Knee joint imaging method and device, server and storage medium

Abstract

The invention discloses a knee joint imaging method and device, a server and a storage medium. The method is executed by a server, the server is in wireless communication connection with electrical impedance imaging equipment and terminal equipment, and the method comprises the following steps: receiving electrical impedance imaging data collected by the electrical impedance imaging equipment for a knee joint area of a target object; performing image reconstruction on the basis of electrical impedance imaging data acquired from the knee joint area of the target object through an electrical impedance imaging device to obtain a knee joint effusion detection image; the knee joint effusion detection image is sent to terminal equipment, and the terminal equipment displays the knee joint effusion detection image through a graphical user interface. According to the technical scheme, the electrical impedance imaging data collected by the knee joint area of the target object is subjected to image reconstruction through the server, cloud imaging is achieved, compared with an existing local imaging scheme, the image reconstruction speed is increased, a high-performance computer does not need to be installed locally, and knee joint effusion detection is more convenient.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to a knee joint imaging method, device, server and storage medium. Background Art

[0002] Knee effusion is a common symptom of knee disease and can be caused by a variety of factors, including trauma, inflammatory disease, or degenerative changes. Accurate detection and monitoring of knee effusion is crucial for diagnosis, treatment, and rehabilitation.

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

[0004] Existing electrical impedance imaging technologies are all solved locally and require local high-performance computers for processing. They have poor portability and cannot meet the diagnosis and treatment needs of knee joint lesions caused by accidents during outdoor work. Summary of the Invention

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

[0006] According to one aspect of the present invention, a knee joint imaging method is provided, which is performed by a server, wherein the server is wirelessly connected to an electrical impedance imaging device and a terminal device, respectively, and the method comprises:

[0007] receiving electrical impedance imaging data collected from a knee joint region of a target subject by an electrical impedance imaging device;

[0008] Reconstructing the electrical impedance imaging data collected from the knee joint area of ​​the target object by the electrical impedance imaging device to obtain a knee joint effusion detection image;

[0009] 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.

[0010] According to another aspect of the present invention, there is provided a knee joint imaging apparatus, which is executed by a server, wherein the server is wirelessly connected to an electrical impedance imaging device and a terminal device, respectively, and the apparatus comprises:

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

[0012] a knee joint image reconstruction module, configured to reconstruct an image based on the electrical impedance imaging data collected from the knee joint area of ​​the target object by the electrical impedance imaging device, to obtain a knee joint effusion detection image;

[0013] The terminal device image display module is used to send 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.

[0014] According to another aspect of the present invention, a server is provided, comprising:

[0015] at least one processor;

[0016] and a memory communicatively coupled to the at least one processor;

[0017] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the knee joint imaging method described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the knee joint imaging method described in any embodiment of the present invention when executed.

[0019] According to the technical solution of the embodiment of the present invention, the knee joint imaging method is executed by a server, and the server is wirelessly connected to 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 area 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 area of ​​the target object to obtain a knee joint effusion detection image. The server then 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 realizes cloud imaging by reconstructing the electrical impedance imaging data collected by the server on the knee joint area of ​​the target object. Compared with the existing local imaging solution, the use of the server improves the image reconstruction speed and does not require the installation of a high-performance computer locally, making knee joint effusion detection more convenient and meeting the diagnosis and treatment needs of knee joint lesions caused by accidents during outdoor work.

[0020] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 This is a flow chart of a knee joint imaging method provided according to the first embodiment of the present invention;

[0023] Figure 2 1 is a schematic structural diagram of an electrical impedance tomography system provided according to an embodiment of the present invention;

[0024] Figure 3 is a flow chart of a knee joint imaging method provided according to embodiment 2 of the present invention;

[0025] Figure 4 This is a schematic structural diagram of a knee joint imaging device provided according to a third embodiment of the present invention;

[0026] Figure 5 2 is a schematic diagram of the structure of a server for implementing the knee joint imaging method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

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

[0029] Example 1

[0030] Figure 1 This is a flowchart of a knee joint imaging method provided in the first embodiment of the present invention. This embodiment is applicable to the case where knee joint image reconstruction is performed on a server. The method can be executed by a knee joint imaging device, which can be implemented in the form of hardware and / or software. The knee joint imaging device can be configured in a server, and the server is wirelessly connected to the electrical impedance imaging device and the terminal device. Figure 1 As shown, the method includes:

[0031] S110: Receive electrical impedance imaging data collected from a knee joint area of ​​a target object by an electrical impedance imaging device.

[0032] An electrical impedance tomography device refers to a wearable device capable of acquiring electrical impedance tomography data. It may include a current excitation system, a signal acquisition system, and a controller. The current excitation system and the controller may communicate via a serial peripheral interface protocol, while the signal acquisition system and the controller may communicate via an integrated circuit bus protocol. The target object may 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] For example, an EIT device can use an ESP8266 wireless module to transmit EIT data collected from a target patient's knee joint to a server in real time. The server then receives the data. The server and the EIT device can communicate using the Message Queuing Telemetry Transport (MQTT) protocol, making the transmission of EIT data more flexible and efficient.

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

[0035] For example, the server may reconstruct the electrical impedance imaging data collected from the knee joint area of ​​the target object using a finite element model reconstruction algorithm (such as the Newton-Raphson algorithm) or other reconstruction algorithms to obtain a knee joint effusion detection image.

[0036] In some embodiments, the server may be a distributed server cluster, which may use GPU acceleration technology to increase the image reconstruction speed to ensure real-time data processing.

[0037] In some embodiments, the server may also generate a diagnosis and treatment recommendation report based on the knee joint effusion detection image, and send the diagnosis and treatment recommendation report to the terminal device for user query and analysis.

[0038] S130: 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.

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

[0040] For example, an interactive web page can be constructed using Web front-end technology, and the knee joint effusion detection image can be loaded into the interactive web page. Users can access the interactive web page through electronic devices such as mobile phones, tablets, or personal computers, thereby achieving multi-terminal access to 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 to the low-pass filter, and the low-pass filter is connected to the constant current module; the waveform generator is used to generate a sine wave of a preset frequency and amplitude; the low-pass filter is used to low-pass filter the sine wave of a preset frequency and amplitude; and the constant current module is used to output a constant current based on the sine wave after low-pass filtering.

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

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

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

[0045] Figure 2 FIG. 1 is a schematic structural diagram of an electrical impedance imaging system according to an embodiment of the present invention; FIG. Figure 2 As shown, the electrical impedance imaging system includes 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 transmission communication protocol, and the server and the terminal device can communicate through mobile communication or wireless communication methods such as Wi-Fi. The electrical impedance imaging device includes 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, and the signal acquisition system and the controller can communicate through an integrated circuit bus communication protocol. The current excitation system includes a waveform generator, a low-pass filter and a constant current module, etc. The signal acquisition system includes an analog-to-digital conversion module with a sampling rate of 40Msps, an operational amplifier and an electrode interface, etc.

[0046] According to the technical solution of the embodiment of the present invention, the knee joint imaging method is executed by a server, and the server is wirelessly connected to 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 area 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 area of ​​the target object to obtain a knee joint effusion detection image. The server then 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 realizes cloud imaging by reconstructing the electrical impedance imaging data collected by the server on the knee joint area of ​​the target object. Compared with the existing local imaging solution, the use of the server improves the image reconstruction speed and does not require the installation of a high-performance computer locally, making knee joint effusion detection more convenient and meeting the diagnosis and treatment needs of knee joint lesions caused by accidents during outdoor work.

[0047] Example 2

[0048] Figure 3A flowchart of a knee joint imaging method provided in embodiment 2 of the present invention, the method of this embodiment can be combined with the various optional schemes in the knee joint imaging method provided in the above embodiments. The knee joint imaging method provided in this embodiment has been further optimized. Optionally, the image reconstruction is performed on the electrical impedance imaging data collected from the knee joint area of ​​the target object by the electrical impedance imaging device to obtain a knee joint effusion detection image, including: based on the Newton-Raphson algorithm and the Tickhoff regularization algorithm, the image reconstruction is performed on the electrical impedance imaging data collected from the knee joint area of ​​the target object by the electrical impedance imaging device to obtain a knee joint effusion detection image.

[0049] like Figure 3 As shown, the method includes:

[0050] S210: Receive electrical impedance imaging data collected from a knee joint area of ​​a target object by an electrical impedance imaging device.

[0051] S220 , based on the Newton-Raphson algorithm and the Tickhoff regularization algorithm, reconstruct the electrical impedance imaging data collected from the knee joint area of ​​the target object by the electrical impedance imaging device to obtain a knee joint effusion detection image.

[0052] S230: 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.

[0053] The existing Newton-Raphson algorithm suffers from defects such as inaccurate reconstructed images and unstable reconstruction effects due to the pathological and nonlinear nature of its inverse problem. The embodiment of the present invention introduces the Tickhoff regularization algorithm to effectively suppress noise and artifacts in the reconstructed image and improve the stability of the reconstructed image.

[0054] Among them, the objective functions corresponding to the Newton-Raphson algorithm and the Tickhoff regularization algorithm are:

[0055] ;

[0056] Where 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 the error term of the objective function, which represents 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.

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

[0058] Example 3

[0059] Figure 4 This is a schematic diagram of the structure of a knee joint imaging device provided by the third embodiment of the present invention. The knee joint imaging device is executed by a server, and the server is wirelessly connected to the electrical impedance imaging device and the terminal device, such as Figure 4 As shown, the device includes:

[0060] The electrical impedance imaging data acquisition module 310 is configured to receive electrical impedance imaging data acquired from the knee joint region of the target object by an electrical impedance imaging device;

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

[0062] The terminal device image display module 330 is 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] According to the technical solution of the embodiment of the present invention, the knee joint imaging method is executed by a server, and the server is wirelessly connected to 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 area 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 area of ​​the target object to obtain a knee joint effusion detection image. The server then 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 realizes cloud imaging by reconstructing the electrical impedance imaging data collected by the server on the knee joint area of ​​the target object. Compared with the existing local imaging solution, the use of the server improves the image reconstruction speed and does not require the installation of a high-performance computer locally, making knee joint effusion detection more convenient and meeting the diagnosis and treatment needs of knee joint lesions caused by accidents during outdoor work.

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

[0065] Based on the Newton-Raphson algorithm and the Tickhoff regularization algorithm, image reconstruction is performed on the electrical impedance imaging data collected from the knee joint area of ​​the target object by the electrical impedance imaging device to obtain a knee joint effusion detection image.

[0066] In some optional implementations, the objective functions corresponding to the Newton-Raphson algorithm and the Tickhoff regularization algorithm are:

[0067] ;

[0068] Where 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 the error term of the objective function, which represents 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.

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

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

[0071] In some optional embodiments, the current excitation system includes a waveform generator, a low-pass filter, and a constant current module, wherein the waveform generator is connected to the low-pass filter, and the low-pass filter is connected to the constant current module;

[0072] The waveform generator is used to generate a sine wave of preset frequency and amplitude;

[0073] The low-pass filter is used to perform low-pass filtering on the sine wave of the preset frequency and amplitude;

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

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

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

[0077] The knee joint imaging device provided in the embodiment of the present invention can execute the knee joint imaging method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0078] Example 4

[0079] Figure 5FIG2 is a block diagram of a server 10 that can be used to implement an embodiment of the present invention. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit 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 the at least one processor. Processor 11 can perform various appropriate actions and processes based on the computer programs 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] Various components in the server 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard and mouse; an output unit 17, such as various types of displays and speakers; a storage unit 18, such as a magnetic disk and optical disk; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the server 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

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

[0083] receiving electrical impedance imaging data collected from a knee joint region of a target subject by an electrical impedance imaging device;

[0084] Reconstructing the electrical impedance imaging data collected from the knee joint area of ​​the target object by the electrical impedance imaging device to obtain a knee joint effusion detection image;

[0085] 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.

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

[0087] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0088] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0089] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or apparatus. A computer-readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0090] To provide interaction with a user, the systems and techniques described herein 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 pointing device (e.g., a mouse or trackball) through which the user can provide input to the server. Other types of devices can also be used to provide interaction with the user; for example, the 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 input, voice input, or tactile input).

[0091] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, 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] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0093] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0094] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A knee joint imaging method, characterized in that: The method is executed by a server, wherein the server is wirelessly connected to an electrical impedance imaging device and a terminal device respectively, and the method includes: receiving electrical impedance imaging data collected from a knee joint region of a target subject by an electrical impedance imaging device; Reconstructing the electrical impedance imaging data collected from the knee joint area of ​​the target object by the electrical impedance imaging device to obtain a knee joint effusion detection image; 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.

2. The method according to claim 1, characterized in that The method of reconstructing the image based on the electrical impedance imaging data collected from the knee joint area of ​​the target object by the electrical impedance imaging device to obtain a knee joint effusion detection image includes: Based on the Newton-Raphson algorithm and the Tickhoff regularization algorithm, image reconstruction is performed on the electrical impedance imaging data collected from the knee joint area of ​​the target object by the electrical impedance imaging device to obtain a knee joint effusion detection image.

3. The method according to claim 2, characterized in that The objective functions corresponding to the Newton-Raphson algorithm and Tickhoff regularization algorithm are: ； Where 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 the error term of the objective function, which represents 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.

4. The method according to claim 1, wherein The server communicates with the electrical impedance imaging device via a message queue telemetry transmission communication protocol.

5. The method according to claim 1, wherein The electrical impedance imaging device includes a current excitation system, a signal acquisition system and a controller. The current excitation system communicates with the controller via a serial peripheral interface communication protocol, and the signal acquisition system communicates with the controller via an integrated circuit bus communication protocol.

6. The method according to claim 5, characterized in that The current excitation system includes a waveform generator, a low-pass filter, and a constant current module, wherein the waveform generator is connected to the low-pass filter, and the low-pass filter is connected to the constant current module; The waveform generator is used to generate a sine wave of preset frequency and amplitude; The low-pass filter is used to perform low-pass filtering on the sine wave of the preset frequency and amplitude; The constant current module is used to output a constant current based on the sine wave after low-pass filtering.

7. The method according to claim 5, characterized in that The signal acquisition system includes an analog-to-digital conversion module with a sampling rate of 40Msps; The signal acquisition system sends the acquired electrical impedance imaging data to the controller through the analog-to-digital conversion module with a sampling rate of 40Msps.

8. A knee joint imaging device, characterized in that: The method is executed by a server, wherein the server is wirelessly connected to an electrical impedance imaging device and a terminal device respectively, and the apparatus comprises: An electrical impedance imaging data acquisition module, configured to receive electrical impedance imaging data acquired from a knee joint region of a target object by an electrical impedance imaging device; a knee joint image reconstruction module, configured to reconstruct an image based on the electrical impedance imaging data collected from the knee joint area of ​​the target object by the electrical impedance imaging device, to obtain a knee joint effusion detection image; The terminal device image display module is used to send 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.

9. A server, characterized in that: The server includes: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the knee joint imaging method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the knee joint imaging method according to any one of claims 1 to 7 when executed.

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