Intelligent stoma evaluation system and method combining spectral analysis and image recognition

Abstract

The invention belongs to the technical field of spectral analysis, and discloses a spectral analysis and image recognition combined intelligent stoma evaluation system and method.A three-dimensional scanning module captures the three-dimensional form of a stoma and the three-dimensional form of surrounding tissue of the stoma through the high-precision laser or structured light scanning technology; the spectral analysis module is used for accurately analyzing the color change of the stoma; the tiny color difference of the stoma area is detected to help to identify potential tissue abnormality; the image recognition and processing module is used for analyzing the collected stoma image by using a deep learning algorithm and automatically recognizing morphological characteristics of the stoma; the data analysis and feedback system is used for automatically generating a stoma health assessment report according to the collected multi-dimensional data; through a set standard reference value, an actual measurement value is compared, and a corresponding suggestion is given, for example, whether a nursing scheme needs to be adjusted or further medical intervention needs to be carried out. According to the method, the real-time state of the stoma is accurately evaluated through non-contact scanning and spectrum detection.

Description

Technical Field

[0001] The present invention belongs to but is not limited to the field of spectral analysis technology, and in particular relates to an intelligent stoma assessment system and method combining spectral analysis and image recognition. Background Art

[0002] As the number of patients undergoing stoma surgery continues to grow, the demand for professional stoma care is increasing. Traditional stoma care relies on the professional judgment and experience of medical staff, which is labor-intensive and relatively inefficient. Therefore, intelligent means are needed to improve the efficiency and quality of care. The existing technology has the following technical problems:

[0003] 1. Difficulty in multi-dimensional accurate assessment: Traditional stoma assessment mainly relies on manual observation, which may lead to inaccurate assessment due to subjective errors. This system combines 3D scanning technology and spectral analysis technology to accurately assess stomas in multiple dimensions, reducing the uncertainty caused by subjective judgment.

[0004] 2. Non-contact assessment problem: Traditional stoma assessment requires contact with the stoma or its surrounding tissues, which may bring infection risks. The non-contact scanning and spectral detection of the present invention avoids direct contact with the stoma and reduces the risk of infection.

[0005] 3. Data standardization and automated analysis: Data in stoma assessment is usually not quantifiable, resulting in a lack of standardization in the assessment results. Through the intelligent system, the invention can automatically generate quantitative assessment data, and combine big data analysis to achieve standardized judgment and recording of stoma status, providing more accurate nursing guidance. Summary of the invention

[0006] In view of the problems existing in the prior art, the present invention provides an intelligent stoma assessment system and method combining spectral analysis and image recognition.

[0007] The present invention is implemented as follows: an intelligent stoma assessment system combining spectral analysis and image recognition, the system comprising:

[0008] The 3D scanning module uses high-precision laser scanning or structured light scanning technology to capture the 3D morphology of the stoma and its surrounding tissues. It can accurately measure the stoma's height, size, shape and other physical parameters and generate a 3D image.

[0009] Spectral analysis module, which uses multispectral imaging (MSI) or hyperspectral imaging (HSI) technology to accurately analyze the color changes of the stoma, detect small color differences in the stoma area through spectral data, and identify potential tissue abnormalities such as inflammation, infection or poor blood flow;

[0010] The image recognition and processing module is connected to the above-mentioned three-dimensional scanning module and spectrum analysis module, and uses a deep learning algorithm to analyze the collected stoma images, automatically identify the morphological characteristics of the stoma, and automatically calculate the area, contour, height and other information of the stoma based on the scanned three-dimensional data and spectrum analysis results, and generate an accurate evaluation report;

[0011] The data analysis and feedback system is connected to the 3D scanning module and the image recognition and processing module, and integrates intelligent evaluation software. It can automatically generate a stoma health assessment report based on the collected multi-dimensional data, and compare the actual measurement values ​​with the set standard reference values ​​to provide corresponding nursing suggestions or medical intervention suggestions;

[0012] The data collection module is connected to the central control module. The data collection module receives the instructions from the central control module and first sends the request information to the switch, which then sends it to the router. The router sends the request to the DNS server. The DNS server calls the vertical search engine to establish a search engine on the Internet, finds the data information to be collected through network radar and automatic indexing technology, and then calls the information tracking and automatic sorting technology to classify the information.

[0013] The central control module is connected with the data collection module, image recognition and processing module, model building module, cloud storage module, local storage module and data encryption module. It is responsible for collecting external signals (data and requests transmitted by each module), and outputting them to the output channel after analysis and processing. When external analog output is required, the system converts the signal into a standard electrical signal through a D / A converter to control the normal operation of each module.

[0014] The cloud storage module is connected to the central control module. To use the cloud storage service, a cloud storage platform is first created in the local server deployment data center. The storage protocol is implemented through a third-party gateway. The user writes local data to the cloud storage gateway through a network cable. The cloud storage gateway transmits the data to the edge router. The edge router transmits the data to the cloud platform through a dedicated public network. An object storage request is initiated in the cloud platform. The data is transmitted to the cloud storage gateway in the cloud platform. The cloud storage gateway sends the data to the cloud storage availability zone through a vSwitch to realize cloud storage of data.

[0015] The local storage module is connected to the central control module and uses the SQL interface to connect to the SQL service database. The data acquisition and reading module packages the converted data and sends it to the central control module. The central control module transmits the data to the SQL service database and the cloud storage module through label operations.

[0016] The data encryption module is connected to the central control module and is responsible for encrypting the data in the local storage module and the cloud storage module. When the data is stored, the data encryption server randomly generates two pairs of keys to encrypt the data, which act on the local storage module and the cloud storage module respectively. When the user requests to view the data, the data encryption server performs identity authentication and requests the key. After the user enters the corresponding information, the data encryption server verifies and feedbacks the license. The data decryption server decrypts the data and packages it for transmission to the central control module.

[0017] Furthermore, the image recognition and processing module uses convolutional neural network (CNN) and generative adversarial network (GAN) for deep learning training to improve the accuracy and robustness of image recognition.

[0018] Furthermore, the data analysis and feedback system includes a decision curve analysis (DCA) function for evaluating the clinical practicality of the prediction model and automatically generating nursing recommendations or medical intervention plans based on the analysis results.

[0019] Furthermore, the user interaction and interface design includes multi-language support and customized settings to meet the needs of medical institutions in different regions and allow users to customize system settings and evaluation criteria according to actual needs.

[0020] The system integration and compatibility module supports seamless integration with hospital information systems (HIS) and electronic medical records (EMR), realizes automatic import and export of data, and improves work efficiency.

[0021] The system adopts a modular design to support subsequent expansion and upgrading of functions, such as adding more sensor modules or introducing new data analysis algorithms, to ensure the long-term applicability and maintainability of the system.

[0022] The data encryption module uses the Advanced Encryption Standard (AES) algorithm to encrypt data and is equipped with a strict access control mechanism to ensure that only authorized personnel can access sensitive data.

[0023] Through the preparation of the above claims, the various functional modules of the intelligent ostomy assessment system and their mutual connections and functions are fully covered, ensuring that the innovation and practicality of the system are fully reflected, which helps to improve the success rate of patent applications.

[0024] Further, the three-dimensional scanning module is implemented as follows:

[0025] S1: Operates through high-precision laser or structured light scanning technology; the scanning device emits a beam of light, including laser or structured light, and projects it onto the stoma and surrounding tissue;

[0026] S2: Based on the light reflection time or light deformation, the sensor collects the reflection signal and converts it into 3D point cloud data; each point records the 3D coordinates of the scanned area;

[0027] S3: Through multi-angle scanning, the system can reconstruct a three-dimensional model of the opening.

[0028] Furthermore, the spectral analysis module uses multi-spectral or hyperspectral imaging equipment to irradiate light of different wavelengths onto the stoma area and record the reflected spectrum through a sensor; each pixel has complete spectral information and can analyze the color changes in the stoma area; then, by processing these spectral data, subtle differences in the tissue can be identified.

[0029] Furthermore, the image recognition and processing module inputs the collected stoma images into a pre-trained neural network model based on a deep learning algorithm; the neural network automatically extracts relevant geometric features and physical parameters by identifying the boundaries, shapes and textures of the stoma; the image processing algorithm is combined with three-dimensional scanning and spectral analysis to provide a more accurate evaluation.

[0030] Furthermore, the data analysis and feedback system integrates intelligent evaluation software, and automatically performs data fusion and analysis through the collected three-dimensional scanning data, spectral data and image recognition results; the system sets standard reference values ​​and compares the actual test results to determine the health status of the stoma; the intelligent algorithm generates an evaluation report based on preset evaluation standards and gives corresponding nursing recommendations.

[0031] Another object of the present invention is to provide an intelligent stoma assessment method combining spectral analysis and image recognition based on the intelligent stoma assessment system combining spectral analysis and image recognition, characterized in that the method specifically comprises:

[0032] S21: The three-dimensional scanning module continuously acquires the reflected light signals of the stoma surface contour to generate the three-dimensional shape of the stoma in real time; combined with the machine learning model, the system can calculate the physical parameters of the stoma, such as height, size, shape, etc., through the scanning data; these data can be used to evaluate the stoma healing progress and care needs;

[0033] S22: Using the spectral analysis module, when different wavelengths of light are irradiated to the stoma area, the reflective properties of the tissue vary due to different physiological states, such as blood flow, tissue inflammation, etc. By capturing these tiny differences in reflection, the system can identify color changes and detect potential tissue abnormalities, such as inflammation, infection, or poor blood flow. The spectral data combined with the three-dimensional morphology of the stoma can help further understand the physiological changes of the stoma.

[0034] S23: The deep learning algorithm in the image recognition and processing module learns and recognizes subtle differences in stoma morphology through training with a large amount of labeled image data. The system can automatically calculate parameters such as area, contour and height by identifying the stoma contour and its three-dimensional shape in the image. These parameters, combined with spectral data, can be used to generate more accurate stoma assessment reports and predict the healing status of the stoma.

[0035] S24: The data collected by all modules are integrated using the data analysis and feedback system, and the set evaluation criteria, such as normal stoma color range, morphological characteristics, size, etc., are used to automatically determine whether the stoma status meets the standards; if abnormalities are detected, such as tissue inflammation, poor healing or infection, the system will remind the caregiver through a feedback mechanism; at the same time, the system can generate a dynamic stoma healing curve based on data from multiple evaluations to help caregivers adjust care plans or recommend further medical intervention.

[0036] Another object of the present invention is to provide a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the intelligent stoma assessment method combining spectral analysis and image recognition.

[0037] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to perform the steps of the intelligent stoma assessment method combining spectral analysis and image recognition.

[0038] Another object of the present invention is to provide an information data processing terminal, characterized in that the information data processing terminal is used to implement the intelligent stoma assessment system combining spectral analysis and image recognition.

[0039] In combination with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0040] First, the present invention can improve the accuracy of stoma assessment: through three-dimensional scanning and spectral analysis, the system can accurately identify slight changes in the stoma, provide more accurate analysis results of color, shape, size and height, and significantly improve the accuracy of the assessment.

[0041] The present invention can reduce the risk of infection during the evaluation process: the non-contact evaluation method not only improves safety, but also reduces secondary infection that may be caused by contact with the stoma, thereby ensuring the health and safety of stoma patients.

[0042] The present invention is capable of real-time monitoring and dynamic evaluation: the system supports real-time monitoring of stoma changes, and through image recognition and spectral analysis functions, it can promptly capture any abnormal conditions of the stoma, helping medical staff or nursing staff to quickly adjust the nursing plan and improve the patient's recovery effect.

[0043] The present invention can improve nursing efficiency and standardization: through intelligent data processing and automatic analysis, the system can quickly generate standardized stoma assessment reports, helping nursing staff to manage patients more efficiently while reducing human errors.

[0044] Second, the intelligent stoma assessment system combining spectral analysis and image recognition provided by the present invention realizes a comprehensive, accurate and intelligent assessment of the stoma and its surrounding tissues by integrating multiple advanced technical modules. The specific technical effects are as follows:

[0045] 1. High-precision 3D shape capture and measurement

[0046] Accurate measurement: Using high-precision laser scanning or structured light scanning technology, the system can accurately capture the three-dimensional morphology of the stoma and its surrounding tissues, and accurately measure the stoma's height, size, shape and other physical parameters. This high-precision measurement capability significantly improves the accuracy of stoma assessment and reduces human measurement errors.

[0047] Detailed 3D image generation: The generated 3D images provide medical staff with an intuitive and detailed view of the stoma and surrounding tissues, helping to gain a more comprehensive understanding of the status and changes of the stoma.

[0048] 2. Accurate spectral analysis and tissue abnormality detection

[0049] Combination of multispectral and hyperspectral imaging: Through multispectral imaging (MSI) and hyperspectral imaging (HSI) technology, the system can accurately analyze the color changes in the stoma area and detect tiny color differences. These differences can reflect potential tissue abnormalities, such as inflammation, infection or poor blood flow, and help early detection and intervention.

[0050] Real-time spectral data processing: The integrated real-time spectral data processing unit can instantly analyze the collected spectral data and quickly identify abnormal areas, improving diagnostic efficiency and response speed.

[0051] 3. Intelligent image recognition and processing

[0052] Deep learning algorithm optimization: The system uses advanced deep learning algorithms (such as convolutional neural networks (CNN) and generative adversarial networks (GAN)) and is trained on large-scale data sets to significantly improve the accuracy and robustness of image recognition. The system can automatically identify the morphological features of stomas, reducing the workload and subjective errors of manual analysis.

[0053] Multimodal data fusion analysis: Fusion of 3D scanning data and spectral analysis data to comprehensively analyze the morphological characteristics and color changes of the stoma to generate a more accurate and comprehensive evaluation report.

[0054] 4. Comprehensive data management and security assurance

[0055] Distributed data storage architecture: Through the combination of cloud storage modules and local storage modules, the system achieves efficient access and flexible management of data. Cloud storage ensures high availability and scalability of data, while local storage ensures fast access and local backup of data.

[0056] Advanced data encryption and access control: The Advanced Encryption Standard (AES) algorithm is used to encrypt data, and a strict access control mechanism is provided to ensure that only authorized personnel can access sensitive data. This effectively protects patient privacy and complies with relevant data protection regulations.

[0057] 5. Intelligent data analysis and personalized feedback

[0058] Intelligent assessment report generation: The integrated intelligent assessment software can automatically generate detailed stoma health assessment reports based on multi-dimensional data, provide scientific and comprehensive assessment results, and assist medical staff in formulating reasonable care plans.

[0059] Personalized nursing advice: The system automatically generates personalized nursing advice or medical intervention plans based on the set standard reference values ​​and compares the actual measured values, thus improving the targetedness and effectiveness of nursing care.

[0060] 6. Optimized user interaction and clinical integration

[0061] Friendly user interface design: The intuitive and concise user interface allows medical staff to easily operate through touch screens or mobile devices, quickly view three-dimensional images, spectral analysis results and evaluation reports, and significantly improve the ease of use.

[0062] Seamless integration with hospital information systems (HIS) and electronic medical records (EMR): It realizes automatic import and export of data, supports multi-device sharing and remote access, promotes data sharing and collaborative work among medical institutions in multiple locations, and improves the overall efficiency of medical services.

[0063] 7. Modular design and system scalability

[0064] Modular expansion design: The system adopts a modular design to support the expansion and upgrade of subsequent functions, such as adding more sensor modules or introducing new data analysis algorithms, ensuring that the system can adapt to future technological developments and changes in clinical needs.

[0065] Long-term applicability and maintainability: The modular design not only improves the flexibility of the system, but also simplifies the maintenance and upgrade process, extends the service life of the system and reduces operating costs.

[0066] In summary, the intelligent stoma assessment system of the present invention realizes efficient, accurate and intelligent stoma assessment by integrating high-precision three-dimensional scanning, precise spectral analysis, intelligent image recognition, multimodal data fusion, comprehensive data management and security, as well as a friendly user interface and modular design. Compared with existing paper / electronic spreadsheets or simple image recognition methods, this system not only improves the accuracy and reliability of the assessment, but also significantly improves the efficiency and security of data processing, optimizes the convenience and practicality of clinical applications, and has significant technological progress and broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 It is a structural diagram of an intelligent stoma assessment system combining spectral analysis and image recognition provided by an embodiment of the present invention;

[0068] Figure 2 is a flow chart of a method for implementing a three-dimensional scanning module provided by an embodiment of the present invention;

[0069] Figure 3 It is a flow chart of an intelligent stoma assessment method combining spectral analysis and image recognition provided by an embodiment of the present invention;

[0070] In the figure: 1. 3D scanning module; 2. Spectral analysis module; 3. Image recognition and processing module; 4. Data analysis and feedback system. DETAILED DESCRIPTION

[0071] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0072] The present invention provides an intelligent stoma assessment system combining spectral analysis and image recognition, comprising:

[0073] 1. 3D scanning module

[0074] High-precision scanning technology: High-precision laser scanning or structured light scanning technology is used to capture the three-dimensional morphology of the stoma and its surrounding tissues, ensuring that the scanning resolution reaches the sub-millimeter level to obtain detailed stoma contours and surrounding tissue structures.

[0075] Automatic alignment and calibration function: The system has automatic alignment and calibration functions to ensure the data consistency of each scan and improve the accuracy and comparability of three-dimensional images.

[0076] 2. Spectral analysis module

[0077] Combination of multispectral and hyperspectral imaging: Combining multispectral imaging (MSI) and hyperspectral imaging (HSI) technology, a comprehensive spectral analysis of the stoma area is performed to obtain richer spectral information.

[0078] Real-time spectral data processing: The integrated real-time spectral data processing unit can instantly analyze color changes and quickly identify potential tissue abnormalities such as inflammation, infection or poor blood flow.

[0079] 3. Image recognition and processing module

[0080] Deep learning algorithm optimization: Adopt the latest deep learning architecture (such as convolutional neural network CNN, generative adversarial network GAN, etc.) and train with large-scale data sets to improve the accuracy and robustness of image recognition.

[0081] Multimodal data fusion: Fusion of 3D scanning data and spectral analysis data to comprehensively analyze the morphological characteristics and color changes of the stoma to improve the accuracy of the assessment report.

[0082] Automatic labeling and anomaly detection: The system can automatically label key areas of the stoma and surrounding tissues, and automatically identify and mark potential abnormal areas through anomaly detection algorithms to assist medical staff in further examination.

[0083] 4.Data analysis and feedback system

[0084] Intelligent assessment software: Integrates advanced data analysis software that can conduct comprehensive assessments based on multi-dimensional data (such as three-dimensional morphology, spectral information, historical assessment data, etc.) and generate detailed health assessment reports.

[0085] Generation of personalized care recommendations: Based on the assessment results and set standard reference values, the system can generate personalized care recommendations to guide medical staff to develop or adjust care plans, or indicate the need for further medical intervention.

[0086] Cloud data storage and access: Assessment data and reports can be stored synchronously in the cloud, supporting remote access and multi-device sharing, facilitating data sharing and collaborative work among multi-location medical institutions.

[0087] 5. User interaction and interface design

[0088] Intuitive and user-friendly interface: The simple and intuitive user interface allows medical staff to easily operate the instrument through a touch screen or mobile device to view 3D images, spectral analysis results and evaluation reports.

[0089] Real-time feedback and visualization: Provides real-time feedback function, medical staff can instantly view the scanning and analysis results, and intuitively understand the stoma status through visual charts and 3D models.

[0090] Multi-language support and customized settings: Supports multi-language interface to meet the needs of medical institutions in different regions, and allows users to customize system settings and evaluation criteria according to actual needs.

[0091] 6. System integration and compatibility

[0092] Integration with hospital information system (HIS): The system can be seamlessly integrated with the existing hospital information system (HIS) and electronic medical record (EMR) to realize automatic import and export of data and improve work efficiency.

[0093] Modular expansion design: The modular design supports subsequent expansion and upgrade of functions, such as adding more sensor modules or introducing new data analysis algorithms, ensuring the long-term applicability and maintainability of the system.

[0094] 7. Security and Privacy Protection

[0095] Data encryption and access control: All collected and stored data are encrypted using advanced encryption algorithms to ensure data security during transmission and storage. At the same time, the system has a strict access control mechanism, and only authorized personnel can access sensitive data.

[0096] Compliance design: The system design complies with relevant medical data protection regulations and standards (such as GDPR, HIPAA, etc.) to ensure that the privacy and security of user data are fully protected.

[0097] Improved system advantages:

[0098] 1. Comprehensiveness and accuracy: By combining 3D scanning, hyperspectral imaging and deep learning algorithms, the system can comprehensively and accurately assess the health of the stoma and surrounding tissues, providing more detailed and reliable assessment results than traditional methods.

[0099] 2. Automation and intelligence: The system is highly automated, which reduces errors caused by human operation, improves evaluation efficiency, and assists medical staff in making scientific decisions through intelligent analysis and feedback.

[0100] 3. User experience optimization: Intuitive and friendly interface design and real-time feedback function improve the user experience of medical staff, reduce training costs, and improve the actual application value of the system.

[0101] 4. Data management and sharing: Cloud storage and system integration design promote efficient data management and cross-institutional sharing, support multi-location collaborative work, and improve the overall efficiency of medical services.

[0102] 5. Security and Compliance: Complete data encryption and privacy protection mechanisms ensure data security and compliance of the system in actual applications, enhancing user trust and the market competitiveness of the system.

[0103] Through the above improvements, the intelligent stoma assessment system not only realizes the comprehensive analysis and intelligent assessment of multimodal data in terms of technology, but also comprehensively optimizes the system architecture, user experience, security, etc., significantly improving the innovation and practicality of the system. The system has significant technological progress and application advantages in the field of stoma assessment, and meets the requirements of the patent law for novelty, creativity and practicality.

[0104] like Figure 1 As shown, an embodiment of the present invention provides an intelligent stoma assessment system combining spectral analysis and image recognition, the system comprising:

[0105] The three-dimensional scanning module 1 uses high-precision laser or structured light scanning technology to capture the three-dimensional morphology of the stoma and its surrounding tissues; it can accurately measure the height, size, shape and other physical parameters of the stoma and generate a three-dimensional image;

[0106] Spectral analysis module 2 uses multispectral or hyperspectral imaging technology to accurately analyze color changes in the stoma. Through spectral data, it can detect subtle color differences in the stoma area and help identify potential tissue abnormalities such as inflammation, infection or poor blood flow.

[0107] The image recognition and processing module 3 is connected to the three-dimensional scanning module 1 and the spectrum analysis module 2, and uses a deep learning algorithm to analyze the collected stoma images and automatically identify the morphological characteristics of the stoma. The image processing algorithm can automatically calculate the area, contour, height and other information of the stoma based on the scanned three-dimensional data and the spectrum analysis results, and generate an accurate evaluation report;

[0108] The data analysis and feedback system 4 is connected to the three-dimensional scanning module 1 and the spectral analysis module 2. Through the integrated intelligent evaluation software, the system can automatically generate a health assessment report of the stoma based on the collected multi-dimensional data; the system can compare the actual measurement values ​​with the set standard reference values ​​and give corresponding suggestions, such as whether the care plan needs to be adjusted or further medical intervention is needed.

[0109] like Figure 2 As shown, the implementation method of the three-dimensional scanning module 1 is as follows:

[0110] S1: Operates through high-precision laser or structured light scanning technology; the scanning device emits a beam of light, including laser or structured light, and projects it onto the stoma and surrounding tissue;

[0111] S2: Based on the light reflection time or light deformation, the sensor collects the reflection signal and converts it into 3D point cloud data; each point records the 3D coordinates of the scanned area;

[0112] S3: Through multi-angle scanning, the system can reconstruct a three-dimensional model of the opening.

[0113] The spectral analysis module 2 uses multi-spectral or hyperspectral imaging equipment to irradiate light of different wavelengths to the stoma area and record the reflected spectrum through a sensor; each pixel has complete spectral information and can analyze the color changes in the stoma area; then, by processing these spectral data, subtle differences in the tissue are identified.

[0114] The image recognition and processing module 3 inputs the collected stoma image into a pre-trained neural network model based on a deep learning algorithm; the neural network automatically extracts relevant geometric features and physical parameters by identifying the boundaries, shapes and textures of the stoma; the image processing algorithm is combined with three-dimensional scanning and spectral analysis to provide a more accurate evaluation.

[0115] The data analysis and feedback system 4 integrates intelligent evaluation software, and automatically performs data fusion and analysis through the collected three-dimensional scanning data, spectral data and image recognition results; the system sets standard reference values ​​and compares the actual test results to determine the health status of the stoma; the intelligent algorithm generates an evaluation report based on the preset evaluation criteria and gives corresponding nursing suggestions.

[0116] like Figure 3 As shown, an embodiment of the present invention provides an intelligent stoma assessment method combining spectral analysis and image recognition based on the intelligent stoma assessment system combining spectral analysis and image recognition, and the method specifically includes:

[0117] S21: The three-dimensional scanning module continuously acquires the reflected light signals of the stoma surface contour to generate the three-dimensional shape of the stoma in real time; combined with the machine learning model, the system can calculate the physical parameters of the stoma, such as height, size, shape, etc., through the scanning data; these data can be used to evaluate the stoma healing progress and care needs;

[0118] S22: Using the spectral analysis module, when different wavelengths of light are irradiated to the stoma area, the reflective properties of the tissue vary due to different physiological states, such as blood flow, tissue inflammation, etc. By capturing these tiny differences in reflection, the system can identify color changes and detect potential tissue abnormalities, such as inflammation, infection, or poor blood flow. The spectral data combined with the three-dimensional morphology of the stoma can help further understand the physiological changes of the stoma.

[0119] S23: The deep learning algorithm in the image recognition and processing module learns and recognizes subtle differences in stoma morphology through training with a large amount of labeled image data. The system can automatically calculate parameters such as area, contour and height by identifying the stoma contour and its three-dimensional shape in the image. These parameters, combined with spectral data, can be used to generate more accurate stoma assessment reports and predict the healing status of the stoma.

[0120] S24: The data collected by all modules are integrated using the data analysis and feedback system, and the set evaluation criteria, such as normal stoma color range, morphological characteristics, size, etc., are used to automatically determine whether the stoma status meets the standards; if abnormalities are detected, such as tissue inflammation, poor healing or infection, the system will remind the caregiver through a feedback mechanism; at the same time, the system can generate a dynamic stoma healing curve based on data from multiple evaluations to help caregivers adjust care plans or recommend further medical intervention.

[0121] An embodiment of the present invention provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the intelligent stoma assessment method combining spectral analysis and image recognition.

[0122] An embodiment of the present invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the intelligent stoma assessment method combining spectral analysis and image recognition.

[0123] An embodiment of the present invention provides an information data processing terminal, which is used to implement the intelligent stoma assessment system combining spectral analysis and image recognition.

[0124] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. It can be understood by a person of ordinary skill in the art that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0125] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. An intelligent stoma assessment system combining spectral analysis and image recognition, characterized in that: The system includes: The 3D scanning module uses high-precision laser scanning or structured light scanning technology to capture the 3D morphology of the stoma and its surrounding tissues. It can accurately measure the stoma's height, size, shape and other physical parameters and generate a 3D image. Spectral analysis module, which uses multispectral imaging (MSI) or hyperspectral imaging (HSI) technology to accurately analyze the color changes of the stoma, detect small color differences in the stoma area through spectral data, and identify potential tissue abnormalities such as inflammation, infection or poor blood flow; The image recognition and processing module is connected to the above-mentioned three-dimensional scanning module and spectrum analysis module, and uses a deep learning algorithm to analyze the collected stoma images, automatically identify the morphological characteristics of the stoma, and automatically calculate the area, contour, height and other information of the stoma based on the scanned three-dimensional data and spectrum analysis results, and generate an accurate evaluation report; The data analysis and feedback system is connected to the 3D scanning module and the image recognition and processing module, and integrates intelligent evaluation software. It can automatically generate a stoma health assessment report based on the collected multi-dimensional data, and compare the actual measurement values ​​with the set standard reference values ​​to provide corresponding nursing suggestions or medical intervention suggestions; The data collection module is connected to the central control module. The data collection module receives the instructions from the central control module and first sends the request information to the switch, which then sends it to the router. The router sends the request to the DNS server. The DNS server calls the vertical search engine to establish a search engine on the Internet, finds the data information to be collected through network radar and automatic indexing technology, and then calls the information tracking and automatic sorting technology to classify the information. The central control module is connected with the data collection module, image recognition and processing module, model building module, cloud storage module, local storage module and data encryption module. It is responsible for collecting external signals (data and requests transmitted by each module), and outputting them to the output channel after analysis and processing. When external analog output is required, the system converts the signal into a standard electrical signal through a D / A converter to control the normal operation of each module. The cloud storage module is connected to the central control module. To use the cloud storage service, a cloud storage platform is first created in the local server deployment data center. The storage protocol is implemented through a third-party gateway. The user writes local data to the cloud storage gateway through a network cable. The cloud storage gateway transmits the data to the edge router. The edge router transmits the data to the cloud platform through a dedicated public network. An object storage request is initiated in the cloud platform. The data is transmitted to the cloud storage gateway in the cloud platform. The cloud storage gateway sends the data to the cloud storage availability zone through a vSwitch to realize cloud storage of data. The local storage module is connected to the central control module and uses the SQL interface to connect to the SQL service database. The data acquisition and reading module packages the converted data and sends it to the central control module. The central control module transmits the data to the SQL service database and the cloud storage module through label operations. The data encryption module is connected to the central control module and is responsible for encrypting the data in the local storage module and the cloud storage module. When the data is stored, the data encryption server randomly generates two pairs of keys to encrypt the data, which act on the local storage module and the cloud storage module respectively. When the user requests to view the data, the data encryption server performs identity authentication and requests the key. After the user enters the corresponding information, the data encryption server verifies and feedbacks the license. The data decryption server decrypts the data and packages it for transmission to the central control module.

2. The intelligent stoma assessment system according to claim 1, characterized in that: The image recognition and processing module uses convolutional neural networks (CNN) and generative adversarial networks (GAN) for deep learning training to improve the accuracy and robustness of image recognition; the data analysis and feedback system includes a decision curve analysis (DCA) function to evaluate the clinical practicality of the prediction model and automatically generate nursing recommendations or medical intervention plans based on the analysis results; the user interaction and interface design includes multi-language support and customized settings to meet the needs of medical institutions in different regions, and allows users to customize system settings and evaluation standards according to actual needs; the system integration and compatibility module supports seamless integration with hospital information systems (HIS) and electronic medical records (EMR), realizes automatic import and export of data, and improves work efficiency.

3. The intelligent stoma assessment system according to claim 1, characterized in that: The system adopts a modular design to support subsequent expansion and upgrading of functions, such as adding more sensor modules or introducing new data analysis algorithms, to ensure the long-term applicability and maintainability of the system; the data encryption module adopts the Advanced Encryption Standard (AES) algorithm for data encryption and is equipped with a strict access control mechanism to ensure that only authorized personnel can access sensitive data.

4. The intelligent stoma assessment system combining spectral analysis and image recognition according to claim 1, characterized in that: The three-dimensional scanning module is implemented as follows: S1: Operates through high-precision laser or structured light scanning technology; the scanning device emits a beam of light, including laser or structured light, and projects it onto the stoma and surrounding tissue; S2: Based on the light reflection time or light deformation, the sensor collects the reflection signal and converts it into 3D point cloud data; each point records the 3D coordinates of the scanned area; S3: Through multi-angle scanning, the system can reconstruct a three-dimensional model of the opening.

5. The intelligent stoma assessment system combining spectral analysis and image recognition as claimed in claim 1, characterized in that: The spectral analysis module uses multi-spectral or hyperspectral imaging equipment to irradiate light of different wavelengths onto the stoma area and record the reflected spectrum through a sensor; each pixel has complete spectral information and can analyze the color changes in the stoma area; then, by processing these spectral data, subtle differences in the tissue can be identified.

6. The intelligent stoma assessment system combining spectral analysis and image recognition as claimed in claim 1, characterized in that: The image recognition and processing module is based on a deep learning algorithm, and the collected stoma images are input into a pre-trained neural network model; the neural network automatically extracts relevant geometric features and physical parameters by identifying the boundaries, shapes and textures of the stoma; the image processing algorithm is combined with three-dimensional scanning and spectral analysis to provide a more accurate evaluation.

7. The intelligent stoma assessment system combining spectral analysis and image recognition as claimed in claim 1, characterized in that: The data analysis and feedback system integrates intelligent evaluation software, and automatically performs data fusion and analysis through the collected three-dimensional scanning data, spectral data and image recognition results; the system sets standard reference values ​​and compares the actual test results to determine the health status of the stoma; The intelligent algorithm generates an assessment report based on preset assessment criteria and gives corresponding care recommendations.

8. An intelligent stoma assessment method combining spectral analysis and image recognition based on the intelligent stoma assessment system combining spectral analysis and image recognition as described in claims 1-5, characterized in that: The method specifically includes: S21: The three-dimensional scanning module continuously acquires the reflected light signals of the stoma surface contour to generate the three-dimensional shape of the stoma in real time; combined with the machine learning model, the system can calculate the physical parameters of the stoma, such as height, size, shape, etc., through the scanning data; these data can be used to evaluate the stoma healing progress and care needs; S22: Using the spectral analysis module, when different wavelengths of light are irradiated to the stoma area, the reflective properties of the tissue vary due to different physiological states, such as blood flow, tissue inflammation, etc. By capturing these tiny differences in reflection, the system can identify color changes and detect potential tissue abnormalities, such as inflammation, infection, or poor blood flow. The spectral data combined with the three-dimensional morphology of the stoma can help further understand the physiological changes of the stoma. S23: The deep learning algorithm in the image recognition and processing module learns and recognizes subtle differences in stoma morphology through training with a large amount of labeled image data. The system can automatically calculate parameters such as area, contour and height by identifying the stoma contour and its three-dimensional shape in the image. These parameters, combined with spectral data, can be used to generate more accurate stoma assessment reports and predict the healing status of the stoma. S24: The data collected by all modules are integrated using the data analysis and feedback system, and the set evaluation criteria, such as normal stoma color range, morphological characteristics, size, etc., are used to automatically determine whether the stoma status meets the standards; if abnormalities are detected, such as tissue inflammation, poor healing or infection, the system will remind the caregiver through a feedback mechanism; at the same time, the system can generate a dynamic stoma healing curve based on data from multiple evaluations to help caregivers adjust care plans or recommend further medical intervention.

9. A computer device, characterized in that: The computer device includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the intelligent stoma assessment method combining spectral analysis and image recognition as claimed in claim 8.

10. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the steps of the intelligent stoma assessment method combining spectral analysis and image recognition as claimed in claim 8.

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