Detection processing method and medical detection system
By automatically determining the target light panel and its driving parameters, combined with image acquisition equipment and a closed-loop feedback mechanism, the problems of long debugging time and poor consistency of LED light sources in existing technologies have been solved, realizing an efficient and automated medical testing process and improving testing consistency and production efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-09
- Publication Date
- 2026-03-27
AI Technical Summary
In existing technologies, the debugging of LED-based light sources relies on human experience, resulting in time-consuming, subjective, and inconsistent processes for medical testing equipment, making it difficult to meet the needs of large-scale production.
Based on the user's detection accuracy information, the target light panel and its driving parameters are automatically determined. The driving parameters of the light panel are iteratively adjusted using image acquisition equipment to achieve automatic uniform illumination. The target driving parameters are dynamically generated in conjunction with the image closed-loop feedback mechanism.
It significantly shortens the preparation time for medical testing, eliminates the influence of subjective factors, improves the repeatability and consistency of testing, saves labor costs, and improves production efficiency and image acquisition quality.
Smart Images
Figure CN121751440A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of medical testing technology, and more specifically, to a testing and processing method and a medical testing system. Background Technology
[0002] In the field of in vitro diagnostics (IVD), optical imaging-based detection devices are widely used in rapid detection scenarios such as colloidal gold test strips, fluorescence immunochromatography, and chemiluminescence. During the detection process, creating a highly stable and uniform lighting environment has become a key technical challenge for improving the performance of medical testing equipment.
[0003] Currently, existing technologies typically use light-emitting diodes (LEDs) as the light source. During the detection process, technicians manually adjust the illumination of the LEDs to provide uniform backlighting to the imaging area.
[0004] However, this method relies on technicians repeatedly observing images and adjusting parameters based on their experience, which results in a long process, strong subjectivity, and poor consistency. At the same time, it is difficult to meet the needs of large-scale production. Summary of the Invention
[0005] The purpose of this application is to provide a detection and processing method and a medical detection system to address the shortcomings of the prior art, thereby solving the problems of long processing time, high subjectivity, and poor consistency in the prior art.
[0006] To achieve the above objectives, the technical solutions adopted in the embodiments of this application are as follows: In a first aspect, one embodiment of this application provides a detection processing method applied to a controller in a medical detection system. The medical detection system includes: a detection instrument, multiple light panels, an image acquisition device, and the controller, wherein each light panel includes two groups of lights on both sides; the method includes: Based on the user's detection accuracy information, the target light panel among multiple light panels is determined; Determine whether the target driving parameters of the target light panel exist; If so, the detection instrument is used to perform detection based on the target driving parameters of the target light panel; If not, the initial driving parameters of the target light panel are obtained, and the target light panel is controlled to illuminate the detection instrument with the initial driving parameters. During the illumination process of the two light groups on both sides of the target light panel, the detection instrument is photographed by the image acquisition device to obtain the detection image of the detection instrument. Based on the detection image, the driving parameters of the target light panel are iteratively adjusted. After the iteration is completed, the target driving parameters of the target light panel are obtained, and the detection instrument is detected based on the target driving parameters of the target light panel.
[0007] In one possible implementation, determining the target light panel among multiple light panels based on the user's detection accuracy information includes: Based on the user's detection accuracy information, determine the user's desired number of LED chips; Based on the desired number of LED beads and the preset mapping relationship between the desired number of LED beads and the LED panel, the target LED panel among multiple LED panels is determined.
[0008] In one possible implementation, determining the user's desired number of LEDs based on the user's detection accuracy information includes: Based on the user's detection accuracy information and the setting distance between the detection instrument and the target light board in the medical detection system, the user's desired number of LED beads is determined.
[0009] In one possible implementation, the step of iteratively adjusting the driving parameters of the target light panel based on the detected image, and obtaining the target driving parameters of the target light panel after the iteration is completed, includes: The area to be detected is determined based on the illumination areas of the lamp groups on both sides of the target lamp panel; In the current iteration, the target region corresponding to the region to be detected in the detection image is determined. A target image containing the target region is cropped from the detection image. Based on the target image, light deviation information is determined. Based on the light deviation information, it is determined whether to end the adjustment of the driving parameters of the target light panel. If yes, the driving parameters of the target light panel in the current iteration are used as the target driving parameters of the target light panel. If no, the driving parameters of the target light panel in the current iteration are adjusted based on the light deviation information.
[0010] In one possible implementation, determining the area to be detected based on the illumination areas of the lamp groups on both sides of the target lamp panel includes: Determine the illumination intersection area between the first side lamp group and the second side lamp group in the target lamp panel; Based on the length of the test strip in the detection instrument, a sub-region in the irradiated cross region is determined, and the sub-region is used as the region to be detected.
[0011] In one possible implementation, determining the target image corresponding to the region to be detected in the detection image based on the detection image includes: Based on the region to be detected, the target image corresponding to the region to be detected in the detection image is extracted from the detection image.
[0012] In one possible implementation, determining the light deviation information based on the target image includes: Determine the grayscale value of each pixel in the target image; A real-time grayscale distribution curve is generated based on the grayscale values of each pixel in the target image; The deviation between the real-time grayscale distribution curve and the ideal grayscale distribution curve is calculated, and the obtained deviation result is used as the light deviation information.
[0013] In one possible implementation, determining whether to terminate the adjustment of the target light panel's driving parameters based on the light deviation information includes: If the light deviation information is less than or equal to a preset deviation threshold, then the adjustment of the driving parameters of the target light panel is terminated. If the light deviation information is greater than a preset deviation threshold, then it is determined not to end the adjustment of the driving parameters of the target light panel.
[0014] In one possible implementation, adjusting the driving parameters of the target light panel in the current iteration based on the light deviation information includes: The light deviation information and the driving parameters in the current iteration are input into the pre-trained control model. The control model generates driving adjustment instructions, and based on the driving adjustment instructions, the driving parameters of the target light panel in the current iteration are adjusted.
[0015] Secondly, another embodiment of this application provides a detection processing device applied to a controller in a medical detection system. The medical detection system includes: a detection instrument, multiple light panels, an image acquisition device, and the controller, each light panel including two groups of lights on both sides; the device includes: The first determination module is used to determine the target light board among multiple light boards based on the user's detection accuracy information; The second determining module is used to determine whether the target driving parameters of the target light panel exist. If so, the detection module is used to detect the detection instrument based on the target driving parameters of the target light board; If not, the adjustment module is used to obtain the initial driving parameters of the target light panel and control the target light panel to illuminate the detection instrument with the initial driving parameters. During the illumination process of the two light groups on both sides of the target light panel, the detection instrument is photographed by the image acquisition device to obtain the detection image of the detection instrument. Based on the detection image, the driving parameters of the target light panel are iteratively adjusted. After the iteration is completed, the target driving parameters of the target light panel are obtained, and the detection instrument is detected based on the target driving parameters of the target light panel.
[0016] In one possible implementation, the first determining module is specifically used for: Based on the user's detection accuracy information, determine the user's desired number of LED chips; Based on the desired number of LED beads and the preset mapping relationship between the desired number of LED beads and the LED panel, the target LED panel among multiple LED panels is determined.
[0017] In one possible implementation, the first determining module is specifically used for: Based on the user's detection accuracy information and the setting distance between the detection instrument and the target light board in the medical detection system, the user's desired number of LED beads is determined.
[0018] In one possible implementation, the adjustment module is specifically used for: The area to be detected is determined based on the illumination areas of the lamp groups on both sides of the target lamp panel; In the current iteration, the target region corresponding to the region to be detected in the detection image is determined. A target image containing the target region is cropped from the detection image. Based on the target image, light deviation information is determined. Based on the light deviation information, it is determined whether to end the adjustment of the driving parameters of the target light panel. If yes, the driving parameters of the target light panel in the current iteration are used as the target driving parameters of the target light panel. If no, the driving parameters of the target light panel in the current iteration are adjusted based on the light deviation information.
[0019] In one possible implementation, the adjustment module is specifically used for: Determine the illumination intersection area between the first side lamp group and the second side lamp group in the target lamp panel; Based on the length of the test strip in the detection instrument, a sub-region in the irradiated cross region is determined, and the sub-region is used as the region to be detected.
[0020] In one possible implementation, the adjustment module is specifically used for: Based on the region to be detected, the target image corresponding to the region to be detected in the detection image is extracted from the detection image.
[0021] In one possible implementation, the adjustment module is specifically used for: Determine the grayscale value of each pixel in the target image; A real-time grayscale distribution curve is generated based on the grayscale values of each pixel in the target image; The deviation between the real-time grayscale distribution curve and the ideal grayscale distribution curve is calculated, and the obtained deviation result is used as the light deviation information.
[0022] In one possible implementation, the adjustment module is specifically used for: If the light deviation information is less than or equal to a preset deviation threshold, then the adjustment of the driving parameters of the target light panel is terminated. If the light deviation information is greater than a preset deviation threshold, then it is determined not to end the adjustment of the driving parameters of the target light panel.
[0023] In one possible implementation, the adjustment module is specifically used for: The light deviation information and the driving parameters in the current iteration are input into the pre-trained control model. The control model generates driving adjustment instructions, and based on the driving adjustment instructions, the driving parameters of the target light panel in the current iteration are adjusted.
[0024] Thirdly, another embodiment of this application provides a medical testing system, including: a testing instrument, multiple light panels, an image acquisition device, a controller, a memory, and a bus. The memory stores machine-readable instructions executable by the controller. When the medical testing system is running, the controller communicates with the memory via the bus, and the controller executes the machine-readable instructions to perform the steps of any of the methods described in the first aspect above.
[0025] Fourthly, another embodiment of this application provides a computer-readable storage medium storing a computer program, which, when executed by a controller, performs the steps of any of the methods described in the first aspect above.
[0026] The beneficial effects of this application are as follows: By using the user's detection accuracy information, the target light board among multiple light boards is determined, and the existence of target driving parameters for the target light board is confirmed. When the target driving parameters exist, the detection instrument is tested based on these parameters. When the target driving parameters do not exist, the initial driving parameters of the target light board are obtained, and the target light board is controlled to illuminate the detection instrument with these initial driving parameters. During the illumination process of the light groups on both sides of the target light board, the detection instrument is photographed using an image acquisition device to obtain the detection image. Based on the detection image, the driving parameters of the target light board are iteratively adjusted. After the iteration, the target driving parameters of the target light board are obtained, and the detection instrument is tested based on these parameters. This allows for direct and rapid medical detection when target driving parameters exist, and automatic determination of target driving parameters to achieve uniform illumination when no target driving parameters are available. This significantly shortens the preparation time for medical detection, eliminates the influence of subjective factors, improves the repeatability and consistency between detections of different accuracies, saves labor costs, and increases production efficiency.
[0027] Furthermore, by dynamically generating target-driven parameters through an image closed-loop feedback mechanism, it can adapt to differences in actual equipment and environmental changes, achieving a more uniform illumination effect, thereby improving image acquisition quality and the accuracy of detection results. In addition, the storability of the target-driven parameters allows them to be reused under the same or similar detection conditions, which is beneficial for the standardization and large-scale application of the detection process. Attached Figure Description
[0028] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0029] Figure 1 A schematic diagram of a system architecture for a medical testing system involved in the detection and processing method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the structure of multiple light panels provided in the embodiments of this application; Figure 3 This is a schematic flowchart of a detection and processing method provided in an embodiment of this application; Figure 4 This is a flowchart illustrating the process of determining a target light panel among multiple light panels in the detection and processing method provided in the embodiments of this application. Figure 5This is a flowchart illustrating the process of obtaining the target driving parameters of the target light board in the detection and processing method provided in the embodiments of this application. Figure 6 A schematic flowchart illustrating the process of determining the area to be detected in the detection processing method provided in the embodiments of this application; Figure 7 A schematic flowchart illustrating the determination of light deviation information in the detection processing method provided in this application embodiment; Figure 8 This is a schematic diagram of a detection and processing device provided in an embodiment of this application. Detailed Implementation
[0030] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.
[0031] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.
[0032] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.
[0033] In the field of in vitro diagnostics (IVD), detection devices based on optical imaging principles are widely used in rapid detection scenarios such as colloidal gold test strips, fluorescence immunochromatography, and chemiluminescence. These devices use industrial cameras to acquire images of the test line (T line) and control line (C line) on the test strip, and use image processing algorithms to analyze their grayscale values or fluorescence intensity, thereby achieving qualitative or quantitative judgment.
[0034] Currently, existing technologies typically use light-emitting diodes (LEDs) as the light source. During the detection process, technicians manually adjust the illumination of the LEDs to provide uniform backlighting to the imaging area.
[0035] However, this method relies on technicians repeatedly observing images and adjusting parameters based on their experience, which results in a long process, strong subjectivity, and poor consistency. At the same time, it is difficult to meet the needs of large-scale production.
[0036] This application proposes a detection processing method to address the aforementioned problems. By using the user's detection accuracy information, a target light panel among multiple light panels is identified, and the existence of target driving parameters for that target light panel is determined. If the target driving parameters exist, the detection instrument is tested based on them. If the target driving parameters are not present, the initial driving parameters of the target light panel are obtained, and the target light panel is controlled to illuminate the detection instrument with these initial driving parameters. During the illumination process by the light groups on both sides of the target light panel, an image acquisition device captures images of the detection instrument, obtaining detection images. Based on these images, the driving parameters of the target light panel are iteratively adjusted. After iteration, the target driving parameters of the target light panel are obtained, and the detection instrument is tested based on these parameters. This method enables rapid medical detection, with the homogenization process completed automatically, saving labor costs and improving production efficiency. Simultaneously, it also improves image quality.
[0037] First, the medical testing system involved in the detection and processing method provided in the embodiments of this application will be described in detail.
[0038] Figure 1 This is a schematic diagram of a system architecture for a medical testing system involved in the detection and processing method provided in the embodiments of this application, with reference to... Figure 1 As shown, the medical testing system includes: testing instruments, multiple light panels, image acquisition equipment, and the controller. Each light panel includes two light groups on both sides.
[0039] For example, Figure 1 The following example illustrates a medical testing system that includes a light panel.
[0040] The testing instrument can be a medical colloidal gold testing instrument, which is a rapid in vitro diagnostic device combining immunochromatography and precision optical imaging analysis. The instrument can contain colloidal gold reagent strips for medical testing. The image acquisition device can be an industrial camera, etc.
[0041] The light panel can be an intelligent lighting array system with independent controllability, and each light panel supports different detection accuracies. The light panel includes two light groups on both sides, each containing multiple LED beads and a driving circuit. The LED beads are arranged in an array to provide illumination. The driving circuit is used to adjust the brightness of each LED bead.
[0042] The medical testing system also includes a memory, and optionally, a bus. The memory stores machine-readable instructions executable by the controller. When the medical testing system is running, the controller communicates with the memory via the bus, and the controller executes the machine-readable instructions to perform the steps of the detection processing method provided in this application embodiment.
[0043] For example, Figure 2 This is a schematic diagram of the structure of multiple light panels provided in the embodiments of this application, with reference to... Figure 2 As shown, each light panel can be arranged in a ring, rectangle, or strip shape, with a through hole in the middle to allow the lens of the image acquisition device to pass through, achieving a coaxial confocal imaging structure and avoiding obstruction. Each light panel includes two light groups on both sides, and each light group on both sides can include multiple sub-light groups.
[0044] The detection and processing method provided in this application will be described below with reference to several embodiments.
[0045] Figure 3 This is a schematic flowchart of a detection processing method provided in an embodiment of this application, referred to... Figure 3 As shown, the executing entity of this method can be the aforementioned medical testing system, and the method includes: S301. Based on the user's detection accuracy information, determine the target light board among multiple light boards.
[0046] Optionally, the detection accuracy information input by the user can be obtained, and the target light panel among multiple light panels can be determined based on the detection accuracy information input by the user.
[0047] Among them, the detection accuracy information is used to indicate the level of measurement accuracy that the user has set or expects to achieve for the upcoming medical test.
[0048] For example, the medical testing system also provides users with a graphical user interface (GUI) where users can select preset modes to determine the testing accuracy. Preset modes may include, for example, "high-precision quantitative mode," "standard screening mode," and "rapid initial screening mode."
[0049] For example, the detection accuracy information can be matched with the preset mapping relationship between the detection accuracy information and the light board to obtain the target light board among multiple light boards.
[0050] S302. Determine if there are target driving parameters for the target light panel.
[0051] Optionally, it can be determined whether the target driving parameters for the target light panel exist in the memory.
[0052] The target driving parameters refer to a set of adjustable electrical or control parameters that enable the target lamp board to provide optimal illumination conditions for the testing instruments under medical testing tasks. The target driving parameters include at least the current of each LED chip or lamp group, and also include the duty cycle of the pulse width modulation (PWM) signal, the brightness compensation coefficient between different chips, the light intensity ratio between the lamp groups on both sides of the lamp board, and the driving timing.
[0053] S303. If so, the detection instrument is tested based on the target driving parameters of the target light board.
[0054] Optionally, if target driving parameters for the target light panel exist, the target light panel can be controlled to illuminate the detection instrument based on the target driving parameters of the target light panel, so as to perform detection on the detection instrument.
[0055] Specifically, the user places the sample to be tested (such as a test strip) into the testing instrument. The medical testing system controls the target light panel to illuminate the testing instrument with the target driving parameters, and automatically completes image acquisition, analysis, interpretation and output of test results.
[0056] S304. If not, obtain the initial driving parameters of the target light board and control the target light board to illuminate the detection instrument with the initial driving parameters. During the illumination process of the light groups on both sides of the target light board, the detection instrument is photographed by the image acquisition device to obtain the detection image of the detection instrument. Based on the detection image, the driving parameters of the target light board are iteratively adjusted. After the iteration is completed, the target driving parameters of the target light board are obtained. Based on the target driving parameters of the target light board, the detection instrument is detected.
[0057] Optionally, if no target driving parameters for the target light panel are available, the initial driving parameters of the target light panel can be obtained, and the target light panel can be controlled to illuminate the detection instrument with the initial driving parameters. During the illumination process of the two light groups on both sides of the target light panel, the location of the detection instrument is captured by an image acquisition device to obtain the detection image of the detection instrument. Based on the detection image, the driving parameters of the target light panel are iteratively adjusted, and after the iteration is completed, the target driving parameters of the target light panel are obtained. Based on the target driving parameters of the target light panel, the detection instrument is detected.
[0058] The initial driving parameters refer to the driving parameters for the first time the target light panel is lit. The values of the driving parameters can be default values or preset values.
[0059] For example, the detection instrument can be photographed by an image acquisition device to obtain the detection image of the detection instrument. The detection image is then input into a pre-trained image diagnostic model. The image diagnostic model judges the detection image to determine whether the driving parameters of the target light board should be iteratively adjusted. If so, the image diagnostic model infers and outputs the driving parameters of the target light board, and iteratively adjusts them. If not, the target driving parameters of the target light board are obtained, and the detection instrument is detected based on the target driving parameters of the target light board.
[0060] In this embodiment, the target light panel among multiple light panels is determined based on the user's detection accuracy information, and the existence of target driving parameters for the target light panel is confirmed. When the target driving parameters exist, the detection instrument is tested based on them. When the target driving parameters are absent, the initial driving parameters of the target light panel are obtained, and the target light panel is controlled to illuminate the detection instrument with these initial driving parameters. During the illumination process of the light groups on both sides of the target light panel, an image acquisition device captures images of the detection instrument, obtaining detection images. Based on these images, the driving parameters of the target light panel are iteratively adjusted. After the iteration, the target driving parameters of the target light panel are obtained, and the detection instrument is tested based on these parameters. This method allows for direct and rapid medical detection when target driving parameters exist, and automatically determines them when they are absent, achieving uniform illumination. This significantly shortens the preparation time for medical detection, eliminates the influence of subjective factors, improves the repeatability and consistency between detections of different accuracies, saves labor costs, and increases production efficiency.
[0061] Furthermore, by dynamically generating target-driven parameters through an image closed-loop feedback mechanism, it can adapt to differences in actual equipment and environmental changes, achieving a more uniform illumination effect, thereby improving image acquisition quality and the accuracy of detection results. In addition, the storability of the target-driven parameters allows them to be reused under the same or similar detection conditions, which is beneficial for the standardization and large-scale application of the detection process.
[0062] In one possible implementation, Figure 4 This is a flowchart illustrating the process of determining a target light panel among multiple light panels in the detection and processing method provided in this application embodiment, with reference to... Figure 4 As shown, in step S301 above, the target light panel among multiple light panels is determined based on the user's detection accuracy information, including: S401. Determine the user's desired number of LED beads based on the user's detection accuracy information.
[0063] Optionally, the user's desired number of LEDs can be matched from a pre-stored mapping relationship between detection accuracy information and the desired number of LEDs, based on the user's detection accuracy information.
[0064] Alternatively, the user's detection accuracy information can be input into a pre-prepared formula for calculating the expected number of LEDs to obtain the user's expected number of LEDs.
[0065] S402. Based on the expected number of LED beads and the preset mapping relationship between the expected number of LED beads and the LED panel, determine the target LED panel among multiple LED panels.
[0066] Optionally, the target light panel among multiple light panels can be determined from a preset mapping relationship between the expected number of LEDs and the light panel, based on the expected number of LEDs.
[0067] By determining the user's desired number of LEDs and using the pre-defined mapping between this desired number and the LED board, the target LED board can be selected from multiple options. This automates and automates LED board selection, reducing manual intervention and improving configuration efficiency. Simultaneously, it ensures a proper match between the number of LEDs and the LED board's driving capabilities, avoiding resource waste or performance bottlenecks. Furthermore, it supports precise matching based on the individual needs of different users, enhancing the user experience.
[0068] In one possible implementation, determining the user's desired number of LEDs based on the user's detection accuracy information in step S401 includes: Based on the user's detection accuracy information and the setting distance between the detection instrument and the target light board in the medical detection system, the user's desired number of LED beads is determined.
[0069] Optionally, the required total luminous flux can be calculated based on the user's detection accuracy information and the setting distance between the detection instrument and the target lamp board in the medical detection system, and the average luminous flux of a single lamp bead can be determined. Thus, based on the required total luminous flux and the average luminous flux of a single lamp bead, the user's desired number of lamp beads can be calculated.
[0070] By using the user's detection accuracy information and the distance between the detection instrument and the target light board in the medical testing system, the desired number of LEDs is determined. This achieves closed-loop linkage control between medical testing accuracy and the lighting system, making the light source configuration no longer a fixed design but a dynamically adjustable functional unit according to the testing task. Simultaneously, it improves the adaptability and versatility of the testing system; the same hardware platform can support multiple accuracy levels of testing tasks by changing the light board configuration. Furthermore, it avoids false positives and false negatives caused by insufficient illumination, ensuring the reliability of medical testing results. It also prevents energy waste or excessive heat generation due to over-configuration of light sources, achieving a balance between energy conservation, environmental protection, and performance.
[0071] In one possible implementation, Figure 5This is a flowchart illustrating the process of obtaining the target driving parameters of the target light board in the detection and processing method provided in the embodiments of this application, with reference to... Figure 5 As shown, in step S304 above, the driving parameters of the target light panel are iteratively adjusted based on the detected image, and the target driving parameters of the target light panel are obtained after the iteration, including: S501. Determine the area to be tested based on the illumination areas of the lamp groups on both sides of the target lamp panel.
[0072] Optionally, the illumination areas of the lamp groups on both sides of the target light panel can be determined, and the area to be tested can be determined based on the illumination areas of the lamp groups on both sides of the target light panel. The illumination area of the lamp group refers to the spatial range where the light emitted by the lamp group actually reaches and produces effective illumination; specifically, the illumination area of the lamp group refers to the projected area on the plane where the testing instrument is located. The illumination area of the lamp group is a continuous area on the plane where the illumination intensity of the lamp group on the testing instrument is greater than a preset illumination intensity threshold.
[0073] Specifically, the spatial configuration information of the lamp groups on both sides of the target light panel can be obtained, and based on this information, illumination area models for each lamp group on one side can be constructed, thereby determining the illumination areas of the lamp groups on both sides of the target light panel. The spatial configuration information includes: lamp installation position, LED arrangement density, emission angle, and installation tilt angle.
[0074] For example, after obtaining the spatial configuration information of each lamp group, the coverage area of each lamp bead on the plane where the detection instrument is located can be calculated by geometric projection, and the coverage areas of all lamp beads can be superimposed to generate a two-dimensional illumination distribution map, thereby obtaining the illumination area of the lamp group.
[0075] For example, the illumination areas of both sides of the target light panel can be used as the areas to be detected.
[0076] For example, the illumination areas of the lamp groups on both sides of the target lamp panel can be superimposed to obtain the overlapping illumination area as the area to be detected, so that the sample in the intersection area is illuminated by both sides with a high signal-to-noise ratio, which is suitable for precision detection.
[0077] S502. In the current iteration, determine the target region corresponding to the region to be detected in the detection image, crop the target image containing the target region from the detection image, determine the light deviation information based on the target image, and determine whether to stop adjusting the driving parameters of the target light board based on the light deviation information; if yes, use the driving parameters of the target light board in the current iteration as the target driving parameters of the target light board; if no, adjust the driving parameters of the target light board in the current iteration based on the light deviation information.
[0078] Optionally, in the current iteration, based on the region to be detected and the detection image, the target region corresponding to the region to be detected in the detection image is determined, and a preset cropping threshold is superimposed on the region to be detected, and the target image corresponding to the region to be detected in the detection image is extracted from the detection image.
[0079] For example, a 1 cm layer is superimposed on the area to be detected to obtain a new area to be detected, and the target image corresponding to the new area to be detected is extracted from the detection image.
[0080] Optionally, the light deviation information is determined based on the target image, and the adjustment of the driving parameters of the target light panel is terminated based on the light deviation information.
[0081] For example, the target image can be input into a pre-trained image deviation determination model, which infers the light deviation information based on the target image and determines whether to stop adjusting the driving parameters of the target light panel based on the light deviation information.
[0082] Optionally, if yes, the driving parameters of the target light panel in the current iteration are used as the target driving parameters of the target light panel; otherwise, the driving parameters of the target light panel in the current iteration are adjusted according to the light deviation information.
[0083] The detection area is determined by the illumination area of the lamps on both sides of the target light panel. The target area corresponding to the detection area in the detection image is then identified, and the target image containing the target area is cropped from the detection image. Based on the target image, the driving parameters of the target light panel are iteratively obtained. This ensures that detection is only performed in areas with sufficient and uniform illumination, avoiding reliance on human experience and achieving fully automatic optimal lighting configuration. This improves data reliability, avoids interference from invalid edge areas, and reduces computational load, allowing for focus on key information.
[0084] In one possible implementation, Figure 6 This is a flowchart illustrating the process of determining the area to be detected in the detection processing method provided in the embodiments of this application, with reference to... Figure 6 As shown, in step S501 above, the area to be detected is determined based on the illumination areas of the lamp groups on both sides of the target lamp panel, including: S601. Determine the area where the first and second side light groups of the target light panel intersect.
[0085] Optionally, after obtaining the illumination area of each lamp group in the target light panel, the illumination area of the first lamp group and the illumination area of the second lamp group in the target light panel can be intersected to obtain the illumination intersection area.
[0086] S602. Based on the length of the test strip in the testing instrument, determine the sub-region in the irradiated cross region, and use the sub-region as the area to be tested.
[0087] Optionally, based on the length of the test strip in the testing instrument, a sub-region within the irradiated cross region can be determined, and the sub-region can be used as the region to be tested.
[0088] The length of the sub-region can be the length of the irradiated intersection area, and the width of the sub-region can be the length of the test paper.
[0089] By irradiating the cross-region and the length of the test strip in the testing instrument, the area to be tested is determined, which improves the accuracy and reliability of the test results. Simultaneously, the testing area is dynamically and adaptively defined during the testing process, no longer relying on a fixed template, supporting the mixing of multiple test strip sizes, and enhancing the error tolerance of the medical testing system and the user experience.
[0090] In one possible implementation, S502 above, determining the target image corresponding to the region to be detected in the detected image based on the detected image, includes: Based on the region to be detected, the target image corresponding to the region to be detected is extracted from the detection image.
[0091] Optionally, the physical coordinates of the region to be detected can be determined, and the mapping relationship between the pre-calibrated physical coordinates and pixel coordinates can be obtained. The region to be detected can then be mapped to the image coordinate system, thereby cropping the target image from the detected image.
[0092] In one possible implementation, Figure 7 This is a schematic flowchart illustrating the determination of light deviation information in the detection and processing method provided in this application embodiment, with reference to... Figure 7 As shown, in step S502 above, determining the light deviation information based on the target image includes: S701. Determine the grayscale value of each pixel in the target image.
[0093] Optionally, the pixel matrix of the target image can be read to obtain the grayscale value of each pixel.
[0094] S702. Generate a real-time grayscale distribution curve based on the grayscale values of each pixel in the target image.
[0095] Optionally, after obtaining the grayscale values of each pixel, a real-time grayscale distribution curve can be generated. The horizontal axis of the real-time grayscale distribution curve represents the pixel's position in the image, and the vertical axis represents the pixel's grayscale value.
[0096] S703. Calculate the deviation between the real-time grayscale distribution curve and the ideal grayscale distribution curve, and use the obtained deviation result as the light deviation information.
[0097] Optionally, the difference between the grayscale value of the real-time grayscale distribution curve and the ideal grayscale distribution curve at each pixel is calculated to obtain a pixel difference sequence, and the deviation result is calculated based on the pixel difference sequence.
[0098] For example, the root mean square error (RMSE) or mean absolute error (MAE) of the pixel difference sequence can be calculated to obtain the deviation result, and the obtained deviation result can be used as the light deviation information.
[0099] In one possible implementation, the step S502 above, determining whether to stop adjusting the driving parameters of the target lamp panel based on the light deviation information, includes: If the light deviation information is less than or equal to the preset deviation threshold, then the adjustment of the target light panel's driving parameters is terminated; if the light deviation information is greater than the preset deviation threshold, then the adjustment of the target light panel's driving parameters is not terminated.
[0100] Optionally, the light deviation information is compared with a preset deviation threshold. If the light deviation information is less than or equal to the preset deviation threshold, the adjustment of the target light panel's driving parameters is terminated. If the light deviation information is greater than the preset deviation threshold, the adjustment of the target light panel's driving parameters is not terminated.
[0101] In one possible implementation, step S502 above adjusts the driving parameters of the target light panel in the current iteration based on the light deviation information, including: The light deviation information and the driving parameters in the current iteration are input into the pre-trained control model. The control model generates driving adjustment instructions and adjusts the driving parameters of the target light panel in the current iteration based on the driving adjustment instructions.
[0102] Optionally, the light deviation information and the driving parameters in the current iteration are input into the pre-trained control model, which generates driving adjustment instructions and adjusts the driving parameters of the target light panel in the current iteration based on the driving adjustment instructions.
[0103] The control model can be implemented based on a neural network or a PID control algorithm. The drive adjustment command is a digital control command used to dynamically optimize the drive parameters of the LED beads, acting on independently addressable LED beads or groups of LEDs.
[0104] Based on the same inventive concept, this application also provides a detection processing device corresponding to the detection processing method. Since the principle of the device in this application is similar to the detection processing method described above in this application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.
[0105] Reference Figure 8 As shown, Figure 8 This is a schematic diagram of a detection processing device provided in an embodiment of this application. The detection processing device is applied to a controller in a medical detection system. The medical detection system includes: a detection instrument, multiple light panels, an image acquisition device, and the controller. Each light panel includes two light groups on both sides. The device includes: a first determination module 801, a second determination module 802, a detection module 803, and an adjustment module 804. The first determining module 801 is used to determine the target light board among multiple light boards based on the user's detection accuracy information; The second determining module 802 is used to determine whether there are target driving parameters for the target light board; If so, the detection module 803 is used to detect the detection instrument based on the target driving parameters of the target light board; If not, the adjustment module 804 is used to obtain the initial driving parameters of the target light board and control the target light board to illuminate the detection instrument with the initial driving parameters. During the illumination process of the two light groups on both sides of the target light board, the detection instrument is photographed by the image acquisition device to obtain the detection image of the detection instrument. Based on the detection image, the driving parameters of the target light board are iteratively adjusted. After the iteration is completed, the target driving parameters of the target light board are obtained, and the detection instrument is detected based on the target driving parameters of the target light board.
[0106] In one possible implementation, the first determining module 801 is specifically used for: Based on the user's detection accuracy information, determine the user's desired number of LED chips; Based on the desired number of LED chips and the preset mapping relationship between the desired number of LED chips and the LED panel, the target LED panel among multiple LED panels is determined.
[0107] In one possible implementation, the first determining module 801 is specifically used for: Based on the user's detection accuracy information and the setting distance between the detection instrument and the target light board in the medical detection system, the user's desired number of LED beads is determined.
[0108] In one possible implementation, module 804 is adjusted specifically for: The area to be tested is determined based on the illumination areas of the lamp groups on both sides of the target lamp panel; In the current iteration, the target region corresponding to the region to be detected in the detection image is determined. The target image containing the target region is cropped from the detection image. Based on the target image, the light deviation information is determined. Based on the light deviation information, it is determined whether to stop adjusting the driving parameters of the target light board. If yes, the driving parameters of the target light board in the current iteration are used as the target driving parameters of the target light board. If no, the driving parameters of the target light board in the current iteration are adjusted based on the light deviation information.
[0109] In one possible implementation, module 804 is adjusted specifically for: Determine the overlapping area of the first and second side light groups in the target light panel; Based on the length of the test strip in the testing instrument, a sub-region within the irradiated cross region is determined, and this sub-region is used as the area to be tested.
[0110] In one possible implementation, module 804 is adjusted specifically for: Based on the region to be detected, the target image corresponding to the region to be detected is extracted from the detection image.
[0111] In one possible implementation, module 804 is adjusted specifically for: Determine the grayscale value of each pixel in the target image; Generate a real-time grayscale distribution curve based on the grayscale values of each pixel in the target image; The deviation between the real-time grayscale distribution curve and the ideal grayscale distribution curve is calculated, and the obtained deviation result is used as the light deviation information.
[0112] In one possible implementation, module 804 is adjusted specifically for: If the light deviation information is less than or equal to the preset deviation threshold, then the adjustment of the target light panel's driving parameters is terminated. If the light deviation information is greater than the preset deviation threshold, then the adjustment of the target light panel's driving parameters will not be terminated.
[0113] In one possible implementation, module 804 is adjusted specifically for: The light deviation information and the driving parameters in the current iteration are input into the pre-trained control model. The control model generates driving adjustment instructions and adjusts the driving parameters of the target light panel in the current iteration based on the driving adjustment instructions.
[0114] The processing flow of each module in the device and the interaction flow between each module can be referred to the relevant descriptions in the above method embodiments, and will not be detailed here.
[0115] This application also provides a computer-readable storage medium storing a computer program, which is executed by the controller to perform the steps of the above-described detection processing method.
[0116] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and devices described above can be referred to the corresponding processes in the method embodiments, and will not be repeated here. In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some communication interfaces; the indirect coupling or communication connection of devices or modules can be electrical, mechanical, or other forms.
[0117] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.
[0118] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.
Claims
1. A detection and processing method, characterized in that, A controller for use in a medical testing system, the medical testing system comprising: a testing instrument, multiple light panels, an image acquisition device, and the controller, each light panel comprising two groups of lights on both sides; the method comprising: Based on the user's detection accuracy information, the target light panel among multiple light panels is determined; Determine whether the target driving parameters for the target light panel exist; If so, the detection instrument is used to perform detection based on the target driving parameters of the target light panel; If not, the initial driving parameters of the target light panel are obtained, and the target light panel is controlled to illuminate the detection instrument with the initial driving parameters. During the illumination process of the two light groups on both sides of the target light panel, the detection instrument is photographed by the image acquisition device to obtain the detection image of the detection instrument. Based on the detection image, the driving parameters of the target light panel are iteratively adjusted. After the iteration is completed, the target driving parameters of the target light panel are obtained, and the detection instrument is detected based on the target driving parameters of the target light panel.
2. The detection and processing method according to claim 1, characterized in that, The step of determining the target light panel among multiple light panels based on the user's detection accuracy information includes: Based on the user's detection accuracy information, determine the user's desired number of LED chips; Based on the desired number of LED beads and the preset mapping relationship between the desired number of LED beads and the LED panel, the target LED panel among multiple LED panels is determined.
3. The detection and processing method according to claim 2, characterized in that, The step of determining the user's desired number of LED chips based on the user's detection accuracy information includes: Based on the user's detection accuracy information and the setting distance between the detection instrument and the target light board in the medical detection system, the user's desired number of LED beads is determined.
4. The detection and processing method according to claim 1, characterized in that, The step of iteratively adjusting the driving parameters of the target light panel based on the detected image, and obtaining the target driving parameters of the target light panel after the iteration is completed, includes: The area to be detected is determined based on the illumination area of the lamp groups on both sides of the target lamp panel; In the current iteration, the target region corresponding to the region to be detected in the detection image is determined. A target image containing the target region is cropped from the detection image. Based on the target image, light deviation information is determined. Based on the light deviation information, it is determined whether to end the adjustment of the driving parameters of the target light panel. If yes, the driving parameters of the target light panel in the current iteration are used as the target driving parameters of the target light panel. If no, the driving parameters of the target light panel in the current iteration are adjusted based on the light deviation information.
5. The detection and processing method according to claim 4, characterized in that, The step of determining the area to be detected based on the illumination areas of the lamp groups on both sides of the target lamp panel includes: Determine the illumination intersection area between the first side lamp group and the second side lamp group in the target lamp panel; Based on the length of the test strip in the detection instrument, a sub-region is determined within the irradiated cross region, and the sub-region is used as the region to be detected.
6. The detection and processing method according to claim 4, characterized in that, The step of determining the target image corresponding to the region to be detected in the detection image based on the detection image includes: Based on the region to be detected, the target image corresponding to the region to be detected in the detection image is extracted from the detection image.
7. The detection and processing method according to claim 4, characterized in that, Determining the light deviation information based on the target image includes: Determine the grayscale value of each pixel in the target image; A real-time grayscale distribution curve is generated based on the grayscale values of each pixel in the target image; The deviation between the real-time grayscale distribution curve and the ideal grayscale distribution curve is calculated, and the obtained deviation result is used as the light deviation information.
8. The detection and processing method according to claim 4, characterized in that, The step of determining whether to stop adjusting the driving parameters of the target light panel based on the light deviation information includes: If the light deviation information is less than or equal to a preset deviation threshold, then the adjustment of the driving parameters of the target light panel is terminated. If the light deviation information is greater than a preset deviation threshold, then it is determined not to end the adjustment of the driving parameters of the target light panel.
9. The detection and processing method according to claim 4, characterized in that, The step of adjusting the driving parameters of the target light panel in the current iteration based on the light deviation information includes: The light deviation information and the driving parameters in the current iteration are input into the pre-trained control model. The control model generates driving adjustment instructions, and based on the driving adjustment instructions, the driving parameters of the target light panel in the current iteration are adjusted.
10. A medical testing system, characterized in that, include: The system includes a detection instrument, multiple light panels, an image acquisition device, a controller, and a memory. The memory stores machine-readable instructions executable by the controller. When the medical detection system is running, the controller executes the machine-readable instructions to perform the steps of the detection processing method as described in any one of claims 1 to 9.