WO2023093693A1 - Medical tool inspection method and system, computer device, and storage medium - Google Patents

Abstract

The present application relates to a medical tool inspection method and system, a computer device, and a storage medium. The method comprises: acquiring image and/or component state information collected by a medical tool; performing image overall performance parameter measurement on the image and/or performing fault detection according to the component state information, the image overall performance parameter measurement being obtained by calculation according to parameters of a selected area of the image; and outputting an image overall performance parameter measurement result and/or a fault detection result. By using the method, the intelligence level can be improved.

Description

Medical tool detection method, system, computer equipment and storage medium

related application

This application claims the priority of the Chinese patent application filed on November 23, 2021, with application number 202111393059.8, entitled "medical tool detection method, system, computer equipment and storage medium", which is hereby incorporated by reference in its entirety.

technical field

The present application relates to the technical field of medical devices, in particular to a medical tool detection method, system, computer equipment and storage medium.

Background technique

The endoscope enters the human body through the natural orifice of the human body, or through a small incision made through surgery. When in use, the endoscope is introduced into the organ to be inspected, and the changes of the relevant parts can be directly observed.

The quality of the endoscope image and whether it operates efficiently and safely directly affects the use effect of the endoscope, and also marks the development level of the endoscope technology. Therefore, the objective evaluation of endoscope image quality and real-time fault alarm play an important role in product safety.

However, current endoscopes can only determine whether the endoscope has a malfunction based on the user's feeling. For example, when the user uses the endoscope, according to the pictures collected by the endoscope, he checks the pictures through human experience to determine whether the endoscope is malfunctioning. If the image stays on one interface, it may be artificially judged to be a collection failure or a network problem, and then check; if the image is blurred, it may be judged to be a lens contamination or a problem with the image sensor, and then check one by one, resulting in intelligent low level.

Contents of the invention

Based on this, it is necessary to provide a medical tool detection method, system, computer equipment and storage medium that can improve the level of intelligence in order to address the above technical problems.

A medical tool detection method, said method comprising:

Obtaining images and/or component status information collected by the medical tool;

Perform image overall performance parameter detection on the image and/or perform fault detection based on the component status information; the image overall performance parameter detection is calculated based on parameters of a selected area of the image;

Outputting the detection result of the overall performance parameter of the image and/or the result of the fault detection.

In one of the embodiments, the obtaining the image collected by the medical tool includes:

After the medical tool is turned on, acquire an image collected by the medical tool;

The said overall performance parameter detection of the image includes:

Performing quality analysis on the image to obtain an image index;

When the image index does not meet the preset requirements, generate information indicating that the detection of the overall image performance parameter fails; otherwise, generate information indicating that the detection of the overall image performance parameter succeeds.

In one of the embodiments, the results of the overall performance parameter detection of the output image include:

Obtain the unsatisfied image index according to the failure information of the overall image performance parameter detection, and output the unsatisfied image index and/or output the alarm information.

In one of the embodiments, the results of the overall performance parameter detection of the output image include:

Acquire all image indexes according to the successful detection information of the overall image performance parameters, and output the obtained image indexes.

In one of the embodiments, after the image index that does not meet the requirements is output, the method includes:

receiving an adjustment instruction of a control parameter corresponding to the image index;

The control parameter is adjusted according to the adjustment instruction, and the adjusted control parameter is sent to the image acquisition component of the medical tool.

In one of the embodiments, before acquiring the image collected by the medical tool, it also includes:

judging whether the medical tool is collecting images normally;

When the medical tool normally collects images, continue to acquire the images collected by the medical tool;

When the medical tool fails to capture an image, output a prompt message that the image capture fails.

In one embodiment, the method also includes:

During the detection of the overall performance parameters of the image, the stage information of the detection of the overall performance parameters of the image is output.

In one of the embodiments, performing image overall performance parameter detection on the image includes at least one of the following:

Performing image uniformity detection on the image, the image uniformity detection includes: dividing the image into at least two image areas, and calculating the area index of each image area, and calculating the overall uniformity of the image according to the area index index;

Performing image distortion rate detection on the image, the image distortion rate detection includes: calculating the restored image corresponding to the image, and obtaining the image center point, image boundary and restored image boundary, based on the image center point, image boundary and Restore the image boundary to calculate the image distortion rate;

Performing image signal-to-noise ratio detection on the image, the image signal-to-noise ratio detection includes: extracting a noise signal and an effective signal according to the image, and calculating an image signal-to-noise ratio according to the effective signal and the noise signal.

In one of the embodiments, the fault detection according to the component status information includes:

According to the real-time analysis of the component status information, the fault type is obtained;

Obtain the fault code corresponding to the fault type;

The output of the result of the fault detection includes:

Output the fault code.

In one of the embodiments, the fault detection based on the component status information includes at least one of the following:

Perform communication anomaly detection according to the component state information, and the communication anomaly detection includes at least one of error code detection, packet loss detection and timeout detection;

Performing temperature and humidity detection according to the component state information, the temperature and humidity detection includes performing threshold judgment according to data collected by the temperature and humidity sensor;

The service life detection is performed according to the component state information, and the service life detection includes the service life detection of at least one of the endoscope plug-in interface, the internal Flash of the endoscope and the image host, the fan of the image host, and the power supply module.

A medical tool detection system, the system comprising: a medical tool, an image processing host, a lighting source host, and a display; wherein, the image processing host and the lighting source host are respectively connected to the medical tool, and the display connected with the image processing host;

the medical tool is used to acquire images;

The lighting source host is used to provide medical cold light source;

The image processing host is used to execute the above medical tool detection method;

The display is used for displaying the detection result of the overall performance parameter of the image and/or the fault detection result.

In one of the embodiments, the image processing host is connected to the medical tool through an optical fiber, so as to acquire images collected by the medical tool.

In one of the embodiments, the image processing host is connected to the medical tool through a serial port, so as to obtain component status information of the medical tool.

In one of the embodiments, the display is connected to the image processing host through an HDMI cable, a DVI cable or a DP cable.

A computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned method are realized.

The above-mentioned medical tool detection method, device, computer equipment, and storage medium perform overall image performance parameter detection based on the image and/or perform fault detection based on component status information, and output the result of the overall image performance parameter detection and/or fault detection result, There is no need for manual judgment, so that medical tools can be detected at any time during or before use, and the overall performance parameters of the image can be detected and/or fault detection can be performed based on component status information to avoid medical tool failures. Inconvenient to use, thereby improving the level of intelligence.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application or the conventional technology, the following will briefly introduce the accompanying drawings that need to be used in the description of the embodiments or the traditional technology. Obviously, the accompanying drawings in the following description are only the present invention For the embodiments of the application, those skilled in the art can also obtain other drawings based on the disclosed drawings without creative effort.

FIG. 1 is a schematic diagram of a medical tool detection system in an embodiment of the present application.

FIG. 2 is a schematic diagram of data transmission of hardware devices in an embodiment of the present application.

FIG. 3 is a schematic diagram of various functional modules of the image processing host in an embodiment of the present application.

Fig. 4 is a schematic flowchart of a medical tool detection method in an embodiment of the present application.

FIG. 5 is a schematic diagram of image uniformity detection in an embodiment of the present application.

FIG. 6 is a flow chart of distortion rate detection in an embodiment of the present application.

FIG. 7 is a schematic diagram of distortion rate detection in an embodiment of the present application.

FIG. 8 is a flowchart of a method for detecting a signal-to-noise ratio in an embodiment of the present application.

FIG. 9 is a schematic diagram of a communication anomaly detection function in an embodiment of the present application.

FIG. 10 is a schematic diagram of a temperature and humidity detection function in an embodiment of the present application.

FIG. 11 is a schematic diagram of a service life detection function in an embodiment of the present application.

FIG. 12 is a schematic diagram of an overall image performance parameter detection process in an embodiment of the present application.

FIG. 13 is a schematic diagram of an overall image performance parameter detection process in another embodiment of the present application.

FIG. 14 is a schematic diagram of an overall image performance parameter detection process in still another embodiment of the present application.

FIG. 15 is a schematic diagram of a fault detection process in an embodiment of the present application.

FIG. 16 is a schematic diagram of a fault detection signal transmission process in an embodiment of the present application.

Fig. 17 is a schematic diagram of fault detection interaction in an embodiment of the present application.

FIG. 18 is an internal structure diagram of a computer device in an embodiment of the present application.

Detailed ways

In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

The medical tool detection method provided in this application can be applied to the medical tool detection system shown in FIG. 1 . The medical tool detection system includes a medical tool 101 , an image processing host 103 , an illumination source host 102 and a display 104 . The image processing host 103 and the illumination source host 102 are respectively connected to the medical tool 101 ; the display 104 is connected to the image processing host 103 .

The medical tool 101 is used to acquire images. For example, the medical tool 101 includes an image acquisition device and an illumination device; wherein the image acquisition device is used for acquiring images, and the illumination device is used for illuminating the target area.

The illuminating light source host 102 is used for providing a medical cold light source, for example, providing a medical cold light source in the abdominal cavity.

The image processing host 103 is used to execute the medical tool detection method hereinafter, mainly for acquiring images collected by the medical tool 101 and/or component status information, so as to perform image overall performance parameter detection and failure according to the image and/or component status information Detect, and send the detection result of the overall performance parameter of the image and/or the fault detection result to the display 104.

The display 104 is used for displaying the result of detection of overall performance parameters of the image and/or the result of fault detection.

Wherein, as shown in FIG. 2, FIG. 2 is a schematic diagram of hardware device data transmission in an embodiment. In this embodiment, the image processing host is connected to the medical tool through an optical fiber to obtain images collected by the medical tool; and/or the image The processing host is connected with the medical tool through the serial port, so as to obtain the status information of the components of the medical tool. In addition, the display is connected to the image processing host through an HDMI cable, a DVI cable or a DP cable.

In practical applications, the medical tool is an endoscope, in which the endoscope is connected to the image processing host through an optical fiber to transmit image signals; the status and control signals are transmitted to the image processing host through RS485 signals; the image processing host displays data through HDMI The /DVI/DP cable is connected to the monitor to detect the overall performance parameters of the image and transmit the fault detection results.

Wherein, the image processing host includes a main processor and state information acquisition modules of each sub-component, such as sub-component 1, sub-component 2 and sub-component 3 in the figure. In other embodiments, the state information acquisition module may also include other subcomponents, which are not specifically limited here. The status information acquisition module of each sub-component is used to receive the status information of the sub-components, and send the status information of the sub-components to the main processor, wherein the main processor can be FPGA (Field Programmable Gate Array, Field Programmable Logic Gate Array ).

With reference to FIG. 3 , FIG. 3 is a schematic diagram of various functional modules of the image processing host in an embodiment. In this embodiment, the image processing host mainly includes an overall image performance parameter detection module, a status detection module, a control and failure analysis module, and a display interface module.

Wherein, the overall image performance parameter detection module is used to detect the performance of the endoscope image, convert it into corresponding image performance parameters, and record it. The state detection module is used to actively obtain the state of the relevant sub-components of the endoscope image system, and record the state. The control and fault analysis module is used to control the power-on image self-inspection process and obtain image performance parameters, obtain the sub-component status information recorded by the status detection module in real time, analyze whether there is a fault, convert the analysis result into a fault code and record it; the display interface module is used To obtain image performance parameters and fault codes, and realize uploading and displaying image performance and fault codes.

In one embodiment, as shown in FIG. 4 , a medical tool detection method is provided, which is described by taking the application of the method to the image processing host in FIG. 1 as an example, including the following steps:

S402: Obtain images collected by the medical tool and/or component status information.

Specifically, the image refers to the image collected by the medical tool, which may refer to the first image collected by the medical tool after it is turned on, or the first image collected by the medical tool after it is turned on and moved to the target position; wherein The first image here refers to the image collected after the medical tool is stabilized, not specifically the first image.

The component status information is the status information collected for each component in the medical tool, including but not limited to the functional parameters of the communication component, the temperature and humidity of each component, and the service life information of each component.

In some embodiments, the image and component status information can be transmitted through different communication channels, for example, the image is transmitted through optical fiber, while the component status information is transmitted through serial communication.

S404: Perform overall image performance parameter detection on the image and/or perform fault detection based on component status information; wherein the overall image performance parameter detection is calculated based on parameters of a selected area of the image.

Specifically, in some embodiments, the overall performance parameter detection of the image is calculated based on parameters of a selected area of the image, where the selected area of the image is the entire image. In other embodiments, the selected area of the image can also be set as required, and is not limited to the entire image. Among them, the overall performance parameter detection of the image is mainly to realize the self-inspection of the medical tool, so as to judge whether the image index of the medical tool meets the requirements. For example, after the medical tool is turned on, it will immediately run the image overall performance parameter detection function to determine whether the image indicators meet the requirements, and if it meets the requirements, it will output a prompt that meets the requirements. In other embodiments, the overall performance parameter detection of the image may be performed periodically or irregularly after the medical tool is turned on, so as to ensure that the image index of the medical tool always meets the requirements.

The fault detection of component status information can be performed after the detection of the overall performance parameters of the image, or in parallel with the detection of the overall performance parameters of the image. In some embodiments, the fault detection is performed after the overall performance parameter detection of the image is passed. Wherein, the fault detection may be to compare the extracted component state information with a standard threshold to determine whether each component is in a normal state.

Wherein, performing image overall performance parameter detection on the image includes at least one of the following: performing image uniformity detection on the image, wherein the image uniformity detection includes: dividing the image into at least two image regions, and calculating the region index of each image region , calculate the overall uniformity index of the image according to the area index; detect the image distortion rate of the image, and the image distortion rate detection includes: calculate the restored image corresponding to the image, and obtain the image center point, image boundary and restored image boundary, based on the image center Points, image boundaries, and restored image boundaries are calculated to obtain the image distortion rate; image signal-to-noise ratio detection is performed on the image, and the image signal-to-noise ratio detection includes: extracting noise signals and effective signals according to the image, and calculating image information based on the effective signals and noise signals noise ratio.

Wherein, the overall performance parameter detection of the image may be to use a self-built algorithm to process the image to obtain corresponding image performance parameters. Performance parameters include, but are not limited to, color, dynamic range, signal-to-noise ratio, brightness, distortion rate, sharpness, and contrast. As shown in Figure 5, the image uniformity detection can be detected using the average variance method. Specifically, the image is evenly divided into several image regions, for example, a 1920x1080 resolution image is divided into 48x27 (40x40) image regions, and the average variance is calculated to obtain parameters related to image uniformity. Specifically, the following formula can be used for calculation:

Among them, x ₁ , x ₂ , x ₃ , ... x _(n-1) , x _n is the mean value of the image area, and x is the mean value of the whole image.

In other embodiments, the image uniformity detection may also be calculated using other existing methods, which is not limited in the present application.

In one embodiment, as shown in FIG. 6 and FIG. 7 , wherein FIG. 6 is a flow chart of distortion rate detection, and FIG. 7 is a schematic diagram of distortion rate detection. In this embodiment, regarding the calculation method of image distortion rate detection, The image processing host can obtain the coordinates of point A (image center point), point B (distorted image boundary), and point C (restored image boundary), assuming that they are (Xa, Ya), (Xb, Yb), ( Xc, Yc).

Among them, point B is obtained through image boundary detection calculation, and point C is obtained through distortion restoration calculation, then:

Wherein the distortion rate=(Δy/y)·100%, where y is the distance between the boundary point of the restored image and the center point of the image, and Δy is the distance between the boundary point of the restored image and the boundary point of the distorted image.

In one embodiment, as shown in FIG. 8 , FIG. 8 is a flow chart of a method for detecting SNR in one embodiment. Regarding the method for detecting SNR of an image, the image analysis and control module configures the image sensor to adjust Image brightness and exposure time, so as to adjust the output image data, so as to extract the noise signal and effective signal, and calculate the signal-to-noise ratio = effective signal/noise signal, record the result, wait for the image analysis and control module to read the information, so that you can Analyze image parameters.

In one embodiment, performing fault detection according to component state information includes at least one of the following: performing communication anomaly detection according to component state information, where communication anomaly detection includes at least one of error code detection, packet loss detection, and timeout detection; Status information for temperature and humidity detection, where temperature and humidity detection includes threshold judgment based on data collected by temperature and humidity sensors; service life detection based on component status information, where service life detection includes endoscope plug-in interface, endoscope and image host The service life detection of at least one of the internal Flash, the image host fan and the power supply module.

In one embodiment, as shown in FIG. 9 , FIG. 9 is a schematic diagram of a communication anomaly detection function in an embodiment. In this embodiment, each sub-component records the communication status in real time during normal operation, and the communication anomaly detection module performs Error detection, packet loss detection and timeout detection; error detection uses CRC (cyclic redundancy check code verification method); packet loss detection uses packet sequence encoding.

In one embodiment, as shown in FIG. 10, FIG. 10 is a schematic diagram of the temperature and humidity detection function in one embodiment. In this embodiment, a plurality of temperature and humidity sensors are used, and the measurement data is averaged to avoid detection errors; Humidity sensors can be arranged around the image sensor of the endoscope, around the photoelectric conversion chip, and around the image processing chip of the image host; when the temperature and humidity measurement data exceeds the threshold, the fault alarm information is recorded.

In one embodiment, as shown in FIG. 11, FIG. 11 is a schematic diagram of the service life detection function in one embodiment. In this embodiment, the components related to service life detection include endoscope plug-in interface, endoscope and The internal Flash of the image host, the fan of the image host, the power supply module, etc.; when the service life exceeds the threshold, the fault alarm information is recorded, and the service life can be expressed by the use time and/or the number of uses, so the image processing host is used in medical tools. , you can record the usage time and/or the number of usage times, so as to facilitate the judgment of the subsequent service life.

S406: Output the detection result of the overall image performance parameter and/or the fault detection result.

Specifically, the image processing host may output the detection result of the overall image performance parameter and/or the fault detection result after calculating and obtaining the detection result of the overall image performance parameter and/or the result of the fault detection. For example, the image processing host outputs the detection result of the overall performance parameter of the image and/or the fault detection result to a display, an indicator light or a buzzer and the like.

The above-mentioned medical tool detection method detects the overall performance parameters of the image and/or performs fault detection according to the component status information according to the image, and outputs the result of the overall performance parameter detection of the image and/or the result of the fault detection, which does not require manual judgment, so The level of intelligence has been improved.

In one embodiment, acquiring the image collected by the medical tool includes: acquiring the image collected by the medical tool after the medical tool is turned on. Detecting the overall performance parameters of the image, including: analyzing the quality of the image to obtain the image index; when the image index does not meet the preset requirements, generating information that the overall performance parameter detection of the image fails; otherwise generating information that the overall performance parameter detection of the image is successful .

In one embodiment, before obtaining the image collected by the medical tool, the medical tool detection method further includes: judging whether the medical tool collects the image normally; when the medical tool normally collects the image, continue to obtain the image collected by the medical tool; When the image cannot be collected, the prompt message of image collection failure will be output.

In one embodiment, as shown in FIG. 12, FIG. 12 is a schematic diagram of an overall image performance parameter detection process in one embodiment. In this embodiment, after the medical tool is turned on, it is judged whether the medical tool is normally collecting images. When the tool fails to capture an image, it outputs a prompt message of image capture failure, for example, to a display, so that the display actively prompts the user.

If the medical tool collects images normally, run the overall performance parameter detection function of the image to analyze the quality of the image to obtain image indicators, and judge whether the image indicators meet the preset requirements. If the relevant image indicators do not meet the preset requirements, the display will list the specific Unqualified items; when all the image indicators are met, the display will list the relevant parameters one by one.

In one embodiment, outputting the result of the detection of the overall performance parameters of the image includes: obtaining image indicators that do not meet the requirements according to the information that the detection of the overall performance parameters of the image fails, and outputting the image indicators that do not meet the requirements and/or outputting alarm information; or Acquire all image indexes according to the successful detection information of the overall image performance parameters, and output the obtained image indexes.

In one embodiment, after outputting the image index that does not meet the requirements, the medical tool detection method includes: receiving an adjustment instruction of the control parameter corresponding to the image index; adjusting the control parameter according to the adjustment instruction, and sending the adjusted control parameter to Image acquisition components to medical tools.

In one embodiment, as shown in FIG. 13 , FIG. 13 is a schematic diagram of an overall image performance parameter detection process in another embodiment. In this embodiment, first, the overall image performance parameter detection module acquires images collected by medical tools data, and then process the image data to obtain image performance parameters, and send the image performance parameters to the image analysis and control module, and the image analysis and control module sends the detection results of the overall performance parameters of the image to the display, such as displaying in the display device.

The image analysis and control module can also calculate the image sensor control information according to the image performance parameters, and send the image sensor parameters to the image sensor through the image sensor control module, so as to adjust the image quality.

In one embodiment, the medical tool detection method further includes: when detecting the overall performance parameters of the image, outputting phase information of the overall performance parameter detection of the image.

In one embodiment, as shown in FIG. 14 , FIG. 14 is a schematic diagram of the overall image performance parameter detection process in another embodiment. In this embodiment, when the medical tool is turned on and the image starts self-checking, the display device displays Prompt "Start image self-inspection"; when the medical tool is in the state of image self-inspection, it will display that the medical tool is in a specific link of image self-inspection, for example: "Signal-to-noise ratio test", "Image uniformity test in progress", etc. ;The image self-inspection is completed, the indicators are qualified, and the display device displays the image parameters; the image self-inspection is completed, the indicators are unqualified, the display device displays the unqualified image index parameters, and alarm prompts can be given through the display device, lights, and sounds.

In one embodiment, performing fault detection according to the component state information includes: analyzing in real time according to the component state information to obtain a fault type; obtaining a fault code corresponding to the fault type; outputting the fault detection result includes: outputting a fault code.

In one embodiment, as shown in FIG. 15, FIG. 15 is a schematic diagram of a fault detection process in an embodiment; FIG. 16 is a schematic diagram of a fault detection signal transmission process in an embodiment; FIG. 17 is a fault detection in an embodiment Interaction diagram.

In this embodiment, after the power-on image self-inspection is completed, it enters the real-time fault detection state; when the state of the relevant sub-components is abnormal, the state information is comprehensively fed back, and the fault type is analyzed; finally, the fault type is displayed on the display device in the form of a fault code.

Combined with Figure 16, the detected component transmits the recorded status information to the status detection module in real time; when the relevant sub-components are abnormal, the status detection module sends the integrated status information to the fault analysis module in the form of fault information, and finally the fault The analysis module displays the fault type on the device display in the form of fault codes.

Combined with Figure 17, the image processing host enters the real-time fault detection state after completing the image self-test; when the component is abnormal, it analyzes the fault type and displays the fault code on the display device, for example: Error Code: 0x01: abnormal image channel ;0x02: abnormal command control channel; 0x03: abnormal high temperature; 0x04: abnormal high humidity; and 0x05: abnormal service life. In other embodiments, it may be other fault codes, which are not specifically limited here.

It should be understood that although the various steps in the flowcharts of FIGS. The sequence indicated by the arrow is executed sequentially. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in Fig. 4, Fig. 6, Fig. 8, Fig. 12, Fig. 13, Fig. 14, Fig. 15 and Fig. 16 may include multiple steps or multiple stages, and these steps or stages are not necessarily in the same It can be performed at different times, and the execution sequence of these steps or stages is not necessarily sequential, but can be performed in turn or alternately with other steps or at least a part of steps or stages in other steps.

In an embodiment, the present application provides a computer device, which may be a terminal, and its internal structure may be as shown in FIG. 18 . The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Wherein, the processor of the computer device is used to provide calculation and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, an operator network, NFC (Near Field Communication) or other technologies. When the computer program is executed by the processor, a medical tool detection method is realized. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a button, a trackball or a touch pad provided on the casing of the computer device , and can also be an external keyboard, touchpad, or mouse.

Those skilled in the art can understand that the structure shown in Figure 18 is only a block diagram of a partial structure related to the solution of this application, and does not constitute a limitation to the computer equipment on which the solution of this application is applied. The specific computer equipment can be More or fewer components than shown in the figures may be included, or some components may be combined, or have a different arrangement of components.

In one embodiment, the present application also provides a computer device, including a memory and a processor, a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: acquiring images and/or components collected by medical tools State information; perform image overall performance parameter detection on the image and/or perform fault detection based on component state information, the overall image performance parameter detection is calculated based on parameters in a selected area of the image; output the result of the image overall performance parameter detection and/or or the result of fault detection.

In one embodiment, when the processor executes the computer program, the step of acquiring the image collected by the medical tool includes: after the medical tool is powered on, acquiring the image collected by the medical tool. When the processor executes the computer program, the steps of detecting the overall image performance parameters of the image include: performing quality analysis on the image to obtain image indicators; when the image indicators do not meet the preset requirements, generating information indicating that the overall image performance parameters have failed to be detected; Otherwise, information indicating that the detection of the overall performance parameter of the image is successful is generated.

In one embodiment, when the processor executes the computer program, the step of outputting the result of the detection of the overall performance parameter of the image includes: obtaining the image index that does not meet the requirements according to the information that the detection of the overall performance parameter of the image fails, and outputting the result of the detection that does not meet the requirements Image indicators and/or output alarm information; or obtain all image indicators according to the successful detection information of the overall performance parameters of the image, and output the obtained image indicators.

In one embodiment, after the processor executes the computer program to output the image index that does not meet the requirements, the following steps are also implemented: receiving an adjustment instruction of the control parameter corresponding to the image index; adjusting the control parameter according to the adjustment instruction, and The adjusted control parameters are sent to the image acquisition part of the medical tool.

In one embodiment, before the processor executes the computer program to obtain the image collected by the medical tool, the following steps are further implemented: judging whether the medical tool normally collects the image; when the medical tool normally collects the image, continue to obtain the image collected by the medical tool Image; when the medical tool fails to collect an image, output a prompt message of image collection failure.

In one embodiment, when the processor executes the computer program, the following steps are further implemented: when detecting the overall performance parameters of the image, output stage information of the overall image performance parameter detection.

In one embodiment, when the processor executes the computer program, the overall image performance parameter detection of the image includes at least one of the following: performing image uniformity detection on the image, wherein the image uniformity detection includes: dividing the image into at least Two image areas, and calculate the area index of each image area, and calculate the overall uniformity index of the image according to the area index; perform image distortion rate detection on the image, wherein the image distortion rate detection includes: calculate the restored image corresponding to the image, and obtain the image Center point, image boundary and restored image boundary, calculate the image distortion rate based on the image center point, image boundary and restored image boundary; perform image signal-to-noise ratio detection on the image, wherein the image signal-to-noise ratio detection includes: extracting noise signals and Effective signal, the signal-to-noise ratio of the image is calculated according to the effective signal and the noise signal.

In one embodiment, when the processor executes the computer program, the step of performing fault detection according to the component state information includes: analyzing and obtaining the fault type according to the component state information in real time; obtaining the fault code corresponding to the fault type; wherein the result of the fault detection is The output includes: output fault code.

In one embodiment, when the processor executes the computer program, the fault detection according to the component state information includes at least one of the following: performing communication abnormality detection according to the component state information, and the communication abnormality detection includes bit error detection, packet loss detection and At least one of overtime detection; temperature and humidity detection based on component state information, temperature and humidity detection includes threshold judgment based on data collected by temperature and humidity sensors; service life detection based on component state information, service life detection includes endoscope plug-in interface , the endoscope and the internal Flash of the image host, the fan of the image host and the service life detection of at least one of the power supply modules.

In one embodiment, the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: acquiring images collected by medical tools and/or component status information; Perform image overall performance parameter detection on the image and/or perform fault detection based on component status information. The image overall performance parameter detection is calculated based on the parameters of the selected area of the image; output the result of image overall performance parameter detection and/or fault detection the result of.

In one embodiment, when the computer program is executed by the processor, the step of acquiring the image collected by the medical tool includes: acquiring the image collected by the medical tool after the medical tool is turned on. When the processor executes the computer program, the steps of detecting the overall image performance parameters of the image include: performing quality analysis on the image to obtain image indicators; when the image indicators do not meet the preset requirements, generating information indicating that the overall image performance parameters have failed to be detected; Otherwise, information indicating that the detection of the overall performance parameter of the image is successful is generated.

In one embodiment, when the computer program is executed by the processor, the step of outputting the result of the overall performance parameter detection of the image includes: obtaining the image index that does not meet the requirements according to the information that the overall performance parameter detection of the image fails, and outputting the unsatisfied requirements image indicators and/or output alarm information; or obtain all image indicators according to the successful detection information of the overall performance parameters of the image, and output the obtained image indicators.

In one embodiment, after the computer program is executed by the processor to output the image index that does not meet the requirements, the following steps are also implemented: receiving an adjustment instruction of the control parameter corresponding to the image index; adjusting the control parameter according to the adjustment instruction, and The adjusted control parameters are sent to an image acquisition component of the medical tool.

In one embodiment, before the computer program is executed by the processor to obtain the image collected by the medical tool, the following steps are further implemented: judging whether the medical tool normally collects the image; when the medical tool normally collects the image, continue to obtain the image collected by the medical tool image; when the medical tool fails to collect the image, output a prompt message of image collection failure.

In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: when detecting the overall performance parameters of the image, output stage information of the detection of the overall image performance parameters.

In one embodiment, when the computer program is executed by the processor, the step of detecting the overall image performance parameters of the image includes at least one of the following: performing image uniformity detection on the image, and the image uniformity detection includes: dividing the image into At least two image areas, and calculate the area index of each image area, and calculate the overall uniformity index of the image according to the area index; detect the image distortion rate of the image, and the image distortion rate detection includes: calculating the restored image corresponding to the image, and obtaining the image Center point, image boundary and restored image boundary, calculate the image distortion rate based on the image center point, image boundary and restored image boundary; perform image signal-to-noise ratio detection on the image, image signal-to-noise ratio detection includes: extract noise signal and effective Signal, the signal-to-noise ratio of the image is calculated according to the effective signal and the noise signal.

In one embodiment, when the computer program is executed by the processor, the step of performing fault detection according to the component state information includes: analyzing and obtaining the fault type according to the component state information in real time; obtaining the fault code corresponding to the fault type; The output includes: output fault code.

In one embodiment, when the computer program is executed by the processor, the step of performing fault detection according to the component state information includes at least one of the following: performing communication anomaly detection according to the component state information, and the communication anomaly detection includes bit error detection, packet loss At least one of detection and overtime detection; temperature and humidity detection according to component state information, temperature and humidity detection includes threshold judgment based on data collected by temperature and humidity sensors; service life detection according to component state information, service life detection includes endoscope insertion The service life detection of at least one of the plug-in interface, the endoscope, the internal Flash of the image host, the fan of the image host and the power supply module.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above-mentioned embodiments can be completed by instructing related hardware through computer programs, and the computer programs can be stored in a non-volatile computer-readable memory In the medium, when the computer program is executed, it may include the processes of the embodiments of the above-mentioned methods. Wherein, any references to memory, storage, database or other media used in the various embodiments provided in the present application may include at least one of non-volatile memory and volatile memory. Non-volatile memory may include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

The technical features of the above embodiments can be combined arbitrarily. To make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be It is considered to be within the range described in this specification.

The above-mentioned embodiments only represent several implementation modes of the present application, and the description thereof is relatively specific and detailed, but it should not be construed as limiting the scope of the patent for the invention. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the scope of protection of the patent application should be based on the appended claims.

Claims (16)

1. A medical tool detection method, comprising:

   Obtaining images and/or component status information collected by the medical tool;

   Perform image overall performance parameter detection on the image and/or perform fault detection based on the component status information; the image overall performance parameter detection is calculated based on parameters of a selected area of the image;

   Outputting the detection result of the overall performance parameter of the image and/or the result of the fault detection.
2. The method according to claim 1, wherein said obtaining the image collected by said medical tool comprises:

   After the medical tool is turned on, acquire an image collected by the medical tool;

   The said overall performance parameter detection of the image includes:

   Performing quality analysis on the image to obtain an image index;

   When the image index does not meet the preset requirements, generate information indicating that the detection of the overall image performance parameter fails; otherwise, generate information indicating that the detection of the overall image performance parameter succeeds.
3. The method according to claim 2, wherein the result of the overall performance parameter detection of the output image comprises:

   Acquiring unsatisfactory image indicators according to the failure information of the overall image performance parameter detection, and outputting the unsatisfactory image indicators and/or outputting alarm information.
4. The method according to claim 2, wherein the result of the overall performance parameter detection of the output image comprises:

   Acquiring all image indicators according to the successful detection information of the image overall performance parameters, and outputting all the acquired image indicators.
5. The method according to claim 3, wherein, after outputting the image index that does not meet the requirements, comprising:

   receiving an adjustment instruction of a control parameter corresponding to the image index;

   The control parameter is adjusted according to the adjustment instruction, and the adjusted control parameter is sent to the image acquisition component of the medical tool.
6. The method according to claim 2, wherein, before acquiring the image collected by the medical tool, further comprising:

   judging whether the medical tool is collecting images normally;

   When the medical tool normally collects images, continue to acquire the images collected by the medical tool;

   When the medical tool fails to capture an image, output a prompt message that the image capture fails.
7. The method according to any one of claims 1 to 6, further comprising:

   During the detection of the overall performance parameters of the image, the stage information of the detection of the overall performance parameters of the image is output.
8. The method according to any one of claims 1 to 6, wherein performing the overall image performance parameter detection on the image includes at least one of the following:

   Performing image uniformity detection on the image, the image uniformity detection includes: dividing the image into at least two image areas, and calculating the area index of each image area, and calculating the overall uniformity of the image according to the area index index;

   Performing image distortion rate detection on the image, the image distortion rate detection includes: calculating the restored image corresponding to the image, and obtaining the image center point, image boundary and restored image boundary, based on the image center point, image boundary and Restore the image boundary to calculate the image distortion rate;

   Performing image signal-to-noise ratio detection on the image, the image signal-to-noise ratio detection includes: extracting a noise signal and an effective signal according to the image, and calculating an image signal-to-noise ratio according to the effective signal and the noise signal.
9. The method according to claim 1, wherein said performing fault detection according to said component state information comprises:

   According to the real-time analysis of the component status information, the fault type is obtained;

   Obtain the fault code corresponding to the fault type;

   The output of the result of the fault detection includes:

   Output the fault code.
10. The method according to claim 1, wherein the fault detection according to the component status information comprises at least one of the following:

    Perform communication anomaly detection according to the component state information, and the communication anomaly detection includes at least one of error code detection, packet loss detection and timeout detection;

    Performing temperature and humidity detection according to the component state information, the temperature and humidity detection includes performing threshold judgment according to data collected by the temperature and humidity sensor;

    The service life detection is performed according to the component state information, and the service life detection includes the service life detection of at least one of the endoscope plug-in interface, the internal Flash of the endoscope and the image host, the fan of the image host, and the power supply module.
11. A medical tool detection system, comprising: a medical tool, an image processing host, a lighting source host, and a display; wherein, the image processing host and the lighting source host are respectively connected to the medical tool, and the display is connected to the The image processing host is connected;

    the medical tool is used to acquire images;

    The lighting source host is used to provide medical cold light source;

    The image processing host is used to execute the medical tool detection method described in any one of claims 1 to 10;

    The display is used for displaying the detection result of the overall performance parameter of the image and/or the fault detection result.
12. The system according to claim 11, wherein the image processing host is connected to the medical tool through an optical fiber, so as to obtain images collected by the medical tool.
13. The system according to claim 11, wherein the image processing host is connected to the medical tool through a serial port, so as to obtain the status information of the medical tool components.
14. The system according to claim 11, wherein the display is connected to the image processing host through an HDMI cable, a DVI cable or a DP cable.
15. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method according to any one of claims 1 to 10 when executing the computer program.
16. A computer-readable storage medium, on which a computer program is stored, wherein, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 10 are implemented.

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