A method and system for signal transmission of a maxillary sinus stent in an intelligent medical system

Abstract

The present application provides a method and system for transmitting maxillary sinus stent signals in an intelligent medical system. The method first obtains the maxillary sinus stent signals sent by the signal sending end of the maxillary sinus stent, and performs signal decision sub-adjustment to obtain multiple stent signal decision entropies; obtains the user's physical sign signals, and performs relevant feature extraction on the multiple stent signal decision entropies according to the user's physical sign signals to obtain the stability of the maxillary sinus stent signals; the main control process selects a communication link according to the stability of the maxillary sinus stent signals; the first subprocess transmits the maxillary sinus stent signals to the second subprocess of the intelligent medical system according to the selected communication link. The present application selects a communication link according to the stability of the maxillary sinus stent signals and performs signal transmission, realizing the classified transmission of the maxillary sinus stent signals, avoiding that the maxillary sinus stent signals with a higher degree of abnormality cannot be transmitted for a long time due to queue waiting, and improving the transmission speed of the abnormal maxillary sinus stent signals.

Description

Technical Field

[0001] This application relates to the field of communication technologies, and more particularly, to a method and system for transmitting maxillary sinus stent signals in an intelligent medical system. Background Art

[0002] Maxillary sinus stent signals are the maxillary sinus detection Computed Tomography (CT) signals obtained after scanning the cross-sectional layers of the maxillary sinus stent. They can be used to observe the postoperative conditions of the bone powder implanted during the simultaneous maxillary sinus internal sinus lift, and to adjust the maxillary sinus stent in a timely manner, thus avoiding the situation where the respiratory pressure of the patient after surgery pushes the bone powder, resulting in the compression and collapse of the bone graft around the implant, and maintaining the osteogenic space around the implant.

[0003] Currently, in an intelligent medical system, the transmission of maxillary sinus stent signals is achieved through inter-process communication. After the signals are transmitted to the intelligent terminal, they are printed as maxillary sinus CT images and then passed to the patients and physicians. In this signal transmission method, since the discrimination of the detected CT signals of the maxillary sinus stent can only rely on the clinical experience of the physician, it is difficult to classify and transmit according to the stored information of the maxillary sinus stent signals. Therefore, in the prior art, inter-process communication needs to transmit signals one by one in chronological order through a common inter-system process communication link. When there is too much information to be processed on the inter-process communication link, a large number of application programs will be delayed in receiving cross-process information, resulting in low efficiency of inter-process communication. Patients and physicians need to wait for a long time to obtain the CT images of the maxillary sinus stent. Summary of the Invention

[0004] This application provides a method and system for transmitting maxillary sinus stent signals in an intelligent medical system, which can classify and transmit according to the stability of the maxillary sinus stent signals, and improve the transmission speed of abnormal maxillary sinus stent signals.

[0005] In a first aspect, this application provides a method for transmitting maxillary sinus stent signals in an intelligent medical system, including:

[0006] The main control process of the intelligent medical system establishes connections with multiple sub-processes, and the multiple sub-processes include the first sub-process and the second sub-process in the intelligent medical system;

[0007] The first sub-process obtains the maxillary sinus stent signals sent by the maxillary sinus stent signal sender, and performs signal decision sub-adjustment on the maxillary sinus stent signals according to a preset standard comparison matrix to obtain multiple stent signal decision entropies;

[0008] Obtain the user's physical sign signals, perform relevant feature extraction on multiple stent signal decision entropies according to the user's physical sign signals, and obtain the stability of the maxillary sinus stent signal.

[0009] The first subprocess returns the stability of the maxillary sinus stent signal to the main control process, and the main control process selects a communication link according to the stability of the maxillary sinus stent signal.

[0010] The first subprocess transmits the maxillary sinus stent signal to the second subprocess of the intelligent medical system according to the selected communication link.

[0011] Combined with the first aspect, in some implementation manners of the first aspect, before obtaining multiple stent signal decision entropies by performing signal decision sub - adjustment on the maxillary sinus stent signal according to a preset standard comparison matrix, it further includes: the first subprocess sends a signal decision sub - adjustment request instruction to the main control process.

[0012] Combined with the first aspect, in some implementation manners of the first aspect, the first subprocess transmitting the maxillary sinus stent signal to the second subprocess of the intelligent medical system according to the selected communication link specifically includes: the first subprocess first sends the maxillary sinus stent signal to the main control process, and after receiving the message, the main control process forwards the maxillary sinus stent signal to the second subprocess through the selected communication link.

[0013] Combined with the first aspect, in some implementation manners of the first aspect, the first subprocess and the second subprocess in the intelligent medical system perform signal transmission through multiple communication links, and the multiple communication links include a first communication link and a second communication link.

[0014] Combined with the first aspect, in some implementation manners of the first aspect, the maxillary sinus stent signal includes: the first maxillary sinus stent CT voxel information and the second maxillary sinus stent CT voxel information of the user of the intelligent medical system.

[0015] Combined with the first aspect, in some implementation manners of the first aspect, performing signal decision sub - adjustment on the maxillary sinus stent signal according to a preset standard comparison matrix to obtain multiple stent signal decision entropies specifically includes:

[0016] Obtain the first maxillary sinus stent CT voxel information and the second maxillary sinus stent CT voxel information in the maxillary sinus stent signal;

[0017] Perform edge information extraction on the first maxillary sinus stent CT voxel information to obtain first edge voxel information;

[0018] Perform edge information extraction on the second maxillary sinus stent CT voxel information to obtain second edge voxel information;

[0019] Obtain a preset standard comparison matrix, extract the coordinates of each standard edge voxel in the standard comparison matrix, and determine a plurality of stent signal decision entropies according to the first edge voxel information, the second edge voxel information, and all the standard edge voxel coordinates.

[0020] Combined with the first aspect, in some implementation manners of the first aspect, extracting edge information from the first maxillary sinus stent CT voxel information to obtain the first edge voxel information specifically includes:

[0021] Obtain the CT scanning direction and the voxel threshold;

[0022] According to the CT scanning direction and the voxel threshold, screen all the voxel values in the first maxillary sinus stent CT voxel information to obtain a plurality of edge voxel values, and form all the edge voxels into the first edge voxel information;

[0023] Determining a plurality of stent signal decision entropies according to the first edge voxel information, the second edge voxel information, and all the standard edge voxel coordinates specifically includes:

[0024] Obtain the position coordinates corresponding to all the edge voxel values in the first edge voxel information, and perform position difference on the position coordinates corresponding to all the edge voxel values in the first edge voxel information according to the CT scanning direction to obtain a first stent width value sequence;

[0025] Obtain the position coordinates corresponding to all the edge voxel values in the first edge voxel information, and perform position difference on the position coordinates corresponding to all the edge voxel values in the first edge voxel information according to the CT scanning direction to obtain a second stent width value sequence;

[0026] Determine a stent width value difference sequence according to the first stent width value sequence and the second stent width value sequence;

[0027] Obtain all the standard edge voxel coordinates, perform position difference on all the standard edge voxel coordinates according to the CT scanning direction to obtain a standard stent width value sequence;

[0028] Determine a plurality of stent signal decision entropies according to the standard stent width value sequence and the stent width value difference sequence.

[0029] In a second aspect, the present application provides a maxillary sinus stent signal transmission system for an intelligent medical system, including a signal transmission unit, and the signal transmission unit includes:

[0030] A processing module, configured to call the main control process of the intelligent medical system to establish connections with a plurality of sub-processes, and the plurality of sub-processes include a first sub-process and a second sub-process in the intelligent medical system;

[0031] A processing module, configured to call the first subprocess to obtain a maxillary sinus stent signal sent by a signal sending end of the maxillary sinus stent, and perform signal decision sub - adjustment on the maxillary sinus stent signal according to a preset standard comparison matrix to obtain a plurality of stent signal decision entropies;

[0032] A processing module, configured to obtain a user physical sign signal, and perform relevant feature extraction on a plurality of stent signal decision entropies according to the user physical sign signal to obtain the stability of the maxillary sinus stent signal;

[0033] A processing module, configured to call the first subprocess to return the stability of the maxillary sinus stent signal to the main control process, and the main control process selects a communication link according to the stability of the maxillary sinus stent signal;

[0034] An execution module, configured to call the first subprocess to transmit the maxillary sinus stent signal to a second subprocess of the intelligent medical system according to the selected communication link.

[0035] In a third aspect, the present application provides a computer terminal device, which includes a memory and a processor. The memory stores code, and the processor is configured to obtain the code and execute the above - mentioned method for transmitting a maxillary sinus stent signal for an intelligent medical system.

[0036] In a fourth aspect, the present application provides a computer - readable storage medium, which stores at least one computer program, and the computer program is loaded and executed by a processor to implement the operations performed by the above - mentioned method for transmitting a maxillary sinus stent signal for an intelligent medical system.

[0037] The technical solution provided by the disclosed embodiments of the present application has the following beneficial effects:

[0038] In a method and system for transmitting maxillary sinus stent signals for an intelligent medical system provided by this application, first, the maxillary sinus stent signals sent by the maxillary sinus stent signal transmitter are obtained, and the maxillary sinus stent signals are subjected to signal decision sub - adjustment according to a preset standard comparison matrix to obtain multiple stent signal decision entropies, thereby realizing the preliminary classification and analysis of the signals to determine the stability and abnormality degree of each group of information in the Shanghedu stent signals; the user's physical sign signals are obtained, and relevant features are extracted from the multiple stent signal decision entropies according to the user's physical sign signals to obtain the stability of the maxillary sinus stent signals; the first subprocess returns the stability of the maxillary sinus stent signals to the main control process, and the main control process selects a communication link according to the stability of the maxillary sinus stent signals. The lower the signal stability, that is, the higher the abnormality degree of the signal, the higher - speed and lower - signal - compression - rate communication link is preferentially selected to ensure that abnormal signals can be transmitted quickly and accurately; the first subprocess transmits the maxillary sinus stent signals to the second subprocess of the intelligent medical system according to the selected communication link. This application selects a communication link according to the stability of the maxillary sinus stent signals and conducts signal transmission, realizing the classified transmission of the maxillary sinus stent signals, avoiding the situation that the maxillary sinus stent signals with a higher abnormality degree cannot be transmitted for a long time due to queue waiting, and improving the transmission speed of abnormal maxillary sinus stent signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is an exemplary flowchart of a method for transmitting maxillary sinus stent signals for an intelligent medical system according to some embodiments of this application;

[0040] Figure 2 is an exemplary flowchart for determining the stent signal decision entropy in some embodiments of this application;

[0041] Figure 3 is a schematic diagram of the exemplary hardware and / or software of a signal transmission unit according to some embodiments of this application;

[0042] Figure 4 is a schematic diagram of the structure of a computer terminal device for implementing a method for transmitting maxillary sinus stent signals for an intelligent medical system according to some embodiments of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] This application obtains the maxillary sinus stent signal sent by the signal sending end of the maxillary sinus stent, and performs signal decision sub - adjustment on the maxillary sinus stent signal according to a preset standard comparison matrix to obtain multiple stent signal decision entropies; obtains the user's physical sign signal, extracts relevant features from the multiple stent signal decision entropies according to the user's physical sign signal to obtain the stability of the maxillary sinus stent signal; the first subprocess returns the stability of the maxillary sinus stent signal to the main control process, and the main control process selects a communication link according to the stability of the maxillary sinus stent signal; the first subprocess transmits the maxillary sinus stent signal to the second subprocess of the intelligent medical system according to the selected communication link. This application selects a communication link according to the stability of the maxillary sinus stent signal and performs signal transmission, realizing the classified transmission of the maxillary sinus stent signal, avoiding the situation that the maxillary sinus stent signal with a higher degree of abnormality cannot be transmitted for a long time due to queue waiting, and improving the transmission speed of the abnormal maxillary sinus stent signal.

[0044] To better understand the above - mentioned technical solution, the following will explain the above - mentioned technical solution in detail in combination with the accompanying drawings of the specification and specific implementation manners. Refer to Figure 1 , which is an exemplary flowchart of a method for transmitting a maxillary sinus stent signal for an intelligent medical system according to some embodiments of the present application. The method 100 for transmitting a maxillary sinus stent signal for an intelligent medical system mainly includes the following steps:

[0045] In step S101, the main control process of the intelligent medical system establishes connections with multiple subprocesses, and the multiple subprocesses include the first subprocess and the second subprocess in the intelligent medical system.

[0046] In this application, the intelligent medical system is a regional medical information platform for health records. The intelligent medical system uses advanced information technology and Internet of Things technology to achieve efficient interaction among patients, medical staff, medical institutions, and medical devices by constructing and integrating electronic health records, intelligent devices, and data analysis platforms, improving the quality and efficiency of medical services.

[0047] It should be noted that the main control process in the software system for implementing the intelligent medical system is the core process, responsible for coordinating and managing multiple subprocesses. In some embodiments, the main control process runs on an operating system that supports multitasking, such as Linux, Windows, embedded RTOS, etc. The main responsibilities of the main control process include: creating and starting subprocesses, monitoring the status and performance of subprocesses, receiving data and status information returned by subprocesses, making decisions and allocating tasks according to the data of subprocesses, and maintaining the overall stability and reliability of the intelligent medical system.

[0048] Optionally, in some embodiments, the first subprocess and the second subprocess in the intelligent medical system described in this application transmit signals through multiple communication links, where the multiple communication links include a first communication link and a second communication link. Specifically, in implementation, the first communication link and the second communication link are inter-process communication links, which can specifically be communication pipes or message queues, etc.

[0049] In step S102, the first subprocess acquires the maxillary sinus stent signal sent by the maxillary sinus stent signal sender, and performs signal decision sub-adjustment on the maxillary sinus stent signal according to a preset standard comparison matrix to obtain multiple stent signal decision entropies.

[0050] Optionally, in some embodiments, the maxillary sinus stent signal includes: the first maxillary sinus stent CT voxel information of the user and the second maxillary sinus stent CT voxel information of the user. Specifically, in implementation, the maxillary sinus stent signal sender can be a signal transmission device mounted on a CT scanner. It should be noted that the first maxillary sinus stent CT voxel information and the second maxillary sinus stent CT voxel information are respectively CT value matrices composed of CT values collected at different voxel positions after the user undergoes the first and second facial CT scans. The voxel value in this application is the CT value corresponding to each voxel position in the CT value matrix, and the voxel coordinate is the matrix coordinate in the CT value scan matrix.

[0051] It should be noted that the stent signal decision entropy is a decision parameter for making a decision on the communication link of the maxillary sinus stent signal. The stent signal decision entropy is determined based on the information standard degree of the first maxillary sinus stent CT voxel information and the second maxillary sinus stent CT voxel information in the maxillary sinus stent signal. Optionally, in some embodiments, as shown in Figure 2 This figure is an exemplary flowchart for determining the stent signal decision entropy in some embodiments of this application. Performing signal decision sub-adjustment on the maxillary sinus stent signal according to a preset standard comparison matrix to obtain multiple stent signal decision entropies can be implemented by the following steps:

[0052] In step S1021, acquire the first maxillary sinus stent CT voxel information and the second maxillary sinus stent CT voxel information in the maxillary sinus stent signal; extract the edge information from the first maxillary sinus stent CT voxel information to obtain the first edge voxel information;

[0053] In step S1022, extract the edge information from the second maxillary sinus stent CT voxel information to obtain the second edge voxel information;

[0054] In step S1023, obtain a preset standard comparison matrix, extract the coordinates of each standard edge voxel in the standard comparison matrix, and determine a plurality of stent signal decision entropies according to the first edge voxel information, the second edge voxel information, and all the standard edge voxel coordinates.

[0055] It should be noted that as a tomographic scanning technology, CT scanning forms the CT value scanning matrix by scanning the X-ray penetration degrees of different cross-sections inside the user's body. Therefore, the CT value acquisition time for each row of the matrix in the CT scanning direction is the same. The number of finally determined stent signal decision entropies in this application is equal to the number of rows of the CT value scanning matrix in the CT scanning direction. Each stent signal decision entropy is used to reflect the abnormality degree of one row of CT values in the CT value scanning matrix of the first maxillary sinus stent CT voxel information and the second maxillary sinus stent CT voxel information. Furthermore, according to the correlation degree between the multiple stent signal decision entropies and the user's physical signs information, determine the abnormal situation of the maxillary sinus stent signal.

[0056] Optionally, in some embodiments, the extraction of the edge information from the first maxillary sinus stent CT voxel information to obtain the first edge voxel information can be implemented by the following steps:

[0057] Obtain the CT scanning direction and the voxel threshold;

[0058] According to the CT scanning direction and the voxel threshold, screen all the voxel values in the first maxillary sinus stent CT voxel information to obtain a plurality of edge voxel values, and form the first edge voxel information by all the edge voxels.

[0059] In some embodiments, each voxel value vector of the CT value matrix in the CT scanning direction of the first maxillary sinus stent CT voxel information can be classified according to the voxel threshold respectively to obtain a stent region voxel value set and a background region voxel value set. Furthermore, all the stent region voxel values in the boundary region are used as edge voxel values to form the first edge voxel information. Specifically, when implemented, the CT scanning direction is defaulted to be longitudinal, and the voxel threshold can be calibrated as a constant according to the attenuation coefficient of the X-ray of the maxillary sinus stent material. For example, when the maxillary sinus stent is a bone-like material, the voxel threshold can be set as a constant between 400 and 1000.

[0060] Optionally, in some embodiments, when the step of extracting the edge information from the second maxillary sinus stent CT voxel information to obtain the second edge voxel information is specifically implemented, the same method as that for extracting the edge information from the first maxillary sinus stent CT voxel information can be adopted, which will not be elaborated here.

[0061] Optionally, in some embodiments, before performing signal decision sub - adjustment on the maxillary sinus stent signal according to a preset standard comparison matrix to obtain multiple stent signal decision entropies, the following is further included: a first sub - process sends a signal decision sub - adjustment request instruction to the main control process.

[0062] In some embodiments, a corresponding storage unit in the first sub - process contains a preset standard comparison matrix, and the standard comparison matrix is a CT value scan matrix of the maxillary sinus stent in a standard environment. In the process of extracting the respective standard edge voxel coordinates in the standard comparison matrix, the same method for extracting edge information from the first maxillary sinus stent CT voxel information can be used to extract all edge voxel points in the CT value scan matrix, and the voxel coordinates corresponding to each edge voxel point are used as the standard edge voxel coordinates, where the voxel coordinates can be matrix coordinates in the CT value scan matrix.

[0063] Optionally, in some embodiments, determining multiple stent signal decision entropies according to the first edge voxel information, the second edge voxel information, and all standard edge voxel coordinates can be implemented by the following steps:

[0064] Obtain the position coordinates corresponding to all edge voxel values in the first edge voxel information, and perform position difference on the position coordinates corresponding to all edge voxel values in the first edge voxel information according to the CT scan direction to obtain a first stent width value sequence;

[0065] Obtain the position coordinates corresponding to all edge voxel values in the first edge voxel information, and perform position difference on the position coordinates corresponding to all edge voxel values in the first edge voxel information according to the CT scan direction to obtain a second stent width value sequence;

[0066] Determine a stent width value difference sequence according to the first stent width value sequence and the second stent width value sequence;

[0067] Obtain all standard edge voxel coordinates, perform position difference on all standard edge voxel coordinates according to the CT scan direction to obtain a standard stent width value sequence;

[0068] Determine multiple stent signal decision entropies according to the standard stent width value sequence and the stent width value difference sequence.

[0069] In some embodiments, the first stent width value sequence, the second stent width value sequence, and the standard stent width value sequence are each composed of respective stent width values. The position difference according to the CT scanning direction is specifically represented as, for example, the first stent width value in the first stent width value sequence, which is specifically the abscissa difference between two edge voxel values in the first row matrix of the CT value scanning matrix in the first edge voxel information in the CT scanning direction. The remaining stent width values are determined in the same manner and will not be elaborated here.

[0070] It should be noted that the difference between the stent width value and the standard stent width value can reflect the stent position fluctuation caused by various factors. Among them, the stent position fluctuation caused by respiratory pressure will affect the effect of the maxillary sinus internal lift procedure and even lead to the risk of rupture of the patient's maxillary sinus mucosa.

[0071] Optionally, in some embodiments, the stent width value difference sequence is the difference sequence between the first stent width value sequence and the second stent width value sequence. The number of the stent signal decision entropies is equal to the sequence length of the standard stent width value sequence. The stent signal decision entropy is the ratio between each sequence value in the stent width value difference sequence and each sequence value in the standard stent width value sequence. For example, the first stent signal decision entropy is the ratio between the first sequence value in the stent width value difference sequence and the first sequence value in the standard stent width value sequence. It should be noted that each stent signal decision entropy reflects the degree of information abnormality collected during a single tomographic scan of the CT signal.

[0072] In step S103, a user physical sign signal is obtained, and relevant features are extracted from multiple stent signal decision entropies according to the user physical sign signal to obtain the stability of the maxillary sinus stent signal.

[0073] Optionally, in some embodiments, the user physical sign signal includes: the respiratory frequency information of the user corresponding to the maxillary sinus stent signal. Specifically, when implemented, the user physical sign signal can be collected by a respiratory frequency sensor worn on the user when collecting the first maxillary sinus stent CT voxel information and the second maxillary sinus stent CT voxel information of the user.

[0074] It should be noted that the maxillary sinus stent is used for bone implant transplantation in the maxillary sinus area. However, when the maxillary sinus mucosa is successfully dissected, the filling of bone grafts is carried out blindly. Due to the large elasticity of the mucosa, there is no restraint on the bone grafts during the filling process, and the breathing pressure will also push the bone powder, often resulting in the bone grafts not being able to be stable above the tip of the implant but being compressed and collapsed around the implant. It is difficult to maintain the lifting height at the top of the implant. If it cannot be repaired in time and the compression of the breathing pressure on the bone graft material is not reduced, there will be a risk of mucosal rupture and failure of osteogenesis at the root end of the implant. In this application, relevant features are extracted from the decision entropy of multiple stent signals according to the user's physical sign signals. According to the correlation between the breathing frequency in the user's physical sign information and the fluctuation of the decision entropy of the stent signal, it can be determined whether the abnormal degree of the stent signal is caused by the user's breathing pressure, so as to timely detect and classify and transmit the abnormal maxillary sinus stent signals in this part, which can avoid message blockage when the abnormal maxillary sinus stent signals in this part are transmitted between processes, enabling the position of the maxillary sinus stent of the intelligent medical system user to be corrected in time and reducing the risk of surgical failure of the intelligent medical system user.

[0075] Optionally, in some embodiments, extracting relevant features from the decision entropy of multiple stent signals according to the user's physical sign signals to obtain the stability of the maxillary sinus stent signal can be achieved by the following steps:

[0076] Obtain the user's physical sign signals, obtain the CT scanning speed value, and obtain the CT scaling coefficient;

[0077] According to the user's physical sign signals, the CT scanning speed value, and the CT scaling coefficient, determine the physical sign influence period of the maxillary sinus stent;

[0078] Group the decision entropy of multiple stent signals according to the physical sign influence period to obtain multiple signal decision sequences;

[0079] Perform cross-correlation feature extraction according to multiple signal decision sequences to obtain the stability of the maxillary sinus stent signal.

[0080] Specifically, the CT scanning speed value can be obtained through the signal transmission device installed in the CT scanner. The CT scaling coefficient represents the scaling ratio of the voxel distance to the actual distance in the two-dimensional direction in the CT voxel information of the first maxillary sinus stent and the CT voxel information of the user's second maxillary sinus stent. In some embodiments, the ratio of the number of rows of the CT value scanning matrix to the CT scanning distance in the CT voxel information of the first maxillary sinus stent can be used as the CT scaling coefficient.

[0081] Optionally, in some embodiments, the sign influence period of the maxillary sinus stent is the fluctuation period of the maxillary sinus stent signal caused by the user's breathing frequency. Specifically, when implemented, the sign influence period of the maxillary sinus stent = floor[CT scan speed value / (user breathing frequency × CT scaling factor)].

[0082] Preferably, in some embodiments, grouping the multiple stent signal decision entropies according to the sign influence period to obtain multiple signal decision sequences specifically includes: performing equally-spaced grouping on the multiple stent signal decision entropies according to the sign influence period of the maxillary sinus stent. For example, when the sign influence period of the maxillary sinus stent is X, the 1st, the (1 + X)th, the (1 + 2X)th, etc. stent signal decision entropies are sequentially used as the first signal decision sequence, and the 2nd, the (2 + X)th, the (2 + 2X)th, etc. stent signal decision entropies are sequentially used as the second signal decision sequence, thereby obtaining multiple signal decision sequences. The number of the signal decision sequences is equal to the sign influence period value of the maxillary sinus stent, obtaining multiple signal decision sequences. In some embodiments, the mean value of the Pearson correlation coefficients between the respective signal decision sequences can be used as the stability of the maxillary sinus stent signal.

[0083] In step S104, the first subprocess returns the stability of the maxillary sinus stent signal to the main control process, and the main control process selects a communication link according to the stability of the maxillary sinus stent signal.

[0084] Optionally, in some embodiments, the main control process selecting a communication link according to the stability of the maxillary sinus stent signal can be implemented by the following steps:

[0085] Obtain a stability threshold;

[0086] When the stability of the maxillary sinus stent signal is higher than the preset stability threshold, the main control process takes the first communication link as the selected communication link;

[0087] When the stability of the maxillary sinus stent signal is lower than the preset stability threshold, the main control process takes the second communication link as the selected communication link.

[0088] Optionally, in some embodiments, the stability threshold can be calibrated as a constant according to historical experience. In some embodiments, it can also be determined through implementation. For example, implanting a maxillary sinus stent in a pig model with tooth defects and obtaining the maxillary sinus stent signal, and using the stability of the maxillary sinus stent signal of this maxillary sinus stent signal as the stability threshold, which will not be elaborated here.

[0089] Optionally, in some embodiments, the signal compression degree of the second communication link during signal transmission is relatively low. The second communication link is set as the communication link with a relatively low signal compression degree, so as to improve the signal integrity and quality of the maxillary sinus stent signal with a relatively high degree of abnormality during transmission. For example, after the maxillary sinus stent information in the maxillary sinus stent signal with a relatively high degree of abnormality transmitted through the second communication link is printed into a CT image, it has a relatively high resolution, while the maxillary sinus stent information in the maxillary sinus stent signal with a relatively low degree of abnormality transmitted through the first communication link can be partially compressed and pooled, so as to avoid process congestion and improve the transmission efficiency.

[0090] In step S105, the first subprocess transmits the maxillary sinus stent signal to the second subprocess of the intelligent medical system according to the selected communication link.

[0091] Optionally, in some embodiments, the first subprocess transmitting the maxillary sinus stent signal to the second subprocess of the intelligent medical system according to the selected communication link can be implemented by the following steps: the first subprocess first sends the maxillary sinus stent signal to the main control process, and after receiving the message, the main control process forwards the maxillary sinus stent signal to the second subprocess through the selected communication link.

[0092] In addition, on the other hand of the present application, in some embodiments, the present application provides a maxillary sinus stent signal transmission system for an intelligent medical system. The system includes a signal transmission unit. Refer to Figure 3 , this figure is a schematic diagram of exemplary hardware and / or software of the signal transmission unit shown according to some embodiments of the present application. The signal transmission unit 200 includes: a processing module 201 and an execution module 202, which are described as follows:

[0093] The processing module 201, in some specific embodiments of the present application, the processing module 201 is used to call the main control process of the intelligent medical system to establish connections with multiple subprocesses. The multiple subprocesses include the first subprocess and the second subprocess in the intelligent medical system;

[0094] The processing module 201, in some specific embodiments of the present application, the processing module 201 is used to call the first subprocess to obtain the maxillary sinus stent signal sent by the maxillary sinus stent signal sender, and perform signal decision sub - adjustment on the maxillary sinus stent signal according to a preset standard comparison matrix to obtain multiple stent signal decision entropies;

[0095] The processing module 201, in some specific embodiments of the present application, the processing module 201 is used to obtain the user physical sign signal, and perform relevant feature extraction on multiple stent signal decision entropies according to the user physical sign signal to obtain the maxillary sinus stent signal stability;

[0096] The processing module 201, in some specific embodiments of the present application, the processing module 201 is used to call the first subprocess to return the signal stability of the maxillary sinus stent to the main control process, and the main control process selects a communication link according to the signal stability of the maxillary sinus stent;

[0097] The execution module 202, in some specific embodiments of the present application, the execution module 202 is mainly used to call the first subprocess to transmit the maxillary sinus stent signal to the second subprocess of the intelligent medical system according to the selected communication link.

[0098] The above has introduced in detail an example of a method for transmitting a maxillary sinus stent signal for an intelligent medical system provided by the embodiments of the present application. It can be understood that, in order to implement the above functions, the corresponding device includes the corresponding hardware structure and / or software module for executing each function.

[0099] Those skilled in the art should easily realize that, combining the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function in the application is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Therefore, those skilled in the art can use different methods to implement the described function for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0100] In addition, the present application also provides a computer terminal device, the computer terminal device includes a memory and a processor, the memory stores code, and the processor is configured to obtain the code and execute the above-mentioned method for transmitting a maxillary sinus stent signal for an intelligent medical system.

[0101] In some embodiments, refer to Figure 4 , this figure is a schematic structural diagram of a computer terminal device applying a method for transmitting a maxillary sinus stent signal for an intelligent medical system according to some embodiments of the present application. The above-mentioned method for transmitting a maxillary sinus stent signal for an intelligent medical system in the above embodiments can be implemented by Figure 4 the computer terminal device shown. The computer terminal device 300 includes at least one communication bus 301, a communication interface 302, a processor 303, and a memory 304.

[0102] The processor 303 can be a general-purpose central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more are used to control the execution of a method for transmitting signals of a maxillary sinus stent in an intelligent medical system of the present application.

[0103] The communication bus 301 may include a path for transmitting information between the above components.

[0104] The memory 304 can be a read-only memory (ROM), or other types of static storage devices that can store static information and instructions, a random access memory (RAM), or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disks, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 304 can exist independently and be connected to the processor 303 through the communication bus 301. The memory 304 can also be integrated with the processor 303.

[0105] Among them, the memory 304 is used to store the program code for executing the solution of the present application, and is controlled by the processor 303 to execute. The processor 303 is used to execute the program code stored in the memory 304. The program code may include one or more software modules. The determination of the signal stability of the maxillary sinus stent in the above embodiments can be implemented by one or more software modules in the program code in the processor 303 and the memory 304.

[0106] The communication interface 302, using any device such as a transceiver, is used to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0107] Optionally, the above computer terminal device 300 may further include a power supply 305 for supplying power to various components or circuits in the real-time computer terminal device.

[0108] In a specific implementation, as an embodiment, the computer terminal device may include multiple processors, and each of these processors may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, the processor may refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0109] The above computer terminal device may be a general-purpose computer terminal device or a dedicated computer terminal device. In a specific implementation, the computer terminal device may be a desktop computer, a laptop computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of the present application do not limit the type of the computer terminal device.

[0110] In addition, in other aspects of the present application, there is provided a computer-readable storage medium storing at least one computer program, and the computer program is loaded and executed by a processor to implement the operations performed by the above-mentioned method for transmitting signals of a maxillary sinus stent for an intelligent medical system.

[0111] In summary, in a method and system for transmitting signals of a maxillary sinus stent for an intelligent medical system disclosed in the embodiments of the present application, first, a maxillary sinus stent signal sent by a maxillary sinus stent signal sending end is obtained, and signal decision sub-adjustment is performed on the maxillary sinus stent signal according to a preset standard comparison matrix to obtain multiple stent signal decision entropies; a user physical sign signal is obtained, and relevant feature extraction is performed on the multiple stent signal decision entropies according to the user physical sign signal to obtain the stability of the maxillary sinus stent signal; the first subprocess returns the stability of the maxillary sinus stent signal to the main control process, and the main control process selects a communication link according to the stability of the maxillary sinus stent signal; the first subprocess transmits the maxillary sinus stent signal to the second subprocess of the intelligent medical system according to the selected communication link. The present application selects a communication link according to the stability of the maxillary sinus stent signal and performs signal transmission, realizing classified transmission of the maxillary sinus stent signal, avoiding that a maxillary sinus stent signal with a higher degree of abnormality cannot be transmitted for a long time due to queue waiting, and improving the transmission speed of the abnormal maxillary sinus stent signal.

[0112] The above are only embodiments of the present application, and common general technical solutions or features in the solutions are not described in detail herein. It should be noted that for those skilled in the art, without departing from the technical solution of the present application, several modifications and improvements can be made, which should also be regarded as the protection scope of the present application, and these will not affect the implementation effect of the present application and the practicality of the patent.

[0113] The protection scope required by the present application shall be subject to the content of its claims, and the specific implementation manners and the like recorded in the specification can be used to interpret the content of the claims. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these changes and modifications.

Claims

1. A maxillary sinus stent signal transmission method for an intelligent medical system, characterized in that: include: A main control process of the intelligent medical system establishes a connection with a plurality of sub-processes, wherein the plurality of sub-processes include a first sub-process and a second sub-process in the intelligent medical system; The first sub-process obtains the maxillary sinus stent signal sent by the maxillary sinus stent signal sending end, and performs signal decision separation and modulation on the maxillary sinus stent signal according to a preset standard comparison matrix to obtain multiple stent signal decision entropies; Acquire a user's vital sign signal, extract relevant features of multiple stent signal decision entropies according to the user's vital sign signal, and obtain the stability of the maxillary sinus stent signal; The first sub-process returns the stability of the maxillary sinus stent signal to the main control process, and the main control process selects a communication link according to the stability of the maxillary sinus stent signal; The first subprocess transmits the maxillary sinus bracket signal to a second subprocess of the intelligent medical system according to the selected communication link; The maxillary sinus stent signal includes: the first maxillary sinus stent CT voxel information and the second maxillary sinus stent CT voxel information of the user of the intelligent medical system. The maxillary sinus stent signal is subjected to signal decision separation according to a preset standard contrast matrix, and the multiple stent signal decision entropies are obtained, which specifically include: Acquire the first maxillary sinus stent CT voxel information and the second maxillary sinus stent CT voxel information in the maxillary sinus stent signal; Extracting edge information from the first maxillary sinus stent CT voxel information to obtain first edge voxel information; Extracting edge information from the second maxillary sinus stent CT voxel information to obtain second edge voxel information; Obtaining a preset standard contrast matrix, extracting coordinates of each standard edge voxel in the standard contrast matrix, and determining a plurality of stent signal decision entropies according to the first edge voxel information, the second edge voxel information and all standard edge voxel coordinates; Among them, the user vital sign signal includes: the maxillary sinus stent signal corresponds to the user's breathing rate information, the stent signal decision entropy is the ratio between each sequence value in the stent width value differential sequence determined based on the first edge voxel information and the second edge voxel information and each sequence value in the standard stent width value sequence, the first maxillary sinus stent CT voxel information and the second maxillary sinus stent CT voxel information are respectively CT value matrices composed of CT values ​​collected at different voxel positions after performing one and two facial CT scans on the user.

2. The method according to claim 1, characterized in that The signal decision and modulation of the maxillary sinus stent signal is performed according to a preset standard comparison matrix to obtain multiple stent signal decision entropies, and the method also includes: the first sub-process sends a signal decision and modulation request instruction to the main control process.

3. The method according to claim 1, characterized in that The first sub-process transmits the maxillary sinus stent signal to the second sub-process of the intelligent medical system according to the selected communication link. Specifically, the first sub-process first sends the maxillary sinus stent signal to the main control process, and after receiving the message, the main control process forwards the maxillary sinus stent signal to the second sub-process through the selected communication link.

4. The method according to claim 1, characterized in that The first sub-process and the second sub-process in the intelligent medical system transmit signals through multiple communication links, and the multiple communication links include the first communication link and the second communication link.

5. The method according to claim 1, characterized in that Extracting edge information from the first maxillary sinus stent CT voxel information to obtain first edge voxel information specifically includes: Obtain CT scan direction and voxel threshold; According to the CT scanning direction and the voxel threshold, all voxel values ​​in the first maxillary sinus stent CT voxel information are screened to obtain a plurality of edge voxel values, and all edge voxels are combined into the first edge voxel information; Determining the decision entropies of multiple stent signals according to the first edge voxel information, the second edge voxel information and all standard edge voxel coordinates specifically includes: Acquire position coordinates corresponding to all edge voxel values ​​in the first edge voxel information, and perform position differentiation on the position coordinates corresponding to all edge voxel values ​​in the first edge voxel information according to a CT scanning direction to obtain a first stent width value sequence; Acquire position coordinates corresponding to all edge voxel values ​​in the first edge voxel information, and perform position differentiation on the position coordinates corresponding to all edge voxel values ​​in the first edge voxel information according to a CT scanning direction to obtain a second stent width value sequence; Determining a bracket width value difference sequence according to the first bracket width value sequence and the second bracket width value sequence; Obtain all standard edge voxel coordinates, perform positional differentiation on all standard edge voxel coordinates according to the CT scanning direction, and obtain a standard stent width value sequence; A plurality of bracket signal decision entropies are determined based on the standard bracket width value sequence and the bracket width value difference sequence.

6. A maxillary sinus stent signal transmission system for an intelligent medical system, which uses the method according to any one of claims 1 to 5 to perform maxillary sinus stent signal transmission, the system comprising a signal transmission unit, characterized in that: The signal transmission unit comprises: A processing module, used for calling a main control process of the intelligent medical system to establish a connection with a plurality of sub-processes, wherein the plurality of sub-processes include a first sub-process and a second sub-process in the intelligent medical system; A processing module, used for calling the first sub-process to obtain the maxillary sinus stent signal sent by the maxillary sinus stent signal sending end, and performing signal decision separation and modulation on the maxillary sinus stent signal according to a preset standard comparison matrix to obtain a plurality of stent signal decision entropies; A processing module, used for acquiring a user's vital sign signal, extracting relevant features of a plurality of stent signal decision entropies according to the user's vital sign signal, and obtaining the stability of the maxillary sinus stent signal; A processing module, used for calling the first sub-process to return the stability of the maxillary sinus stent signal to the main control process, and the main control process selects a communication link according to the stability of the maxillary sinus stent signal; An execution module is used to call the first sub-process to transmit the maxillary sinus bracket signal to the second sub-process of the intelligent medical system according to the selected communication link.

7. A computer terminal device, characterized in that: The computer terminal device includes a memory and a processor, the memory stores codes, and the processor is configured to obtain the codes and execute a maxillary sinus stent signal transmission method for an intelligent medical system as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing at least one computer program, characterized in that: The computer program is loaded and executed by a processor to implement the operations performed by a maxillary sinus stent signal transmission method for an intelligent medical system as described in any one of claims 1 to 5.

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