Method and system for analyzing tissue structure space of polysaccharide hydrogel cells

Abstract

The invention relates to the technical field of tissue structure spatial analysis methods, discloses a tissue structure spatial analysis method and system for polysaccharide hydrogel cells, and aims to provide a method and system which are high in spatial resolution, simple and convenient to operate and high in data processing capacity and are used for analyzing a three-dimensional tissue structure of the cells in polysaccharide hydrogel. The method comprises the steps of sample preparation, three-dimensional imaging, image data processing, result analysis and the like, and accurate analysis of the growth state and distribution of cells in the hydrogel is realized by adopting an advanced optical imaging technology and an efficient data processing algorithm. The system provided by the invention integrates the functions of sample preparation, imaging and analysis, is suitable for various polysaccharide hydrogel and cell types, and has wide applicability. By means of the method, researchers can understand cell behaviors more deeply, the design of biological materials is optimized, and scientific research and technical progress in the field of biological medicine are promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of organizational structure spatial analysis methods, and specifically to a method and system for analyzing the organizational structure space of polysaccharide hydrogel cells. Background Art

[0002] In the fields of biomedicine and materials science, hydrogels, as an important type of biomaterial, are widely used in drug delivery, tissue engineering, cell culture, etc. due to their good biocompatibility and adjustable physicochemical properties. Polysaccharide hydrogels, especially those prepared from natural polysaccharides such as hyaluronic acid and chitosan, have become a research hotspot due to their excellent biodegradability and bioactivity.

[0003] In cell culture and tissue engineering, understanding the growth state, distribution, and interaction of cells in hydrogels is crucial for optimizing material design and improving the application effect of biomaterials. However, traditional cell analysis methods are often limited to two-dimensional planes and cannot comprehensively reflect the true growth status of cells in three-dimensional space. In addition, existing three-dimensional cell analysis technologies have the following limitations:

[0004] Low spatial resolution: Many existing three-dimensional analysis technologies are difficult to achieve sufficient resolution to accurately depict the interaction between cells and hydrogels and the three-dimensional organizational structure of cells.

[0005] Complex analysis process: Existing three-dimensional cell analysis technologies often require complex sample preparation processes, with high operation difficulty and high technical requirements for operators.

[0006] Difficult data processing: Three-dimensional cell image data is large, and traditional data processing methods are difficult to effectively process and analyze this data, resulting in inaccurate analysis results or excessive time consumption.

[0007] Lack of systematic analysis tools: Currently, there is a lack of a complete system in the market that can provide one-stop services from sample preparation, image acquisition, data processing to result display.

[0008] Therefore, it is necessary to develop a new method and system for analyzing the organizational structure space of polysaccharide hydrogel cells to improve spatial resolution, simplify the analysis process, enhance data processing capabilities, and provide a systematic solution to meet the needs of scientific research and clinical diagnosis. The present invention precisely addresses the defects and deficiencies in the above background art and provides an innovative method and system for analyzing the organizational structure space of polysaccharide hydrogel cells. Summary of the Invention

[0009] (1) Technical problems to be solved

[0010] In view of the deficiencies of the prior art, the present invention provides a method and system for analyzing the tissue structure space of polysaccharide hydrogel cells, solving the problems raised in the above-mentioned background art.

[0011] (II) Technical solutions

[0012] To achieve the above object, the present invention provides the following technical solutions: A method and system for analyzing the tissue structure space of polysaccharide hydrogel cells, comprising the following steps:

[0013] Step 1, prepare a polysaccharide hydrogel cell sample;

[0014] Step 2, fix, section and stain the polysaccharide hydrogel cell sample;

[0015] Step 3, observe the cell section with an optical microscope or an electron microscope to obtain a cell tissue structure image;

[0016] Step 4, use image processing software to denoise, enhance, segment and extract features from the obtained cell tissue structure image. The image denoising formula is:

[0017] I denoised = I original - N

[0018] wherein, I denoised is the denoised image, I original is the original image, and N is the noise;

[0019] Step 5, construct a spatial analysis model according to the extracted cell tissue structure features, and quantitatively analyze the tissue structure of the polysaccharide hydrogel cells;

[0020] Step 6, output the analysis result to realize the spatial analysis of the tissue structure of the polysaccharide hydrogel cells.

[0021] Preferably, in the above Step 1, the method for preparing the polysaccharide hydrogel cell sample is as follows:

[0022] Ⅰ. Select a polysaccharide material with biocompatibility;

[0023] Ⅱ. Dissolve the polysaccharide material in deionized water to prepare a polysaccharide solution with a certain concentration;

[0024] Ⅲ. Add cell culture medium to the polysaccharide solution and mix evenly;

[0025] Ⅳ. Inject the mixed solution into a cell culture dish to form a polysaccharide hydrogel;

[0026] Ⅴ. Inoculate cells on the polysaccharide hydrogel and culture them.

[0027] Preferably, in step 2, the fixation, sectioning and staining treatment methods are as follows:

[0028] Ⅰ. Fix the cells with glutaraldehyde or paraformaldehyde;

[0029] Ⅱ. Prepare cell sections using cryosectioning technology;

[0030] Ⅲ. Stain the cell sections with hematoxylin-eosin (HE) staining, immunofluorescence staining and other suitable staining methods.

[0031] Preferably, in step 4, the image processing software is: software with image processing functions, and in step 5, the spatial analysis model is: a fractal dimension model suitable for analyzing cell tissue structure.

[0032] Preferably, the system includes a polysaccharide hydrogel cell sample preparation module, a microscope imaging module, an image acquisition and transmission module, an image processing and analysis module, a result display and output module, a data storage and management module, a user interaction interface module, and a control and automation module;

[0033] The polysaccharide hydrogel cell sample preparation module is used to prepare polysaccharide hydrogel cell samples, including steps of cell culture, fixation, embedding and sectioning for subsequent microscopic observation;

[0034] The microscope imaging module uses an optical microscope or an electron microscope to image the cell sections to obtain detailed images of cell tissue structure;

[0035] The image acquisition and transmission module is used to transmit the images obtained by the microscope imaging module to the image processing and analysis module;

[0036] The image processing and analysis module performs a series of processing and analysis on the acquired cell tissue structure images, including denoising, enhancement, segmentation, feature extraction and quantitative analysis;

[0037] The result display and output module displays and outputs the results obtained by the image processing and analysis module in the form of graphs, tables and reports;

[0038] The data storage and management module is used to store and manage the original image data, intermediate data during the processing and final analysis results;

[0039] The user interaction interface module is used to provide a platform for users to interact with the system, allowing users to input parameters, start the analysis process, view results and adjust settings;

[0040] The control and automation module is used to control the operation process of the entire system to realize the automation of sample preparation, imaging, image processing and analysis steps.

[0041] Preferably, the polysaccharide hydrogel cell sample preparation module includes: a polysaccharide solution preparation device, a cell culture device, and a cell seeding device.

[0042] Preferably, the result display and output module includes:

[0043] Component 1, a high-resolution display: used to clearly display the cell tissue structure image and analysis results output by the image processing and analysis module for visual inspection and evaluation by researchers;

[0044] Component 2, a color printer: used to print the images and analysis results of the cell tissue structure into hard copies for easy recording, archiving, and sharing;

[0045] Component 3, a three-dimensional visualization device: used to convert the two-dimensional image of the cell tissue structure into a three-dimensional model for more intuitive analysis of the spatial structure and interactions of cells;

[0046] Component 4, a data storage device: including a hard disk drive, a solid-state drive, and network-attached storage, used for long-term storage of original image data, processed images, and analysis results;

[0047] Component 5, an interactive touch screen: provides an intuitive user interface that allows researchers to select, zoom, rotate, and analyze cell images through touch operations;

[0048] Component 6, a network connection interface: used to upload analysis results to a remote server to achieve remote sharing and collaborative research of data;

[0049] Component 7, a report generation software: automatically generates detailed analysis reports, including images, statistical data, charts, and conclusions, for easy writing of research papers and reports;

[0050] Component 8, a projector: used to project the images and analysis results of the cell tissue structure onto a large screen for team discussions and teaching demonstrations.

[0051] Preferably, the image processing and analysis module includes:

[0052] Component 1, an image preprocessing unit: an autofocus function to ensure that images are captured at the best focal length, improving image clarity; an automatic white balance adjustment to adapt to different light source conditions and maintain color consistency of images; an image stitching function to stitch low-resolution images into a high-resolution large image to obtain a broader field of view and more detailed details;

[0053] Component Two, Noise Cancellation Unit: It is used for the adaptive noise cancellation algorithm, dynamically adjusts the denoising parameters according to the image content to adapt to different noise levels, and maintains the edge feature algorithm to protect the edge information of the cell structure during the denoising process and avoid over-blurring;

[0054] Component Three, Image Enhancement Unit: It is used for multi-scale enhancement technology and performs targeted enhancement according to the scale characteristics of the cell structure; through the structure-preserving enhancement algorithm, it enhances the image without introducing artificial effects and maintains the naturalness of the cell structure;

[0055] Component Four, Image Segmentation Unit: It is used for the interactive segmentation tool, allowing users to participate in the segmentation process to improve the accuracy and flexibility of segmentation. Based on the machine learning-based segmentation algorithm, it learns the cell features through training data to achieve automatic and accurate segmentation;

[0056] Component Five, Feature Extraction Unit: It is used for multi-dimensional feature extraction, including the geometric features, texture features, and spectral features of the cells;

[0057] Component Six, 3D Reconstruction and Analysis Unit: It is used to calculate the 3D volume and surface area parameters of the cells; for dynamic tracking and analysis, it tracks the movement and changes of the cells in 3D space for studying cell behavior;

[0058] Component Seven, Quality Control and Verification Unit: It is used for image quality assessment to automatically evaluate the reliability of the image processing results; for segmentation result verification, it ensures the accuracy of the segmentation algorithm by comparing with the manually annotated results.

[0059] Preferably, the data analysis and statistics module includes

[0060] Component One, Data Integration Unit: It is used to integrate the feature data extracted from the image processing and analysis module to form a unified data set, ensuring the consistency and integrity of the data and providing accurate basic data for subsequent analysis;

[0061] Component Two, Data Cleaning Unit: It automatically identifies and eliminates abnormal data, and improves the data quality through data verification and correction;

[0062] Component Three, Statistical Analysis Unit: It performs statistical analysis on the integrated data, applies the ANOVA statistical method to compare the data differences under different samples or experimental conditions;

[0063] Component Four, Pattern Recognition Unit: It uses machine learning algorithms to classify and identify cell features and identify different states or types of cells;

[0064] Component Five, Correlation Analysis Unit: It analyzes the correlation between different feature parameters and visually displays the mutual relationship between features through a correlation matrix and a heat map;

[0065] Component Six, 3D Reconstruction Unit: Using the extracted cell feature data, it reconstructs and analyzes the three-dimensional spatial structure, provides a stereoscopic view of the cell tissue structure, and helps researchers better understand the spatial distribution and interaction of cells.

[0066] Preferably, the result output and display module includes:

[0067] Component One, Data Visualization Unit: Used to display the statistical distribution of cell features; using 3D visualization technology, it provides a stereoscopic display of cells and tissue structures, including functions such as rotation, scaling, and slicing interaction;

[0068] Component Two, Report Generation Unit: Integrates the analysis results, charts, and conclusions into a professional report document; customizes the report template, allowing users to select different report formats and contents according to their needs;

[0069] Component Three, Data Export Unit: Supports the export of multiple data formats for further analysis and sharing of data; exports high-resolution images to ensure that the exported images meet the requirements of publication and presentation;

[0070] Component Four, Interactive Analysis Unit: Used for real-time data analysis, where users can adjust parameters in real-time and observe the changes in the analysis results; with the support of virtual reality and augmented reality, it provides an immersive experience to help users better understand the cell structure;

[0071] Component Five, Remote Access and Sharing Unit: Used for cloud service support, allowing users to remotely access and analyze data through the Internet;

[0072] Component Six, Intelligent Prompt and Auxiliary Decision-making Unit: Based on artificial intelligence-based anomaly detection, it automatically identifies abnormal patterns in the data and prompts the user.

[0073] (III) Beneficial Effects

[0074] Compared with the prior art, the present invention provides a method and system for spatial analysis of the tissue structure of polysaccharide hydrogel cells, having the following beneficial effects:

[0075] 1. High spatial resolution: The present invention adopts advanced optical imaging technology, which can provide high-resolution images of cells and the internal structure of hydrogels, thereby more accurately analyzing the distribution of cells in three-dimensional space and the tissue structure.

[0076] 2. Simplified operation process: The present invention provides a set of simplified sample preparation and imaging processes, reducing the operation difficulty, enabling non-professionals to easily perform three-dimensional cell analysis.

[0077] 3. Strong data processing capabilities: The present invention adopts efficient data processing algorithms, which can quickly process a large amount of three-dimensional image data, improving the accuracy and efficiency of data analysis.

[0078] 4. Systematic solution: The present invention provides a complete system from sample preparation to result analysis, realizing the automation and integration of the analysis process and greatly improving the research efficiency.

[0079] 5. Wide applicability: The present invention is applicable to various types of polysaccharide hydrogels and cell types, providing wide applicability for scientific research and clinical applications in different fields.

[0080] 6. Improving research accuracy: Through the methods and systems of the present invention, researchers can more accurately understand the growth behavior and interactions of cells in hydrogels, providing reliable data support for research in fields such as drug screening and tissue engineering.

[0081] 7. Promoting the development of biomaterials: The present invention helps to optimize the design of polysaccharide hydrogels and promotes the application and development of biomaterials in the biomedical field.

[0082] 8. Reducing costs: The present invention reduces the costs of scientific research and clinical diagnosis by improving experimental efficiency and reducing operation errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 It is a schematic diagram of the overall system architecture of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0084] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0085] As Figure 1 shown: The method and system for analyzing the organizational structure space of polysaccharide hydrogel cells, the system includes a polysaccharide hydrogel cell sample preparation module, a microscope imaging module, an image acquisition and transmission module, an image processing and analysis module, a result display and output module, a data storage and management module, a user interface module, and a control and automation module;

[0086] The polysaccharide hydrogel cell sample preparation module is used to prepare polysaccharide hydrogel cell samples, including steps of cell culture, fixation, embedding, and sectioning for subsequent microscopic observation;

[0087] The microscope imaging module uses an optical microscope or an electron microscope to image cell sections and obtain detailed images of cell tissue structures;

[0088] The image acquisition and transmission module is used to transmit the images obtained by the microscope imaging module to the image processing and analysis module;

[0089] The image processing and analysis module performs a series of processing and analysis on the acquired cell tissue structure images, including denoising, enhancement, segmentation, feature extraction, and quantitative analysis;

[0090] The result display and output module displays and outputs the results obtained by the image processing and analysis module in the form of graphs, tables, and reports;

[0091] The data storage and management module is used to store and manage the original image data, intermediate data during the processing, and final analysis results;

[0092] The user interaction interface module is used to provide a platform for users to interact with the system, allowing users to input parameters, start the analysis process, view results, and adjust settings;

[0093] The control and automation module is used to control the operation process of the entire system and realize the automation of sample preparation, imaging, image processing, and analysis steps;

[0094] The polysaccharide hydrogel cell sample preparation module includes: a polysaccharide solution preparation device, a cell culture device, and a cell inoculation device;

[0095] The result display and output module includes:

[0096] Component 1, a high-resolution display: used to clearly display the cell tissue structure images and analysis results output by the image processing and analysis module for researchers to conduct visual inspection and evaluation;

[0097] Component 2, a color printer: used to print the images and analysis results of cell tissue structures into hard copies for easy recording, archiving, and sharing;

[0098] Component 3, a 3D visualization device: used to convert the two-dimensional images of cell tissue structures into 3D models for more intuitive analysis of the spatial structure and interactions of cells;

[0099] Component 4, a data storage device: including a hard disk drive, a solid-state drive, and network-attached storage, used for long-term storage of original image data, processed images, and analysis results;

[0100] Component 5, an interactive touch screen: provides an intuitive user interface, allowing researchers to select, zoom, rotate, and analyze cell images through touch operations;

[0101] Component Six, Network Connection Interface: Used to upload analysis results to a remote server to achieve remote sharing of data and collaborative research;

[0102] Component Seven, Report Generation Software: Automatically generates detailed analysis reports, including images, statistical data, charts, and conclusions, facilitating the writing of research papers and reports;

[0103] Component Eight, Projector: Used to project images of cell tissue structures and analysis results onto a large screen for team discussions and teaching demonstrations;

[0104] The image processing and analysis module includes:

[0105] Component One, Image Preprocessing Unit: Automatic focusing function to ensure image acquisition at the best focal length, improving image clarity; automatic white balance adjustment to adapt to different light source conditions and maintain color consistency of the image; image stitching function to stitch low-resolution images into a high-resolution large image to obtain a broader view and more detailed details;

[0106] Component Two, Noise Elimination Unit: Used for an adaptive noise elimination algorithm that dynamically adjusts denoising parameters according to image content to adapt to different noise levels, and a structure-preserving edge algorithm to protect the edge information of cell structures during the denoising process and avoid over-blurring;

[0107] Component Three, Image Enhancement Unit: Used for multi-scale enhancement techniques to perform targeted enhancement according to the scale characteristics of cell structures; through a structure-preserving enhancement algorithm, enhance the image without introducing artificial effects and maintain the naturalness of cell structures;

[0108] Component Four, Image Segmentation Unit: Used for an interactive segmentation tool that allows users to participate in the segmentation process to improve the accuracy and flexibility of segmentation, and a machine learning-based segmentation algorithm that learns cell features through training data to achieve automatic and accurate segmentation;

[0109] Component Five, Feature Extraction Unit: Used for multi-dimensional feature extraction, including geometric features, texture features, and spectral features of cells;

[0110] Component Six, 3D Reconstruction and Analysis Unit: Used to calculate three-dimensional volume and surface area parameters of cells; dynamic tracking analysis to track the movement and changes of cells in three-dimensional space for studying cell behavior;

[0111] Component Seven, Quality Control and Verification Unit: Used for image quality assessment to automatically evaluate the reliability of image processing results; segmentation result verification to ensure the accuracy of the segmentation algorithm by comparing with manually annotated results;

[0112] The data analysis and statistics module includes

[0113] Component 1, Data Integration Unit: It is used to integrate the feature data extracted from the image processing and analysis module to form a unified data set, ensuring the consistency and integrity of the data and providing accurate basic data for subsequent analysis;

[0114] Component 2, Data Cleaning Unit: It automatically identifies and eliminates abnormal data, and improves data quality through data verification and correction;

[0115] Component 3, Statistical Analysis Unit: It conducts statistical analysis on the integrated data, applies the ANOVA statistical method, and compares the data differences under different samples or experimental conditions;

[0116] Component 4, Pattern Recognition Unit: It uses machine learning algorithms to classify and identify cell features, and identify different states or types of cells;

[0117] Component 5, Correlation Analysis Unit: It analyzes the correlation between different feature parameters, and visually displays the mutual relationship between features through a correlation matrix and a heat map;

[0118] Component 6, 3D Reconstruction Unit: It uses the extracted cell feature data to reconstruct and analyze the three-dimensional spatial structure, provides a three-dimensional view of the cell tissue structure, and helps researchers better understand the spatial distribution and interaction of cells;

[0119] The result output and display module includes:

[0120] Component 1, Data Visualization Unit: It is used to display the statistical distribution of cell features; uses three-dimensional visualization technology to provide a three-dimensional display of cells and tissue structures, including rotation, scaling, and slicing interaction functions;

[0121] Component 2, Report Generation Unit: It integrates the analysis results, charts, and conclusions into a professional report document; customizes the report template, allowing users to select different report formats and contents according to their needs;

[0122] Component 3, Data Export Unit: It supports the export of multiple data formats for further analysis and sharing of data; exports high-resolution images to ensure that the exported images meet the requirements of publication and presentation;

[0123] Component 4, Interactive Analysis Unit: It is used for real-time data analysis. Users can adjust parameters in real time and observe the changes in the analysis results; with the support of virtual reality and augmented reality, it provides an immersive experience to help users better understand the cell structure;

[0124] Component 5, Remote Access and Sharing Unit: It is used for cloud service support, allowing users to remotely access and analyze data through the Internet;

[0125] Component Six: Intelligent Prompting and Auxiliary Decision-making Unit: Based on artificial intelligence anomaly detection, it automatically identifies abnormal patterns in data and prompts the user. Specific Embodiment:

[0127] Embodiment 1: Preparation of Polysaccharide Hydrogel Cell Samples

[0128] First, prepare the polysaccharide hydrogel. Select hyaluronic acid as the polysaccharide material and crosslink it with a crosslinking agent to form a hydrogel matrix with appropriate mechanical properties.

[0129] Inoculate human umbilical vein endothelial cells (HUVECs) into the pre-prepared polysaccharide hydrogel at a density of 1×10^6 cells / mL, and place it in an incubator at 37°C and 5% CO2 for 24 hours to promote cell adhesion and diffusion in the hydrogel.

[0130] After culturing for 24 hours, take out the hydrogel cell sample, and wash it three times with phosphate buffer solution (PBS) to remove unadhered cells and impurities.

[0131] Embodiment 2: Fixation, Sectioning, and Staining of Polysaccharide Hydrogel Cell Samples

[0132] Put the cultured polysaccharide hydrogel cell sample into a 4% paraformaldehyde solution and fix it for 4 hours to fix the cell structure.

[0133] After fixation, cut the hydrogel sample into 100-micron-thick sections using a vibratome.

[0134] After sectioning, stain the cells using hematoxylin-eosin (H&E) staining to enhance the contrast of the cell structure.

[0135] Embodiment 3: Image Acquisition and Transmission

[0136] Place the stained hydrogel cell section on the stage of a fluorescence microscope.

[0137] Use a fluorescence microscope equipped with a high-resolution CCD camera to image the section, and adjust the focal length and light source intensity of the microscope to obtain clear cell images.

[0138] Transmit the image captured by the camera to the computer through the USB interface, and use professional image acquisition software to capture and perform preliminary processing on the image.

[0139] Embodiment 4: Image Processing and Analysis

[0140] Use image processing software to perform denoising, contrast enhancement, and three-dimensional reconstruction processing on the acquired cell images.

[0141] Through the analysis tools in the software, quantitative analysis is carried out on parameters such as the spatial distribution, morphology, and density of cells.

[0142] Example 5: Results Display and Output

[0143] The spatial information of the processed and analyzed cell tissue structure is displayed through a high-resolution monitor for researchers to observe and analyze.

[0144] Use a printer to print out the key images and analysis results for easy recording and sharing.

[0145] In addition, the analysis results can also be saved as electronic files and shared with other researchers via email or cloud platforms.

[0146] Through the above embodiments, the method and system provided by the present invention can effectively analyze the tissue structure of cells in the polysaccharide hydrogel, providing strong technical support for research in related fields.

[0147] In summary, the method and system for spatial analysis of the tissue structure of polysaccharide hydrogel cells of the present invention have significant advantages in improving analysis accuracy, simplifying the operation process, enhancing data processing capabilities, etc., and are of great significance for promoting research in the fields of biomedicine and materials science.

[0148] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the element.

[0149] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for spatial analysis of the tissue structure of polysaccharide hydrogel cells, characterized in that: It includes the following steps: Step 1: Prepare a polysaccharide hydrogel cell sample; Step 2: Fix, section, and stain the polysaccharide hydrogel cell sample; Step 3: Observe the cell section using an optical microscope or an electron microscope to obtain an image of the cell tissue structure; Step 4: Use image processing software to denoise, enhance, segment, and extract features from the obtained cell tissue structure image. The image denoising formula: I denoised = I original - N Among them, I denoised is the denoised image, I original is the original image, and N is the noise; Step 5: Construct a spatial analysis model based on the extracted cell tissue structure features to quantitatively analyze the tissue structure of the polysaccharide hydrogel cells; Step 6: Output the analysis results to achieve spatial analysis of the tissue structure of the polysaccharide hydrogel cells.

2. The method for analyzing the tissue structure space of a polysaccharide hydrogel cell according to claim 1, characterized in that: In the said Step 1, the method for preparing the polysaccharide hydrogel cell sample is as follows: Ⅰ. Select a polysaccharide material with biocompatibility; Ⅱ. Dissolve the polysaccharide material in deionized water to prepare a polysaccharide solution with a certain concentration; Ⅲ. Add cell culture medium to the polysaccharide solution and mix evenly; Ⅳ. Inject the mixed solution into a cell culture dish to form a polysaccharide hydrogel; Ⅴ. Inoculate cells on the polysaccharide hydrogel and culture them.

3. A method for analyzing the tissue structure space of a polysaccharide hydrogel cell according to claim 1, characterized in that: In the said Step 2, the methods for fixation, sectioning, and staining are as follows: Ⅰ. Fix the cells using glutaraldehyde or paraformaldehyde; Ⅱ. Use cryosectioning technology to prepare cell sections; Ⅲ. Stain the cell sections using hematoxylin-eosin (HE) staining, immunofluorescence staining, and other suitable staining methods.

4. A method for analyzing the organizational structure space of a polysaccharide hydrogel cell according to claim 1, characterized in that: In the said Step 4, the image processing software is: software with image processing functions. In the said Step 5, the spatial analysis model is: a fractal dimension model, a model suitable for cell tissue structure analysis.

5. A spatial analysis system for the tissue structure of polysaccharide hydrogel cells, characterized in that: This system includes a polysaccharide hydrogel cell sample preparation module, a microscope imaging module, an image acquisition and transmission module, an image processing and analysis module, a result display and output module, a data storage and management module, a user interaction interface module, and a control and automation module; The said polysaccharide hydrogel cell sample preparation module is used to prepare a polysaccharide hydrogel cell sample, including steps of culturing, fixing, embedding, and sectioning cells for subsequent microscopic observation; The said microscope imaging module uses an optical microscope or an electron microscope to image the cell sections to obtain detailed images of the cell tissue structure; The said image acquisition and transmission module is used to transmit the images obtained by the microscope imaging module to the image processing and analysis module; The said image processing and analysis module performs a series of processing and analysis on the acquired cell tissue structure images, including denoising, enhancement, segmentation, feature extraction, and quantitative analysis; The said result display and output module displays and outputs the results obtained by the image processing and analysis module in the forms of graphs, tables, and reports; The said data storage and management module is used to store and manage the original image data, intermediate data during the processing, and the final analysis results; The said user interaction interface module is used to provide a platform for users to interact with the system, allowing users to input parameters, start the analysis process, view results, and adjust settings; The said control and automation module is used to control the operation process of the entire system to automate the steps of sample preparation, imaging, image processing, and analysis.

6. The organizational structure space analysis system of a polysaccharide hydrogel cell according to claim 5, characterized in that: The polysaccharide hydrogel cell sample preparation module includes: a polysaccharide solution preparation device, a cell culture device, and a cell seeding device.

7. The organizational structure space analysis system of a polysaccharide hydrogel cell according to claim 5, characterized in that: The result display and output module includes: Component 1, a high-resolution display: used to clearly display the cell tissue structure image and analysis results output by the image processing and analysis module for researchers to conduct visual inspection and evaluation; Component 2, a color printer: used to print the images and analysis results of the cell tissue structure into hard copies for easy recording, archiving, and sharing; Component 3, a 3D visualization device: used to convert the 2D image of the cell tissue structure into a 3D model for more intuitive analysis of the spatial structure and interactions of cells; Component 4, a data storage device: including a hard disk drive, a solid-state drive, and network-attached storage, used for long-term storage of original image data, processed images, and analysis results; Component 5, an interactive touch screen: provides an intuitive user interface, allowing researchers to select, zoom, rotate, and analyze cell images through touch operations; Component 6, a network connection interface: used to upload analysis results to a remote server to achieve remote sharing of data and collaborative research; Component 7, a report generation software: automatically generates detailed analysis reports, including images, statistical data, charts, and conclusions, for easy writing of research papers and reports; Component 8, a projector: used to project the images and analysis results of the cell tissue structure onto a large screen for team discussions and teaching demonstrations.

8. An organizational structure space analysis system for polysaccharide hydrogel cells according to claim 5, characterized in that: The image processing and analysis module includes: Component 1, an image preprocessing unit: an automatic focusing function to ensure that images are captured at the best focal length, improving image clarity; automatic white balance adjustment to adapt to different light source conditions and maintain color consistency of images; an image stitching function to stitch low-resolution images into a high-resolution large image to obtain a broader field of view and more detailed details; Component 2, a noise reduction unit: used for an adaptive noise reduction algorithm to dynamically adjust denoising parameters according to image content to adapt to different noise levels; an edge-preserving algorithm to protect the edge information of cell structures during the denoising process and avoid over-blurring; Component 3, an image enhancement unit: used for multi-scale enhancement techniques to perform targeted enhancement according to the scale characteristics of cell structures; through a structure-preserving enhancement algorithm to enhance the image without introducing artificial effects and maintain the naturalness of cell structures; Component 4, an image segmentation unit: used for an interactive segmentation tool that allows users to participate in the segmentation process to improve the accuracy and flexibility of segmentation; a machine learning-based segmentation algorithm to learn cell characteristics through training data to achieve automatic and accurate segmentation; Component 5, a feature extraction unit: used for multi-dimensional feature extraction, including geometric features, texture features, and spectral features of cells; Component 6, a 3D reconstruction and analysis unit: used to calculate the 3D volume and surface area parameters of cells; dynamic tracking analysis to track the movement and changes of cells in 3D space for studying cell behavior; Component Seven, Quality Control and Verification Unit: Used for image quality assessment to automatically evaluate the reliability of image processing results; for segmentation result verification, by comparing with manually annotated results to ensure the accuracy of the segmentation algorithm.

9. The organizational structure space analysis system for polysaccharide hydrogel cells according to claim 5, characterized in that: The data analysis and statistics module includes Component One, Data Integration Unit: Used to integrate the feature data extracted from the image processing and analysis module to form a unified data set, ensuring the consistency and integrity of the data and providing accurate basic data for subsequent analysis; Component Two, Data Cleaning Unit: Automatically identifies and eliminates abnormal data, and improves data quality through data verification and correction; Component Three, Statistical Analysis Unit: Conducts statistical analysis on the integrated data, applies ANOVA statistical method to compare data differences under different samples or experimental conditions; Component Four, Pattern Recognition Unit: Uses machine learning algorithms to classify and identify cell features, and identify different states or types of cells; Component Five, Correlation Analysis Unit: Analyzes the correlation between different feature parameters, and visually displays the mutual relationship between features through a correlation matrix and heat map; Component Six, 3D Reconstruction Unit: Uses the extracted cell feature data to perform 3D spatial structure reconstruction and analysis, provides a stereoscopic view of the cell tissue structure, and helps researchers better understand the spatial distribution and interaction of cells.

10. A polysaccharide hydrogel cell tissue structure space analysis system according to claim 5, characterized in that: The result output and display module includes: Component One, Data Visualization Unit: Used to display the statistical distribution of cell features; uses 3D visualization technology to provide a stereoscopic display of cells and tissue structures, including rotation, zoom, and slicing interaction functions; Component Two, Report Generation Unit: Integrates the analysis results, charts, and conclusions into a professional report document; customizes report templates, allowing users to select different report formats and contents according to their needs; Component Three, Data Export Unit: Supports the export of multiple data formats for further analysis and sharing of data; exports high-resolution images to ensure that the exported images meet the requirements of publication and demonstration; Component Four, Interactive Analysis Unit: Used for real-time data analysis, users can adjust parameters in real-time and observe the changes in analysis results; uses virtual reality and augmented reality support to provide an immersive experience to help users better understand cell structures; Component Five, Remote Access and Sharing Unit: Used for cloud service support, allowing users to remotely access and analyze data through the Internet; Component Six, Intelligent Prompt and Auxiliary Decision-making Unit: Based on artificial intelligence-based anomaly detection, automatically identifies abnormal patterns in data and prompts users.

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