Intelligent lung cancer cell detection system based on liquid-based cytology

Abstract

The invention discloses an intelligent lung cancer cell detection system based on liquid-based cytology, and the system is characterized in that the system comprises an information input and preprocessing module which is used for receiving basic information and a sampling request of a patient, and carrying out the preprocessing of the received information; the fiber bronchoscope sampling module is used for sampling in the lung of the patient; the liquid-based cell processing and detecting module is used for performing liquid-based cell processing on the collected sample and identifying and analyzing the cells by utilizing an image identification algorithm; and the intelligent detection module is used for automatically generating a detection report according to a liquid-based cell detection result. Through liquid-based cell processing and an image recognition algorithm, the system can automatically recognize and analyze cells, subjectivity and errors of manual judgment are reduced, accuracy and consistency of diagnosis are improved, and time needed by detection is shortened through the automatic process.

Description

Technical Field

[0001] The invention belongs to the technical field of cancer cell detection, and in particular relates to an intelligent lung cancer cell detection system based on liquid-based cytology. Background Art

[0002] Lung cancer is the leading cause of death from malignant tumors worldwide, with high morbidity and mortality rates. With the aging of the population and changes in lifestyle, the prevalence of lung cancer has shown an increasing trend year by year. Traditional methods for detecting lung cancer cells mainly rely on the experience of doctors and pathological examinations, but this method has problems such as strong subjectivity, large workload, and long diagnosis cycle, which makes it difficult to meet the needs of current clinical diagnosis and treatment. In addition, the preparation of pathological sections is cumbersome, time-consuming, and easily affected by human factors, such as section thickness and staining quality. Therefore, it is particularly important to develop an efficient, accurate, and intelligent lung cancer cell detection system. Summary of the invention

[0003] In order to solve the deficiencies of the prior art, the present invention aims to provide an intelligent lung cancer cell detection system based on liquid-based cytology. In order to achieve the above object, the present invention adopts the following technical solution: The intelligent detection system for lung cancer cells based on liquid-based cytology includes: The information input and preprocessing module is responsible for receiving the patient's basic information and sampling request, and preprocessing the received information; A fiberoptic bronchoscope sampling module, used to take samples from the patient's lungs; Liquid-based cell processing and detection module, used to perform liquid-based cell processing on the collected samples and identify and analyze cells using image recognition algorithms; The intelligent detection module is used to automatically generate a detection report based on the results of liquid-based cell detection.

[0004] Preferably, the aforementioned information input and preprocessing module includes an information receiving unit, an information preprocessing unit and a sampling plan generating unit. The information receiving unit is used to receive the patient's basic information and sampling request. The information preprocessing unit is used to verify the integrity and accuracy of the information and recommend appropriate sampling schemes and detection procedures based on the patient information. The sampling plan generating unit generates a detailed sampling plan based on the recommended sampling scheme.

[0005] Preferably, the aforementioned fiber bronchoscope sampling module is used to sample the patient's lungs through a fiber bronchoscope, obtain suspected lung cancer cell samples, and match the sampling information with the medical record file established by the information input module. The fiber bronchoscope sampling module is signal-connected to the liquid-based cell processing and detection module.

[0006] Preferably, the aforementioned liquid-based cell processing and detection module comprises: The liquid-based cell processing unit is used to perform liquid-based processing on the collected cell samples to ensure the integrity and dispersion of the cells; the image processing unit is used to pre-process the processed cell images; A feature extraction unit, which uses an image recognition algorithm to extract features from cell images; The classification and recognition unit classifies and recognizes the cells according to the extracted features to determine whether they are lung cancer cells.

[0007] Preferably, the aforementioned intelligent detection module includes a diagnosis report generation unit, a personalized treatment recommendation unit and a data sharing unit. The diagnosis report generation unit automatically generates a diagnosis report based on the classification and recognition results, including the type, quantity, and distribution information of lung cancer cells; the personalized treatment recommendation unit provides personalized treatment recommendations based on the diagnosis report and patient information; the data sharing unit realizes real-time sharing and exchange of data with the hospital information system and the electronic medical record system.

[0008] Preferably, it also includes a system optimization and upgrade module, which includes a user feedback collection unit, a performance data monitoring unit and a continuous optimization unit. The user feedback collection unit is used to collect user feedback on the use of the system, the performance data monitoring unit is used to monitor and analyze system performance data in real time, and the continuous optimization unit continuously optimizes and upgrades the system based on user feedback and performance data.

[0009] Preferably, it also includes an information storage and output module, including an information storage unit and an information output unit. The information storage unit is used to store relevant pathological information, sampling information, and test result information for query and call. The information output unit converts and outputs the judgment information and sends the printed report and electronic report to an email address or medical system.

[0010] The benefits of the present invention are as follows: through liquid-based cell processing and image recognition algorithms, the system can automatically identify and analyze cells, reduce the subjectivity and errors of human judgment, improve the accuracy and consistency of diagnosis, and the automated process reduces the time required for testing; the system provides personalized treatment recommendations based on the patient's specific situation and diagnostic results, which helps doctors develop treatment plans that are more suitable for the patient; data sharing with hospital information systems and electronic medical record systems makes doctors' decisions more comprehensive and timely, and facilitates the query and management of patient information; user feedback and real-time monitoring of performance data enable the system to be continuously improved and optimized, improving system stability and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a structural schematic diagram of the present invention. DETAILED DESCRIPTION

[0012] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0013] See also Figure 1 The present invention provides an intelligent detection system for lung cancer cells based on liquid-based cytology, comprising: an information input and preprocessing module, which is responsible for receiving the patient's basic information and sampling request, and preprocessing the received information; a fiber bronchoscope sampling module, which is used to take samples from the patient's lungs; a liquid-based cell processing and detection module, which is used to perform liquid-based cell processing on the collected samples, and use an image recognition algorithm to identify and analyze the cells; and an intelligent detection module, which is used to automatically generate a detection report based on the results of the liquid-based cell detection.

[0014] The information input and preprocessing module includes an information receiving unit, an information preprocessing unit and a sampling plan generating unit. The information receiving unit is used to receive the patient's basic information and sampling request. The information preprocessing unit is used to verify the integrity and accuracy of the information and recommend appropriate sampling schemes and testing procedures based on the patient's information. The sampling plan generating unit generates a detailed sampling plan based on the recommended sampling scheme.

[0015] The fiber bronchoscope sampling module is used to sample the patient's lungs through a fiber bronchoscope, obtain suspected lung cancer cell samples, and match the sampling information with the medical record file established by the information input module. The fiber bronchoscope sampling module is signal-connected to the liquid-based cell processing and detection module.

[0016] Liquid-based cell processing and detection module The liquid-based cell processing and detection module includes: a liquid-based cell processing unit, which is used to perform liquid-based processing on the collected cell samples to ensure the integrity and dispersion of the cells; an image processing unit, which is used to pre-process the processed cell images; a feature extraction unit, which uses an image recognition algorithm to extract features in the cell image; and a classification and recognition unit, which classifies and recognizes the cells according to the extracted features to determine whether they are lung cancer cells.

[0017] The intelligent detection module includes a diagnosis report generation unit, a personalized treatment recommendation unit and a data sharing unit. The diagnosis report generation unit automatically generates a diagnosis report based on the classification and recognition results, including the type, quantity and distribution information of lung cancer cells; the personalized treatment recommendation unit provides personalized treatment recommendations based on the diagnosis report and patient information; the data sharing unit realizes real-time sharing and exchange of data with the hospital information system and electronic medical record system.

[0018] The detection system also includes a system optimization and upgrade module, which includes a user feedback collection unit, a performance data monitoring unit and a continuous optimization unit. The user feedback collection unit is used to collect user feedback on system usage, the performance data monitoring unit is used to monitor and analyze system performance data in real time, and the continuous optimization unit continuously optimizes and upgrades the system based on user feedback and performance data.

[0019] The detection system also includes an information storage and output module, including an information storage unit and an information output unit. The information storage unit is used to store relevant pathological information, sampling information, and test result information for query and call. The information output unit converts and outputs the judgment information and sends the printed report and electronic report to the mailbox or medical system.

[0020] In order to better illustrate the present invention, the working process is specifically described below: 1. Information entry and preprocessing Enter the patient's basic information, such as name, age, gender, medical history, etc., through the system, and make a sampling request based on the patient's symptoms and medical history, and enter it into the system. The system automatically pre-processes the received information, verifies the completeness and accuracy of the information, and recommends appropriate sampling plans and testing procedures based on the patient's information.

[0021] 2. Fiberoptic bronchoscopy sampling According to the sampling plan generated by the system, a fiberoptic bronchoscope is used to sample the patient's lungs. During the sampling process, the system will record the sampling information in real time and match it with the patient's medical records. After the sampling is completed, the sample is sent to the liquid-based cell processing and detection module for further processing.

[0022] 3. Liquid-based cell processing and detection The collected cell samples are subjected to liquid-based treatment by the liquid-based cell processing unit to ensure the integrity and dispersion of the cells. The processed cell images are pre-processed by the image processing unit, including denoising, contrast enhancement, etc., to improve the image quality. The feature extraction unit uses the image recognition algorithm to extract features in the cell image, such as shape, size, texture, etc. The classification and recognition unit classifies and recognizes the cells according to the extracted features to determine whether they are lung cancer cells and determine their type and quantity.

[0023] 4. Intelligent detection and report generation The system automatically generates a diagnosis report based on the classification and recognition results, including the type, quantity, and distribution of lung cancer cells. The personalized treatment recommendation unit provides personalized treatment recommendations for patients based on the diagnosis report and patient information, combined with medical resources. The data sharing unit enables real-time sharing and exchange of data such as diagnosis reports and treatment recommendations with the hospital information system and electronic medical record system for easy reference.

[0024] 5. Information storage and output The system will store the patient's pathological information, sampling information, test result information, etc. in the information storage unit for query and call. When the patient needs to view the diagnosis report, the information output unit will convert and output the report, such as printing the report or sending an electronic report to the patient's email. The patient's diagnosis report and treatment recommendations can be viewed through the medical system to develop a more accurate treatment plan.

[0025] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the above embodiments do not limit the present invention in any form, and any technical solution obtained by equivalent replacement or equivalent transformation falls within the protection scope of the present invention.

Claims

1. The intelligent detection system of lung cancer cells based on liquid-based cytology is characterized by: include: The information input and preprocessing module is responsible for receiving the patient's basic information and sampling request, and preprocessing the received information; A fiberoptic bronchoscope sampling module, used to take samples from the patient's lungs; Liquid-based cell processing and detection module, used to perform liquid-based cell processing on the collected samples and identify and analyze cells using image recognition algorithms; The intelligent detection module is used to automatically generate a detection report based on the results of liquid-based cell detection.

2. The liquid-based cytology-based intelligent lung cancer cell detection system according to claim 1, characterized in that: The information input and preprocessing module includes an information receiving unit, an information preprocessing unit and a sampling plan generating unit. The information receiving unit is used to receive basic patient information and sampling requests. The information preprocessing unit is used to verify the integrity and accuracy of the information and recommend appropriate sampling plans and testing procedures based on the patient information. The sampling plan generating unit generates a detailed sampling plan according to the recommended sampling scheme.

3. The intelligent detection system for lung cancer cells based on liquid-based cytology according to claim 1, characterized in that: The fiber bronchoscope sampling module is used to sample the patient's lungs through a fiber bronchoscope, obtain suspected lung cancer cell samples, and match the sampling information with the medical record file established by the information input module. The fiber bronchoscope sampling module is signal-connected to the liquid-based cell processing and detection module.

4. The intelligent detection system for lung cancer cells based on liquid-based cytology according to claim 1, characterized in that: The liquid-based cell processing and detection module includes: The liquid-based cell processing unit is used to perform liquid-based processing on the collected cell samples to ensure the integrity and dispersion of the cells; the image processing unit is used to pre-process the processed cell images; A feature extraction unit, which uses an image recognition algorithm to extract features from cell images; The classification and recognition unit classifies and recognizes the cells according to the extracted features to determine whether they are lung cancer cells.

5. The intelligent detection system for lung cancer cells based on liquid-based cytology according to claim 1, characterized in that: The intelligent detection module includes a diagnosis report generation unit, a personalized treatment recommendation unit and a data sharing unit. The diagnosis report generation unit automatically generates a diagnosis report according to the classification and recognition results, including the type, quantity and distribution information of lung cancer cells; the personalized treatment recommendation unit provides personalized treatment recommendations based on the diagnosis report and patient information; the data sharing unit realizes real-time sharing and exchange of data with the hospital information system and the electronic medical record system.

6. The intelligent detection system for lung cancer cells based on liquid-based cytology according to claim 1, characterized in that: It also includes a system optimization and upgrade module, which includes a user feedback collection unit, a performance data monitoring unit and a continuous optimization unit. The user feedback collection unit is used to collect user feedback on system usage, the performance data monitoring unit is used to monitor and analyze system performance data in real time, and the continuous optimization unit continuously optimizes and upgrades the system based on user feedback and performance data.

7. The intelligent detection system for lung cancer cells based on liquid-based cytology according to claim 1, characterized in that: It also includes an information storage and output module, including an information storage unit and an information output unit. The information storage unit is used to store relevant pathological information, sampling information, and test result information for query and call. The information output unit converts and outputs the judgment information and sends the printed report and electronic report to an email or medical system.

Images