252 results about "Cell morphology" patented technology

The invention relates to the technical field of medical image analysis, in particular to a CAR-T cell culture monitoring system based on image recognition, which comprises a cell region division module, a cell morphology analysis module, a cell behavior dynamic analysis module and a cell population collaborative monitoring module. According to the method, through cell image gradient intensity analysis, refined cell edge detection and dynamic adjustment of a segmentation threshold value, high-precision extraction of cell boundaries is ensured, noise interference is avoided, cell shapes, textures and geometric features are refined, the identification degree of morphological features is improved, and tiny changes of cell morphologies are accurately captured; dynamic tracking and trend evaluation are carried out on cell behaviors based on adjacent frame images, tiny dynamic changes such as cell division, aggregation and migration are accurately reflected, excessive smoothness in the dynamic process is avoided, cell population behavior monitoring is combined with interaction and corresponding speed calculation, the population synergistic effect change trend is comprehensively evaluated, and the cell population behavior monitoring effect is improved. And finer cell culture environment optimization and clinical research support are provided.

The invention discloses a reticulocyte recognition and grading system based on a blood smear, and particularly relates to the field of medical cell morphology examination, and the system comprises an image acquisition module, a staining normalization module, an instance segmentation module, an erythrocyte classification module, a reticulocyte grading module and a statistics output module. The image acquisition module adopts an automatic microscope platform to continuously scan the blood smear under a 100-time visual field, acquires a high-quality bright field channel image through an automatic focusing technology, and monitors image definition, contrast and illumination uniformity; the statistical output module is used for calculating the proportion and bluish violet intensity statistics of reticulocytes of each level, and generating a visual quality control result and a diagnostic report; according to the invention, full-automatic processing from samples to reports is realized, interpretability and high classification precision are both considered, subjective difference and omission ratio of manual microscopic examination are significantly reduced, and efficiency and consistency of clinical detection are improved.

In some examples, a method includes using a machine learning encoder to extract respective sets of machine learning (ML)-based features from respective images of cells that are dying and unstained. Cells of a first subset are at a first state of dying, and cells of a second subset are at a second state of dying. The method may include using a computer vision encoder to extract respective sets of cell morphometric features from the respective images. The method may include using the respective sets of ML-based features and the respective sets of cell morphometric features to generate respective multi-dimensional feature vectors that represent respective cell phenotypes. The method may include using the respective multi-dimensional feature vectors to correlate, to the first state of dying or to the second state of dying, a phenotypic difference between the cells of the first subset and the cells of the second subset.

In some examples, a method of processing includes using a machine learning encoder to extract respective sets of machine learning (ML)-based features from respective images of viable, unstained cells. Cells of a first subset of the cells have a first genetic edit, and cells of a second subset of the cells lack the first genetic edit. The method may include using a computer vision encoder to extract respective sets of cell morphometric features from the respective images. The method may include using the respective sets of ML-based features and the respective sets of cell morphometric features to generate respective multi-dimensional feature vectors that represent respective cell phenotypes. The method may include using the respective multi-dimensional feature vectors to correlate, to the first genetic edit, a phenotypic difference between the cells of the first subset and the cells of the second subset.

The invention discloses a classification method and a classification device for pancreatic neuroendocrine tumors. The classification method comprises the following steps: using a pre-trained segmentation model to segment a plurality of HE full slice images from a plurality of patients; quantizing each segmented HE full slice image to determine a plurality of first feature parameters; based on the cellular morphology and topological features of each HE full-slice image, extracting a plurality of second feature parameters from each HE full-slice image; for each HE full slice image, screening out a target feature from the plurality of first feature parameters and the plurality of second feature parameters, and calculating a pathological omics score; inputting the pathological omics scores and the conventional pathological features of the plurality of HE full slice images into a logistic regression model for training to obtain a trained logistic regression model; and classifying the HE full slice images to be classified by using the logistic regression model. According to the method, pancreatic neuroendocrine tumor G classification can be quickly and accurately realized at low cost.

The invention relates to the technical field of image processing, and discloses a gynecological cell morphology intelligent identification method and system based on machine vision, and the method comprises the steps: collecting an original image of gynecological cells, carrying out the color normalization processing of the collected original image, carrying out the denoising processing through employing a wavelet threshold value, and carrying out the image enhancement through employing adaptive histogram equalization; according to the method, color consistency errors of different batches of dyed images are reduced, noise introduced in the image acquisition process is eliminated, cell structure details are reserved, and the accuracy of diagnosis is improved. And then image enhancement is carried out, the contrast ratio of cell nucleuses and cytoplasm is improved, so that the characteristics in the cells are more obvious, segmentation can be more accurately completed during subsequent image segmentation, the lesion level of the gynecological cells can be accurately identified, and the accuracy of an identification result is ensured.

The invention discloses a breast cancer neoadjuvant chemotherapy curative effect prediction method and system, and relates to the medical image processing and analysis technology, and the method comprises the steps: carrying out the Macenko dyeing normalization of a sample HE pathological image of a patient; extracting a tissue region from the normalized sample HE pathological image by using an HEST method; inputting the extracted tissue region into a Prov-GigaPath network, extracting a feature vector of a specified dimension under set parameters, and performing dimension reduction on the extracted feature vector; inputting the feature vectors subjected to dimension reduction into an ABMIL model, and training the feature vectors; and predicting the HE pathological image of the patient based on the trained ABMIL model, and visualizing the prediction result by using the attention score of the trained ABMIL model. According to the method provided by the invention, multi-level complex features such as cellular morphology and tissue structure in the HE image can be automatically mined, and the accuracy and reliability of prediction are greatly improved.

The invention belongs to the technical field of medical diagnosis, and discloses a quantum multicolor immune digital pathological diagnosis analysis system, which comprises the following steps: acquiring high-resolution digital images of an immunohistochemical or immunofluorescence slice and a slide, and analyzing multicolor signal distribution in the images to obtain a quantum chromatographic image set; pixel-level color separation and intensity quantization are carried out on the quantum chromatographic image set, and a quantum intensity index set of each pixel is generated; performing multi-target color overlay analysis and post-translational modification protein specificity evaluation on the quantum intensity index set to construct a multi-color modification index set; identifying a single cell boundary and a multi-cell community based on the multicolor modification index set, and extracting a cell morphological parameter and a spatial adjacency relation to obtain a cell quantum analysis set; performing consistency correction and traceable recording by applying an automatic quality control mechanism, and generating a digital diagnosis report; the accuracy of accurate qualitative and quantitative analysis of immunohistochemistry and immunofluorescence is greatly improved.

The invention discloses a cell morphology dynamic monitoring method and system fused with time sequence image analysis, and the method comprises the steps: firstly obtaining a time sequence image sequence of a cell at a plurality of continuous time points, and extracting an initial feature vector set containing the morphology, size, texture and the like of the cell; inputting the time sequence image into a time sequence image multi-focus fusion model to obtain a fusion feature vector, and forming a refined feature vector through dimension transformation and feature screening; and inputting an improved long-short-term memory network to learn a cell state evolution mode, determining the state of the cell at each time point, generating a change track and predicting a future state. The system comprises an image acquisition and initial feature extraction unit, a time sequence image multi-focus fusion unit, a dimension transformation and feature screening unit, an improved long-short-term memory network unit, a cell state determination unit and a cell state prediction unit, all the units are connected in sequence, image features at different time points are associated through a fusion model, the network is optimized in combination with cell parameters, and the cell state is predicted. The accurate monitoring on the dynamic change of the cell morphology is realized.

The invention belongs to the technical field of active peptide preparation, and particularly relates to an active collagen peptide with an immunoregulation function and a preparation method and application thereof. The active collagen peptide with an immunoregulation function is prepared by using a method of performing composite enzymolysis and separating and collecting specified collection liquid by using a chromatographic column, and a new thought is provided for improving the immunity; the prepared active collagen peptide can significantly improve the proliferative activity, phagocytic ability and NO secretion amount of RAW264.7 cells and change the cell morphology, has an important regulation effect on immune balance recovery of immunosuppression model mice, and can regulate the problem of low immunologic function of mice induced by cyclophosphamide, regulate immune balance and improve the body immunity.

The invention discloses a morphological feature-based cell segmentation and cell nucleus identification method for a turned unstained bone tissue pathological image. The method comprises the following steps of: 1, eliminating tool marks by adopting a tool mark elimination method combining local frequency domain analysis and directional suppression; 2, performing cell segmentation by using a K-means method, and performing morphological expansion and topological analysis on a segmented single cell image to identify a cell nucleus in the single cell image; step 3, calculating morphological characteristic indexes of each region; the method comprises the following steps: establishing a multi-dimensional Gaussian mixture model according to existing bone cell labeled sample information, performing outlier detection according to statistical data analysis, and removing results which do not conform to cell morphology; classifying different regions, and removing non-cell regions; by calculating morphological characteristic indexes of each region, different regions are distinguished according to the indexes, and cells are preliminarily screened. According to the method, high-precision cell segmentation and cell nucleus identification can be carried out on the cut undyed bone tissue pathological image.

According to the method, a plant explant callus culture mode is adopted, a carbon source containing a fluorophore is added into a culture medium, the callus which is provided with the fluorophore, thin in cell wall, easy to dissociate by a single enzyme and uniform in cell shape and size is generated through induction, and the cell dissociated by the single enzyme is detected by a flow cytometry, so that the cell quality is improved. The single cell purity and activity of the prepared leaf are 98.5% and 99.95% respectively, the clotting rate is only 1.5%, the cell purity and activity are improved by 32.6% and 21.05% respectively compared with those of a traditional technical scheme, and the clotting rate is reduced by 31.0%; according to the method, rice seeds are used as explants, seed single cells with the cell purity and activity being up to 99.5% and 100% respectively are obtained, and the limitation that the seed single cells cannot be prepared by a traditional enzymolysis method is broken through; besides, through co-induction of the safflower leaves and the rice seeds, the purity and activity of the prepared cells are as high as 99.98% and 100.0 respectively, and the limitation of single cell preparation caused by heterogeneity among species is overcome.

The invention discloses a liquid cell product, a preparation method thereof and a preserving fluid for preparing the liquid cell product, and belongs to the technical field of immunodetection. The dendritic polymer is creatively added into the preserving fluid for preparing the liquid cell product, the cell morphology in the liquid cell product can be improved, and a thermal acceleration test proves that the preserving fluid can maintain the cell morphology in the liquid cell product for a long time. When the preservation solution is used for preparing the liquid cell quality control product for immunodetection, quality control spots with complete circles can be formed after sample application on slides made of different materials, it can be obviously judged that cells in the liquid cell quality control product are dispersed very uniformly after immunohistochemical staining, and the preservation solution has very high application value.

The invention discloses application of plant-derived glyceroglycolipid in preparation of an anti-inflammatory product, inflammation is RAW264.7 cell inflammatory response induced by LPS (lipopolysaccharide), and the plant-derived glyceroglycolipid can resist inflammation by inhibiting expression of inflammatory factors. By combining column chromatography with chromatographic analysis, efficient extraction, precise separation and structural identification of the plant GL are realized, and important technical support is provided for research of plant lipids. The plant GL can significantly inhibit inflammatory response of RAW264.7 macrophages, including reduction of LPS-induced cellular morphological change, down-regulation of inflammatory factor mRNA expression and reduction of CD86 expression level. The invention provides a solid molecular level theoretical basis for the application of the plant glycerol glycolipid in the development of anti-inflammatory functional foods and medicines.

The invention discloses a cat kidney suspension culture cell line suitable for serum-free suspension culture and application of the cat kidney suspension culture cell line. The name of the cell line is F81-B4, and the preservation number is CGMCC (China General Microbiological Culture Collection Center) No.46350. After 50 generations of continuous subculture, the cells still can maintain the original proliferation level and cellular morphology, the cell number can reach 9.0 * 10 < 6 > / mL after the cells are subcultured at the density of 1.0 * 10 < 6 > / mL for three days, the multiplication time is 22-26 hours, and the cell proliferation speed is equivalent to that in a shake flask when the cells are amplified to a 10L bioreactor for culture. The cell line is highly susceptible to feline parvovirus, feline calicivirus, feline herpes virus, canine parvovirus and canine distemper virus, the virus content of a virus solution harvested 72 h after FPV virus inoculation can reach 107.5 TCID50 / mL, the virus content of a virus solution harvested 24 h after FCV virus inoculation can reach 1010.8 TCID50 / mL, the virus content of a virus solution harvested 48 h after FHV-1 virus inoculation can reach 107.5 TCID50 / mL, compared with an existing F81 adherent cell production process, the production process has the advantages that the production efficiency is high, and the production cost is low. The method has the characteristics of rapid lesion, short virus collection time and high titer. The cell matrix is an ideal cell matrix which can be used for culturing the three viruses.

In some examples, a method of processing includes using a machine learning encoder to extract respective sets of machine learning (ML)-based features from respective images of viable, unstained cells. Cells of a first subset of the cells have a first genetic edit, and cells of a second subset of the cells lack the first genetic edit. The method may include using a computer vision encoder to extract respective sets of cell morphometric features from the respective images. The method may include using the respective sets of ML-based features and the respective sets of cell morphometric features to generate respective multi-dimensional feature vectors that represent respective cell phenotypes. The method may include using the respective multi-dimensional feature vectors to correlate, to the first genetic edit, a phenotypic difference between the cells of the first subset and the cells of the second subset.

The present invention relates to a method for producing recombinant proteins, in which a larger cellular morphology is produced by, for example, degrading tags (SsrA16 and SsrA21) by SsrA, regulating morphology-related genes (including but not limited to mreBCD, ftsABEIQWXYZ, sulA, minCDE), thereby enabling more intracellular proteins to be accommodated, thereby improving the production of recombinant proteins (such as MTG and Vip) and single cell proteins.

The invention discloses a crop root system 3D microscopic phenotype detection system and detection method. The electric three-dimensional module is adopted to drive the high-resolution microscopic imaging system to move, and super-large-range and multi-angle crop root microscopic imaging is achieved. Through combination of depth-of-field synthesis, image depth estimation and an automatic focusing technology, various root system microscopic phenotypes such as root hair and root epidermis cell morphology can be rapidly obtained. The device adopts a mode of combining synchronous dark field light supplement with other various lighting, and enhances the microstructure characteristics of the root system, so as to realize high-quality microscopic imaging of the crop root system. The result shows that the root system microscopic image obtained by using the system and the method is high in quality. Compared with the prior art, the invention provides a rapid, efficient and low-cost crop root system microscopic phenotype detection technology. According to the system, microscopic imaging can be carried out on a super-large-range area under the condition that a sample is fixed, the crop root system microscopic phenotype collection efficiency can be remarkably improved, and the cost is reduced.

The invention discloses a Wright staining peripheral blood cell accurate identification system and method based on intelligent microscopic imaging and multi-modal fusion deep learning, belongs to the crossing field of medical examination and artificial intelligence, and is suitable for cell morphology analysis under a 10 * 40-time microscope. The core scheme comprises the following steps: standardized slide preparation and dyeing (the slide pushing angle is 25 + / -2 degrees, the pH is 6.8 + / -0.2, and color sensing dynamic regulation is performed); intelligent imaging (focusing formula and color normalization; the method comprises the following steps of (1) data processing, (2) data processing, (3) data processing, (4) data processing, (5) data processing, (6) data processing, (7) data processing, (8) data processing, (7) data processing, (8) data processing, (8) data processing, (8) data processing, (8) data processing, (8) data processing and (8) data processing.

The invention discloses a cell image segmentation and function prediction method and device and computer equipment. The method comprises the steps of obtaining a to-be-processed cell image; inputting the to-be-processed cell image into the segmentation model for segmentation to obtain physical morphological features; inputting the physical morphological characteristics into a function prediction model to predict relevant parameters of the cell biological characteristics and relevant indexes of a set type of curative effect so as to obtain the parameters of the cell biological characteristics and the relevant indexes; and outputting physical morphological characteristics, cell biological characteristic parameters and related indexes. By implementing the method provided by the invention, the undyed bright field cell image can be effectively processed, the cell morphology and function are associated, the method is specially used for segmenting the mesenchymal stem cells, and the problem of instance segmentation under the condition of cell overlapping is solved.

The invention relates to a management method and system for a leukemia cell morphology intelligent recognition microscopic device, and solves the problems that imaging quality fluctuates, suspicious cell recognition precision is limited, and clinical efficient standardization requirements are difficult to meet. Extracting sample features and calling a parameter library according to rules to select optimal scanning and imaging parameters for initialization; starting an X / Y-axis motor according to the parameters, and correcting the deviation by combining an anti-interference rule and an encoder; z-axis dual-stage focusing is carried out after stable stopping, and an FPGA time sequence control camera carries out acquisition; aI judgment results are sent to images, suspicious cells are delineated and then positioned, and high-power lens re-focusing collection and AI recognition are carried out. The method has the advantages that sample adaptation and positioning precision is improved, suspicious cell recognition is optimized, and detection efficiency and precision are improved.

The invention relates to the technical field of medical information processing, in particular to a cervical cancer cell early screening and intelligent evaluation system based on multi-modal data, which comprises a data acquisition module, a form detection module and a screening early warning module, the data acquisition module is used for acquiring multi-modal data of a current detection object in a plurality of inspection processes; the morphology detection module is used for calculating a cellular morphology score of a current detection object in any target inspection process; the screening early warning module is used for determining similar detection objects of the current detection object, and correcting differences between the current detection object and the similar detection objects in the aspects of cellular morphology scores and lesion detection indexes according to the approximation degree between different types of lesion detection indexes of the current detection object; and obtaining the screening early warning coefficient of the current detection object by using the relative change condition of the correction result. According to the invention, the early screening and evaluation effects on cervical cancer cells are improved.

The application provides a cell fixing solution for a myasthenia gravis antibody spectrum (IgG) detection kit (cellular immunofluorescence method) and a product and application thereof, and relates to the technical field of in-vitro detection. The cell fixing solution provided by the application is composed of polyoxymethylene, formaldehyde, acetic acid, raffinose and a buffer solution, can effectively fix the cell morphology, maximally retains the natural spatial conformation and antigen epitope integrity of myasthenia gravis related antigens AChR, Titin, RyR1, MuSK and LRP4, reduces the problems of antigen denaturation, epitope shielding and protein loss in the fixing process, can efficiently and accurately realize the synchronous joint detection of various specific antibodies, and the myasthenia gravis antibody spectrum (IgG) detection kit (cellular immunofluorescence method) prepared by the application has stable detection results, and has important clinical application value and industrial popularization prospect.

The present application relates to a centrifugal system, a cell processing method and an apparatus. The centrifugal system includes: a sample chamber, a mixing and resuspension chamber, a collection chamber and a waste liquid chamber; the sample chamber is used to place a preset reagent; the mixing and resuspension chamber is connected to the sample chamber and has a first channel that allows the liquid in the sample chamber to enter the mixing and resuspension chamber at a preset centrifugal speed, and is used to mix the preset reagent entering from the first channel and the sample liquid to be tested input from the input channel at the mixing centrifugal speed to obtain a mixed liquid, and separate the mixed liquid to obtain a cell precipitate and a waste liquid; the collection chamber is used to collect the cell precipitate; the waste liquid chamber is used to collect the waste liquid. The centrifugal structure can realize automated centrifugal separation while reducing damage to cell morphology and interference with other cells.

The invention relates to a B cell specific light chain detection kit, and belongs to the technical field of biology. The B cell specific light chain detection kit comprises an antibody composition, a fixing agent and a permeabilized buffer solution, the antibody composition comprises an A group antibody and a B group antibody, wherein the A group antibody comprises an anti-Kappa antibody and an anti-Lambda antibody; the group B antibody comprises an anti-CD19 antibody, an anti-CD38 antibody, an anti-CD5 antibody, an anti-CD10 antibody, an anti-CD20 antibody and an anti-CD45 antibody; the permeabilization buffer solution comprises amino acid modified saponin. And the contained permeabilized buffer solution is modified by amino acid, so that the permeability of cell membranes can be ensured, the cell morphology cannot be excessively damaged, and the accuracy of B cell specific light chain detection is improved.

The invention belongs to the technical field of freeze-drying of lactic acid bacteria, and particularly relates to a freeze-drying protective agent for lactic acid bacteria, a preparation method and application. The invention provides a freeze-drying protective agent for lactic acid bacteria, which comprises the following components in parts by weight: 12-20 parts of dried skim milk, 12-20 parts of synanthrin and 8-16 parts of trehalose. Wherein the skimmed milk powder is beneficial to keeping the structure of lactic acid bacteria stable and maintaining the cell morphology of the lactic acid bacteria; the synanthrin is cross-linked with proteins in the trehalose and the skimmed milk powder to form a wall material, so that the lactic acid bacteria can be better protected; the trehalose can be combined with protein to form a hydrated membrane, phase change of phospholipid, protein denaturation and ice crystal generation can be inhibited under the action of hydrogen bonds, and the stability of cell membranes can be maintained. When the freeze-drying protective agent is used for freeze-drying lactic acid bacteria, the survival rate of the lactic acid bacteria is high, and the activity of the lactic acid bacteria in gastrointestinal tracts can be improved.

The invention discloses an optical fiber micro-beam probe and system capable of achieving synchronous imaging of cell morphology and mechanical characteristics, the optical fiber micro-beam probe comprises a single-mode optical fiber, a Bragg grating, a supporting column, a micro-beam and a nanometer needle tip, the single-mode optical fiber comprises a fiber core and a wrapping layer outside the fiber core, and the Bragg grating is located in the fiber core of the single-mode optical fiber; the first end of the supporting column is fixed to the second end face of the single-mode optical fiber, one end of the micro-beam is fixed to the second end of the supporting column, and the nanometer needle tip is located on the surface of the other end of the micro-beam. The metal film is introduced to enhance the reflectivity of the micro-beam, and the nano needle tip is introduced to improve the cell morphology and mechanical imaging resolution. An optical fiber FPI sensitive external weak force is formed on the end face of an optical fiber by adopting a micro-beam probe, resonance of the micro-beam probe is excited by light driving, the resonance is influenced by the weak attractive force on the surface of a cell, the change of information such as resonant frequency and amplitude is monitored, and synchronous imaging of the morphology and the mechanical property of the living cell is realized. Miniaturization, integration and high efficiency of an imaging system are facilitated, and a new method is provided for cell imaging in the fields of biomedicine and the like.

The invention belongs to the technical field of biology, and relates to a bronchoalveolar lavage fluid (BALF) preserving fluid, a kit and a cytological test method. The preservation solution is composed of TCEP, N-acetylcysteine, EDTA.2Na, trehalose, Proclin300, methanol, sodium chloride and HEPES, and all the components have a synergistic effect to achieve sample viscosity removal, oxidation resistance, corrosion prevention, cell protection and pH stabilization. The preserving fluid is suitable for morphological observation and nucleic acid detection of BALF cells, and can stably preserve samples at room temperature and maintain completeness of cell membranes and clear morphological structure. The kit comprises two preparations which are mixed to form a working solution, and the working solution can be directly used for sample preservation on a sampling site. The cytological test method comprises the steps of sample collection, preservation, centrifugal slide preparation, Wright-Giemsa staining and microscopic observation. Experimental results show that preservation solutions of different formulas are compatible with a chromosome system, the cell morphology is kept stable within 3 days, the dyeing effect is good, and it is proved that the preservation system can remarkably improve the preservation stability and detection reliability of BALF samples and is suitable for cytology and molecular diagnosis application of lower respiratory diseases.

The invention discloses a cell morphology image noise reduction method and device, equipment, a medium and a product, and relates to the technical field of image processing, the method comprises the following steps: obtaining a morphology image and an amplitude image generated by scanning a target cell through a probe of a tapping mode atomic force microscope; gray level conversion is carried out on the morphology image and the amplitude image; performing image fusion on the morphology grayscale image and the amplitude grayscale image to obtain a fused image; performing non-linear relation fitting on the pixel value of each pixel point in a non-noise area in the morphology grayscale image and the pixel value of the corresponding pixel point in the fused image to obtain a mapping relational expression between the pixel value in the morphology grayscale image and the pixel value in the fused image; mapping the pixel value of each pixel point in the fused image by adopting a mapping relational expression to obtain a de-noised morphology grayscale image; and performing gray inverse conversion on the de-noised morphology gray image to obtain a de-noised color morphology image. According to the invention, the noise of the cell morphology image can be reduced.

The invention discloses an optical positioning method and system for papillary thyroid cancer cells of a terahertz near-field system, and relates to the field of terahertz near-field imaging, and the method comprises the following steps: carrying out the imaging observation of a thyroid tissue section under a first magnification factor through a microscope, carrying out low-magnification imaging partitioning on an area where imaging observation is located according to the morphological characteristics of the cells to form partitioned images; selecting an area of suspected papillary thyroid cancer cells, performing observation and comparison under a second magnification, comparing the observed morphology with the known optical characteristics of the papillary thyroid cancer cells, and selecting an area near the area with the suspected characteristics as an optical positioning point and performing marking; and carrying out positioning according to the optical positioning point, and carrying out scanning imaging by using a terahertz near-field system. The problems that a terahertz near-field system is long in time consumption and difficult to locate when finding papillary cancer cells in multiple cells of thyroid tissue slices are mainly solved.