Microscope early warning system and method

Abstract

This specification provides a microscope early warning system and method. The system includes a control device and a microscope. The microscope includes an optical system, an optical path system, a mechanical system, an auxiliary illumination device, and an optical camera. The control device includes an early warning device, a controller, and a memory. The controller is configured to issue a first control command to control the optical camera to capture a full-view image of the sample to be tested and send it to the memory for storage. It obtains user requirements from a smart terminal, determines the optimal imaging parameters of the sample to be tested based on the full-view image, and generates a second control command to control the microscope to image the sample to be tested with the optimal imaging parameters. In response to the microscope being in manual adjustment mode, it acquires detection data, including at least one of the sample height data, light intensity, and objective lens movement speed. In response to abnormal detection data, the controller issues a third control command to control the early warning device to perform a preset operation.

Description

[0001] Case Analysis

[0002] This application is a divisional application of Chinese application filed on July 5, 2023, with application number 202310819797.7, entitled "A Microscope Control System and Method". Technical Field

[0003] This specification relates to the field of microscopy technology, and in particular to a microscope early warning system and method. Background Technology

[0004] When industrial microscopes image samples, variations in surface reflectivity and light intensity can lead to oversaturated pixels in the imaging results. This can prevent the acquisition of clear surface morphology features, resulting in measurement deviations and affecting the accuracy of image acquisition. Furthermore, some opaque samples (e.g., metal samples) can produce darker microscope images, requiring supplemental lighting.

[0005] To address the aforementioned issues, CN113985596A discloses an intelligent lighting control system and method for microscopes. This system uses a microcontroller unit to identify the light source signal and switches between LED and halogen lamp drive units based on the signal, enabling intelligent identification and convenient interchangeability between LED and halogen lamps. However, this method only addresses lighting control based on the light source signal during microscope use and does not consider the need for different lighting parameters under varying imaging effects. Furthermore, poor microscope imaging results can also be caused by the settings of operating parameters for various microscope components (such as eyepieces and objectives). Relying solely on lighting control to improve microscope imaging may not be comprehensive or accurate enough.

[0006] Therefore, it is desirable to provide a microscope early warning system and method to obtain clear and accurate images of the sample to be tested. Summary of the Invention

[0007] This specification provides one or more embodiments of a microscope early warning system. The system includes a control device and a microscope. The microscope includes an optical system, an optical path system, a mechanical system, an auxiliary illumination device, and an optical camera. The control device includes an early warning device, a controller, and a memory. The optical path system includes an illumination unit. The mechanical system includes a support device, a microscope body component, and accessories. The microscope body component includes an objective lens turret, and the accessories include a photomicrography device. The controller is configured to: issue a first control command to control the optical camera to capture a full-view image of the sample to be tested and send it to the memory for storage; obtain user requirements from a smart terminal, determine the optimal imaging parameters of the sample to be tested based on the full-view image, and generate a second control command to control the microscope to image the sample to be tested with the optimal imaging parameters; and respond to the microscope being in manual adjustment mode. The system acquires detection data, including at least one of the following: sample height data, light intensity, and objective lens movement speed. In response to the sample height data being less than a first height threshold, a third control command is generated to control the warning device to issue a first warning and trigger a first preset operation, whereby the first preset operation is to trigger a locking device to lock the objective lens. In response to the light intensity being greater than a light intensity threshold, the third control command is generated to control the warning device to issue a second warning and trigger a second preset operation, whereby the second preset operation is to provide a reminder via a warning light and / or a warning sound control device. In response to the objective lens movement speed being greater than a speed threshold, a third control command is generated to control the warning device to issue a third warning and trigger the second preset operation, whereby the speed threshold dynamically changes based on the sample height data.

[0008] This specification provides a microscope early warning method through one or more embodiments. The method includes: issuing a first control command to control the optical camera to capture a full-view image of the sample to be tested and send it to the memory for storage; obtaining user requirements from a smart terminal, determining the optimal imaging parameters of the sample to be tested in combination with the full-view image, and generating a second control command to control the microscope to image the sample to be tested with the optimal imaging parameters; in response to the microscope being in manual adjustment mode, acquiring detection data, the detection data including at least one of sample height data, light intensity, and objective lens movement speed; in response to the sample height data being less than a first height threshold, generating a third control command to control the warning device to issue a first warning and trigger a first preset operation, the first preset operation being to trigger a locking device to lock the objective lens; in response to the light intensity being greater than a light intensity threshold, generating the third control command to control the warning device to issue a second warning and trigger a second preset operation; the second preset operation being to provide a reminder via a warning light and / or a warning sound control device; in response to the objective lens movement speed being greater than a speed threshold, generating the third control command to control the warning device to issue a third warning and trigger the second preset operation; the speed threshold dynamically changes based on the sample height data.

[0009] This specification provides a microscope early warning device according to one or more embodiments. The device includes at least one memory and at least one processor. The at least one memory is used to store computer instructions, and the at least one processor executes the computer instructions or some of the instructions to implement the microscope early warning method described in the above embodiments.

[0010] This specification provides one or more embodiments of a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions from the storage medium, the computer executes the microscope early warning method described in the above embodiments. Attached Figure Description

[0011] This specification will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, the same numbers represent the same structures, wherein:

[0012] Figure 1 This is an exemplary structural schematic diagram of a microscope control system according to some embodiments of this specification;

[0013] Figure 2 This is an exemplary flowchart illustrating the determination of optimal imaging parameters and a second control command according to some embodiments of this specification;

[0014] Figure 3This is an exemplary flowchart illustrating the acquisition of a target image according to some embodiments of this specification;

[0015] Figure 4 This is a schematic diagram illustrating the imaging effect of determining candidate imaging parameters according to some embodiments of this specification. Detailed Implementation

[0016] To more clearly illustrate the technical solutions of the embodiments of this specification, the following briefly describes the drawings required for describing the embodiments. Obviously, the drawings described below are merely examples or embodiments of this specification. Those skilled in the art can apply this specification to other similar scenarios based on these drawings without inventive effort. Unless otherwise apparent from the context or otherwise noted, the same reference numerals in the figures represent the same structure or operation.

[0017] It should be understood that the terms “system,” “device,” “unit,” and / or “module” used herein are one way to distinguish different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0018] As indicated in this specification and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0019] Flowcharts are used in this specification to illustrate the operations performed by the system according to embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0020] When imaging a sample, variations in surface reflectivity and light intensity can lead to oversaturated pixels in the image, making it difficult to obtain clear morphological features of the sample surface. This results in measurement deviations and affects the accuracy of image acquisition. CN113985596A only adjusts the illumination parameters for sample testing by switching between LEDs and halogen lamps, without considering other parameters that may affect the microscope imaging effect.

[0021] Therefore, in some embodiments of this specification, it is desirable to provide a microscope control system and method that, through a controller, issues a first control command to control a built-in optical camera to capture a full-view image of the sample to be tested and sends it to a memory for storage; based on user requirements obtained from a smart terminal and the full-view image of the sample to be tested, the optimal imaging parameters of the sample to be tested are determined, and a second control command is generated to control the microscope to image the sample to be tested with the optimal imaging parameters. In this way, the imaging parameters can be adjusted according to user requirements and analysis of the full-view image to improve the imaging effect.

[0022] Figure 1 This is an exemplary structural schematic diagram of a microscope control system according to some embodiments of this specification.

[0023] like Figure 1 As shown, the microscope control system 100 may include a control device 110 and a microscope 120.

[0024] The control device 110 is a device for controlling a microscope. In some embodiments, the control device 110 may include a controller 111 and a memory 112.

[0025] The controller 111 is a device for generating and issuing commands to control the microscope. In some embodiments, the controller 111 can be used to issue a first control command, based on which the built-in optical camera is controlled to capture a full-view image of the sample under test and send it to a memory for storage. In some embodiments, the controller 111 can also be used to determine the optimal imaging parameters of the sample under test based on user requirements obtained from a smart terminal and the full-view image of the sample under test, and generate a second control command, based on which the microscope is controlled to image the sample under test with the optimal imaging parameters. In some embodiments, the controller 111 may include one or more sub-control devices.

[0026] In some embodiments, the controller 111 may further include a warning device 111-1.

[0027] The early warning device 111-1 is a device used to issue early warnings for abnormal situations.

[0028] For example, the warning device 111-1 may include a warning light, a warning sound control device, a locking device, and a distance detection device. Among them, the warning light and the warning sound control device can be used to issue warnings when the light intensity is too strong or when the objective lens is too close to the sample, and the locking device can be used to lock the objective lens when the user activates the locking device and the objective lens is below a certain distance threshold.

[0029] Memory 112 is a means for storing instructions and / or data. In some embodiments, memory 112 may store data acquired from controller 111 and / or other devices. For example, memory 112 may store a full-view image of the sample under test taken by a built-in optical camera.

[0030] Microscope 120 is a device used to image the sample to be tested.

[0031] In some embodiments, the microscope 120 may include: an optical system 121, an optical path system 122, a mechanical system 123, an auxiliary illumination device 124, and an optical camera 125.

[0032] The optical system 121 is a system for physically imaging a sample to be tested. For example, the optical system 121 may include an eyepiece and an objective lens.

[0033] The optical path system 122 is a system for performing optical processing (e.g., illumination control) on a sample to be tested. In some embodiments, the optical path system 122 may include one or more illumination units 122-1. Illumination unit 122-1 may include an illumination device, such as an LED lamp, a halogen lamp, etc. The illumination device can be used to illuminate the sample to be tested.

[0034] In some embodiments, the optical path system 122 may also include a light source, a color filter, an aperture stop, a field stop, etc.

[0035] Mechanical system 123 is a system for providing structural support for the microscope. In some embodiments, mechanical system 123 may include support device 123-1, microscope body component 123-2, and accessory 123-3.

[0036] The support device 123-1 is a device used to support the various components of the microscope. For example, it includes the base, frame, stage, fine adjustment device, etc.

[0037] The lens body component 123-2 is a component used to connect eyepieces, objectives, etc. For example, it includes objective lens turrets, etc.

[0038] Appendix 123-3 describes apparatuses for processing the imaging results of samples to be tested. These include, for example, photomicrography devices, polarizing devices, and dark-field devices. The photomicrography device, in particular, can be used to process the results of microscopic imaging and acquire test images.

[0039] The auxiliary lighting device 124 is used to fix, move, or adjust the lighting device.

[0040] In some embodiments, the auxiliary lighting device 124 may include a lighting fixing device and a moving adjustment device. The lighting fixing device can be used to fix the lighting device, and the moving adjustment device may include an electromagnetic drive device and an adjustment rod. The electromagnetic drive device can be used to drive the adjustment rod to adjust the distance between the lighting device and the sample to be tested.

[0041] The optical camera 125 is used to capture images of the sample under test to obtain a full-view image of the sample.

[0042] For further details regarding the generation of initial and optimal imaging parameters as described above, please refer to other parts of this manual (such as...). Figure 2 Related descriptions.

[0043] It should be noted that the above description of the microscope control system 100 and its modules is for ease of description only and should not be construed as limiting this specification to the scope of the embodiments described. It is understood that those skilled in the art, after understanding the principles of this system, may arbitrarily combine the various modules or construct subsystems connected to other modules without departing from these principles.

[0044] In some embodiments, the microscope control method can be implemented by the controller of the microscope control system performing the following steps one to two.

[0045] Step one: Issue the first control command to control the optical camera to capture a full-view image of the sample under test and send it to the memory for storage.

[0046] The first control command refers to the instruction that instructs the optical camera to acquire or transmit information (such as a full-view image of the sample under test).

[0047] The sample to be tested refers to a sample that needs to be observed under a microscope. For example, this includes industrial parts, industrial materials, and industrial products.

[0048] A panoramic image is an image that reflects the overall condition of the sample being tested. For example, it includes images that reflect the surface of industrial parts.

[0049] In some embodiments, the controller can control the built-in optical camera of the microscope to capture a full-view image of the sample under test based on a first control command and send it to the memory for storage. In some embodiments, the controller can also obtain a full-view image of the sample under test by accessing the memory.

[0050] Step two: Obtain user requirements, determine the optimal imaging parameters of the sample to be tested by combining the overall image, and generate a second control command to control the microscope to image the sample to be tested with the optimal imaging parameters.

[0051] User requirements refer to the user's demands for image quality. For example, the requirement for image sharpness. More details on user requirements can be found here. Figure 2 Related instructions.

[0052] In some embodiments, the controller can acquire user requests input by the user on the smart terminal.

[0053] Optimal imaging parameters refer to imaging parameters that meet user needs and produce good imaging results.

[0054] The second control command refers to the instruction that directs the microscope to acquire or transmit information with optimal imaging parameters.

[0055] In some embodiments, the controller can determine the optimal imaging parameters by analyzing user requirements and a full-view image of the sample to be tested, and generate a second control command based on the optimal imaging parameters. For example, the controller can determine the morphological features of the sample to be tested (e.g., the transparency of the sample to be tested) based on the full-view image, and combine this with the clarity requirements in the user requirements to determine the optimal imaging parameters by querying a preset table. The preset table stores multiple sets of different sample types, clarity requirements, and their corresponding optimal imaging parameters. The preset table can be obtained based on experience or determined based on historical imaging data.

[0056] In some embodiments, the controller can also determine the optimal imaging parameters and generate a second control command based on the initial imaging parameters and the corresponding target image. (See also...) Figure 2 Related explanations.

[0057] In some embodiments, the controller may generate second control commands based on optimal imaging parameters to control the parameters of various devices and / or systems of the microscope (e.g., movement parameters of the optical system, etc.) to image the sample to be tested.

[0058] In some embodiments of this specification, the optimal imaging parameters are determined and images are formed based on user requirements and a complete image of the sample to be tested, which helps to obtain a more accurate microscope image of the sample to be tested that meets user requirements.

[0059] In some embodiments, in response to the microscope being in manual adjustment mode, the controller can acquire detection data and determine whether the detection data is abnormal; in response to abnormal detection data, the controller issues a third control command to control the warning device to perform a preset operation.

[0060] Manual adjustment mode refers to a mode in which the user needs to manually adjust various parameters of the microscope.

[0061] Detection data refers to relevant data when testing a sample. Examples include sample height, light intensity, and objective lens movement speed.

[0062] In some embodiments, the controller can acquire detection data in a variety of ways. For example, it can acquire detection data through sensors.

[0063] In some embodiments, the controller may pre-set abnormal conditions, and determine that the detection data is abnormal in response to the detection data meeting the abnormal conditions. In some embodiments, abnormal conditions may include altitude conditions, lighting conditions, and speed conditions, etc.

[0064] In some embodiments, when the detection data is determined to be abnormal, the controller can issue a third control command to control the warning device to perform a preset operation in order to issue a warning.

[0065] The third control command refers to the instruction that directs the early warning device to collect or send information.

[0066] More details about the early warning device can be found in [link / reference]. Figure 1 And related explanations.

[0067] Preset operations refer to pre-defined warning actions. Examples include locking the objective lens with a locking device, emitting colored light or flashing warning lights, and emitting sound from a warning sound control device.

[0068] In some embodiments, in response to abnormal detection data, the controller can, based on a third control command, control the locking device, warning light, warning sound control device, etc., to perform corresponding warning operations. Different abnormal detection data may correspond to different preset operations.

[0069] In some embodiments, the detection data includes the height data of the sample to be detected. In response to the height data of the sample to be detected being less than a first height threshold, the controller can control the warning device to issue a first warning and trigger a first preset operation based on a third control command.

[0070] The height data of the sample under test refers to the distance between the objective lens and the stage when the sample is being tested. For example, the first height, the second height, the third height, etc.

[0071] In some embodiments, the controller can acquire the height data of the sample to be tested based on a preset distance detection device.

[0072] More information regarding the height data of the sample to be measured, the first height, the second height, and the third height can be found in [link to relevant documentation]. Figure 3 Related instructions.

[0073] The first warning is issued when the height data of the sample to be tested is abnormal.

[0074] The first preset operation refers to the preset operation corresponding to the abnormal height data of the sample under test. In some embodiments, the first preset operation may be to trigger a locking device to lock the objective lens.

[0075] In some embodiments of this specification, locking the objective lens at the first height threshold height of the sample height data can keep the objective lens and the sample at a safe distance, thus avoiding damage to both the objective lens and the sample.

[0076] In some embodiments, the detection data may include the light intensity of the auxiliary lighting device. In response to the light intensity being greater than a light intensity threshold, the controller may control the warning device to issue a second warning and trigger a second preset operation through a third control command.

[0077] In some embodiments, the controller can obtain the light intensity through a light sensor or automatically read the light intensity through the setting parameters of the lighting device.

[0078] The light intensity threshold refers to the critical value of light intensity used to determine whether to issue a second warning. For example, a preset light intensity value.

[0079] The second warning refers to the warning issued when the light intensity is abnormal.

[0080] The second preset operation refers to the preset operation corresponding to abnormal light intensity or abnormal objective lens movement speed. In some embodiments, the second preset operation may be a reminder via a warning light and / or a warning sound control device.

[0081] In some embodiments of this specification, setting a light intensity threshold to determine whether the light intensity is abnormal helps to reduce the impact of light intensity on the optical camera and avoid damage to the built-in optical camera due to excessive light intensity.

[0082] In some embodiments, in response to the objective lens moving speed being greater than a speed threshold, the controller controls the warning device to issue a third warning and trigger a second preset operation based on a third control execution command.

[0083] Objective lens movement speed can include the movement speed of high-magnification objectives or low-magnification objectives.

[0084] In some embodiments, the objective lens movement speed can be obtained based on a preset algorithm. An exemplary preset algorithm may include: objective lens movement speed = (H2-H1)÷(T2-T1), where T1 and T2 are two different time points, and H1 and H2 are the height data corresponding to T1 and T2, respectively.

[0085] The speed threshold refers to the critical value of the objective lens movement speed for determining whether to issue a second warning. It can be set manually based on experience.

[0086] In some embodiments, the velocity threshold changes dynamically based on the height data of the sample under test. For example, the greater the distance between the objective lens and the stage, the higher the velocity threshold, but the velocity threshold cannot exceed the upper limit, which can be preset based on experience.

[0087] In some embodiments of this specification, the velocity threshold changes dynamically based on the height data of the sample under test, which helps to find the optimal imaging position more quickly.

[0088] The third warning is issued when the objective lens moves at an abnormal speed.

[0089] In some embodiments of this specification, by issuing a warning for abnormal objective lens movement speed, the user can be reminded to perform safer operations, reducing wear and tear on the microscope or damage to the sample to be tested.

[0090] In some embodiments of this specification, by issuing warnings for abnormal detection data and performing preset operations in manual adjustment mode, the wear and damage to the microscope device and the sample under test caused by improper operation can be effectively reduced.

[0091] Figure 2 This is an exemplary flowchart illustrating the determination of optimal imaging parameters and second control commands according to some embodiments of this specification.

[0092] Step 210: In response to the microscope being in automatic adjustment mode, initial imaging parameters are generated based on user requirements and the overall image.

[0093] Automatic adjustment mode refers to the automatic operating mode of the microscope. In some embodiments, in response to the microscope being in automatic adjustment mode, the controller can automatically adjust the microscope's imaging parameters.

[0094] In some embodiments, user requirements may include the location coordinates of the field of view of interest to the user and the overall magnification. Further details regarding user requirements can be found in the relevant description above.

[0095] The user's field of view refers to the area of ​​the sample being tested that the user is interested in. For example, a user might want to zoom in further on a specific area of ​​the sample being tested.

[0096] The position coordinates of the user's field of view refer to the position coordinates of any point (such as the center point) in the center of the user's field of view. In some embodiments, the controller can establish a Cartesian coordinate system based on the stage as a reference point to determine the position coordinates of the user's field of view.

[0097] Overall magnification refers to the total magnification of the sample under test by the microscope, which can be expressed as the product of the eyepiece magnification and the objective lens magnification.

[0098] In some embodiments, the controller can obtain the user's field of view and overall magnification through a smart terminal.

[0099] In some embodiments of this specification, user requirements include the position coordinates of the field of view of interest to the user and the overall magnification, which helps to obtain a magnified and clear image of the sample to be detected in the area of ​​interest to the user, thereby meeting the user's requirements.

[0100] Initial imaging parameters refer to the parameters used in the first imaging based on user requirements.

[0101] In some embodiments, the controller can generate initial imaging parameters based on user requirements and a panoramic image in various ways. For example, the controller can determine the type and / or size of the sample to be tested based on the panoramic image, and determine the initial imaging parameters by querying a preset parameter table based on the type and / or size of the sample to be tested and user requirements. The preset parameter table stores multiple sets of different types and / or sizes of the samples to be tested, user requirements, and corresponding initial imaging parameters. The preset parameter table can be obtained based on experience or determined based on historical imaging data.

[0102] In some embodiments, the initial imaging parameters include a first illumination parameter, a specimen mover parameter, a first adjustment parameter, a second adjustment parameter, and a third adjustment parameter; in response to the microscope being in automatic adjustment mode, generating initial imaging parameters based on user needs and a panoramic image includes: determining the initial imaging parameters through a preset method.

[0103] The first lighting parameter refers to light intensity.

[0104] Specimen mover parameters refer to the movement parameters of the specimen mover. For example, the direction of movement and the distance of movement.

[0105] The first adjustment parameter refers to the adjustment parameter of the coarse focus knob in direction A. For example, the adjustment amount L1 in direction A. When the coarse focus knob is rotated in direction A, the objective lens moves downward (closer to the stage).

[0106] The second adjustment parameter refers to the adjustment parameter of the coarse focus knob in direction B (opposite to direction A). For example, the adjustment amount L2 in direction B. When the coarse focus knob is rotated in direction B, the objective lens moves upward (away from the stage).

[0107] The third adjustment parameter refers to the adjustment parameter of the fine focus screw in direction B. For example, the adjustment amount L3 in direction B.

[0108] In some embodiments, the controller may determine the initial imaging parameters based on a preset method in the following manner:

[0109] In some embodiments, the controller may preset the first lighting parameters based on experience, or use the lighting parameters of historical test samples of the same type and with the same historical user needs as the first lighting parameters.

[0110] In some embodiments, the controller can determine the specimen mover parameters based on the current position coordinates A (x1, y1) of the user's field of view and the preset position coordinates B (x2, y2). For example, using coordinate A as a reference point, the controller can determine the direction of movement relative to coordinate B as the direction of movement; and determine the distance between coordinate A and coordinate B as the movement distance. The preset position can be the intersection of the objective lens central axis and the stage.

[0111] In some embodiments, the controller can determine the height difference between the current sample height data H1 and the minimum distance H2 between the objective lens and the stage (i.e., the first height), and determine the adjustment amount L1 of the coarse focus knob based on the height difference. H2 can be based on an empirical preset. In some embodiments, the controller can determine the coarse focus knob adjustment amount L1 based on a preset correspondence between the height difference and the adjustment amount L1 of the coarse focus knob. For further explanation regarding the sample height data H1 and the minimum distance H2 (first height) between the objective lens and the stage, please refer to [link to relevant documentation]. Figure 3 And its related descriptions.

[0112] In some embodiments, the controller can determine the second adjustment parameter in a variety of ways. For example, it can preset the adjustment amount L2 of the coarse focus spiral based on experience; or it can take the adjustment amount of the historical coarse focus spiral corresponding to the historical second adjustment parameter in the same type of test samples in history, which has met the sharpness requirements after adjustment by the historical second adjustment parameter, as the current adjustment amount L2 of the coarse focus spiral.

[0113] In some embodiments, the controller can process the sharpness of the second detection image, the sharpness of the target, and the features of the sample to be tested using a parametric prediction model to determine a third adjustment parameter. For further explanation of the second detection image, please refer to [link to relevant documentation]. Figure 3 And its related descriptions.

[0114] Sharpness refers to the clarity of an image. For example, image resolution is defined as sharpness. In some embodiments, the controller can determine the sharpness of the second detection image using a preset sharpness algorithm (e.g., Brenner gradient function, Tenengrad gradient function, etc.).

[0115] Target sharpness refers to the user's desired level of clarity. In some embodiments, the controller may preset the image resolution as the target sharpness.

[0116] The characteristics of a test sample refer to features related to the surface properties of the test sample. For example, these include light transmittance, surface reflectance, and color distribution.

[0117] In some embodiments, the controller can acquire the features of the sample under test in a variety of ways. For example, the controller can retrieve the transmittance and surface reflectance of the sample under test from a storage device. Another example is that the controller can divide the overall image of the sample under test into multiple regions of preset size and shape, perform cluster analysis based on color, and determine the color distribution of the sample under test.

[0118] In some embodiments, the parameter prediction model can be a machine learning model, such as a neural network (NN) model.

[0119] In some embodiments, the parameter prediction model can be trained using multiple first training samples with a first label. The training method may include, but is not limited to, gradient descent.

[0120] In some embodiments, the first training sample may include the sharpness of the sample second detection image, the sharpness of the sample target, and the features of the sample to be tested; the first label may include the adjustment amount L3 of the historical fine focus helix in the direction B corresponding to the first training sample, which meets the historical imaging requirements. In some embodiments, the first training sample and the first label may be obtained based on historical data.

[0121] In some embodiments of this specification, the third adjustment parameter is determined more efficiently and accurately by processing the second detection image sharpness, target sharpness, and features of the sample to be tested through a parameter prediction model, thus avoiding errors caused by manual determination or input.

[0122] In some embodiments of this specification, in response to the microscope being in automatic adjustment mode, initial imaging parameters are generated based on user needs and a full-view image using a preset method. This makes the determination of initial imaging parameters efficient and accurate, meeting user needs and the detection requirements of the sample to be tested, and avoiding errors caused by manual determination.

[0123] Step 220: Control the microscope to image the sample under test with the initial imaging parameters, and control the photomicrography device to acquire the target image.

[0124] In some embodiments, the controller can drive the microscope's eyepiece, objective lens, and other accessories to be imaged under a microscope according to the initial imaging parameters.

[0125] The target image refers to an image generated based on the results of microscopic imaging.

[0126] In some embodiments, the controller can acquire a target image using a photomicrography device based on the results of microscope imaging.

[0127] In some embodiments, the controller can acquire the target image based on the first detected image and the second detected image. Further details can be found in [link to documentation]. Figure 3 And its related descriptions.

[0128] Step 230: Determine the optimal imaging parameters based on the target image and generate a second control command.

[0129] In some embodiments, the controller may adjust the initial imaging parameters based on the sharpness of the target image and the difference between the sharpness and the target image, thereby determining the optimal imaging parameters and generating a second control command.

[0130] In some embodiments, the controller can determine the optimal imaging parameters and generate a second control command based on the analysis results of the target image and a preset generation algorithm. Further details can be found in [link to documentation]. Figure 4 And its related descriptions.

[0131] In some embodiments of this specification, in response to the microscope being in automatic adjustment mode, initial imaging parameters are generated based on user needs and a panoramic image, the sample to be tested is imaged, a target image is acquired, and then the optimal imaging parameters are determined based on the target image, which helps to obtain higher quality imaging results and make the imaging results meet user needs.

[0132] It should be noted that the above description of process 200 is for illustrative purposes only and does not limit the scope of this specification. Those skilled in the art can make various modifications and changes to process 200 under the guidance of this specification. However, these modifications and changes remain within the scope of this specification.

[0133] Figure 3 This is an exemplary flowchart illustrating the acquisition of a target image according to some embodiments of this specification.

[0134] Step 310: Move the field of view of the sample to be tested to a preset position, which is the intersection of the objective lens central axis and the stage.

[0135] In some embodiments, the controller can control the specimen mover based on specimen mover parameters to move the user's field of view of the sample to a preset position. This involves moving the position coordinates of the user's field of view to coincide with the intersection of the objective lens's central axis and the stage, thereby more accurately placing the user's field of view in the center of the objective lens's field of view and reducing or avoiding subsequent searches of the user's field of view based on the first detection image.

[0136] Step 320: In response to the user's concern that the field of view has moved to a preset position, control the objective lens converter to move the low-magnification objective lens to the preset position.

[0137] In some embodiments, in response to the user's concern that the field of view has moved to a preset position, the controller can control the objective lens converter to rotate the low-power objective lens to the preset position, and observe the sample to be tested with the low-power objective lens first.

[0138] Step 330: Based on the first adjustment parameter, control the low-magnification objective lens to move downwards at a constant speed until it reaches the first height with the stage.

[0139] For more information on the first adjustment parameter and how to determine it, please refer to [link to relevant documentation]. Figure 2 And its related descriptions.

[0140] The first height refers to the distance between the objective lens and the stage after adjustment based on the first adjustment parameter.

[0141] In some embodiments, the controller can acquire the height data of the sample to be tested (i.e., the distance between the objective lens and the stage, including a first height, a second height, and a third height) based on a preset distance detection device.

[0142] In some embodiments, after the low-power objective lens is rotated to a preset position, the controller can control the coarse focus knob to adjust based on a first adjustment parameter (e.g., the coarse focus knob rotates by an adjustment amount L1 along direction A) so that the low-power objective lens moves downward (closer to the stage) at a constant speed until it reaches a first height with the stage and then stops.

[0143] The first height is greater than or equal to the first height threshold, that is, greater than or equal to the minimum allowable distance between the objective lens and the stage, in order to avoid the low-magnification objective lens from contacting the sample under test and damaging the low-magnification objective lens or the sample under test.

[0144] Step 340: Based on the second adjustment parameter, control the low-magnification objective lens to move upward at a constant speed until it reaches the second height with the stage, and acquire the first detection image.

[0145] The second height refers to the distance between the low-power objective lens and the stage after adjustment based on the second adjustment parameter. For more information on the second adjustment parameter and how to determine it, please refer to [link to relevant documentation]. Figure 2 And its related descriptions.

[0146] The first detection image refers to the image used to determine whether the detection meets the preset requirements and whether subsequent detection steps (e.g., steps 350 and 360) can be performed.

[0147] In some embodiments, in response to the completion of the adjustment of the second adjustment parameter, the controller can acquire a first detection image by capturing an image of the microscope imaging result at the current moment based on the microscope imaging device.

[0148] In some embodiments, the controller can acquire the sharpness of the first detected image and determine whether the sharpness of the first detected image meets a preset sharpness requirement. In response to the first detected image's sharpness not meeting the preset sharpness requirement, the controller updates the second adjustment parameter and acquires the updated first detected image until the sharpness of the first detected image meets the preset sharpness requirement. The preset sharpness requirement may include, but is not limited to, sharpness greater than a sharpness threshold.

[0149] In some embodiments, the controller can update the second adjustment parameter by increasing the adjustment amount of the coarse focus knob along direction B based on the second adjustment parameter at the current moment and a preset update magnitude. The preset update magnitude can be determined empirically. By updating the second adjustment parameter at least once, the sharpness of the first detected image can gradually approach the sharpness required by the user.

[0150] In some embodiments, in response to the sharpness meeting a preset sharpness requirement, the controller further determines whether the user's field of view appears in the first detection image. In some embodiments, the controller sends the first detection image, whose sharpness meets the preset sharpness requirement, to the smart terminal, where the user determines whether the user's field of view appears. If it appears, the controller can proceed to the subsequent step 350. If it does not appear, the controller obtains the current position information of the sample to be tested, updates the position coordinates of the user's field of view based on the current position information of the sample to be tested, updates the specimen mover parameters, controls the specimen mover to move the user's field of view of the sample to a preset position based on the updated specimen mover parameters, and then proceeds to the subsequent step 350.

[0151] Step 350: Control the objective lens converter to rotate the high-magnification objective lens to a preset position and acquire the second detection image.

[0152] The second detection image refers to the image obtained by observation through a high-power objective lens.

[0153] In some embodiments, in response to switching to a high-power objective lens, the controller can acquire a second detection image based on an image of the microscope imaging result at the current moment captured by the microscopic imaging device.

[0154] Step 360: Based on the third adjustment parameter, control the high-magnification objective lens to move upward at a constant speed until it reaches the third height with the stage, and acquire the target image.

[0155] The third height refers to the distance between the high-power objective lens and the stage after adjustment based on the third adjustment parameter. For more information on the third adjustment parameter and how to determine it, please refer to [link to relevant documentation]. Figure 2 And its related descriptions.

[0156] In some embodiments, in response to the end of the adjustment of the third adjustment parameter, the controller can acquire the target image by capturing an image of the microscope imaging result at the current moment based on the microscope imaging device.

[0157] In some embodiments of this specification, the observation of the sample to be tested is performed based on multiple steps. In each step, the corresponding component of the microscope (such as the coarse adjustment knob) is operated according to the corresponding adjustment parameters (such as the second adjustment parameter), and the detection result (such as the first detection image) is judged to determine whether the preset requirements are met, so as to determine whether to perform subsequent operations. This helps to improve the quality of the target image and meet the user's needs.

[0158] In some embodiments, the controller can analyze the target image, determine the analysis result, and in response to the analysis result not meeting the preset requirements, generate the optimal imaging parameters based on the analysis result using a preset generation algorithm, and generate a second control command.

[0159] The analysis results refer to the data that can reflect the characteristics of the target image.

[0160] In some embodiments, the analysis results include sharpness values, brightness distribution sequences, and total area of ​​oversaturated pixels.

[0161] For further explanation on how to determine the sharpness value of a target image, please refer to [link / reference]. Figure 2 And its related descriptions.

[0162] A brightness distribution sequence refers to a sequence that reflects the brightness distribution of a target image. In some embodiments, the controller can use cluster analysis to divide the target image into multiple sub-regions according to brightness, and construct a brightness distribution sequence based on each sub-region and its corresponding brightness value.

[0163] Oversaturated pixels are pixels whose brightness exceeds a brightness threshold. The brightness threshold can be preset based on relevant experience. The total oversaturated area refers to the total area of ​​all oversaturated pixels in the target image. In some embodiments, the controller can determine the total oversaturated area based on the feature extraction layer; more details can be found in [link to relevant documentation]. Figure 4 Related descriptions.

[0164] Preset requirements refer to the conditions used to determine whether to generate optimal imaging parameters.

[0165] In some embodiments, the preset requirements include: the sharpness value of the target image meets the sharpness condition; the brightness of each sub-region in the brightness distribution sequence meets the brightness condition; and the total oversaturated area meets the preset area condition. Specifically, the controller can only determine that the analysis result meets the preset requirements if the analysis result simultaneously meets the sharpness condition, the brightness condition, and the preset area condition.

[0166] Sharpness conditions refer to the conditions that a sharpness value must meet. In some embodiments, sharpness conditions include: sharpness value > sharpness threshold. The sharpness threshold can be preset, and a sharpness threshold ≥ target sharpness. For more information on target sharpness, please refer to [link to relevant documentation]. Figure 2 And its related descriptions.

[0167] A brightness condition refers to a condition that the brightness distribution sequence must meet. In some embodiments, the brightness condition may include: the brightness value of each sub-region is greater than a brightness threshold, and the difference in brightness values ​​between any two sub-regions is less than a brightness difference threshold. The brightness threshold and the brightness difference threshold can be preset.

[0168] The preset area condition refers to the condition that the total oversaturated area must meet. In some embodiments, the total oversaturated area is less than a preset area threshold. This preset area threshold can be set in advance.

[0169] In some embodiments, the preset area condition is related to the characteristics of the sample to be tested. For example, the greater the transmittance of the sample to be tested, the smaller the preset area threshold. For further explanation of the characteristics of the sample to be tested, please refer to [link to relevant documentation]. Figure 2 And its related descriptions.

[0170] In some embodiments of this specification, the preset area conditions are related to the characteristics of the sample to be tested. More reasonable preset area conditions can be determined based on different samples to be tested, which helps to obtain more accurate target image analysis results.

[0171] Preset generation algorithms refer to algorithms used to generate optimal imaging parameters. Examples include simulation analysis, regression analysis, and discriminant analysis.

[0172] In some embodiments, the controller can use a preset generation algorithm to analyze and process the differences between the analysis results and preset requirements to determine the optimal imaging parameters. For example, the controller can determine the optimal imaging parameters based on a preset correspondence between the analysis results and the imaging parameters.

[0173] In some embodiments, in response to the analysis results not meeting preset requirements, the controller generates optimal imaging parameters based on the analysis results using a preset generation algorithm and generates a second control command, including: the controller generating at least one candidate imaging parameter based on a first illumination parameter and a third adjustment parameter, the candidate imaging parameter including a second illumination parameter and a fine focus knob adjustment parameter; predicting the imaging effect of at least one candidate imaging parameter using an effect prediction model; and determining the optimal imaging parameter based on the imaging effect.

[0174] Candidate imaging parameters refer to parameters that are likely to be the optimal imaging parameters. In some embodiments, candidate imaging parameters may include a second illumination parameter and a fine focus knob adjustment parameter.

[0175] The second lighting parameter refers to the candidate parameter for controlling the lighting intensity.

[0176] In some embodiments, the second illumination parameter further includes illumination distance. Illumination distance refers to the distance between the illumination device and the sample to be tested. In some embodiments, the controller can adjust the illumination distance via an auxiliary illumination device.

[0177] In some embodiments of this specification, the second lighting parameter may also include the lighting distance, which helps to determine a more reasonable light intensity based on consideration of the lighting distance.

[0178] In some embodiments, the controller can generate candidate imaging parameters based on a first illumination parameter and a third adjustment parameter using various methods. For example, the controller can randomly generate at least one second illumination parameter within a preset range of the first illumination parameter (e.g., the first illumination parameter ± 5%); randomly generate at least one candidate fine focus knob adjustment parameter within a preset range of the third adjustment parameter (e.g., the third adjustment parameter ± 5%); and randomly combine at least one set of candidate imaging parameters based on at least one second illumination parameter and at least one candidate fine focus knob adjustment parameter.

[0179] Imaging effect refers to data that reflects the quality of an image. Imaging effect can include sharpness value, brightness distribution sequence, total oversaturation area, etc.

[0180] In some embodiments, the controller can determine the imaging effect using an effect prediction model.

[0181] Figure 4 This is a schematic diagram illustrating the imaging effect of determining candidate imaging parameters according to some embodiments of this specification.

[0182] In some embodiments, the effect prediction model can be a machine learning model with the custom structure described below, or it can be a machine learning model with other structures, such as a neural network (NN) model.

[0183] like Figure 4 As shown, the inputs of the effect prediction model include the target image 410, the sharpness value of the target image 440, the brightness distribution sequence of the target image 450, at least one candidate imaging parameter 460, and the features of the sample to be tested 470. The output includes the imaging effect 490 of at least one candidate imaging parameter.

[0184] In some embodiments, such as Figure 4As shown, the effect prediction model may include a feature extraction layer 420 and an imaging prediction layer 480. Predicting the imaging effect of at least one candidate imaging parameter 460 through the effect prediction model includes: processing the target image 410 based on the feature extraction layer 420 to determine at least one object box and the total oversaturated area 430; and processing the at least one object box and the total oversaturated area 430, the sharpness value 440 of the target image in the analysis result, the brightness distribution sequence 450 of the target image, at least one candidate imaging parameter 460, and the features 470 of the sample to be tested based on the imaging prediction layer 480 to determine the imaging effect 490 of at least one candidate imaging parameter.

[0185] For more information on the imaging results, please refer to the relevant description above.

[0186] In some embodiments, the feature extraction layer may be a convolutional neural network (CNN); the imaging prediction layer may be a neural network (NN).

[0187] For more information about the target image, please refer to [link / reference]. Figure 2 The above descriptions provide further details regarding sharpness values, brightness distribution sequences, candidate imaging parameters, characteristics of the sample under test, and imaging effects.

[0188] The bounding box refers to the region in the target image where there are oversaturated pixels. The total oversaturated area of ​​the bounding box refers to the area comprised of the oversaturated pixels in the region containing oversaturated pixels.

[0189] In some embodiments, the feature extraction layer and the imaging prediction layer can be obtained through joint training.

[0190] The second training sample for the training effect prediction model may include a target image, the corresponding sharpness value and brightness distribution sequence of the target image, candidate imaging parameters, and features of the sample to be tested. The second training sample may be obtained based on historical data. The second label may include the actual imaging effect corresponding to the second training sample. In some embodiments, the actual imaging effect can be determined by analyzing historical target images obtained based on historical samples to be detected.

[0191] The training process may include: inputting a sample target image into the initial feature extraction layer to obtain at least one initial bounding box and the total oversaturated area corresponding to the sample target image; inputting the at least one initial bounding box and the total oversaturated area, the sharpness value of the sample target image, the brightness distribution sequence of the sample target image, the sample candidate imaging parameters, and the features of the sample to be tested into the initial imaging prediction layer to obtain the initial imaging effect. Based on the initial imaging effect and the second label, a loss function is constructed, and the parameters of the initial feature extraction layer and the initial imaging prediction layer are updated synchronously using the loss function. Through parameter updates, a well-trained performance prediction model is obtained.

[0192] In some embodiments of this specification, the imaging effect of candidate imaging parameters is predicted by the effect prediction model. The self-learning capability of the machine learning model can be used to improve the efficiency and accuracy of predicting the imaging effect. By setting different layers in the model to process different data separately, the data processing efficiency can be improved.

[0193] In some embodiments, the controller may select candidate imaging parameters whose imaging effect meets preset requirements as the optimal imaging parameters. If multiple candidate imaging parameters meet the preset requirements, the candidate imaging parameter with the highest clarity among them is selected as the optimal imaging parameter.

[0194] In some embodiments of this specification, by generating at least one candidate imaging parameter within the preset range of the first illumination parameter and the third adjustment parameter, the range of randomly determined candidate imaging parameters can be avoided from being too large, so as to select reasonable candidate imaging parameters; by evaluating the imaging effect of at least one candidate imaging parameter through an effect prediction model to determine the optimal imaging parameter, the accuracy of determining the optimal imaging parameter is improved.

[0195] One embodiment of this specification also provides a microscope control device, which includes at least one memory and at least one processor. The at least one memory is used to store computer instructions, and the at least one processor is used to execute at least a portion of the computer instructions to implement the microscope control method described in any embodiment of this specification.

[0196] One embodiment of this specification also provides a computer-readable storage medium that stores computer instructions that, when executed by a processor, implement the microscope control method described in any embodiment of this specification.

[0197] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are suggested in this specification and therefore remain within the spirit and scope of the exemplary embodiments described herein.

[0198] Furthermore, this specification uses specific terms to describe embodiments thereof. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "an embodiment," "one embodiment," or "an alternative embodiment" in different locations throughout this specification do not necessarily refer to the same embodiment. Moreover, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0199] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this specification are not intended to limit the order of the processes and methods described herein. Although various examples have been discussed in the foregoing disclosure of some embodiments of the invention that are currently considered useful, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the spirit and scope of the embodiments described herein. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely using software solutions, such as installing the described system on existing servers or mobile devices.

[0200] Similarly, it should be noted that, in order to simplify the description disclosed herein and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of embodiments in this specification may sometimes combine multiple features into a single embodiment, drawing, or description thereof. However, this method of disclosure does not imply that the subject matter of this specification requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of a single embodiment disclosed above.

[0201] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this specification are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0202] For each patent, patent application, patent application publication, and other material such as articles, books, specifications, publications, and documents referenced in this specification, the entire contents of which are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this specification, as well as documents that limit the broadest scope of the claims in this specification (currently or subsequently appended to this specification). It should be noted that in the event of any inconsistency or conflict between the descriptions, definitions, and / or terminology used in the supplementary materials to this specification and the content of this specification, the descriptions, definitions, and / or terminology used in this specification shall prevail.

[0203] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A microscope early warning system, characterized in that, The system includes a control device and a microscope. The microscope includes an optical system, an optical path system, a mechanical system, an auxiliary illumination device, and an optical camera. The control device includes an early warning device, a controller, and a memory. The optical path system includes an illumination unit; The mechanical system includes a support device, a mirror body component, and accessories. The mirror body component includes an objective lens turret, and the accessories include a photomicrography device. The controller is configured to: A first control command is issued to control the optical camera to capture a full-view image of the sample under test and send it to the memory for storage; Obtain user needs from smart terminals; In response to the microscope being in automatic adjustment mode, initial imaging parameters are generated based on the user's requirements and the overall image; The microscope is controlled to image the sample under test using the initial imaging parameters to acquire a target image; In response to the analysis results simultaneously satisfying the sharpness condition, the brightness condition, and the preset area condition, it is determined that the analysis results meet the preset requirements, wherein... The sharpness condition includes a sharpness value greater than a sharpness threshold; The brightness condition includes that the brightness value of each sub-region of the target image is greater than a brightness threshold, and the difference in brightness values ​​between any two sub-regions is less than a brightness difference threshold. The preset area condition includes the total area of ​​oversaturated pixels being less than a preset area threshold. The preset area condition is related to the characteristics of the sample to be tested, including light transmittance, surface reflectance, and color distribution. In response to the analysis results not meeting the preset requirements, based on the analysis results of the target image, the optimal imaging parameters are generated by a preset generation algorithm, and a second control command is generated to control the microscope to image the sample under test with the optimal imaging parameters. The analysis results include the sharpness value, the brightness distribution sequence, and the total area of ​​the oversaturated pixels. The preset generation algorithm includes: Based on the first illumination parameter and the third adjustment parameter, at least one candidate imaging parameter is generated, the candidate imaging parameter including the second illumination parameter and the fine focus knob adjustment parameter, the second illumination parameter including the illumination distance; Determining the imaging effect of the at least one candidate imaging parameter includes: The imaging effect of candidate imaging parameters is determined through an effect prediction model, which is a machine learning model. The effect prediction model includes a feature extraction layer and an imaging prediction layer. The feature extraction layer is a convolutional neural network, and the imaging prediction layer is a neural network model, including: The target image is processed based on the feature extraction layer to determine the object box and the total area of ​​the oversaturated pixels; Based on the imaging prediction layer, the object box, the total area of ​​the oversaturated pixels, the sharpness value, the brightness distribution sequence, the candidate imaging parameters, and the features of the sample to be tested are processed to determine the imaging effect of the candidate imaging parameters; Determine the optimal imaging parameters based on the imaging results; In response to the microscope being in manual adjustment mode, detection data is acquired, including at least one of the following: sample height data, light intensity, and objective lens movement speed; In response to the height data of the sample to be tested being less than a first height threshold, a third control command is generated to control the warning device to issue a first warning and trigger a first preset operation, wherein the first preset operation is to trigger the locking device to lock the objective lens. In response to the light intensity exceeding a light intensity threshold, the third control command is generated to control the warning device to issue a second warning and trigger a second preset operation; the second preset operation is to provide a reminder via a warning light and / or a warning sound control device. In response to the objective lens moving speed being greater than a speed threshold, a third control command is generated to control the warning device to issue a third warning and trigger the second preset operation; the speed threshold is dynamically changed based on the height data of the sample to be tested.

2. The system according to claim 1, characterized in that, The user requirements include the position coordinates of the field of view and the overall magnification that the user is concerned about. The initial imaging parameters include a first illumination parameter, a specimen mover parameter, a first adjustment parameter, a second adjustment parameter, and a third adjustment parameter. The first illumination parameter refers to the light intensity, the specimen mover parameter refers to the movement parameter of the specimen mover, the first adjustment parameter refers to the adjustment parameter of the coarse focus knob in direction A, the second adjustment parameter refers to the adjustment parameter of the coarse focus knob in direction B, where direction B is opposite to direction A, and the third adjustment parameter refers to the adjustment parameter of the fine focus knob in direction B.

3. The system according to claim 1, characterized in that, The controller is further configured to: The user's field of view of the sample to be tested is moved to a preset position, which is the intersection of the objective lens central axis and the stage; In response to the user's field of view moving to the preset position, the objective lens converter is controlled to rotate the low-power objective lens to the preset position; Based on the first adjustment parameter, the low-magnification objective lens is controlled to move downward at a constant speed until it reaches the first height with the stage; Based on the second adjustment parameter, the low-magnification objective lens is controlled to move upward at a constant speed until it reaches the second height with the stage, and a first detection image is acquired. In response to the first detection image meeting the preset sharpness requirement and the user's field of view appearing in the first detection image, the objective lens converter is controlled to rotate the high-power objective lens to the preset position to acquire the second detection image; Based on the third adjustment parameter, the low-magnification objective lens is controlled to move upward at a constant speed until it reaches the third height with the stage, thereby acquiring the target image.

4. A microscope early warning method, characterized in that, The method is executed by the microscope early warning system, which includes a control device and a microscope. The microscope includes an optical system, an optical path system, a mechanical system, an auxiliary illumination device, and an optical camera. The control device includes an early warning device, a controller, and a memory. The optical path system includes an illumination unit; The mechanical system includes a support device, a mirror body component, and accessories. The mirror body component includes an objective lens turret, and the accessories include a photomicrography device. The method includes: A first control command is issued to control the optical camera to capture a full-view image of the sample under test and send it to the memory for storage; Obtain user needs from smart terminals; In response to the microscope being in automatic adjustment mode, initial imaging parameters are generated based on the user's requirements and the overall image. The microscope is controlled to image the sample under test using the initial imaging parameters to acquire a target image; In response to the analysis results simultaneously satisfying the sharpness condition, the brightness condition, and the preset area condition, it is determined that the analysis results meet the preset requirements, wherein... The sharpness condition includes a sharpness value greater than a sharpness threshold; The brightness condition includes that the brightness value of each sub-region of the target image is greater than a brightness threshold, and the difference in brightness values ​​between any two sub-regions is less than a brightness difference threshold. The preset area condition includes the total area of ​​oversaturated pixels being less than a preset area threshold. The preset area condition is related to the characteristics of the sample to be tested, including light transmittance, surface reflectance, and color distribution. In response to the analysis results not meeting the preset requirements, based on the analysis results of the target image, the optimal imaging parameters are generated by a preset generation algorithm, and a second control command is generated to control the microscope to image the sample under test with the optimal imaging parameters. The analysis results include the sharpness value, the brightness distribution sequence, and the total area of ​​the oversaturated pixels. The preset generation algorithm includes: Based on the first illumination parameter and the third adjustment parameter, at least one candidate imaging parameter is generated, the candidate imaging parameter including the second illumination parameter and the fine focus knob adjustment parameter, the second illumination parameter including the illumination distance; Determining the imaging effect of the at least one candidate imaging parameter includes: The imaging effect of candidate imaging parameters is determined through an effect prediction model, which is a machine learning model. The effect prediction model includes a feature extraction layer and an imaging prediction layer. The feature extraction layer is a convolutional neural network, and the imaging prediction layer is a neural network model, including: The target image is processed based on the feature extraction layer to determine the object box and the total area of ​​the oversaturated pixels; Based on the imaging prediction layer, the object box, the total area of ​​the oversaturated pixels, the sharpness value, the brightness distribution sequence, the candidate imaging parameters, and the features of the sample to be tested are processed to determine the imaging effect of the candidate imaging parameters; Determine the optimal imaging parameters based on the imaging results; In response to the microscope being in manual adjustment mode, detection data is acquired, including at least one of the following: sample height data, light intensity, and objective lens movement speed; In response to the height data of the sample to be tested being less than a first height threshold, a third control command is generated to control the warning device to issue a first warning and trigger a first preset operation, wherein the first preset operation is to trigger the locking device to lock the objective lens. In response to the light intensity exceeding a light intensity threshold, the third control command is generated to control the warning device to issue a second warning and trigger a second preset operation; the second preset operation is to provide a reminder via a warning light and / or a warning sound control device. In response to the objective lens moving speed being greater than a speed threshold, a third control command is generated to control the warning device to issue a third warning and trigger the second preset operation; the speed threshold is dynamically changed based on the height data of the sample to be tested.

5. A microscope early warning device, characterized in that, The device includes at least one memory and at least one processor, the at least one memory being used to store computer instructions, and the at least one processor executing the computer instructions or parts thereof to implement the microscope early warning method of claim 4.

6. A computer-readable storage medium, characterized in that, The storage medium stores computer instructions, and when the computer reads the computer instructions, the computer executes the microscope early warning method as described in claim 4.

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