Small specimen pathological sampling intelligent robot system and sampling method

Abstract

The invention discloses a small specimen pathological sampling intelligent robot system and a sampling method. Comprising an operation cabin, a central control system, a visual identification device, double mechanical arms, a feeding channel, an embedding box input channel, a specimen bottle recovery port, a tissue fixing liquid recovery port, an embedding box ink-jet printer, a fault code alarm prompt device, a top illumination, negative pressure ventilation and formaldehyde adsorption device, a flushing faucet, a water tank and an ultraviolet disinfection lamp. Wherein the visual identification device comprises a bar code scanner, an AI image identification camera and a monitoring and recording camera, and is used for reading specimen information and positioning tissues; precise tissue positioning is realized through an AI image recognition camera and double mechanical arms; and a bar code scanner is used for intelligently identifying and processing pathological resource marking and filing. By adopting the technical scheme of the invention, an unattended standardized and digital small specimen pathological sampling process is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of pathological sampling, and in particular relates to an intelligent robot system for sampling small specimens of pathological samples and a sampling method. Background Art

[0002] Pathological diagnosis is a core component of disease diagnosis, and tissue specimen collection is a key step in the pathology workflow. However, the current pathology specimen collection process presents numerous significant challenges. First, physicians must spend extended periods handling patient tissue samples at the specimen collection station, directly contacting formalin (a widely used tissue fixative). Short-term exposure can cause conjunctival congestion, respiratory irritation, headaches, nausea, and even acute poisoning, while long-term exposure increases the risk of nasopharyngeal cancer and leukemia. Second, manual specimen collection is labor-intensive and can lead to physician overload and operational errors. Furthermore, specimen thickness and orientation rely heavily on personal experience, compromising subsequent diagnostic accuracy. Currently, several measures are being adopted to mitigate these challenges, such as enhanced ventilation systems, upgraded protective equipment, and alternative fixatives. However, biosafety cabinets only partially reduce formaldehyde concentrations but cannot completely prevent exposure. Fully enclosed protective suits are bulky and restrict operational flexibility. Alternatives such as ethanol are costly and poorly fixative for specific tissues, such as fat.

[0003] During the pathology sampling process, doctors face serious occupational health threats, not only suffering long-term physical damage but also enduring psychological stress, exacerbating burnout and impacting work quality. Fundamentally addressing these issues during the pathology sampling process is of great social and professional significance. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide an intelligent robot system and method for obtaining pathological samples from small specimens.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] An intelligent robotic system for small specimen pathology sampling includes: an operating cabin, a central control system, a visual recognition device, dual robotic arms, a loading channel, an embedding cassette input channel, a specimen bottle recovery port, a tissue fixative recovery port, and a fault code alarm prompt device; wherein, the visual recognition device includes: a barcode scanner and an AI image recognition camera for specimen information reading and tissue positioning; the AI ​​image recognition camera and dual robotic arms are used to achieve precise tissue positioning; and the barcode scanner is used to intelligently recognize and process barcodes for pathology resource labeling and archiving.

[0007] Preferably, the operating cabin is equipped with negative pressure ventilation and formaldehyde adsorption devices to ensure that the formaldehyde concentration in the operating area is less than 0.05 ppm.

[0008] Preferably, the visual recognition device includes: a barcode scanner installed on the upper left side of the operating cabin, AI image recognition cameras installed at the four corners of the top of the operating cabin, and a monitoring and recording camera installed above the back panel of the operating cabin. The barcode scanner is used to read the specimen information contained in the barcode affixed to the specimen bottle, the AI ​​image recognition camera is used to identify the number and location of tissues, and the monitoring and recording camera is used to monitor and record the entire tissue sampling process.

[0009] Preferably, the dual robotic arm includes a main robotic arm and an auxiliary robotic arm, which integrate a clamper, a cutting tool and a staining nozzle, and is used for specimen collection operations, including clamping, cutting and staining operations.

[0010] Preferably, the fault code alarm prompt device is installed on both sides of the top of the back panel of the operating cabin for fault prompting. When the alarm occurs, the light flashes and there is a sound prompt.

[0011] The present invention also provides a method for obtaining pathological samples from small specimens, comprising:

[0012] Step 1: Loading: Send the medical storage box containing the specimen bottles into the operation cabin through the loading channel and place it at the entrance of the loading channel. The specimen bottles in the medical storage box can be placed neatly or in disorder.

[0013] Step 2: Scan the barcode: The main robotic arm picks up the specimen bottle by identifying the green bottle cap in the medical storage box, moves it to the barcode scanner, and slowly rotates the specimen bottle. The barcode scanner reads the patient ID and retrieves the tissue type and sampling requirements from the electronic medical record;

[0014] Step 3: Numbering: Read the barcode, upload the patient information to the backend, read the patient code, input the corresponding number information and tissue quantity into the embedding cassette input channel, and then use the embedding cassette inkjet printer to number the front of the embedding cassette;

[0015] Step 4: Gauze flattening: The main robotic arm and the auxiliary robotic arm cooperate to clamp the sterile gauze and unfold and flatten it to the center of the tissue fixative recovery port;

[0016] Step 5: Tissue pouring: The main robotic arm grabs the specimen bottle and shakes the bottle to soak the tissue in the tissue fixative to prevent the tissue from adhering to the bottle or bottle cap and causing tissue loss. The main robotic arm and the auxiliary robotic arm 302 cooperate to unscrew the bottle cap and pour the liquid in the specimen bottle onto the gauze at a uniform speed.

[0017] Step 6: Tissue staining: Identify the amount of tissue and compare it with the amount of tissue marked by the doctor in the patient code. Once the verification is correct, take the syringe of eosin solution and drip it on the tissue for staining;

[0018] Step 7: Packaging: Fold the gauze, wrap the tissue, and place it in the embedding cassette. Close the top cover and arrange the cassettes neatly in the cassette storage box next to the embedding cassette input channel.

[0019] Step eight, data arrangement: enter the embedding box number into the corresponding patient code, close the background operation, repeat step one, and perform the next specimen bottle pathological sampling operation as preferred. The left mechanical arm is equipped with a force control clamp, and the right mechanical arm assists the left mechanical arm in clamping the specimen bottle neck position.

[0020] As preferred, the AI image recognition camera distinguishes green bottle caps and clamps the specimen bottle to the barcode scanning terminal.

[0021] As preferred, the blockchain technology is used to store the patient code-embedding box correspondence, and the laser positioning is used to assist in marking position error <0.5mm

[0022] The present application realizes the standardization and digitization of the unattended small specimen pathological sampling process through the steps of specimen bottle feeding, code scanning, embedding box marking, gauze flattening, tissue pouring, tissue staining, packaging, and data arrangement. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only a part of the embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of the provided drawings.

[0024] Figure 1 A small specimen pathological sampling intelligent robot system structure schematic diagram according to an embodiment of the present application;

[0025] Figure 2 Another small specimen pathological sampling intelligent robot system structure schematic diagram according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0027] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0028] Embodiment 1:

[0029] As Figure 1 , 2As shown, an embodiment of the present invention provides an intelligent robot system for small specimen pathology sampling, including: an operating cabin 1, a central control system, a visual recognition device 2, a dual robotic arm 3, a loading channel 4, an embedding cassette input channel 5, a specimen bottle recovery port 6, a tissue fixative recovery port 7, an embedding cassette inkjet printer 8, a fault code alarm prompt device 9, a top lighting, a negative pressure ventilation and formaldehyde adsorption device 10, a flushing faucet and sink 11, and an ultraviolet disinfection lamp 12.

[0030] The operating cabin 1 is made of stainless steel frame and stainless steel plate, and the front is made of transparent tempered glass to facilitate observation of the operating process;

[0031] The visual recognition device 2 includes a barcode scanner 201 installed on the upper left side of the operating cabin, AI image recognition cameras 202 installed at the four corners of the top of the operating cabin, and a monitoring and recording camera 203 installed above the back panel of the operating cabin. The barcode scanner 201 is used to read the specimen information contained in the barcode attached to the specimen bottle, the AI ​​image recognition camera 202 is used to identify the number and location of tissues, and the monitoring and recording camera 203 is used to monitor and record the entire tissue sampling process.

[0032] The dual robotic arm 3 includes a main robotic arm 301 and an auxiliary robotic arm 302, which integrate a gripper, a cutting tool, and a staining nozzle. It is mainly used for specimen collection operations, including gripping, cutting, and staining operations.

[0033] The loading channel 4 is located above the operating table on the left side of the operating cabin, and the medical storage box 401 containing the specimen bottles can be sent into the closed operating cabin 1 through the loading channel 4;

[0034] The embedding cassette input channel 5 is located above the operating table on the right side of the operating cabin, and the embedding cassette can be delivered into the closed operating cabin 1 through the embedding cassette input channel 5;

[0035] The specimen bottle recovery port 6 is located at the left rear of the middle of the operating table of the operation cabin 1 and is used to recover the used specimen bottles. The recovery box is connected below.

[0036] The tissue fixative recovery port 7 is located in the center of the operating table of the operating cabin 1 and is used to recover the tissue fixative poured out from the specimen bottle. The waste liquid bucket is connected below.

[0037] The embedding cassette inkjet printer 8 is located in the right corner of the operating table and is used to mark the embedding cassettes with inkjet printer;

[0038] The fault code alarm prompt device 9 is installed on both sides of the top of the back plate of the operating cabin 1 and is used for fault prompting. When the alarm occurs, the light flashes and there is a sound prompt.

[0039] Top lighting, negative pressure ventilation and formaldehyde adsorption device 10 are located in the center of the top of the operating cabin 1 to ensure that the formaldehyde concentration in the operating area is less than 0.05ppm;

[0040] The flushing faucet and sink 11 are located behind the tissue fixative recovery port 7 and are used to flush the gripper of the robotic arm 3, etc.

[0041] The ultraviolet disinfection lamps 12 are installed on both sides of the monitoring recording camera 203 to disinfect and sterilize the interior of the operating cabin.

[0042] At the same time, the central control system coordinates the operation of each module and uploads data to the pathology information system (LIS) based on PLC and AI algorithms.

[0043] For the collection of small specimens for pathological sampling, an intelligent robot system is used for fully enclosed operations. Doctors remotely monitor through a visualization system to completely isolate formaldehyde exposure; AI image recognition cameras and dual robotic arms are used to achieve precise tissue positioning; and barcode scanners are used for intelligent barcode recognition and processing of pathological resource marking and archiving.

[0044] Example 2:

[0045] The present invention also provides a method for obtaining pathological samples from small specimens, comprising the following steps:

[0046] Step 1: Loading: The medical storage box 401 containing the specimen bottles is sent into the operation cabin 1 through the loading channel 4 and placed at the opening of the loading channel 4. The specimen bottles in the medical storage box 401 are placed neatly or in disorder.

[0047] Step 2: Scan the barcode: The main robotic arm 301 picks up the specimen bottle by identifying the green bottle cap in the medical storage box 401, moves it to the barcode scanner 201, and slowly rotates the specimen bottle. The barcode scanner 201 reads the patient ID and retrieves the tissue type and sampling requirements from the electronic medical record;

[0048] Step 3: Numbering: Read the barcode, upload the patient information to the backend, read the patient code, input the corresponding number information and tissue quantity into the embedding cassette input channel 5, and then number the front of the embedding cassette through the embedding cassette inkjet printer 8;

[0049] Step 4: Spreading the gauze: The main robotic arm 301 and the auxiliary robotic arm 302 cooperate to clamp the sterile gauze, unfold it, and spread it flat to the center of the tissue fixative recovery port 7;

[0050] Step 5: Tissue pouring: The main robotic arm 301 grabs the specimen bottle and shakes the bottle to soak the tissue in the tissue fixative to prevent the tissue from adhering to the bottle or bottle cap and causing tissue loss. The main robotic arm 301 and the auxiliary robotic arm 302 cooperate to unscrew the bottle cap and pour the liquid in the specimen bottle onto the gauze at a uniform speed.

[0051] Step 6: Tissue staining: Identify the amount of tissue and compare it with the amount of tissue marked by the doctor in the patient code. Once the verification is correct, take the syringe of eosin solution and drip it on the tissue for staining;

[0052] Step 7: Packaging: Fold the gauze, wrap the tissue, and place it in the embedding cassette. Close the top cover and arrange the embedding cassettes neatly in the embedding cassette storage box next to the embedding cassette input channel 5.

[0053] Step 8. Data collation: Enter the embedding cassette number into the corresponding patient code, close the background operation, repeat step 1, and perform the pathological sampling and processing operation for the next specimen bottle.

[0054] As an implementation method of an embodiment of the present invention, in step one, the volume of the specimen bottle containing tissue fixative and small specimens is 20ml-60ml, the volume of the tissue fixative is approximately 10 times the volume of the small specimen, a barcode is affixed to the middle of the specimen bottle, and the specimen bottles in the medical storage box are placed neatly or in disorder. When placed in disorder, the robotic arm adopts vacuum adsorption grasping (adaptable to ±30° tilt angle).

[0055] As an implementation method of an embodiment of the present invention, in step 2, the left robotic arm is equipped with a force-controlled gripper (0.1N accuracy), the right robotic arm assists the left robotic arm in clamping the neck of the specimen, the AI ​​image recognition camera distinguishes the green bottle cap (wavelength 550nm±10nm), clamps the specimen bottle to the barcode scanning terminal, adjusts the position of the bottle body, and the barcode scanning adopts rotation decoding technology (360° reading without dead angles) to ensure zero error in information during the sampling process and avoid confusion.

[0056] As an implementation method of an embodiment of the present invention, in step three, blockchain technology is used to store the correspondence between patient codes and embedding cassettes, laser positioning is used to assist in numbering with a position error of less than 0.5 mm, a dual-server real-time backup mechanism is implemented, and the entire process is traceable to reduce human errors.

[0057] As an implementation method of an embodiment of the present invention, in steps four to six, sterile gauze is stored in a pre-loaded magazine-type storage bin, and visual servo control ensures that the gauze center positioning error is less than 1mm; to prevent tissue slippage and improve operational stability, the bottle cap is unscrewed with torque control (adjustable from 0.2 to 0.5 N·m) to simulate manual pouring action and avoid tissue damage; a micro-injection pump is used to control the amount of 0.5% eosin solution dye (dosage 0.1 ml ± 0.01 ml), and a micro-force tactile sensor (0.05N detection threshold) is integrated at the end of the robotic arm to identify staining uniformity, accurately mark, and improve the subsequent embedding direction recognition; a bionic folding algorithm is used to simulate the manual folding path; and a residual detection system in the bottle (infrared + weighing double verification) is used to prevent tissue from sticking to the bottle wall and causing loss.

[0058] As an implementation of an embodiment of the present invention, in step seven, the cassette packing is standardized to reduce the folding artifacts during the dehydration process, and the embedding cassette channel is equipped with a weight sensor (to detect abnormal empty cassettes).

[0059] As an implementation method of an embodiment of the present invention, in step eight, digital quality control is implemented to support big data analysis.

[0060] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by persons skilled in the art should fall within the scope of protection defined by the claims of the present invention.

Claims

1. An intelligent robot system for collecting pathological samples from small specimens, characterized by: include: Operation cabin, central control system, visual recognition device, dual robotic arms, loading channel, embedding cassette input channel, specimen bottle recovery, tissue fixative recovery port, embedding cassette inkjet printer, fault code alarm prompt device, top lighting, negative pressure ventilation and formaldehyde adsorption device, flushing faucet and sink, ultraviolet disinfection lamp; among them, the visual recognition device includes: barcode scanner, AI image recognition camera and monitoring recording camera, which are used for specimen information reading and tissue positioning; the dual robotic arms include: main robotic arm and auxiliary robotic arm; through AI image recognition camera and dual robotic arms, accurate tissue positioning is achieved; use barcode scanner for intelligent barcode recognition and processing of pathology resource marking and archiving.

2. The intelligent robot system for collecting small specimens for pathological sampling according to claim 1, characterized in that: The operating cabin is equipped with negative pressure ventilation and formaldehyde adsorption devices to keep the formaldehyde concentration in the operating area below 0.05ppm.

3. The intelligent robot system for collecting small specimens for pathological sampling according to claim 2, characterized in that: The visual recognition device includes: a barcode scanner installed on the upper left side of the operating cabin, AI image recognition cameras installed at the four corners of the top of the operating cabin, and a monitoring and recording camera installed above the back panel of the operating cabin. The barcode scanner is used to read the specimen information contained in the barcode affixed to the specimen bottle, the AI ​​image recognition camera is used to identify the number and location of tissues, and the monitoring and recording camera is used to monitor and record the entire tissue sampling process.

4. The intelligent robot system for collecting small specimens for pathological sampling according to claim 3, characterized in that: The dual robotic arm includes a main robotic arm and an auxiliary robotic arm, which integrates a gripper, a cutting tool and a staining nozzle, and is used for specimen collection operations, including clamping, cutting and staining operations.

5. The intelligent robot system for collecting pathological samples from small specimens as claimed in claim 4, characterized in that: The fault code alarm prompt device is installed on both sides of the top of the back panel of the operating cabin for fault prompts. When the alarm occurs, the light flashes and there is a sound prompt.

6. A method for obtaining pathological samples from small specimens, characterized in that: include: Step 1: Loading: Send the medical storage box containing the specimen bottles into the operation cabin through the loading channel and place it at the entrance of the loading channel. The specimen bottles in the medical storage box can be placed neatly or in disorder. Step 2: Scan the barcode: The main robotic arm picks up the specimen bottle by identifying the green bottle cap in the medical storage box, moves it to the barcode scanner, and slowly rotates the specimen bottle. The barcode scanner reads the patient ID and retrieves the tissue type and sampling requirements from the electronic medical record; Step 3: Numbering: Read the barcode, upload the patient information to the backend, read the patient code, input the corresponding number information and tissue quantity into the embedding cassette input channel, and then use the embedding cassette inkjet printer to number the front of the embedding cassette; Step 4: Gauze flattening: The main robotic arm and the auxiliary robotic arm cooperate to clamp the sterile gauze and unfold and flatten it to the center of the tissue fixative recovery port; Step 5: Tissue pouring: The main robotic arm grabs the specimen bottle, shakes the bottle to soak the tissue in the tissue fixative, and the main robotic arm and the auxiliary robotic arm 302 cooperate to unscrew the bottle cap and pour the liquid in the specimen bottle onto the gauze at a uniform speed; Step 6: Tissue staining: Identify the amount of tissue and compare it with the amount of tissue marked by the doctor in the patient code. Once the verification is correct, take the syringe of eosin solution and drip it on the tissue for staining; Step 7: Packaging: Fold the gauze, wrap the tissue, and place it in the embedding cassette. Close the top cover and arrange the embedding cassettes neatly in the embedding cassette storage box next to the embedding cassette input channel. Step 8. Data collation: Enter the embedding cassette number into the corresponding patient code, close the background operation, repeat step 1, and perform the pathological sampling and processing operation for the next specimen bottle.

7. The method for obtaining pathological samples from small specimens according to claim 6, wherein: The AI ​​image recognition camera distinguishes the green bottle cap and clamps the specimen bottle to the barcode scanning terminal.

8. The method for obtaining pathological samples from small specimens according to claim 7, wherein: Blockchain technology is used to store the correspondence between patient codes and embedding cassettes, and laser positioning is used to assist in numbering with a position error of <0.5mm.

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