and region information; CT image preprocessing information is generated according to the CT image information, and the CT image analysis and processing instruction is obtained from the CT image preprocessing information.
4. The remote control CT machine detection method according to claim 1, characterized in that: The acquiring of the CT standard image format and protocol, wherein the CT standard image format and protocol are used for the CT image preprocessing result to generate the CT image processing result, specifically includes: A CT standard image comparison is performed with the CT standard image format and protocol and the CT image preprocessing result to generate the CT image processing result.
5. The remote control CT machine detection method according to claim 1, characterized in that: The generating of a preliminary disease diagnosis result according to the CT image processing result, and generating graded diagnosis information according to the preliminary disease diagnosis result specifically includes: Acquiring individual characteristics and historical diagnosis information of the patient, and generating the preliminary disease diagnosis result by combining the CT image processing result with the individual characteristics and historical diagnosis information of the patient; The severity information of the disease is obtained from the preliminary disease diagnosis result, and the graded diagnosis information is generated according to the severity information of the disease.
6. The remote control CT machine detection method according to claim 1, characterized in that: The generating of CT image compression information according to the CT image imaging result, and generating CT image cloud storage information according to the CT image compression information specifically includes: generating CT image quality control and verification information according to the CT image imaging result, and generating the CT image compression information according to the CT image quality control and verification information; A CT image compression result is obtained according to the CT image compression information, and the CT image compression result is stored.
7. The remote control CT machine detection method according to claim 5, characterized in that: The obtaining a CT image compression result according to the CT image compression information and storing the CT image compression result specifically includes: A CT image compression algorithm is obtained from the CT image compression information, and a CT image compression ratio standard, a CT image distortion standard, and a CT image file size standard are obtained. The CT image compression ratio standard, the CT image distortion standard, and the CT image file size standard are used for CT image compression control to generate the CT image compression result. According to the CT image compression result, the CT image compression result is stored.
8. A remote control CT machine detection device, characterized in that: The remote control CT machine detection device comprises: A CT image acquisition module, used to acquire patient information, generate remote control CT machine working information according to the patient information, acquire CT image information from the remote control CT machine working information, and generate an analysis and processing CT image instruction, wherein the analysis and processing CT image instruction is used to analyze and process the CT image information to generate a CT image preprocessing result; A CT image processing module, used for acquiring a CT standard image format and protocol, wherein the CT standard image format and protocol are used for the CT image preprocessing result to generate a CT image processing result; A diagnosis information generating module, used to generate a preliminary disease diagnosis result according to the CT image processing result, and to generate graded diagnosis information according to the preliminary disease diagnosis result; The CT image compression module is used to generate CT image compression information according to the CT image imaging result, and generate CT image cloud storage information according to the CT image compression information.
9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the remote control CT machine detection method according to any one of claims 1 to 7 are implemented.
10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the remote control CT machine detection method according to any one of claims 1 to 7 are implemented.