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

A deep learning-based digital / virtual staining method and system enables the creation of digitally / virtually-stained microscopic images from label or stain-free samples. In one embodiment, the method of generates digitally / virtually-stained microscope images of label-free or unstained samples using fluorescence lifetime (FLIM) image(s) of the sample(s) using a fluorescence microscope. In another embodiment, a digital / virtual autofocusing method is provided that uses machine learning to generate a microscope image with improved focus using a trained, deep neural network. In another embodiment, a trained deep neural network generates digitally / virtually stained microscopic images of a label-free or unstained sample obtained with a microscope having multiple different stains. The multiple stains in the output image or sub-regions thereof are substantially equivalent to the corresponding microscopic images or image sub-regions of the same sample that has been histochemically stained.

The invention relates to the technical field of biomedical engineering and digital image processing, in particular to a digital image enhancement method based on cytopathology. The method comprises the following steps: eliminating noise and artifacts caused by non-uniform dyeing, section folding and dust factors; the problem of dyeing difference caused by different scanning devices is solved; key areas including cell nucleuses and cell membranes are highlighted, so that the visual effect of a low-contrast image is improved; segmenting an area, including cell nucleuses and cytoplasm, of the cells, and extracting morphological characteristics; the detail resolution of a low-resolution image, especially the definition of a small cell structure, is improved; the brightness component Y is corrected to compensate for the difference of different dyeing methods and dyeing qualities in brightness response, then the chromatic value is adjusted according to the color correction factor to make the colors of the images more consistent, and finally, the images which are acquired by different dyeing methods and dyeing qualities and subjected to brightness and chroma correction are fused to make the color of the images more consistent. And a final corrected image is obtained.

The invention provides an automatic tumor budding identification method fusing pathological staining migration and YOLO target detection. The method comprises the following steps: training Hamp by using a CUT model; a staining migration model is established from the E image to the immunohistochemical image, and the staining migration model is utilized to carry out Hamp; e, converting the dyed full-width pathological section into a cytokeratin dyed full-width pathological section; and performing tumor budding detection on the generated full-width pathological section dyed by the cytokeratin by using a TB-YOLO model improved on the basis of YOLOv10. According to the method, the CUT is combined for pathological image staining migration, the IHC image generated through TB-YOLO analysis is used for tumor budding detection, meanwhile, accurate translation and detection of positive signals are ensured, richer diagnosis information is provided for pathologists, the diagnosis accuracy is improved, the pathological examination cost of patients is reduced, and the purpose that only Hamp is used for diagnosis is achieved. And E, the tumor budding is accurately detected by the dyed image, so that the comparability of medical images in different dyeing modes and the applicability of a cross-dyeing method are improved.

The invention discloses a UNET supervised network slice HE virtual staining method and system for pathological analysis, and belongs to the technical field of artificial intelligence digital pathological analysis. Global scanning imaging is performed on a pathological slice to obtain an HE scanning image and a fluorescence confocal scanning image, and a UNET supervised network data set is established; a UNET supervised virtual dyeing network model is constructed; training and verifying the UNET supervised virtual dyeing network model by using the UNET supervised network data set; and carrying out HE virtual staining on the fluorescence imaging pathological section image by using the trained UNET supervised virtual staining network model. The method has the remarkable advantages in the aspects of dyeing precision, dyeing efficiency and robustness, and automatic and rapid virtual dyeing of different types of biological tissue sections can be achieved without accurate image registration.

The invention discloses a virtual staining method and system for a pathological section image, and belongs to the technical field of image processing, and the method comprises the steps: constructing a registration data pair for different staining styles through real staining as training data, meanwhile, a virtual dyeing lookup table model comprising a self-adaptive feature encoder, a self-adaptive weight predictor and a basic virtual dyeing lookup table is constructed, and in the model, a feature map and a weight are generated in a self-adaptive mode based on an input original image; the basic virtual dyeing lookup tables are weighted based on the weights to construct the virtual dyeing lookup table for adaptive fusion of the original image, and then the virtual dyeing lookup table is utilized to perform virtual color dyeing of various chemical dyeing styles, so that the dyeing efficiency in the process is high, the dyeing styles can be diversified, and the image quality is improved. The positions and forms of the pixels are not changed, only color values are changed, dyeing is achieved, the dyeing self-adaption is high, the dyeing quality is guaranteed, and the dyeing area has interpretability.

A deep learning-based digital / virtual staining method and system enables the creation of digitally / virtually-stained microscopic images from label or stain-free samples. In one embodiment, the method of generates digitally / virtually-stained microscope images of label-free or unstained samples using fluorescence lifetime (FLIM) image(s) of the sample(s) using a fluorescence microscope. In another embodiment, a digital / virtual autofocusing method is provided that uses machine learning to generate a microscope image with improved focus using a trained, deep neural network. In another embodiment, a trained deep neural network generates digitally / virtually stained microscopic images of a label-free or unstained sample obtained with a microscope having multiple different stains. The multiple stains in the output image or sub-regions thereof are substantially equivalent to the corresponding microscopic images or image sub-regions of the same sample that has been histochemically stained.

The embodiment of the invention provides an image virtual dyeing method and device based on deep learning and a related assembly. The image virtual dyeing method comprises the following steps: utilizing a preprocessed photoacoustic microscopic image and a Hamp; e, performing iterative training on a pre-constructed virtual dyeing model by the dyeing image to obtain a trained virtual dyeing model, and performing virtual dyeing on the new photoacoustic microscopic image by using the trained virtual dyeing model to obtain Hamp; e, dyeing the image of the style (i.e., pseudo Hamp; e, dyeing the image). According to the embodiment of the invention, the image segmentation module is embedded in the generator to help the generator to distinguish cytoplasm and cell nucleus, so that the virtual staining model is constrained, and the generator can better generate a Hamp conforming result; e, dyeing the morphological characteristics of the image to ensure the generated pseudo Hamp; the E dyeing image retains more useful cell nucleus information, and the pre-constructed virtual dyeing model reduces noise in the learning process and effectively prevents the problem of overfitting due to the fact that an image segmentation module is embedded in a generator.

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 full-automatic dyeing machine water-soluble eosin dyeing method based on mechanical arm dynamic control and process optimization, which comprises the following steps: (1) mechanical arm operation logic setting: in the steps of eosin dyeing, washing and 95% ethanol differentiation, the mechanical arm is forbidden to switch idle slot positions by locking slot position distribution; (2) time parameter control: setting the eosin dyeing time to be 2-3 minutes, the washing time to be 30-45 seconds, and the 95% ethanol differentiation time to be 20-30 seconds; and (3) error calibration: performing synchronous verification by adopting a manual timer and a dyeing machine program to ensure that the error between the actual execution time of each step and a set value does not exceed + / -5 seconds.

The invention belongs to the field of biochemical detection equipment, and discloses a flaking and dyeing all-in-one machine and a flaking and dyeing method.The flaking and dyeing all-in-one machine comprises a machine base, and a workbench, a moving mechanism and a manipulator assembly are arranged on the machine base; the working table is provided with a working area, and the working area is at least provided with a pretreatment working position and a flaking and dyeing working position; the manipulator assembly is movably arranged on the moving mechanism, and the manipulator assembly is located above the working area; the manipulator assembly comprises manipulators, the manipulators at least comprise a first manipulator and a second manipulator, the first manipulator at least has a first moving position and a second moving position, and the second manipulator at least has a third moving position and a fourth moving position; and the first moving position, the second moving position, the third moving position and the fourth moving position are at least matched with the pre-treatment working position and the flaking and dyeing treatment working position. According to the slide preparation and dyeing all-in-one machine, slide preparation and dyeing of liquid-based sample cells can be integrated into all-in-one equipment, and all steps can be independently and circularly carried out.

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.

Methods and systems directed to benchtop instruments for sample deposition and staining with machine-learning based image analysis are described. An example system includes an apparatus with a slide processing module, positioned at an upper front position of the apparatus, which has a user interface configured to receive an input from a user that configures a deposition operation and a staining operation for the cellular sample. The system further includes a clamping module positioned at a lower front of the apparatus, an auxiliary systems module positioned at a rear of the apparatus, and an optical imaging and analysis system configured to analyze the cellular sample either on-site or remotely. An example method for depositing, staining and analyzing a cellular sample uses the above-described apparatus.

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.

The invention discloses a method for collecting and dyeing sperms of Chinese prawns, and belongs to the technical field of germplasm resource protection and utilization. The method comprises the following steps: grinding Penaeus chinensis spermatophore with outer membrane removed in a glass homogenizer, adding sterilized artificial seawater, grinding until the solution becomes milky white, and filtering to obtain sperm; and mixing the sperm with eosin-nigrosine dye liquor, and standing to obtain the dyed Chinese prawn sperm. The collecting and dyeing steps are simple and easy to operate, the whole process is short in time consumption, small in sperm damage, visual in effect and high in sperm survival rate. The staining method disclosed by the invention is not only suitable for staining fresh sperms, but also can be used for staining the thawed and resuscitated sperms after cryopreservation, the staining observation after thawing is clear, and the sperms are not easy to crystallize.

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.

The invention relates to the technical field of tissue section staining, in particular to a multicolor composite staining kit, a staining method and application of the multicolor composite staining kit. The multi-color composite staining kit provided by the invention not only can realize a better staining effect and has high discrimination on staining of different tissue structures, but also does not contain dangerous chemical components such as picric acid, ethanol, ammonia and the like, so that related risks and costs are greatly reduced in the processes of production, storage, transportation, use and discarding; in addition, by adopting the kit disclosed by the invention, the operation steps can be effectively simplified, the operation difficulty is reduced, the repeatability of a dyeing result is remarkably improved, meanwhile, the kit is more friendly to the environment and operators, the cost is lower, and the kit has a better application prospect.

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 discloses a staining method for co-staining of three fibrous tissues, which includes the steps of successively using Victoria blue staining and Gordon-Sweets silver ammonia solution staining on the processed tissue sections; the staining method of the present invention combines Victoria blue staining and silver ammonia solution staining, and can clearly present the staining of three fibrous tissues on the same section, clearly show the relationship between the cell nucleus structure and elastic fibers, significantly improve the diagnostic accuracy of the degree of tumor invasion, reduce the demand for tissue samples, and the staining method of the present invention has the advantages of clear color contrast, rich levels, accurate positioning, simple operation, etc., and has important significance for clinical pathological diagnosis and is worthy of popularization and application.