177 results about "Cell morphology" patented technology

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.

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 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.

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 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.

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 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 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 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 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.

The present invention relates to the field of image recognition and judgment technology, and in particular to a method for judging the estrous cycle of rats based on image recognition. Its technical solution includes sample collection and preparation, image collection and optimization, cell segmentation and positioning, feature extraction and analysis, cell classification and recognition, and result verification and feedback. The present invention significantly improves the efficiency and accuracy of morphological recognition of rat vaginal exfoliated cells through systematic and precise operations. From precise sample collection and image acquisition optimization, to multi-dimensional feature extraction and integrated learning classification, and then to result verification and feedback, the scientific nature of recognition is fully guaranteed, which not only greatly shortens the detection time and reduces manual errors, but also continuously improves performance through dynamic optimization, providing efficient and reliable technical support for the study of the estrous cycle of rats.

The invention discloses a cellular morphology recognition method and system for pathological analysis, and relates to the technical field of cellular morphology recognition, a feature screening module is used for calculating a morphological analysis direction tensor field, and a first fusion feature and a second fusion feature are obtained through a depth sequence model Transform and a plane sequence model Transform respectively; a multi-head attention mechanism is used for screening the first fusion features and the second fusion features to form screened fusion features, a regulation and control execution module is used for performing contour surface analysis on the direction tensor field to obtain an interlayer equidistant surface sequence, and spiral angle mapping is performed to obtain a reference spiral direction field; and generating a planar spiral layout map and executing variable density spiral network regulation and control. According to the recognition system, through organic combination of multi-dimensional feature fusion, dynamic grid construction and spiral space regulation and control, the pathological analysis capability which is accurate and accords with cell physiological morphological characteristics is realized.

The invention discloses a human-derived ampulla cancer cell line DPC-X5 and application thereof, and belongs to the field of microbial animal cell lines. The human-derived ampulla cancer cell line is named as a human-derived ampulla cancer cell line (homo sapiens) DPC-X5, and is preserved in the China Center for Type Culture Collection on October 30, 2025, and the preservation number is CCTCC NO: C202580. The human-derived ampulla cancer cell line DPC-X5 can be applied to establishment of a cell model for occurrence, development or metastasis of ampulla cancer. The human-derived ampulla cancer cell line DPC-X5 can be applied to cell models for researching differentiation mechanisms, cell morphology and dysfunction and tumor infiltration and metastasis mechanisms of ampulla cancer and guiding clinical comprehensive diagnosis and treatment. The human-derived ampulla cancer cell line DPC-X5 can be applied to research on the occurrence mechanism of the ampulla cancer and screening of drugs for preventing and treating the ampulla cancer. The human-derived ampulla cancer cell line DPC-X5 can be applied to establishment of an ampulla cancer animal model.

The invention relates to a cell morphology feature extraction and prediction analysis method, in particular to a cell morphology feature extraction and prediction analysis method for a high-throughput cervical TCT image. The method aims at solving the problems that in the cell analysis technology of the cervical TCT image, complex morphological characteristics of cells are not fully considered, the characteristic extraction precision is low, and the manual dependence degree is high. The method comprises the following steps: selecting cellular morphology characteristics of cervical TCT image auxiliary diagnosis; obtaining a segmentation result of the cell nucleus and the cytoplasm based on the segmentation network; extracting, measuring and calculating cell morphological characteristics based on a cervical TCT image segmentation result; and analyzing and visualizing the measurement and calculation results of the morphological characteristics of the cells. According to the method, medical priori knowledge and data-driven research methods are fused, and more interpretable quantitative data are provided for subsequent cervical cell research through conjoint analysis of shape features and texture features. The invention belongs to the technical field of medical image analysis and computer vision.

The invention relates to the field of CAR-T cell concentration detection, in particular to a method for detecting CAR-T cells through combination of microfluidics and immunofluorescence. Through immunomagnetic bead enrichment and micro-fluidic chip partitioning, CAR-T cells are separated from a blood sample through immunomagnetic beads, then labeling is carried out or enhanced by adding a labeling antigen, anti-TCR-PE and DAPI, three-channel fluorescence labeling is achieved, quantitative analysis can be carried out on the number, the cell morphology and the function of the CAR-T cells through automatic immunofluorescence imaging, and the accuracy of CAR-T cell detection is improved. And the detection limit reaches 0.001%.

The application belongs to the technical field of medicine, and discloses a method and system for detecting mucinous pancreatic cystic tumor, acquires a pancreatic cyst fluid sample; performs organoid culture on the pancreatic cyst fluid to obtain a mucinous pancreatic cystic tumor organoid; acquires cell morphology data of the mucinous pancreatic cystic tumor organoid; acquires H&E staining data and IHC detection data of the mucinous pancreatic cystic tumor organoid; acquires immunofluorescence detection data of the mucinous pancreatic cystic tumor organoid; performs scRNA-Seq sequencing on the mucinous pancreatic cystic tumor organoid to complete detection of the mucinous pancreatic cystic tumor; and the method can efficiently culture organoids and be used for verifying potential existence of malignant cells in function.

The application belongs to the technical field of biology, and provides a special complete culture medium for Raw264.7 mouse monocyte macrophage leukemia cells and application, so as to solve the problem that the cell morphology of Raw264.7 is obviously changed during the culture process, and the polygonal, long-cleaved and pseudopod cells are easily formed, prevent the cell from being polarized during the culture process, and ensure that the cell has the induced polarization potential. The special complete culture medium contains 83-89% DMEM, 10-15% fetal bovine serum and 1-2% double antibodies according to the volume percentage, and further contains various supplementary additives. The culture medium of the application can make the cell morphology stable and present the best monocyte morphology of the round and transparent shape.

The invention relates to the technical field of bioengineering, in particular to application of reticular structure collagen with an ECM (extracellular matrix) regulation function in tissue filling and / or compatibilization. The recombinant III-type humanized collagen provided by the invention can be self-crosslinked to form a net structure, and has good mechanical strength. The collagen has short-term and long-term effects at the same time, can be directly used as a filling agent in a short term, and can activate a plurality of signal channels and promote expression of various collagens in an extracellular matrix in a long term, jointly construct and maintain a net structure of the extracellular matrix, improve an extracellular matrix environment and improve the extracellular matrix activity. The cell morphology and the cell adhesion, migration and multiplication capacity are improved, the lasting filling and repairing effects are achieved, and good application prospects are achieved in the field of tissue filling and repairing.

A cell morphology analysis device, a cell identification method and a storage medium, wherein a digital camera captures a cell image of a blood sample under a low-power objective lens, a processor identifies and locates suspected preset type cells in the cell image, obtains an identification result, determines the located number of suspected preset type cells based on the identification result and the target number, and after completing the identification and positioning of the located number of suspected preset type cells, the digital camera captures the identified and located suspected preset type cells under a high-power objective lens, and the processor then identifies whether the captured suspected preset type cells are preset type cells, so as to count the number of preset type cells captured under the high-power objective lens and obtain a statistical value. When the statistical value satisfies: target number ≤ statistical value, the capture is stopped. At the end, the processor identifies at least the target number of preset type cells to meet clinical needs for preset type cells.

The present application adopts the way of plant explant callus culture, adds carbon source containing fluorescent group in the culture medium, induces callus with fluorescent group, thin cell wall, easy to be single enzymolysis, uniform cell morphology and size, the cell after single enzymolysis is detected by flow cytometry, the purity and activity of the prepared leaf single cell are 98.5% and 99.95 respectively, the agglomeration rate is only 1.5%, the cell purity and activity are increased by 32.6% and 21.05 respectively compared with the traditional technical scheme, and the agglomeration rate is reduced by 31.0%; the rice seed is used as the explant, and the seed single cell with cell purity and activity of 99.5% and 100% is obtained, which breaks through the limitation of traditional enzymolysis method that cannot prepare seed single cell; in addition, through the common induction of safflower leaf and rice seed, the cell purity and activity prepared are as high as 99.98% and 100.0, which overcomes the limitation of single cell preparation caused by interspecific heterogeneity.

A porphyrin compound for bioimaging and sonodynamic therapy, as well as its preparation method and application, has a chemical formula shown in Formula 2. The preparation method comprises the following steps: adding p-methylthiobenzaldehyde, a compound of Formula 1, and pyrrole to a reaction flask, evacuating the flask and introducing nitrogen gas, followed by adding anhydrous dichloromethane to obtain a reaction solution; bubbling nitrogen gas through the reaction solution, stirring at 25°C, adding boron trifluoride etherate, maintaining the temperature while continuing to stir, adding DDQ, continuing stirring, adding triethylamine, filtering, concentrating, and purifying to obtain the target product. This method features mild reaction conditions, a short reaction time, and simple operation. The resulting porphyrin compound exhibits excellent sonosensitivity and biocompatibility, can efficiently generate reactive oxygen species under ultrasound, and can produce excellent sonodynamic effects. The compound also exhibits fluorescence emission in the near-infrared region and can be excited by visible light, enabling confocal imaging to detect changes in cell morphology before and after, resulting in excellent bioimaging results. #imgabs0#

This application discloses a method, apparatus, device, medium, and product for denoising cell morphology images, relating to the field of image processing technology. The method includes: acquiring a morphology image and an amplitude image of a target cell generated by probe scanning using a tapping mode atomic force microscope; performing grayscale conversion on the morphology image and the amplitude image respectively; fusing the morphology grayscale image and the amplitude grayscale image to obtain a fused image; performing nonlinear relationship fitting between the pixel values ​​of each pixel in the non-noise region of the morphology grayscale image and the corresponding pixel values ​​in the fused image to obtain a mapping relationship between the pixel values ​​in the morphology grayscale image and the pixel values ​​in the fused image; mapping the pixel values ​​of each pixel in the fused image using the mapping relationship to obtain a denoised morphology grayscale image; and performing inverse grayscale conversion on the denoised morphology grayscale image to obtain a denoised color morphology image. This application can reduce noise in cell morphology images.

A deep neural network-based method for detecting living cell morphology may include identifying and locating one or more living cells within an acquired image to be detected by using a deep neural network-based target detection model, so as to extract one or more living single cell images. segmenting the image of the one or more living single cells by using a deep neural network-based cell segmentation model, so as to obtain one or more feature part of the one or more living single cells. and analyzing and determining a morphological parameter of the one or more living single cells based on the one or more feature parts. Thus, the activity of the detected cells can be ensured, and a non-destructive, accurate, and rapid detection of living cell morphology can be achieved.

The invention provides novel sample chambers, units and multi-well plates, and systems and methods thereof, for built-in measurement assurance of cell counting methods and calibrated and / or quality-assured measurement and analysis of diverse types of biological cells, e.g., cell count, cell size, cell concentration, cell sub-population, cell morphology, cell viability, etc.