37 results about "Blood smear" patented technology

The invention discloses a multispectral microscope blood cell automatic classification and counting system. The system is composed of a multispectral illumination and microscopic imaging module, a spectrum and geometric calibration module, a multispectral preprocessing and cell segmentation module, a multispectral discrimination index and spectral band weight adaptive updating module, a cell graph structure classification module, a man-machine interaction module, an online adaptive learning module and the like. The method comprises the following steps: acquiring a blood smear image by a system under a narrow-band multi-spectrum condition, constructing cellular spectrum-morphological characteristics by combining a multi-scale segmentation result after noise suppression, flat field correction and background deduction, generating a discrimination index with a self-adaptive spectrum band weight, and completing joint classification and counting on a cell map; and meanwhile, carrying out constrained increment updating on the spectral band weight and the classification model by utilizing an artificial correction result of the low-confidence-coefficient cells. Compared with a traditional single-channel microscopic imaging and static classification method, the method has higher classification accuracy and counting stability under different dyeing and imaging conditions, and the workload of manual recheck can be reduced.

The present application relates to the technical field of physical analysis, in particular to a blood smear quality intelligent detection method for clinical laboratory, comprising the following steps: extracting pixel direction and building path block, marking turning connection point as contour chain, splicing boundary to generate closed area, extracting gray gradient to label structure change, matching contour to judge offset overlap, extracting channel barycenter to compare axial difference, and positioning direction abnormal area to generate detection scheme. In the present application, the structural bending points in the image are recognized and the continuous path is constructed, the spatial expression of the shape turning area is enhanced, the accuracy of the closed boundary is improved by combining the edge head-tail coordination judgment, the structure partition identification is constructed relying on the gray gradient and the direction difference, the classification labeling of the structure disturbance area is carried out, the abnormal area is integrated based on the spatial overlap and the direction consistency, the color axial difference is judged by the channel barycenter offset, the comprehensive recognition ability for the shape variation, the boundary offset and the dyeing abnormality is improved, and the multi-dimensional intelligent judgment of the image quality is realized.

The present invention relates to a computer-implemented method for producing a trained model for detecting one or more defined cell types and / or cellular indicators, such as biomarkers or cellular abnormalities, in particular genomic aberrations, from single-cell images obtained from a sample of a body liquid, bone marrow, cytology smear or slide preparations, in particular a blood smear sample. It relates also to a computer-implemented method for detecting one or more defined cell types and / or cellular indicators, such as biomarkers or cellular abnormalities, in particular genomic aberrations, from single-cell images obtained from a sample of a body liquid, bone marrow or cytology smear, in particular a blood smear sample.

The application relates to a blood slice sample pretreatment device, which comprises a box body, a punching and liquid distribution assembly, a sample suction and drying assembly, an oscillator, a first reagent pump, a second reagent pump and a nitrogen generation assembly; the box body is connected with the nitrogen generation assembly; the punching and liquid distribution assembly, the sample suction and drying assembly, the first reagent pump and the second reagent pump are arranged in the box body; the punching and liquid distribution assembly is connected with the first reagent pump; the sample suction and drying assembly is connected with the second reagent pump; the oscillator is arranged on the punching and liquid distribution assembly and the sample suction and drying assembly. The application can realize batch punching and batch liquid adding at the same time, the box body can complete different functions in different areas, different areas can be used simultaneously or separately, different functions can be completed, personnel intervention can be reduced, errors can be reduced, and manpower can be saved.

The utility model discloses a blood cell smear auxiliary device. The blood cell smear auxiliary device comprises a blood filling pool and an adjusting part, the blood filling pool is provided with a containing groove used for containing blood, the groove bottom face of the containing groove is opened to be used for being matched with a glass slide, and the adjusting part comprises a first adjusting piece and a second adjusting piece. The first adjusting piece and the second adjusting piece are oppositely arranged in the blood filling pool, and the first adjusting piece and the second adjusting piece can move so as to adjust the volume of the containing groove. According to the blood cell smear auxiliary device, the preparation efficiency and quality of the blood smear can be remarkably improved, and a more reliable sample is provided for hematological examination, so that the accuracy and efficiency of medical diagnosis are promoted.

This invention relates to a sialylated glycoprotein detection reagent, its preparation method, and its application, belonging to the field of biodetection technology. The detection reagent uses purified water as a solvent and comprises the following components: surface-modified titanium dioxide nanomaterials, metal ions, a pH adjuster, and a solvent. The surface-modified titanium dioxide nanomaterials are obtained by dispersing titanium dioxide nanoparticles in an organic solvent and reacting them with a silane coupling agent. The pH value of the sialylated glycoprotein detection reagent is ≥ 8.0. The reagent of this invention utilizes the high affinity of modified titanium dioxide nanomaterials for sialic acid to specifically aggregate sialylated glycoproteins in blood into particles, facilitating observation. This reagent exhibits good stability, high sensitivity, and strong specificity, making it suitable for rapid tumor screening of blood smear samples.

The present invention pertains to the computer implemented method for identifying a microorganism in a blood comprising: receiving (101) a microscopic image of a blood smear; detecting (102) plurality of microorganism cells in the microscopic image using a deep learning cellular segmentation model; extracting (103) from the segmented microscopic image a patch of size HxW centred around a centroid of the detected microorganism cell for each detected microorganism cell; encoding (104) of each patch by a deep neural network encoding model into a patch representation vector u n of size 1×D; aggregating (105) the patch representation vectors un using a pooling method to generate a sample representation vector u of size 1×D; and indicating (106) a species of microorganism present in the microscopic image by classifying the sample representation vector u by a neural network classifier to class representing specific species. In another aspect the invention relates to the data processing system for carrying out the steps of the method according to the invention.

This invention relates to a constant-temperature blood smear drying device, comprising a housing, a fan, a heater, a temperature sensor, and a constant-temperature control module. The housing contains a sealed drying chamber with an open top. A slide holder is placed at the top opening of the housing, and slides are mounted on the slide holder. The fan is positioned on one side of the upper part of the housing, and the heater is located at the fan's outlet. The temperature sensor is installed outside the housing and extends into the drying chamber to collect the measured temperature in real time. The constant-temperature control module dynamically adjusts the heater power and fan speed based on the difference ΔT between the set target temperature and the measured temperature within the drying chamber, thereby correcting the set target temperature within the drying chamber. The beneficial effects of this invention are: 1. Solving temperature unevenness; 2. Cell protection; 3. Reduced power consumption.

According to the automatic detection method and device for the blood cells in the blood smear image, a local teacher model and an external teacher model are combined to generate high-quality pseudo labels for original extremely sparse labeled data, the models are guided to learn a complete foreground concept, and the problem of a large amount of missing detection caused by insufficient labeling is effectively relieved; the text feature of the blood cell category name is used as a domain invariant anchor point, a detector is guided to generate visual representation with strong generalization, and excellent generalization performance is achieved in multiple visual domains; inter-text comparative learning and inter-visual comparative learning are introduced to promote clearer alignment between text features and visual features from multiple dimensions, and generalization is improved while discrimination is guaranteed.

The application discloses a blood pushing machine and method. The blood pushing machine comprises a pushing device, an image processing device and a dyeing device. The pushing device is used for pushing and processing a sample to be detected on a blood smear to form a blood film sample on the blood smear. The image processing device is used for acquiring a detection image of the blood film sample and determining whether the blood smear meets a qualified condition based on the detection image. The dyeing device is used for dyeing and processing the blood film sample on the blood smear meeting the qualified condition. Through the above implementation, whether the blood smear meets the qualified condition is determined based on the detection image, and then the dyeing device only dyes and processes the blood film sample meeting the qualified condition, so that the quality of the blood film is greatly improved, and the problem of low microscopic examination efficiency caused by unqualified smears is solved.

The application discloses a blood smear white blood cell classification counting method and system based on image analysis, and belongs to the technical field of medical image processing. The method comprises the following steps: after collecting a peripheral blood smear image, performing adaptive background correction and color standardization pretreatment; detecting and segmenting each white blood cell through an instance segmentation network; extracting three-dimensional features of nuclear morphology, cytoplasmic staining and nuclear-cytoplasmic ratio and adaptively fusing; adopting a cascade classifier to perform five-class white blood cell classification and abnormal morphology identification; and counting and labeling suspected abnormal cells for review. The classification coincidence rate of the application reaches more than 95%, can effectively identify abnormal morphologies such as atypical lymphocytes, immature cells and toxic granules, and provides technical support for blood tests at the grassroots level.

The present invention relates to a computer-implemented method for producing a trained model for detecting one or more defined cell types and / or cellular indicators, such as biomarkers or cellular abnormalities, in particular genomic aberrations, from single-cell images obtained from a sample of a body liquid, bone marrow, cytology smear or slide preparations, in particular a blood smear sample. It relates also to a computer-implemented method for classifying a sample of a body liquid, bone marrow or cytology smear, in particular a blood smear sample, as indicative or non-indicative of one or more defined cell types and / or cellular indicators, such as biomarkers or cellular abnormalities, in particular genomic aberrations, from single-cell images obtained from the sample.

The invention provides a deep learning-based blood smear whole red blood cell abnormal morphology evaluation system. The system comprises a dual classification module, a fitting comparison module and an evaluation output module, the method comprises the following steps: collecting a blood smear full-slide image containing various erythrocyte morphological abnormality lesion features, carrying out classification labeling on the image, constructing an abnormal erythrocyte database, realizing double classification of erythrocytes by utilizing a deep convolutional neural network combined with a multi-feature extraction algorithm, and carrying out fitting comparison on double classification results. And generating a comprehensive full-slide blood smear erythrocyte abnormality assessment report. The innovation of the invention lies in that a set of complete deep learning detection process is constructed, through deep learning and multi-feature fusion, the accuracy and interpretability of abnormal red blood cell recognition are significantly improved, accurate evaluation of abnormal red blood cell classification under the full-slide scale is realized, and an objective quantitative evaluation basis is provided for clinical diagnosis.

The utility model belongs to the technical field of medical tools, and particularly relates to an angle-fixed smear pushing plate for blood smear manufacturing, which comprises a U-shaped operation frame, sliding grooves are symmetrically arranged on the inner walls of two sides of the U-shaped operation frame, a clamping groove is arranged on the bottom surface of the inner wall of the U-shaped operation frame, a supporting plate is inserted into the inner sides of the sliding grooves, and the supporting plate is connected with the U-shaped operation frame. An inclined flat barrel is inserted into one side of the supporting plate, a scraping plate penetrates through the inner side of the inclined flat barrel, and a glass slide is clamped to the inner side of a clamping groove. The glass slide is clamped on the inner side of the operation frame, blood drops on the right side of the top face of the glass slide, then the scraping plate is inserted into the inner side of the flat barrel, the flat barrel is moved to make the scraping plate make contact with the blood, then an operator pushes the flat barrel at a constant speed, the scraping plate can scrape the blood drops evenly, the angle of the scraping plate is fixed, and manual operation errors are eliminated; and meanwhile, experience dependence is reduced, the training period is shortened, the success rate of one-time smear is high, and in addition, the whole tool is simple in structure and low in use cost.

The invention relates to the field of intelligent medical treatment, and discloses a pathological recognition analysis method and system based on a blood detection sample. The method comprises the following steps: acquiring a blood smear microscopic image and extracting a cell contour; performing texture analysis on the interior of the contour to obtain morphological characteristics; judging a potential abnormal region based on the features; carrying out local enhancement on the abnormal region and extracting subtle difference features; based on the difference features, obtaining quantitative pathological descriptors through a deep learning model; identifying abnormal cells according to a matching result of the descriptors and the feature library; and comprehensively analyzing according to an identification result to obtain pathological quantitative indexes. Through a mode of combining local enhancement, a deep learning model and feature library matching, the problems of low blood smear abnormal cell recognition precision and poor efficiency are solved, and the accuracy and automation level of pathological analysis are improved.

A method for detecting a single layer of red blood cells (RBCs) in a blood smear or a small section of a blood smear that is suitable for diagnosis. The method comprises: determining the coverage of RBCs in a blood smear; determining the hemoglobin distribution; determining the presence of non-RBC cells and / or abnormal RBCs; and assigning a label of diagnostic usability to the blood smear or a small section of a blood smear.

The invention discloses a blood routine examination system based on a health cloud platform, which belongs to the technical field of blood detection and specifically comprises a sample imaging module, an interstitial feature analysis module, a correction coefficient generation module, a multi-scale feature reconstruction module, a parameter generation module and a parameter correction module. The method comprises the following steps: performing intercellular substance background analysis on a blood smear image, extracting texture features and optical characteristic features, establishing an intercellular substance background interference model to generate an interference level and a parameter correction coefficient, and recovering covered blood cell features by using a multi-scale feature reconstruction technology. Completing blood cell classification identification and parameter calculation based on the reconstructed features, and finally generating an accurate blood routine examination report through interference contribution degree analysis and parameter correction. The problem of detection errors caused by intercellular substance background interference is effectively solved, and the accuracy and reliability of blood routine examination are remarkably improved.

The application discloses a reticulocyte identification and grading system based on blood smears, and particularly relates to the field of medical cell morphology inspection, and comprises an image acquisition module, a staining normalization module, an instance segmentation module, an erythrocyte classification module, a reticulocyte grading module and a statistical output module; the image acquisition module: adopts an automatic microscope platform to continuously scan blood smears under a 100-fold field of view, collects high-quality bright field channel images through automatic focusing technology, and monitors image definition, contrast and illumination uniformity; the statistical output module: calculates the proportion of reticulocytes at all levels and blue-purple intensity statistics, and generates visual quality control results and diagnosis reports; the application realizes full-automatic processing from samples to reports, takes into account interpretability and high classification accuracy, significantly reduces subjective differences and missed detection rates of manual microscopy, and improves the efficiency and consistency of clinical detection.

A sample analysis system (100) and a precision management method thereof can automatically select a quality control sample after the sample analysis system (100) starts a sample test, prepare the quality control sample into a quality control blood smear, then a cell image analysis device (130) photographs and analyzes the quality control blood smear to obtain a detection result based on image photographing and analysis, compares the detection result of the cell image analysis device (130) with a detection result of a blood analyzer (110), and outputs a comparison result, thereby automatically completing precision management of the cell image analysis device (130) or the blood analyzer (110).

The utility model provides a slide dyeing device. The slide dyeing device comprises a dyeing tank assembly, a flushing tank assembly, a drying tank assembly, a first supporting stand column, a second supporting stand column, a transfer assembly fixing plate and guide rail, a first slide transfer assembly, a second slide transfer assembly, a dye filling assembly fixing plate and guide rail, a dye filling assembly and a filling needle 1A. The dyeing tank is fixed through the attraction force of the magnets and is convenient to replace; overflow ports are formed in the dyeing tank and the flushing tank, so that redundant dye liquor can be discharged in time when excessive reagents are injected, and the dye liquor is prevented from leaking; a liquid outlet of the flushing tank wraps the periphery of the slide, so that each surface of the slide can be flushed, and residual dye on the slide can be completely flushed away; two sets of slide transfer assemblies are adopted, so that the slide transfer efficiency can be improved, and the blood smear staining flux can be improved; the air flow completely flows through the surface of the slide through the drying groove, so that the slide drying time is shortened; the dye filling needle is used for adding dye, so that part of liquid paths are saved.

Provided are a method and a device for determining a region of interest of a blood smear slide, the method comprising the steps of: acquiring a plurality of patch images for the blood smear slide; acquiring cell information related to one or more cells included in the respective patch images; acquiring feature information related to the respective patch images on the basis of the cell information; acquiring a plurality of scores corresponding to the respective patch images on the basis of the feature information; selecting a target patch image from among the plurality of patch images on the basis of the plurality of scores; and determining the region of interest including the target patch image.

This invention discloses a blood smear image classification method and system based on knowledge distillation and graph neural networks. The method includes: acquiring a training dataset, preprocessing it to obtain a training feature matrix; inputting the training feature matrix into a pre-trained teacher model to output teacher features and teacher prediction results; inputting the training feature matrix into a student model to output student features and student prediction results; calculating feature distillation loss, classification loss, and temporal consistency loss to generate a student model loss and optimize the student model; when a blood smear image to be processed and the examination period are acquired, preprocessing is performed and the image is input into the trained student model to output classification results. This invention reduces the training difficulty through knowledge distillation, thereby improving the stability and effectiveness of blood smear image processing results, and can be deployed even in resource-limited environments, improving the practicality of the model.

1. The name of the design product: pusher. 2. The use of the design product: the design is used for pushing blood smear or other body fluid smear. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: perspective view.

This invention provides a cell analysis device and method that acquires digital images of cells in a sample and images that characterize the appearance of the sample; and outputs and displays the digital images of cells in the sample and images that characterize the appearance of the sample. This allows users to conveniently monitor the working status of the cell analysis device and observe whether the appearance of blood smears is normal.

Provided are a method and a device, the method comprising the steps of: acquiring a plurality of patch images of a blood smear slide; acquiring cell information regarding one or more cells included in each of the plurality of patch images; acquiring feature information for the plurality of patch images on the basis of the cell information; acquiring red blood cell information for the blood smear slide on the basis of the feature information; providing the red blood cell information; performing staining on the blood smear slide; and performing analysis using the stained blood smear slide.

The utility model discloses a slide for manufacturing malaria blood slides, which relates to the technical field of medical equipment and comprises a glass slide, a slide pushing piece and a slide pushing piece mounting device. Marking grid lines are arranged at the positions, corresponding to the thick blood film circular groove and the thin blood film preparation area, of the back face of the glass slide respectively, the slide glass installation device comprises an installation frame, angle adjusters, a sliding block and a slide glass clamping device, the two ends of the installation frame are each connected with one angle adjuster, and the angle adjusters are connected with the sliding block. Each angle adjuster is connected with one sliding block, the two sliding blocks are arranged at the two ends of the glass slide in a sliding mode respectively, and the glass pushing slide clamping device is arranged on the mounting frame and used for clamping and fixing the glass pushing slide. The device is suitable for manufacturing malaria blood smears, positioning and marking are convenient, and the manufacturing quality of the blood smears is improved.

The utility model provides a blood smear manufacturing device which comprises a slide guide rail fixing plate, a push piece moving assembly connected to one side of the slide guide rail fixing plate, a slide moving assembly movably connected to the slide guide rail fixing plate, a push piece movably connected to the push piece moving assembly and a slide placed above the slide moving assembly. The push piece is located above the slide, the push piece moving assembly drives the push piece to move up and down, and the slide moving assembly drives the slide to move in the transverse direction. When the pushing piece descends to make contact with the surface of the slide and continues to descend, the pushing piece can rotate along the rotating shaft, meanwhile, under the action of the torsional spring, the pushing piece is tightly pressed on the slide, the included angle between the pushing piece and the slide is changed through the descending height to conduct smearing action, and the pushing piece balance fixing frame can also rotate around the shaft. The contact line of the push piece and the slide can also rotate around the shaft, so that when the push piece or the slide is not horizontal due to assembly or processing precision, adaptive correction can be carried out, and the contact line of the push piece is tightly attached to the surface of the slide.

This invention provides a deep learning-based system for evaluating abnormal erythrocyte morphology in whole-slide blood smears. The system includes a dual classification module, a fitting and comparison module, and an evaluation output module. It acquires whole-slide images of blood smears containing various abnormal erythrocyte morphological features, classifies and labels the images, constructs an abnormal erythrocyte database, and uses a deep convolutional neural network combined with a multi-feature extraction algorithm to achieve dual classification of erythrocytes. The dual classification results are then fitted and compared to generate a comprehensive evaluation report of abnormal erythrocyte morphology in the whole-slide blood smear. The innovation of this invention lies in constructing a complete deep learning detection workflow. Through deep learning and multi-feature fusion, it significantly improves the accuracy and interpretability of abnormal erythrocyte identification, achieving accurate evaluation of abnormal erythrocyte classification at the whole-slide scale, and providing objective quantitative evaluation basis for clinical diagnosis.

This invention relates to an automated smear staining device and method for using avian blood samples. The smear staining device includes a base, a working platform, a slide positioning structure, a screw-slide mechanism, a slide pushing component, a heating component, an ultrasonic ceramic transducer, a rotary dispensing component, a staining solution bottle, a rotary servo motor, a micro peristaltic pump, and a control system. The slide pushing component holds a standard glass slide as the slide pusher and, driven by the screw-slide mechanism, completes the spreading and film formation of the blood sample. The rotary dispensing component, driven by the staining rotary servo motor, rotates from a standby position to a working position to quantitatively add staining solution to the slide. The heating component is used for the initial drying of the blood smear and the subsequent drying after staining. The ultrasonic ceramic transducer assists in the spreading of the staining solution. This invention can improve the consistency and continuity of on-site smear preparation and staining of avian blood samples.

This application proposes an automatic detection method and device for blood cells in blood smear images. It combines a local teacher model and an external teacher model to generate high-quality pseudo-labels for the originally extremely sparse labeled data, guiding the model to learn complete foreground concepts and effectively alleviating the problem of a large number of missed detections caused by insufficient labeling. It uses the text features of blood cell category names as domain-invariant anchors to guide the detector to generate visual representations with strong generalization, achieving excellent generalization performance in multiple visual domains. It introduces inter-text contrastive learning and inter-visual contrastive learning to promote clearer alignment between text features and visual features from multiple dimensions, improving generalization while ensuring discriminability.