Knee joint imaging method, device, server and storage medium

Abstract

The application discloses a knee joint imaging method and device, a server and a storage medium. The method is executed by the server, the server is wirelessly connected with an electrical impedance imaging device and a terminal device, and the method comprises the following steps: receiving electrical impedance imaging data collected by the electrical impedance imaging device on a knee joint region of a target object; performing image reconstruction on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object to obtain a knee joint effusion detection image; and sending the knee joint effusion detection image to the terminal device, and displaying the knee joint effusion detection image on the terminal device through a graphical user interface. According to the technical scheme, the electrical impedance imaging data collected by the server on the knee joint region of the target object is subjected to image reconstruction, cloud imaging is realized, compared with the existing local imaging scheme, the image reconstruction speed is improved, and a high-performance computer does not need to be installed locally, so that the knee joint effusion detection is more convenient.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of image processing, and in particular to a knee joint imaging method and device, a server and a storage medium. BACKGROUND

[0002] Knee joint effusion is one of the common symptoms of knee joint diseases, which can be caused by various reasons, including trauma, inflammatory diseases or degenerative changes. Accurate detection and monitoring of knee joint effusion are crucial for the diagnosis, treatment and rehabilitation of diseases.

[0003] With the development of technology, electrical impedance tomography (EIT) is increasingly widely used in medical imaging. Electrical impedance tomography technology reconstructs tissue structure images by measuring the impedance of biological tissue to electric current, providing new possibilities for non-invasive medical imaging.

[0004] Existing electrical impedance tomography technology is all calculated locally and needs to rely on local high-performance computers for processing, which has poor portability and cannot meet the diagnosis and treatment needs of knee joint lesions caused by accidents in outdoor operations. SUMMARY

[0005] The present application provides a knee joint imaging method, device, server and storage medium to generate a knee joint effusion detection image in the cloud, improve the image reconstruction speed, and meet the diagnosis and treatment needs of knee joint lesions caused by accidents in outdoor operations.

[0006] According to an aspect of the present application, a knee joint imaging method is provided, which is executed by a server wirelessly connected with an electrical impedance tomography device and a terminal device, and the method comprises:

[0007] receiving electrical impedance imaging data collected by the electrical impedance tomography device on the knee joint region of a target object;

[0008] performing image reconstruction based on the electrical impedance imaging data collected by the electrical impedance tomography device on the knee joint region of the target object to obtain a knee joint effusion detection image;

[0009] sending the knee joint effusion detection image to the terminal device, and the terminal device displays the knee joint effusion detection image through a graphical user interface.

[0010] According to another aspect of the present application, a knee joint imaging device is provided, which is executed by a server wirelessly connected with an electrical impedance tomography device and a terminal device, and the device comprises:

[0011] An electrical impedance imaging data acquisition module, configured to receive electrical impedance imaging data collected by an electrical impedance imaging device on a knee joint region of a target object;

[0012] A knee joint image reconstruction module, configured to perform image reconstruction based on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object, to obtain a knee joint effusion detection image;

[0013] A terminal device image display module, configured to send the knee joint effusion detection image to a terminal device, and the terminal device displays the knee joint effusion detection image through a graphical user interface.

[0014] According to another aspect of the present application, a server is provided, which comprises:

[0015] at least one processor;

[0016] and a memory connected in communication with the at least one processor;

[0017] wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the knee joint imaging method according to any one of the embodiments of the present application.

[0018] According to another aspect of the present application, a computer readable storage medium is provided, which stores computer instructions for enabling a processor to perform the knee joint imaging method according to any one of the embodiments of the present application when executed by the processor.

[0019] The technical solution of the embodiments of the present application is that the knee joint imaging method is performed by a server, the server is wirelessly connected with an electrical impedance imaging device and a terminal device, the server receives electrical impedance imaging data collected by the electrical impedance imaging device on a knee joint region of a target object, then the server performs image reconstruction based on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object, to obtain a knee joint effusion detection image, and then the server sends the knee joint effusion detection image to the terminal device, and the terminal device displays the knee joint effusion detection image through a graphical user interface. The above technical solution performs image reconstruction on the electrical impedance imaging data collected by the server on the knee joint region of the target object, realizes cloud imaging, and compared with the existing local imaging scheme, the use of the server improves the image reconstruction speed, and a high-performance computer does not need to be installed locally, so that the knee joint effusion detection is more convenient, and the diagnosis and treatment demand of knee joint lesions caused by accidents in outdoor work is met.

[0020] It is to be understood that the details set forth herein do not limit the scope of the embodiments of the application to the specific embodiments described. Rather, the scope of the embodiments of the application is to be defined by the appended claims. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0022] Figure 1 is a flow chart of a knee joint imaging method according to an embodiment of the present application;

[0023] Figure 2 is a structural schematic diagram of an electrical impedance imaging system according to an embodiment of the present application;

[0024] Figure 3 is a flow chart of a knee joint imaging method according to an embodiment of the present application;

[0025] Figure 4 is a structural schematic diagram of a knee joint imaging device according to an embodiment of the present application;

[0026] Figure 5 is a structural schematic diagram of a server for implementing a knee joint imaging method according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the technical personnel in the art better understand the present application scheme, the following will combine the drawings in the embodiments of the present application, and the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only some embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present application.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and in the above drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices. The acquisition, storage, use, processing, etc. of data in the technical solutions of the present application comply with the relevant provisions of national laws and regulations.

[0029] Embodiment one

[0030] Figure 1 A flowchart of a knee joint imaging method provided for the first embodiment of the present application, the present embodiment can be applicable to the case of knee joint image reconstruction in a server, the method can be executed by a knee joint imaging device, which can be realized in the form of hardware and / or software, and the knee joint imaging device can be configured in a server, which is wirelessly communicated and connected with an electrical impedance imaging device and a terminal device. As shown in the figure, the method comprises: Figure 1

[0031] S110, receiving electrical impedance imaging data collected by an electrical impedance imaging device on the knee joint region of a target object.

[0032] The electrical impedance imaging device refers to a wearable device capable of realizing electrical impedance imaging data collection, which can include a current excitation system, a signal acquisition system and a controller, etc. The current excitation system and the controller can communicate through serial peripheral interface communication protocol, and the signal acquisition system and the controller can communicate through integrated circuit bus communication protocol. The target object can be a human or an animal, and the knee joint region includes the lower end of the femur, the upper end of the tibia and the patella.

[0033] Exemplarily, the electrical impedance imaging device can send the electrical impedance imaging data collected on the knee joint region of the target object to the server in real time through the ESP8266 wireless module, and the server receives the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object. The server and the electrical impedance imaging device can communicate through the Message Queuing Telemetry Transport (MQTT) communication protocol, so that the transmission of the electrical impedance imaging data is more flexible and efficient.

[0034] ​S120, image reconstruction is performed on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object, to obtain a knee joint effusion detection image.

[0035] Exemplarily, the server can perform image reconstruction on the electrical impedance imaging data collected on the knee joint region of the target object by a reconstruction algorithm of a finite element model (such as a Newton-Raphson algorithm) or other reconstruction algorithms, to obtain a knee joint effusion detection image.

[0036] In some embodiments, the server can be a distributed server cluster, which can employ GPU acceleration technology to improve the image reconstruction speed, to ensure the real-time performance of data processing.

[0037] In some embodiments, the server can further generate a diagnosis and treatment suggestion report according to the knee joint effusion detection image, and send the diagnosis and treatment suggestion report to the terminal device for user query and analysis.

[0038] S130, the knee joint effusion detection image is sent to a terminal device, and the terminal device displays the knee joint effusion detection image through a graphical user interface.

[0039] The terminal device can be a mobile phone, a tablet computer, or a personal computer, etc., which is not specifically limited here.

[0040] Exemplarily, an interactive web page can be constructed through Web front-end technology, and then the knee joint effusion detection image is loaded to the interactive web page, and the user can access the interactive web page through a mobile phone, a tablet computer, or a personal computer, etc., to realize multi-terminal access of the knee joint effusion detection image.

[0041] In some optional embodiments, the current excitation system includes a waveform generator, a low-pass filter, and a constant current module, the waveform generator is connected with the low-pass filter, and the low-pass filter is connected with the constant current module; the waveform generator is used to generate a sine wave with a preset frequency and amplitude; the low-pass filter is used to perform low-pass filtering on the sine wave with the preset frequency and amplitude; and the constant current module is used to output a constant current based on the low-pass filtered sine wave.

[0042] Exemplarily, the single-chip microcomputer can control the waveform generator to generate a sine wave with a frequency of 1-10 kHz; the low-pass filter is used to perform low-pass filtering on the sine wave with a frequency of 1-10 kHz, with an upper limit of 10 kHz; and the constant current module is used to output a constant current of 20 uA based on the low-pass filtered sine wave, and the electrodes are selected by the multiplexer for excitation.

[0043] In some optional embodiments, the signal acquisition system comprises an analog-digital conversion module with a sampling rate of 40 Msps; the signal acquisition system sends the collected electrical impedance imaging data to the controller through the analog-digital conversion module with a sampling rate of 40 Msps.

[0044] Exemplarily, the signal acquisition system sends the collected electrical impedance imaging data to the controller in parallel through the analog-digital conversion module with a sampling rate of 40 Msps, and can achieve a sampling data amount of 30 KB per second and an imaging speed of 100 frames per second.

[0045] Figure 2 is a structural schematic diagram of an electrical impedance imaging system according to an embodiment of the present application; as Figure 2 shown, the electrical impedance imaging system comprises a server, an electrical impedance imaging device and a terminal device, the server and the electrical impedance imaging device can communicate through a message queue telemetry transfer communication protocol, the server and the terminal device can communicate through mobile communication or wireless communication such as Wi-Fi, the electrical impedance imaging device comprises a current excitation system, a signal acquisition system and a controller, the current excitation system and the controller can communicate through a serial peripheral interface communication protocol, the signal acquisition system and the controller can communicate through an integrated circuit bus communication protocol, the current excitation system comprises a waveform generator, a low-pass filter and a constant current module, etc., and the signal acquisition system comprises an analog-digital conversion module with a sampling rate of 40 Msps, an operational amplifier and an electrode interface, etc.

[0046] The technical scheme of the embodiment of the present application, the knee joint imaging method is executed by the server, the server is wirelessly communicated and connected with the electrical impedance imaging device and the terminal device respectively, the server receives the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object, and then the server performs image reconstruction based on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object, obtains a knee joint effusion detection image, and then the server sends the knee joint effusion detection image to the terminal device, and the terminal device displays the knee joint effusion detection image through a graphical user interface. The above technical scheme, by performing image reconstruction on the electrical impedance imaging data collected by the server on the knee joint region of the target object, realizes cloud imaging, compared with the existing local imaging scheme, through the use of the server, the image reconstruction speed is improved, and a high-performance computer does not need to be installed locally, so that the knee joint effusion detection is more convenient, and the diagnosis and treatment demand of the knee joint lesion caused by accident in outdoor work is met.

[0047] Embodiment two

[0048] Figure 3A flowchart of a knee joint imaging method provided in Embodiment Two of the present application, the method of the present embodiment can be combined with each optional scheme in the knee joint imaging method provided in the above embodiments. The knee joint imaging method provided in the present embodiment is further optimized. Optionally, the image reconstruction based on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object to obtain the knee joint effusion detection image comprises: performing image reconstruction on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object based on the Newton-Raphson algorithm and the Tikhonov regularization algorithm to obtain the knee joint effusion detection image.

[0049] As shown in Figure 3 , the method comprises:

[0050] S210, receiving electrical impedance imaging data collected by an electrical impedance imaging device on a knee joint region of a target object.

[0051] S220, performing image reconstruction on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object based on the Newton-Raphson algorithm and the Tikhonov regularization algorithm to obtain a knee joint effusion detection image.

[0052] S230, sending the knee joint effusion detection image to a terminal device, and the terminal device displays the knee joint effusion detection image through a graphical user interface.

[0053] The existing Newton-Raphson algorithm has defects such as inaccurate reconstructed image and unstable reconstruction effect due to the ill-posedness and nonlinearity of its inverse problem. By introducing the Tikhonov regularization algorithm, the present embodiment can effectively suppress noise and artifacts in the reconstructed image and improve the stability of the reconstructed image.

[0054] The objective functions corresponding to the Newton-Raphson algorithm and the Tikhonov regularization algorithm are:

[0055] ;

[0056] Wherein, x represents the electrical impedance imaging data, y represents the actual knee joint effusion image, A represents the sensitivity matrix, and lambda represents the regularization parameter; The error term of the objective function represents the difference between the knee joint effusion detection image and the actual knee joint effusion image. The regularization term is used to control the smoothness of the knee joint effusion detection image.

[0057] The technical scheme of the present embodiment can effectively suppress noise and artifacts in the reconstructed image and improve the stability of the reconstructed image by introducing the Tikhonov regularization algorithm.

[0058] Embodiment three

[0059] Figure 4 A structural schematic diagram of a knee joint imaging device provided for embodiment three of the present application. The knee joint imaging device is executed by a server, which is respectively wirelessly connected with an electrical impedance imaging device and a terminal device. As shown in the figure, the device comprises: Figure 4

[0060] An electrical impedance imaging data acquisition module 310, configured to receive electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of a target object;

[0061] A knee joint image reconstruction module 320, configured to perform image reconstruction based on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object, to obtain a knee joint effusion detection image;

[0062] A terminal device image display module 330, configured to send the knee joint effusion detection image to a terminal device, and the terminal device displays the knee joint effusion detection image through a graphical user interface.

[0063] The technical scheme of the embodiment of the present application, the knee joint imaging method is executed by a server, the server is respectively wirelessly connected with an electrical impedance imaging device and a terminal device, the server receives electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of a target object, and then the server performs image reconstruction based on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object, to obtain a knee joint effusion detection image, and then the server sends the knee joint effusion detection image to a terminal device, and the terminal device displays the knee joint effusion detection image through a graphical user interface. The above technical scheme, by performing image reconstruction on the electrical impedance imaging data collected by the server on the knee joint region of the target object, realizes cloud imaging, compared with the existing local imaging scheme, through the use of the server, the image reconstruction speed is improved, and high-performance computers do not need to be installed locally, so that the knee joint effusion detection is more convenient, and the diagnosis and treatment demand of knee joint lesions caused by accidents in outdoor work is met.

[0064] In some optional embodiments, the knee joint image reconstruction module 320 can be specifically configured to:

[0065] Perform image reconstruction on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object based on a Newton-Raphson algorithm and a Tikhonov regularization algorithm, to obtain a knee joint effusion detection image.

[0066] In some optional embodiments, the objective function corresponding to the Newton-Raphson algorithm and the Tikhonov regularization algorithm is:

[0067] ​ ;

[0068] wherein, x represents the electrical impedance imaging data, y represents the actual knee effusion image, A represents the sensitivity matrix, and λ represents the regularization parameter; is an error term of the objective function, representing the difference between the knee effusion detection image and the actual knee effusion image; is a regularization term, used to control the smoothness of the knee effusion detection image.

[0069] In some optional embodiments, the server communicates with the electrical impedance imaging device through a message queue telemetry transport communication protocol.

[0070] In some optional embodiments, the electrical impedance imaging device comprises a current excitation system, a signal acquisition system and a controller, the current excitation system communicates with the controller through a serial peripheral interface communication protocol, and the signal acquisition system communicates with the controller through an integrated circuit bus communication protocol.

[0071] In some optional embodiments, the current excitation system comprises a waveform generator, a low-pass filter and a constant current module, the waveform generator is connected with the low-pass filter, and the low-pass filter is connected with the constant current module.

[0072] The waveform generator is configured to generate a sine wave with a preset frequency and amplitude.

[0073] The low-pass filter is configured to perform low-pass filtering on the sine wave with the preset frequency and amplitude.

[0074] The constant current module is configured to output a constant current based on the low-pass filtered sine wave.

[0075] In some optional embodiments, the signal acquisition system comprises an analog-to-digital conversion module with a sampling rate of 40 Msps.

[0076] The signal acquisition system sends the collected electrical impedance imaging data to the controller through the analog-to-digital conversion module with the sampling rate of 40 Msps.

[0077] The knee imaging device provided by the embodiments of the present application can execute the knee imaging method provided by any of the embodiments of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0078] Embodiment Four

[0079] Figure 5A schematic diagram of the structure of a server 10 that can be used to implement embodiments of the present invention is shown. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the invention described and / or claimed herein.

[0080] like Figure 5 As shown, server 10 includes at least one processor 11 and memory, such as read-only memory (ROM) 12 and random access memory (RAM) 13, communicatively connected to at least one processor 11. The memory stores computer programs executable by at least one processor. Processor 11 can perform various appropriate actions and processes based on the computer program stored in ROM 12 or loaded from storage unit 18 into RAM 13. RAM 13 can also store various programs and data required for the operation of server 10. Processor 11, ROM 12, and RAM 13 are interconnected via bus 14. I / O interface 15 is also connected to bus 14.

[0081] Multiple components in server 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of monitors, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows server 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0082] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a knee joint imaging method, which includes:

[0083] Receive electrical impedance imaging data of the knee joint region of the target object acquired by an electrical impedance imaging device;

[0084] Based on the electrical impedance imaging data collected from the knee joint region of the target object by the electrical impedance imaging device, an image of knee joint effusion detection is obtained.

[0085] The knee joint effusion detection image is sent to a terminal device, which displays the knee joint effusion detection image through a graphical user interface.

[0086] In some embodiments, the knee imaging method can be implemented as a computer program tangibly embodied in a computer readable storage medium, e.g., storage unit 18. In some embodiments, parts or all of the computer program can be loaded and / or installed onto server 10 via, e.g., ROM 12 and / or communication unit 19. When the computer program is loaded onto RAM 13 and executed by processor 11, one or more steps of the above-described knee imaging method can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the knee imaging method by other means, e.g., with the aid of firmware.

[0087] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a complex programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0088] Computer programs used to implement the methods of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed by the processor of the machine, implements the functions / acts specified in the flowcharts and / or block diagrams. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as part of a separate software package, or entirely on a remote machine or server.

[0089] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0090] To provide for interaction with a user, the systems and techniques described here can be implemented on a server having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the server. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0091] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0092] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0093] It should be understood that the various forms of flow shown above can be used to reorder, add or delete steps. For example, each step described in the present application can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solutions of the present application can be achieved, which is not limited herein.

[0094] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method of imaging the knee joint, characterized by, The method is executed by a server wirelessly connected with an electrical impedance imaging device and a terminal device respectively, and the method comprises: receiving electrical impedance imaging data collected by the electrical impedance imaging device on a knee joint region of a target object; performing image reconstruction on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object to obtain a knee joint effusion detection image; sending the knee joint effusion detection image to a terminal device, and the terminal device displays the knee joint effusion detection image through a graphical user interface; the image reconstruction on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object to obtain the knee joint effusion detection image comprises: performing image reconstruction on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object to obtain the knee joint effusion detection image based on a Newton-Raphson algorithm and a Tikhonov regularization algorithm; a target function corresponding to the Newton-Raphson algorithm and the Tikhonov regularization algorithm is: ； Wherein, x represents the electrical impedance imaging data, y represents the actual knee joint effusion image, A represents the sensitivity matrix, and λ represents the regularization parameter; is an error term of the objective function, representing the difference between the knee joint effusion detection image and the actual knee joint effusion image; is a regularization term, used to control the smoothness of the knee joint effusion detection image; the electrical impedance imaging device comprises a current excitation system, a signal acquisition system and a controller, the current excitation system communicates with the controller through a serial peripheral interface communication protocol, and the signal acquisition system communicates with the controller through an integrated circuit bus communication protocol; the current excitation system comprises a waveform generator, a low-pass filter and a constant current module, the waveform generator is connected with the low-pass filter, and the low-pass filter is connected with the constant current module; the waveform generator is used for generating a sine wave with a preset frequency and amplitude; the low-pass filter is used for low-pass filtering the sine wave with the preset frequency and amplitude; the constant current module is used for outputting a constant current based on the low-pass filtered sine wave.

2. The method of claim 1, wherein, the server communicates with the electrical impedance imaging device through a message queue telemetry transmission communication protocol.

3. The method of claim 1, wherein, the signal acquisition system comprises a 40Msps sampling rate analog-to-digital conversion module; the signal acquisition system sends the collected electrical impedance imaging data to the controller through the 40Msps sampling rate analog-to-digital conversion module.

4. A knee imaging device, characterized by The device is executed by a server wirelessly connected with an electrical impedance imaging device and a terminal device respectively, and the device comprises: an electrical impedance imaging data acquisition module configured to receive electrical impedance imaging data collected by the electrical impedance imaging device on a knee joint region of a target object; a knee joint image reconstruction module configured to perform image reconstruction on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object to obtain a knee joint effusion detection image; a terminal device image display module configured to send the knee joint effusion detection image to a terminal device, and the terminal device displays the knee joint effusion detection image through a graphical user interface; the knee joint image reconstruction module is specifically configured to: perform image reconstruction on the electrical impedance imaging data collected by the electrical impedance imaging device on the knee joint region of the target object to obtain the knee joint effusion detection image based on a Newton-Raphson algorithm and a Tikhonov regularization algorithm; The objective functions corresponding to the Newton-Raphson algorithm and the Tikhonov regularization algorithm are: ； Wherein, x represents the electrical impedance imaging data, y represents the actual knee joint effusion image, A represents the sensitivity matrix, and λ represents the regularization parameter; is an error term of the objective function, representing the difference between the knee joint effusion detection image and the actual knee joint effusion image; is a regularization term, used to control the smoothness of the knee joint effusion detection image; The electrical impedance imaging device comprises a current excitation system, a signal acquisition system and a controller, the current excitation system communicates with the controller through a serial peripheral interface communication protocol, and the signal acquisition system communicates with the controller through an integrated circuit bus communication protocol; The current excitation system comprises a waveform generator, a low-pass filter and a constant current module, the waveform generator is connected with the low-pass filter, and the low-pass filter is connected with the constant current module; The waveform generator is used for generating a sine wave with a preset frequency and amplitude; The low-pass filter is used for low-pass filtering the sine wave with the preset frequency and amplitude; The constant current module is used for outputting a constant current based on the low-pass filtered sine wave.

5. A server, characterized by The server comprises: at least one processor; and a memory connected in communication with the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the knee imaging method of any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for enabling the processor to execute the knee imaging method of any one of claims 1-3 when executed.

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