Artificial intelligence-based three-level lymphatic structure staining device

Abstract

The application relates to the field of pathological tissue detection, and particularly relates to a three-level lymph structure staining device based on artificial intelligence, which comprises a sectioning module, a staining module and an image analysis module; wherein the sectioning module is used for sectioning paraffin blocks of the three-level lymph structure and preparing standard pathological sections; meanwhile, dynamic parameters in the sectioning process are collected in real time, a motion curve model is constructed and a curve graph is drawn, and the actual thickness of the paraffin section is calculated; and the images of the sectioning area are collected in real time, each paraffin section is independently labeled, the paraffin section thickness is compared with a preset threshold value, and if the thickness of a certain paraffin section exceeds the threshold range, the corresponding label is highlighted and removed. The application reduces the interference of unqualified sections on the detection result from the source through real-time monitoring and intelligent quality control of the sectioning process, and improves the accuracy and reliability of TLS staining analysis.

Description

Technical Field

[0001] This invention relates to the field of pathological tissue detection, and more specifically to a three-level lymphoid structure staining device based on artificial intelligence. Background Technology

[0002] Tertiary lymphoid structures (TLS) are ectopic lymphoid tissues formed in the local tissue microenvironment. Lacking a capsule, they possess functional zones similar to lymph nodes and serve as core sites for the body's local immune response. They are primarily distributed in chronically inflamed tissues, tumor microenvironments, and tissues affected by autoimmune diseases, and are formed by the aggregation of immune cells such as T cells, B cells, follicular dendritic cells, and macrophages. The core functions of TLS are to capture local antigens, initiate specific immune responses, promote lymphocyte activation and proliferation, and produce effector cells and antibodies, playing a crucial role in anti-tumor and anti-infective immunity. The presence of mature TLS in tumor tissue is often associated with better patient prognosis and immunotherapy response, becoming an important biomarker for assessing disease progression and treatment efficacy.

[0003] Pathological analysis of TLS is a core approach to understanding its association with disease progression, typically involving three key steps: pathological section preparation, specific staining, and image analysis. First, tissue samples containing TLS are prepared into pathological sections. Staining then visualizes the cellular composition and structural characteristics of TLS. Finally, morphological observation and quantitative analysis are combined to clarify its biological characteristics. TLS pathological sections are usually prepared using paraffin sectioning technology. This involves using a pathological microtome (e.g., a KD-2508 rotary microtome) to section paraffin blocks (embedded with TLS) into 3-5 μm thin slices, which are then attached to glass slides and baked or fixed to obtain stained pathological sections.

[0004] However, conventional pathological microtome has some technical shortcomings in the preparation of paraffin sections for TLS (Thyroid Lesions). Firstly, after prolonged use, the internal transmission structure of the microtome is prone to wear, leading to deviations in feed accuracy. Even when the scale is adjusted to the standard 3-5 μm graduation, the actual thickness of the TLS sections obtained will still deviate from the preset graduation. Furthermore, this deviation is often subtle and difficult to discern visually. Secondly, the sectioning operation relies on manual rotation of the handle. Excessive or uneven rotation speed can cause fluctuations in section thickness, resulting in TLS sections that do not meet the thickness standard. These excessively thick sections, during subsequent staining, can interfere with the visualization of TLS cell composition and structural characteristics due to cell morphology damage and uneven antigen exposure, leading to distorted staining analysis results and even false negatives. This affects the accuracy of TLS-related pathological assessments and becomes a key bottleneck restricting the reliability of TLS staining analysis. Therefore, this invention provides an artificial intelligence-based three-level lymphoid structure staining device to solve the above problems. Summary of the Invention

[0005] To address the aforementioned issues, this invention provides an artificial intelligence-based staining device for tertiary lymphoid structures (TLS), used for the preparation, standardized staining, and intelligent analysis of pathological sections. The device uses AI to monitor section thickness deviations in real time and mark substandard sections. Combined with automated staining and image recognition, it improves the accuracy of TLS pathological assessment and reduces analytical distortion caused by section quality issues.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows: a three-level lymphatic structure staining device based on artificial intelligence, comprising:

[0007] The slicing module is used to slice paraffin-embedded masses of tertiary lymphoid structures to prepare standard pathological sections of tertiary lymphoid structures.

[0008] The staining module is used to stain pathological sections of tertiary lymphoid structures.

[0009] The image analysis module is used to acquire images of stained pathological sections of tertiary lymphoid structures, and then perform quantitative analysis based on image recognition technology.

[0010] The slicing module is also used to collect dynamic parameters and image information in real time during the slicing process. The dynamic parameters include the single feed amount and feed speed of the paraffin block. Based on the dynamic parameters, a motion curve model is constructed to draw the motion curve of the paraffin block and the corresponding thickness change curve of the paraffin slice for each slice. The actual thickness of the corresponding paraffin slice is calculated by analyzing the curve features. Images of the slicing area are collected in real time, and the morphological features of the paraffin slice at the moment of separation are captured by the image recognition algorithm. Each paraffin slice is independently labeled, and the label is uniquely associated with the corresponding motion curve and thickness change curve. The calculated thickness of the paraffin slice is compared with a preset threshold. If the thickness of a paraffin slice exceeds the threshold range, the corresponding label is highlighted and a prompt signal is triggered, and the highlighted paraffin slice is manually removed.

[0011] Furthermore, in the staining module, following the standardized procedure for staining three-level lymphoid structures, dewaxing, antigen retrieval, immunolabeling, and staining are completed sequentially.

[0012] Furthermore, in the image analysis module, following the standardized analysis process of electronic images after staining of three-level lymphoid structures, image preprocessing, target recognition, structural analysis, and quantitative statistics are completed sequentially.

[0013] Furthermore, the slicing module includes a slicing unit, a motion monitoring unit, an image monitoring unit, and a processing unit;

[0014] The slicing unit is used to slice paraffin-embedded masses of tertiary lymphoid structures;

[0015] The motion monitoring unit is used to capture the mechanical motion parameters during the slicing process in real time, convert the single feed amount of the paraffin block of the tertiary lymphoid structure into the corresponding current change signal, and then generate the corresponding motion curve and thickness change curve; at the same time, according to the feeding motion of the paraffin block of the tertiary lymphoid structure, a regular airflow is generated and flows through the lower end of the freshly cut paraffin slice of the tertiary lymphoid structure.

[0016] The image monitoring unit is used to perform dynamic imaging and feature capture of the slice area, generate a labeled image, and label each paraffin slice in the labeled image;

[0017] The processing unit is used to integrate and analyze the motion curve, thickness change curve, and marked image for quality judgment; extract the peak data in the thickness change curve, calculate the actual thickness value of each paraffin slice of the tertiary lymphoid structure, and compare it with the preset 3-5μm standard threshold to determine whether the thickness of the paraffin slice of the tertiary lymphoid structure meets the standard; at the same time, the thickness analysis results are associated with the labels automatically assigned by the image monitoring unit. If the thickness of a paraffin slice of a certain tertiary lymphoid structure exceeds the threshold range, the corresponding label is immediately highlighted in the marked image, and a "thickness abnormality" prompt message is generated simultaneously.

[0018] Furthermore, the slicing unit consists of a base, a feed box, a rotary wheel, a clamping table, a tool table, and a fixed table. The feed box is mounted on the top of the base, the rotary wheel is rotatably connected to the side wall of the feed box, the fixed table is mounted on the top of the base, the tool table is mounted on the top of the fixed table, the clamping table is slidably connected to the surface of the feed box, and the tool table is located within the movement trajectory of the clamping table.

[0019] Furthermore, the image monitoring unit includes a mounting bracket and an image sensor. The mounting bracket is fixedly connected to the top of the feed box, and the image sensor is fixedly connected to the mounting bracket and located directly above the tool holder. The image sensor is electrically connected to the processing unit.

[0020] Furthermore, the motion monitoring unit includes a synchronizing rod fixedly connected to the bottom of the clamping platform. The fixed platform has a telescopic cavity inside, and a through hole is opened in the side wall of the telescopic cavity. A push rod is slidably fitted inside the telescopic cavity. One end of the push rod passes through the through hole and contacts the synchronizing rod. A spring is fixedly connected to the end of the push rod away from the synchronizing rod, and the end of the spring away from the push rod is fixedly connected to the side wall of the telescopic cavity. A conductive sheet is embedded in the surface of the push rod, and a resistive sheet is embedded in the inner wall of the through hole. The resistive sheet is always in contact with the conductive sheet, and both the conductive sheet and the resistive sheet are electrically connected to the processing unit.

[0021] Furthermore, the tool holder consists of a work plate, a tool post, and cutting inserts. The cutting inserts are mounted on the tool post and correspond to the clamping table. A working groove is opened at the top of the tool post, and the work plate is installed in the working groove. Several guide holes are opened on the surface of the working groove near the clamping table. The guide holes are linearly arrayed along the length of the tool post. All the guide holes are located above the work plate, and the included angle between the work plate and the guide holes is 5 to 15°. An air blowing channel is opened on the inner wall of the telescopic cavity. The air blowing channel extends into the tool post and communicates with several guide holes.

[0022] Furthermore, a magnetic protrusion is provided on the side of the synchronizing rod near the push rod, and a dome-shaped adsorption block is fixedly connected to the end of the push rod near the synchronizing rod.

[0023] Furthermore, the top of the base has a movable groove located directly below the synchronizing rod.

[0024] The above approach has the following beneficial effects:

[0025] 1. This solution addresses the core issues of traditional microtome thickness deviation—high concealment and difficulty in manual judgment—by employing dynamic monitoring and intelligent quality control in the slicing module. The motion monitoring unit converts the paraffin block feed rate into an electrical signal, generating motion and thickness change curves in real time. Combined with the processing unit's algorithm analysis, the actual thickness of each slice is accurately calculated. The image monitoring unit uses image recognition to independently label slices and associate them with thickness data. Slices exceeding the thickness standard are highlighted and trigger prompts, facilitating the rapid removal of unqualified samples. This ensures that the thickness of TLS slices entering the staining stage is strictly controlled within the standard range of 3-5μm, reducing problems such as cell morphology damage and uneven antigen exposure caused by abnormal thickness. It also reduces signal interference during subsequent staining, fundamentally reducing the risk of distorted analysis results and false negatives, and significantly improving the accuracy and reliability of TLS pathological assessment.

[0026] 2. This solution achieves high-precision acquisition of feed parameters through the magnetic attraction between the synchronization rod and the push rod, and the electrical signal conversion structure of the conductive sheet and the resistive sheet. The guide hole of the tool stage is linked with the air blowing channel, using regular airflow to assist in flattening the slices, reducing the impact of wrinkles on image detection, and further ensuring the integrity of the slice morphology. At the same time, the slicing module, staining module, and image analysis module form a closed loop: precise control of slice quality provides high-quality samples for standardized staining, while the AI ​​recognition of the image analysis module achieves accurate quantification of TLS based on qualified samples. The three work together to reduce human operation errors and improve the efficiency and consistency of the entire process from slice preparation to pathological analysis.

[0027] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of an embodiment of the artificial intelligence-based three-level lymphoid structure staining device of the present invention;

[0029] Figure 2 This is an overall isometric view of an embodiment of the artificial intelligence-based three-level lymphoid structure staining device of the present invention;

[0030] Figure 3 This is a schematic diagram of the active groove in an embodiment of the artificial intelligence-based three-level lymphatic structure staining device of the present invention;

[0031] Figure 4 This is an overall left-side view of an embodiment of the artificial intelligence-based three-level lymphoid structure staining device of the present invention.

[0032] Figure 5 for Figure 4 Enlarged view of section A;

[0033] Figure 6 This is a cross-sectional view of the motion monitoring component of an embodiment of the artificial intelligence-based three-level lymphatic structure staining device of the present invention;

[0034] Figure 7 This is an isometric view of the tool table in an embodiment of the artificial intelligence-based three-level lymphatic structure staining device of the present invention;

[0035] Figure 8 for Figure 7 Side sectional view of section B.

[0036] The reference numerals in the accompanying drawings of the instruction manual include: 1. Base; 2. Rotary wheel; 3. Feed box; 4. Fixing frame; 5. Clamping table; 6. Tool table; 601. Working plate; 602. Guide hole; 603. Blade; 7. Fixing table; 701. Telescopic cavity; 702. Spring; 703. Air blowing channel; 8. Synchronizing rod; 801. Magnetic protrusion; 802. Movable groove; 9. Push rod; 901. Conductive sheet; 902. Resistor sheet. Detailed Implementation

[0037] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0039] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0040] The following detailed description illustrates the specific implementation method:

[0041] Example 1:

[0042] As attached Figure 1 As shown: A three-level lymphoid structure staining device based on artificial intelligence includes a slicing module, a staining module and an image analysis module. The three work together to complete the entire process of slicing, staining and analysis of three-level lymphoid structures (TLS), realizing integrated quality control from sample preparation to pathological assessment.

[0043] The slicing module is used to slice paraffin-embedded masses of tertiary lymphoid structures to prepare standard pathological sections of tertiary lymphoid structures.

[0044] The staining module follows a standardized procedure for staining tertiary lymphoid structures, sequentially performing dewaxing, antigen retrieval, immunolabeling, and staining on pathological sections of tertiary lymphoid structures: paraffin matrix is ​​removed by xylene gradient dewaxing, and the tissue environment is balanced by gradient ethanol hydration; an appropriate antigen retrieval method (high-pressure retrieval or enzymatic digestion) is selected according to the marker type (such as CD3, CD20, CD21) to expose the antigen epitopes; specific primary and secondary antibodies are added to complete immunolabeling, and finally, the cellular composition and structure of TLS are visualized by DAB staining or fluorescent labeling, providing a clear signal for image analysis.

[0045] The image analysis module follows a standardized analysis process for electronic images stained with tertiary lymphoid structures, sequentially performing image preprocessing, target identification, structural analysis, and quantitative statistics. First, image quality is optimized through image preprocessing (denoising and contrast correction). Then, the target identification algorithm is used to locate suspected TLS regions, and structural analysis is combined to distinguish between mature and immature TLS (such as identifying CD20+ B cell follicles, CD3+ T cell regions, and CD21+ FDC networks). Finally, quantitative statistics are used to output parameters such as the number of TLS, area ratio, and cell density, providing data support for pathological assessment.

[0046] The slicing module includes a slicing unit, a motion monitoring unit, an image monitoring unit, and a processing unit.

[0047] The slicing unit is used to slice paraffin-embedded masses of tertiary lymphoid structures. The slicing unit employs conventional techniques (such as the KD-2508 rotary microtome), specifically, in conjunction with... Figure 2 As shown, the slicing unit consists of a base 1, a feed box 3, a rotary wheel 2, a clamping table 5, a tool table 6, and a fixed table 7. The feed box 3 is bolted to the top of the base 1. The rotary wheel 2 is rotatably connected to the side wall of the feed box 3 (the specific feeding structure driven by the rotary wheel 2 inside the clamping table 5 can be found in the KD-2508 rotary slicer, and will not be described in detail here). The fixed table 7 is screwed to the top of the base 1, and the tool table 6 is screwed to the top of the fixed table 7. The clamping table 5 is slidably connected to the surface of the feed box 3. The tool table 6 is located within the movement trajectory of the clamping table 5. The tool table 6 consists of a work plate 601, a tool holder, and a blade 603 (see reference). Figure 7 and Figure 8 The blade 603 is engaged with the tool holder and corresponds to the clamping table 5 (i.e., the cutting edge of the blade 603 precisely corresponds to the bearing surface of the clamping table 5: the top of the clamping table 5 carries the paraffin block, and the end face to be cut extends beyond its edge; the cutting edge of the blade 603 is flush with this end face, and the length of the cutting edge is perpendicular to the lateral feed direction of the clamping table 5, ensuring that the cutting edge smoothly cuts the block during feeding, and the slice falls naturally to the working plate 601). A working groove is opened at the top of the tool holder, and the working plate 601 is screwed into the working groove. That is, when the rotary wheel 2 is manually rotated, the clamping table 5 first feeds the paraffin block towards the tool holder (lateral movement), and then the relative movement of the blade 603 and the block completes the slicing (up and down backward movement), completing one slicing action; the slice thickness is adjusted by the dial on the feed box 3 (e.g., ...). Figure 2 (As shown).

[0048] Traditional microtome methods suffer from hidden feed deviations and uneven speeds during manual rotation of the rotary wheel 2, leading to non-standard thickness (3-5 μm) in some paraffin sections of tertiary lymphoid structures. Due to their low thickness, even with deviations, it is difficult for operators to quantify and judge the thickness of the paraffin sections in real time. Consequently, it is difficult to promptly remove substandard paraffin sections, resulting in localized distortion during subsequent staining and affecting the analysis results of the image analysis module. Therefore, the unique feature of this solution is that the motion monitoring unit is used to capture the mechanical motion parameters during the slicing process in real time. It converts the single feed amount of the paraffin block of the tertiary lymphoid structure into a corresponding current change signal, and then generates corresponding motion curves and thickness change curves. Simultaneously, based on the feed motion of the paraffin block of the tertiary lymphoid structure, a regular airflow is generated and flows through the lower end of the freshly cut paraffin section of the tertiary lymphoid structure.

[0049] Specifically, in combination Figure 3 , Figure 4 , Figure 5 and Figure 6 As shown, the motion monitoring unit includes a synchronizing rod 8 screwed to the bottom of the clamping platform 5. The fixed platform 7 has a telescopic cavity 701 inside, with a through hole on the side wall of the telescopic cavity 701. A push rod 9 is slidably fitted inside the telescopic cavity 701, with one end of the push rod 9 passing through the through hole and contacting the synchronizing rod 8. A spring 702 is welded to the end of the push rod 9 away from the synchronizing rod 8, and the end of the spring 702 away from the push rod 9 is welded to the side wall of the telescopic cavity 701. A conductive sheet 901 is embedded in the surface of the push rod 9, and a resistive sheet 902 is embedded in the inner wall of the through hole. The resistive sheet 902 is always in contact with the conductive sheet 901. Both the conductive sheet 901 and the resistive sheet 902 are electrically connected to the processing unit. Furthermore, the top of the base 1 has a movable groove 802 located directly below the synchronizing rod 8 (e.g., ...). Figure 3 As shown in the diagram, sufficient movement space is provided for the synchronizing rod 8 to avoid mechanical interference and ensure movement stability. Specifically, when the push rod 9 slides with the feed movement, the contact length between the conductive sheet 901 and the resistive sheet 902 changes, resulting in a change in the total resistance of the circuit. This is then converted into a current change signal that is linearly related to the feed amount, enabling real-time quantitative calculation of the actual thickness of each slice and solving the problem of thickness deviation being highly concealed and difficult to judge manually.

[0050] The image monitoring unit is used to dynamically image and capture features of the slicing area, generate a labeled image, and label each paraffin slice in the labeled image. The image monitoring unit includes a mounting bracket 4 and an image sensor. The mounting bracket 4 is fixedly connected to the top of the feed box 3, and the image sensor is fixedly connected to the mounting bracket 4 and located directly above the tool holder 6. The image sensor is electrically connected to the processing unit.

[0051] The processing unit is equipped with an artificial intelligence analysis module for integrating and analyzing motion curves, thickness variation curves, and marked images for quality assessment. It extracts peak data from the thickness variation curve using AI algorithms, calculates the actual thickness of each paraffin section of a tertiary lymphoid structure using a preset thickness calculation model, and compares it with a preset 3-5μm standard threshold to automatically determine whether the thickness of the paraffin section of the tertiary lymphoid structure meets the standard. Simultaneously, it associates the thickness analysis results with labels automatically assigned by the image monitoring unit. If the thickness of a paraffin section of a tertiary lymphoid structure exceeds the threshold range, the corresponding label is immediately highlighted in the marked image, and a "thickness anomaly" message is generated simultaneously, enabling rapid identification and early warning of substandard sections.

[0052] Example 2:

[0053] The difference from Embodiment 1 lies in addressing the issue that during continuous slicing, each paraffin slice, due to its thinness and soft texture, is not independent after cutting but rather forms a series of connected strips. This tends to accumulate wrinkles near the blade 603, making it difficult for the image monitoring unit to capture a clear, complete strip pattern. Furthermore, it cannot accurately identify the rectangular outline of a single slice, hindering the use of artificial intelligence algorithms to individually label each slice. Ultimately, this affects the accuracy of subsequent artificial intelligence analysis modules in associating thickness data and determining slice quality. This embodiment incorporates targeted structural optimizations, such as... Figure 6 , Figure 7 and Figure 8 As shown, a number of guide holes 602 are opened on the side surface of the working slot near the clamping table 5. The guide holes 602 are linearly arrayed along the length of the tool holder. The guide holes 602 are all located above the working plate 601, and the included angle between the working plate 601 and the guide holes 602 is 5 to 15°.

[0054] The inner wall of the telescopic cavity 701 has an air blowing channel 703, which extends into the tool holder and communicates with several guide holes 602.

[0055] The specific implementation process is as follows: When the rotary wheel 2 is manually rotated to start continuous slicing, the clamping table 5 carries the TLS paraffin block and feeds it to the tool table 6 at a constant speed. The blade 603 cuts the block in sequence to form continuous long strips of paraffin slices, and the TLS paraffin slices naturally overlap the surface of the working plate 601. At this time, the feeding movement of the clamping table 5 synchronously drives the bottom synchronizing rod 8 to push the push rod 9, so that the air in the telescopic cavity 701 is compressed. Due to the one-way conduction restriction of the first one-way valve, the compressed air is delivered to the guide hole 602 in the tool holder through the air blowing channel 703, and blown obliquely towards the lower end of the long strip slice along the angle of 5-15° between the working plate 601 and the guide hole 602.

[0056] Because the guide holes 602 are linearly arrayed along the length of the blade holder, the blown airflow forms a uniform directional air curtain. On the one hand, the airflow pressure lifts the soft slices, reducing the accumulation and wrinkling caused by the paraffin slices sagging due to their own weight or sticking to the blade 603 and the working plate 601. On the other hand, the continuous and stable pneumatic force can pull the long strip slices to extend smoothly along the length of the working plate 601, always maintaining the complete long strip shape. (During the slicing process, because the single feed amount of the paraffin block is extremely small, the amount of gas generated by each compression of the telescopic cavity 701 is limited, and only a small amount of airflow flows out through the guide holes 602. At the same time, the paraffin slices themselves are thin and light, and their own weight is much less than the lifting and pulling force generated by the small amount of airflow. They can be smoothly driven by the airflow to achieve extension, and will not be torn due to excessive airflow impact, thus ensuring the structural integrity of the long strip slices.)

[0057] Throughout the continuous slicing process, a directional air curtain continuously acts on the elongated slices, ensuring that the TLS paraffin slices remain flat and spread out on the work plate 601. This guarantees that the image sensor can capture clear and complete elongated slice patterns, facilitating subsequent artificial intelligence algorithms to accurately segment each rectangular slice and assign a unique label based on the TLS paraffin slice cutting cycle and spacing. At the same time, maintaining the elongated shape of the TLS paraffin slices also makes it easier for operators to uniformly handle and transfer them to the staining stage.

[0058] Example 3:

[0059] The difference from Example 2 is that, as Figure 5 As shown, a magnetic protrusion 801 is provided on the side of the synchronizing rod 8 near the push rod 9. A dome-shaped adsorption block is fixedly connected to one end of the push rod 9 near the synchronizing rod 8. Through the magnetic adsorption between the magnetic protrusion 801 and the adsorption block, combined with the elastic preload of the spring 702 at the other end of the push rod 9, a dual contact mechanism of "magnetic attraction + elastic force" is formed to ensure that the push rod 9 and the synchronizing rod 8 maintain stable contact throughout the entire slice feeding process, avoiding contact separation caused by mechanical vibration or motion inertia, thereby accurately transmitting the feed displacement and motion state of the clamping stage 5. At the same time, the adsorption block adopts a dome structure design to reduce the frictional resistance between the adsorption block and the magnetic protrusion 801 when the synchronizing rod 8 reciprocates, reducing component wear and ensuring the long-term stability of motion transmission.

[0060] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A three-level lymphoid structure staining device based on artificial intelligence, characterized in that, include: The slicing module is used to slice paraffin-embedded masses of tertiary lymphoid structures to prepare standard pathological sections of tertiary lymphoid structures. The staining module is used to stain pathological sections of tertiary lymphoid structures. The image analysis module is used to acquire images of stained pathological sections of tertiary lymphoid structures, and then perform quantitative analysis based on image recognition technology. The slicing module is also used to acquire dynamic parameters and image information in real time during the slicing process. The dynamic parameters include the single feed amount and feed rate of the paraffin block. Based on dynamic parameters, a motion curve model is constructed, and the motion curve of the paraffin block and the thickness change curve of the corresponding paraffin slice are plotted for each paraffin slice. The actual thickness of the corresponding paraffin slice is calculated by curve feature analysis. Images of the slicing area are acquired in real time, and the morphological features of the paraffin slice at the moment of separation are captured by image recognition algorithm. Each paraffin slice is independently labeled, and the label is uniquely associated with the corresponding motion curve and thickness change curve. The calculated thickness of the paraffin slice is compared with a preset threshold. If the thickness of a paraffin slice exceeds the threshold range, the corresponding number is highlighted and a prompt signal is triggered, and the highlighted paraffin slice is manually removed.

2. The artificial intelligence-based three-level lymphatic structure staining device according to claim 1, characterized in that, In the staining module, following the standardized procedure for staining three-level lymphoid structures, dewaxing, antigen retrieval, immunolabeling, and staining are completed sequentially.

3. The artificial intelligence-based three-level lymphatic structure staining device according to claim 2, characterized in that, In the image analysis module, following the standardized analysis process of electronic images after staining of the three-level lymphoid structures, image preprocessing, target recognition, structural analysis, and quantitative statistics are completed sequentially.

4. The artificial intelligence-based three-level lymphatic structure staining device according to claim 3, characterized in that, The slicing module includes a slicing unit, a motion monitoring unit, an image monitoring unit, and a processing unit; The slicing unit is used to slice paraffin-embedded masses of tertiary lymphoid structures; The motion monitoring unit is used to capture the mechanical motion parameters during the slicing process in real time, convert the single feed amount of the paraffin block of the tertiary lymphoid structure into the corresponding current change signal, and then generate the corresponding motion curve and thickness change curve; at the same time, according to the feeding motion of the paraffin block of the tertiary lymphoid structure, a regular airflow is generated and flows through the lower end of the freshly cut paraffin slice of the tertiary lymphoid structure. The image monitoring unit is used to perform dynamic imaging and feature capture of the slice area, generate a labeled image, and label each paraffin slice in the labeled image; The processing unit is used to integrate and analyze the motion curve, thickness change curve, and marked image for quality judgment; extract the peak data in the thickness change curve, calculate the actual thickness value of each paraffin slice of the tertiary lymphoid structure, and compare it with the preset 3-5μm standard threshold to determine whether the thickness of the paraffin slice of the tertiary lymphoid structure meets the standard; at the same time, the thickness analysis results are associated with the labels automatically assigned by the image monitoring unit. If the thickness of a paraffin slice of a certain tertiary lymphoid structure exceeds the threshold range, the corresponding label is immediately highlighted in the marked image, and a "thickness abnormality" prompt message is generated simultaneously.

5. The artificial intelligence-based three-level lymphatic structure staining device according to claim 4, characterized in that, The slicing unit consists of a base (1), a feed box (3), a rotating wheel (2), a clamping table (5), a tool table (6), and a fixed table (7). The feed box (3) is installed on the top of the base (1), the rotating wheel (2) is rotatably connected to the side wall of the feed box (3), the fixed table (7) is installed on the top of the base (1), the tool table (6) is installed on the top of the fixed table (7), the clamping table (5) is slidably connected to the surface of the feed box (3), and the tool table (6) is located within the movement trajectory of the clamping table (5).

6. The artificial intelligence-based three-level lymphatic structure staining device according to claim 5, characterized in that, The image monitoring unit includes a mounting bracket (4) and an image sensor. The mounting bracket (4) is fixedly connected to the top of the feed box (3), and the image sensor is fixedly connected to the mounting bracket (4) and located directly above the tool table (6). The image sensor is electrically connected to the processing unit.

7. The artificial intelligence-based three-level lymphoid structure staining device according to claim 6, characterized in that, The motion monitoring unit includes a synchronizing rod (8) fixedly connected to the bottom of the clamping platform (5). The fixed platform (7) has a telescopic cavity (701) inside. The telescopic cavity (701) has a through hole on its side wall. A push rod (9) is slidably fitted inside the telescopic cavity (701). One end of the push rod (9) passes through the through hole and contacts the synchronizing rod (8). A spring (702) is fixedly connected to the end of the push rod (9) away from the synchronizing rod (8). The end of the spring (702) away from the push rod (9) is fixedly connected to the side wall of the telescopic cavity (701). A conductive sheet (901) is embedded in the surface of the push rod (9). A resistor (902) is embedded in the inner wall of the through hole. The resistor (902) is always in contact with the conductive sheet (901). Both the conductive sheet (901) and the resistor (902) are electrically connected to the processing unit.

8. The artificial intelligence-based three-level lymphoid structure staining device according to claim 7, characterized in that, The tool holder (6) consists of a working plate (601), a tool holder, and a cutting tool (603). The cutting tool (603) is mounted on the tool holder and corresponds to the clamping table (5). A working groove is opened at the top of the tool holder. The working plate (601) is installed in the working groove. Several guide holes (602) are opened on the side surface of the working groove near the clamping table (5). The guide holes (602) are linearly arrayed along the length of the tool holder. The guide holes (602) are all located above the working plate (601), and the included angle between the working plate (601) and the guide holes (602) is 5 to 15°. The inner wall of the telescopic cavity (701) has an air blowing channel (703), which extends into the tool holder and communicates with several guide holes (602).

9. The artificial intelligence-based three-level lymphatic structure staining device according to claim 8, characterized in that, A magnetic protrusion (801) is provided on the side of the synchronizing rod (8) near the push rod (9), and an adsorption block with a dome structure is fixedly connected to the end of the push rod (9) near the synchronizing rod (8).

10. The artificial intelligence-based three-level lymphoid structure staining device according to claim 9, characterized in that, The top of the base (1) has an active groove (802) located directly below the synchronizing rod (8).

Images