76 results about "H&E Staining Method" patented technology

This invention provides a PAM staining method that enables staining suitable for magnified observation of various samples using a range of microscopes, from optical microscopes to electron microscopes. [Solution] A PAM staining method comprising the steps of: silvering a biological sample; coloring the biological sample; and fixing the color of the biological sample, wherein the biological sample is a biologically derived sample that has been oxidized; the silvering step involves immersing the biological sample in a methenamine silver aqueous solution at room temperature, raising the methenamine silver aqueous solution from room temperature to 62°C or higher and 68°C or lower, and carrying out the silvering reaction for 30 to 40 minutes from the start of the reaction at room temperature; the coloring step involves immersing the silvered biological sample in a 0.2% gold chloride aqueous solution at room temperature for 8 to 12 hours; and the fixing step involves immersing the sample in a hard film fixing solution containing 11% to 13% sodium thiosulfate and aluminum potassium sulfate dodecahydrate for 3 minutes or more at room temperature.

A reagent kit, staining method, and application for combining dual immunohistochemistry with elastin fiber staining. The reagent kit includes a combination of primary antibodies, consisting of anti-CK7 and anti-CD34 monoclonal antibodies from different species, such as rabbit anti-human CK7 monoclonal antibody and mouse anti-human CD34 monoclonal antibody. By selecting CK7 and CD34 as the primary antibody combination, the growth pattern of tumor epithelium can be accurately indicated, and the proliferation and thickening of alveolar septal fibrous tissue caused by tumors can be clearly revealed, as opposed to structural changes of alveoli induced by other factors. Combined with independent Victoria blue staining, the elastin fibers of the walls of arteries and veins, as well as the pleura of the lungs, can be clearly visualized, aiding in the assessment of the integrity of elastin fibers on the lung surface and in determining the extent of tumor infiltration.

The invention discloses a pathological image virtual dyeing method and system based on a diffusion model, and belongs to the technical field of cross of pathological image processing, deep learning and computer vision. Through an end-to-end process of data preprocessing, model construction, model training and virtual dyeing reasoning, AF to Hamp is realized; performing non-paired virtual dyeing on the E; the method comprises the following steps: acquiring a non-paired AF pathological image and a Hamp through data preprocessing; e, acquiring a pathological image; generating a trunk through single-step diffusion, and constructing an STAIN model through a multi-modal semantic enhancement module, a local significance perception module and a composite loss function; the STAIN model is trained; and inputting a to-be-processed AF pathological image into the trained STAIN model for virtual dyeing reasoning. According to the method, the multi-step iteration bottleneck of a diffusion model is broken through, and single-step rapid reasoning is realized; cell nucleus and gland pathological structures are accurately reserved; it is guaranteed that the dyeing style conforms to Hamp; e, clinical standard; a lightweight adaptation strategy is adopted; background noise interference is suppressed; the method adapts to non-pairwise data scenes, and the practicability and generalization are improved.

To provide a slide glass capable of performing staining without peeling off a specimen when performing the staining by using an automatic staining device.SOLUTION: According to the present invention, there is provided a slide glass including a test region including an outer region and a smear region, in which the outer region is formed by performing an antifouling process on the slide glass, the smear region is shaped by being surrounded by the outer region and includes a specimen dropping portion and a staining liquid dropping portion, and the specimen dropping portion and the staining liquid dropping portion are arranged at different positions in the smear region.SELECTED DRAWING: None

The invention discloses a non-degreasing biological tissue dyeing method and device. The dyeing method of the non-degreasing biological tissue comprises the following steps: a sample fixing step: fixing a biological tissue sample by adopting paraformaldehyde and / or glutaraldehyde; and a dyeing step: carrying out electrophoresis dyeing on the fixed biological tissue sample which is not degreased by using a nucleic acid dye and a beta-amyloid protein small molecule dye. According to the non-degreasing biological tissue dyeing method disclosed by the invention, the non-degreasing biological tissue is directly dyed, so that the damage of degreasing operation to a sample is avoided; moreover, the nucleic acid dye is combined with the beta-amyloid protein small molecule dye, so that the whole brain sample can be quickly and efficiently dyed, and high-resolution fluorescence labeling and three-dimensional space distribution imaging of beta-amyloid protein plaques in the whole brain range can be realized; the method is of great significance in revealing the spatial distribution pattern of beta-amyloid protein and explaining the pathogenesis of Alzheimer's disease.

This invention discloses a virtual immunohistochemical staining method and system based on relation generative adversarial networks (GANs) and sequence slide data, comprising the following steps: Step S1, constructing a sequence slide dataset, wherein each H&E-stained slide is followed by three consecutive Ki67-stained slides; Step S2, constructing a relation generative adversarial network (GAN) model, the model comprising two ResNet generators and two relation discriminators, used to train and evaluate the credibility of the sequence relationship between image pairs; Step S3, performing two-stage training on the relation generative adversarial network model, namely, basic style pre-training and Z-axis alignment relation adaptation. This invention fundamentally solves the Z-axis alignment problem, resulting in higher image fidelity and pathological accuracy, significantly improving clinical application value, and providing new research resources and evaluation paradigms.

The invention provides a PN junction dyeing method and a PN junction characterization method.The PN junction dyeing method comprises the steps that a to-be-dyed sample with a to-be-dyed PN junction exposed out of the cross section is provided; preparing a first solution; a second solution is added into the first solution to form a first staining solution, the first staining solution comprises a first component and a second component, and the second component is the same as the second solution; a first substance is added into the first staining solution to form a second staining solution, the second component and the first substance react at the reaction rate smaller than a preset threshold value to generate hydrofluoric acid, and the first substance and the second component react completely after a first duration; and within a second duration of adding the first substance into the first staining solution, immersing the cross section of the PN junction to be dyed exposed in the sample to be dyed into a second staining solution, and dyeing the PN junction to be dyed, the second duration being shorter than the first duration. According to the PN junction dyeing method, the controllability and safety in the operation process of the PN junction dyeing method can be improved.

The invention relates to a method for staining bacteria, comprising the steps of a) staining a bacteria sample by means of a solution of crystal violet, b) adding Lugol's solution to the stained bacteria sample, c) rinsing with distilled water, d) adding a solution of safranine-O and fuchsin in diethylene glycol monoethyl ether, and e) rinsing with distilled water, wherein the method is carried out substantially without alkanol.

To provide a staining device capable of speeding up the staining of a biological tissue.SOLUTION: The staining apparatus 1 includes a cathode chamber 2, an anode chamber 4, a stain solution 21 containing an ionic dye 23 and contained in one of the cathode chamber 2 and the anode chamber 4, a buffer solution 22 contained in the other of the cathode chamber 2 and the anode chamber 4, a first electrode 11 immersed in the stain solution 21, a second electrode 12 immersed in the buffer solution 22, and a communicating tube 3 connecting the cathode chamber 2 and the anode chamber 4. When the living tissue 20 is arranged so as to block the cross section of the communicating tube 3 and electricity is made to flow between the first electrode 11 and the second electrode 12, the dye 23 is electrophoresed so as to pass through the living tissue 20.SELECTED DRAWING: Figure 1

This invention discloses a high-throughput automated immunofluorescence staining device and its staining method. The device includes a liquid injection motion module, a reaction chamber module, a supply and waste collection module, and a control system. The liquid injection motion module includes an X-axis beam and a pipetting and auxiliary material robotic arm, which are driven in parallel to achieve sequential operation. The reaction chamber module includes a temperature-controlled station, a low-temperature reagent storage unit, and an auxiliary material supply unit. The supply and waste collection module includes a waste removal and cleaning unit and an auxiliary material waste collection unit. This invention achieves a 96-station array through a temperature-controlled reaction station, combined with the dual-drive parallel operation of the pipetting and auxiliary material robotic arms, eliminating action waiting time and significantly improving throughput. The use of a closed semiconductor cooling component linked with an automatic flip-top mechanism ensures uniform reagent activity over a long period. A plate-mounted small vacuum pump drives a rigid pipeline with deep-hole waste suction, combined with high-flow-rate wide-area spraying, to thoroughly remove waste liquid and reduce cross-contamination. This achieves full-process automation, significantly improving staining quality and efficiency.

Staining devices and methods for automated systems are provided herein. A dyeing method includes disposing a substrate proximate a dyed surface to establish an overlap between the dyed surface and the substrate. The staining method further includes maintaining a gap between the stained surface and the substrate to define a chromosome product according to the overlap and the gap, where the chromosome product has one or more meniscus edges. The staining method further includes disposing a portion of the staining fluid over the staining surface and distributing the staining fluid over the substrate.

The invention belongs to the technical field of pathological tissue section staining, and particularly relates to a hematoxylin-eosin staining method based on short-time immersion and chaotropic standing diffusion and application of the hematoxylin-eosin staining method. According to the hematoxylin-eosin staining method based on short-time immersion and chaotropic standing diffusion, the staining process time can be remarkably shortened, the working efficiency of pathological section staining can be greatly improved, the staining solution consumption and the cross contamination risk can be effectively reduced, the experiment cost is saved, and the reliability of the staining result is guaranteed; meanwhile, the dyeing uniformity and repeatability can be remarkably improved, the result deviation caused by operation difference is reduced, the dependence on the experience of an operator is reduced, and standardized popularization and application are facilitated; besides, the dyeing method disclosed by the invention is wide in applicability, can meet the dyeing requirements of conventional paraffin sections, frozen sections and trace tissue samples, can meet the use requirements under different pathological detection scenes, and has outstanding clinical and scientific research application prospects.

The present invention addresses the problem of providing a method for staining a cell membrane protein with high accuracy. Provided is a method for detecting a cell membrane protein in an embedded immobilized tissue, the method comprising an embedding medium removal step for removing an embedding medium by bringing the immobilized tissue, which contains an embedding medium in a solid state, into contact with a solution for removal without baking.

The application discloses a kind of pathological image virtual dyeing methods based on multi-task learning, steps include: a pair of virtual dyeing model is constructed, respectively including the generator and discriminator of corresponding source domain and target domain;For generator, it is reconstructed, conversion across dyeing domain in self-supervision;For discriminator, add pathological section category supervision loss in self-supervision adversarial loss;After such alternation training, update, finally realize the image conversion between source domain and target domain and corresponding pathological classification task.The application uses unpaired dyeing dataset, introduces classification loss by pathological category label, optimizes objective function design, adds classification module, back gradient guides model to learn inter-class difference dyeing feature, and improves the generation effect of pathological image virtual dyeing.

This invention discloses a method and system for multi-domain virtual staining of pathological tissues based on generative adversarial networks (GANs). The method includes: acquiring and segmenting a histopathological slide image to obtain multiple segmented images and segment coordinates; inputting each segmented image and its corresponding target staining style label into a generator of a GAN to output the segmented staining image; the generator includes a downsampling module, multiple cascaded GramLIN modules, and an upsampling module; the GramLIN module includes a style encoding dictionary storing information on various target staining styles; and stitching all the segmented staining images together according to their segment coordinates to obtain a histopathological slide image with the target staining style. The generator incorporates multiple cascaded GramLIN modules, each with a style encoding dictionary, enabling staining transfer between multiple staining methods using a single network.

The invention relates to a lensless holographic microscope-integrated microfluidic device for the real-time detection and isolation of circulating tumor microemboli (CTMs), which are extremely rare in blood, and the operating method of said device. The device according to the invention operates on a microfluidic chip (10) using a semi-automated method based on filtration and image processing, and CTMs are imaged and automatically detected without any staining method by means of a trained neural network.

Provided in the present invention are a cytopathological staining kit and a staining method. The staining kit comprises a basic fuchsin staining reagent, a silver nitrate staining reagent, an ethanol-hydrochloric acid fixation solution, a gelatin-formic acid reducing solution, and a washing solution. The kit can reveal the complete cellular structure and morphology thereof, and can particularly delineate the morphology of a nucleolus of a cell nucleus.

The present invention relates to: a composition and kit for immunohistochemistry (IHC) staining, comprising an anti-PAUF monoclonal antibody that specifically binds to a PAUF protein; and an immunohistochemical staining method using same. The present invention exhibits significantly improved staining sensitivity and clarity over conventional PAUF staining methods, thereby providing the advantage of obtaining more accurate and reliable results regarding the expression of the PAUF protein. In addition, the present invention enables accurate staining of a large amount of clinical tissues in a short time by using specialized staining equipment together, thereby providing the advantage of enhancing the reliability of staining results. Accordingly, it is possible to specifically, rapidly, and accurately identify only PAUF within cancer tissues of cancer patients, thereby enabling rapid and efficient cancer diagnosis, and by using this, early cancer diagnosis is possible, thereby enabling early treatment for cancer patients in need of targeted therapy.

The present application relates to a kind of hematoxylin-eosin (HE) staining method and operation steps without xylene and alcohol, belong to pathological technique, apply in pathology, histology and clinical experimental diagnosis biomedical disciplines field such as embryo. The hematoxylin-eosin (HE) staining step of conventional paraffin section is at least 12 more additional steps before and after dyeing into dyeing liquid dyeing to mounting respectively needs to use including xylene and gradient concentration alcohol. Lengthy dyeing step is not only laborious and time-consuming, also pollutes air environment and harms personnel health. The present application is a kind of conventional paraffin section whole process hematoxylin-eosin (HE) dyeing step without using xylene and alcohol method and step, make its application in management HE dyeing process for improving pathological technical room work quality and efficiency, reduce reagent cost and eliminate environmental pollution is crucial.

The invention provides a dyeing method for removing autofluorescence of a single cell sorting micro-fluidic chip and a chip without autofluorescence. The dyeing method comprises the following steps: completely soaking the single-cell sorting micro-fluidic chip in a dye solution for dyeing until the top layer of the chip is dyed into a non-transparent black top layer, thereby obtaining the single-cell sorting micro-fluidic chip without autofluorescence, the dye in the dye solution is black dye; the single cell sorting micro-fluidic chip at least comprises a photosensitive dry film serving as a runner layer. The staining method provided by the technical scheme of the invention can effectively solve the problem of autofluorescence of a single cell sorting micro-fluidic chip prepared from a traditional photosensitive dry film, so that when the stained chip is applied to fluorescence activated cell sorting, recognition of automatically screened fluorescent cells is facilitated, the operation difficulty of fluorescence activated cell sorting is reduced, and the working efficiency is improved. And accuracy and reliability are improved.

To provide an electronic staining method that enables electronic staining of even a resin like PAA which has an acidic functional group and is easy to elute into a reaction liquid, and can evaluate a distribution state of the resin.SOLUTION: There is provided an electron staining method for evaluating a distribution state of a resin by using an electron staining liquid, wherein the resin has an acidic functional group and the electron staining liquid consists of an inorganic compound and a polar organic solvent. Particularly, it is preferred that the resin is a polyacrylic acid having a carboxyl group, the inorganic compound is a cesium (Cs) compound, and the polar organic solvent is an alcohol.SELECTED DRAWING: Figure 1

This invention discloses a method for detecting Candida albicans based on compound fluorescent staining and deep learning, belonging to the field of microbial detection technology. The method first synthesizes a novel NHC-triazolium salt fluorescent molecule, which is then compounded with calcium fluorescent white and DAPI to form a specific staining solution. After treating the sample with this staining solution, multi-channel fluorescence imaging is performed and images are acquired. Simultaneously, ITS sequencing is performed on the samples. Based on the sequencing results, the images are classified and bacterial cells are manually cropped to construct a labeled dataset. A convolutional neural network model is trained using this dataset to learn to recognize the unique "multi-fluorescent fingerprint" presented by Candida albicans stained with the compound staining solution. In application, the same staining and imaging are performed on the test samples, and the trained model automatically analyzes the images to achieve detection. This invention significantly improves the specificity of detection through the synergy of chemical staining and artificial intelligence. Experiments show that compared with traditional single staining or unstained methods, this method improves the specificity of Candida albicans recognition by 37% and 52%, respectively, and has the advantages of being fast, accurate, and highly automated.

The application relates to a pathological image virtual staining method and system based on a diffusion model, and belongs to the cross technical field of pathological image processing, deep learning and computer vision. Through an end-to-end process of data preprocessing-model construction-model training-virtual staining inference, non-paired virtual staining from AF to H&E is realized; through data preprocessing, non-paired AF pathological images and H&E pathological images are obtained; an STAIN model is constructed through a single-step diffusion generation main trunk, a multi-modal semantic enhancement module, a local saliency perception module and a composite loss function; the STAIN model is trained; and an AF pathological image to be processed is input into the trained STAIN model for virtual staining inference. The application breaks through the multi-step iteration bottleneck of the diffusion model, realizes single-step rapid inference, accurately retains pathological structures of cell nuclei and glands, guarantees that the staining style conforms to the H&E clinical standard, adopts a light-weight adaptation strategy, suppresses background noise interference and adapts to a non-paired data scene, thereby improving practicability and generality.

The invention provides a cell virtual staining method and system, computer equipment and a storage medium, and belongs to the field of cell detection.The method comprises the steps that a microscopic image of a to-be-stained cell is obtained; a multi-scale structural feature map is extracted from the microscopic image, the multi-scale structural feature map is weighted based on a regional attention mechanism to obtain cell structural features of the cell to be stained, and the weight of the boundary features is in positive correlation with the cell nucleus density; extracting color distribution features from a preset reference dyed image, and performing spatial alignment and semantic mapping on the color distribution features and the cell structure features to obtain fusion features; and performing image reconstruction according to the fusion features to obtain a staining image of the to-be-stained cell. According to the method, the display effect on fine structures such as cell nuclear membranes and chromatin distribution is improved, and the high-precision requirement of clinical diagnosis on cell substructure recognition is met.

Provided is a microscope slide that allows staining to be performed without a specimen detaching when staining is performed by using an automatic staining device.　The present invention provides a microscope slide comprising an examination region comprising an outer region and a smear region. The outer region is formed by applying an antifouling treatment to the microscope slide. The smear region is shaped by being surrounded by the outer region, and comprises a specimen dropping portion and a staining solution dropping portion. The specimen dropping portion and the staining solution dropping portion are disposed at different positions in the smear region.

The invention relates to a hyperspectral image multi-virtual staining method, which comprises the following steps: S1, selecting an unstained pathological section, acquiring sample images by using a microscopic hyperspectral imaging system, and pairing part of the sample images to acquire the Hamp of the sample images; e, dyeing the image, and performing dark current correction and spectrum normalization processing on an image sample; s2, extracting spectral sequence information and spatial structure characteristics of the sample image; s3, dividing the data into three types according to the pairing degree, and performing progressive transition training from pairing to non-pairing through a beta-ECUT feature decoupling network to obtain three-differentiation data; and S4, inputting the three-differentiation data set into a double-branch expert joint optimization and meta-control virtual dyeing model module, adaptively adjusting the output fusion proportion of a diffusion expert branch and a feature expert branch according to the complexity of an input image, and finally generating a multiple virtual dyeing image through a VEA dyeing encoder. According to the method, the problem of performance degradation caused by data heterogeneity of a traditional model in a real pathological environment is solved.

The application discloses a kind of multiple dyeing image matching method, device, medium and equipment, first obtain the multiple dyeing images of multiple pathological sections, wherein each pathological section is obtained after being dyed by a kind of preset dyeing method and is photographed to obtain a corresponding dyeing image, then in each dyeing image, the contour of pathological section is extracted respectively, and the matching feature of corresponding pathological section is identified based on the extracted contour, then the relative position of the dyeing image to be matched and the preset reference dyeing image is adjusted, until the matching feature of the dyeing image to be matched and the matching feature of reference dyeing image satisfy preset matching requirement, finally obtain the matching parameter between the dyeing image to be matched and reference dyeing image, and calculate matching value according to matching parameter, if matching value is greater than preset matching value threshold, then determine that the dyeing image to be matched is matched successfully. Visible, the present application can automatically complete the automatic matching of pathological image of multiple levels different dyeing methods.

The invention discloses a dyeing method for vagina micro-ecology detection. The dyeing method mainly comprises the following steps: 1) taking female genital tract secretions, and directly diluting the secretions with a diluent to form a suspension; (2) coating the suspension liquid on a glass slide by using a pipettor; 3) drying and fixing the suspension on the glass slide; 4) immersing the fixed suspension liquid glass slide into an eosin dye solution, and washing the glass slide with running water; (5) carrying out gram staining on the glass slide; and 6) observing by using a microscope. The invention also relates to a staining kit. According to the staining method, under the condition that the advantages of a gram staining method in the prior art are reserved, simple and rapid detection of trichomonad vaginalis can be achieved, the trophozoic form and flagellum form of trichomonad vaginalis can be clearly displayed, the accuracy of trichomonad vaginalis detection can be improved, and the method is suitable for popularization and application. The comprehensive and accurate detection on the vagina micro-ecology is facilitated.

The invention discloses an unstained multispectral kidney cancer tissue Hamp; the virtual staining method for the kidney cancer tissue slice comprises the following steps: S1, acquiring original data of the kidney cancer tissue slice white slice; s2, preprocessing the original data to obtain a standardized multispectral image; s3, obtaining a corresponding Hamp through an experiment; e, dyeing the slice image as a reference; s4, constructing a standard data set and inputting the standard data set into the deep learning model for training; s5, inputting the data set into the SwinIR-UNet fusion network, and after inputting an undyed multispectral image, outputting the data set and the Hamp; and E, dyeing the target image with the consistent style. S6, training is finished, and kidney cancer tissue Hamp is obtained; and E, virtualizing the dyeing model. The method fuses a global attention mechanism and an encoder-decoder structure, has excellent image conversion capability and robustness, and can effectively restore the dyeing effect, improve the diagnosis efficiency and reduce time consumption, tissue damage and personal errors in traditional dyeing.

The present application relates to the technical field of image recognition, and particularly relates to a virtual staining method for immunohistochemical section images, comprising: obtaining a pair of training images, extracting a set of two-dimensional coordinates of cell nucleus centers and a normalized gray integral vector, and taking the set of two-dimensional coordinates of cell nucleus centers and the normalized gray integral vector as edge distribution constraints to obtain a set of two-dimensional displacement vectors of cells; determining a local adjacency relationship based on the center coordinates, combining the set of displacement vectors to extract a set of adjacent coordinate offset difference scalars, and reconstructing the set of adjacent coordinate offset difference scalars into a two-dimensional spatial misplacement cost matrix; converting the cost matrix into a pixel-level weight mask, locally truncating a model prediction error to train a generation model; and finally converting an H&E image into a virtual IHC image by using the model. The present application effectively blocks an error gradient return caused by physical misplacement, eliminates false positive coloring, and significantly improves clinical reliability.