16 results about "Sperm morphology" patented technology

1. Name of the product in this design: Sperm Quality Analyzer. 2. Purpose of this design: The product is intended for use by research institutions and medical institutions for sperm concentration detection, motility analysis, sperm morphology identification, and determination of semen pH and DNA fragmentation rate in semen samples. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D rendering 2.

This invention proposes a sperm staining kit based on a sequential staining strategy of tail pre-staining – rapid differentiation – enhanced nuclear staining. A gentle fixation with 4% paraformaldehyde and acetate buffer preserves the complete nucleic acid of the sperm head and the protein structure of the tail. The addition of PVP K30 and Tween-20 effectively inhibits non-specific adsorption and reduces staining background interference. Brilliant Green SF combined with sodium tartrate is used for specific staining of the sperm tail, followed by rapid differentiation to wash away non-specific staining. Nuclear staining is performed using toluidine blue O combined with sodium chloride and sodium tetraborate hydrate, specifically binding to DNA and enhancing color development stability, resulting in a blue sperm head and a light green tail with clear color contrast. This invention produces a clean staining background, accurately distinguishing the morphology of the sperm head, acrosome, and tail, significantly improving the accuracy of microscopic identification of abnormal sperm such as large-headed, small-headed, curled-tailed, broken-tailed, and short-tailed sperm. It is suitable for detecting sperm morphology and abnormality rates in breeding males.

The application provides a general single-stage sperm morphology image segmentation method and system, which comprises the following steps: obtaining a stained or unstained sperm microscopic image; inputting the sperm microscopic image into a single-stage segmentation network model, outputting a domain robust shared feature map through multi-view transformation and adaptive fusion; after multi-scale feature extraction and aggregation, a prediction head is used to output a semantic segmentation and / or instance-aware component segmentation result in parallel; tail skeleton features are extracted and topological optimization is performed based on a continuity constraint loss to maintain tail connectivity. The application enhances the cross-domain generalization capability by structure-appearance decoupling, and uses topological-aware learning to constrain the tail continuity, thereby solving the problems of weak generalization between stained and unstained images and tail segmentation fracture in high-density overlapping scenes in the prior art, and improving the clinical applicability and segmentation integrity.

The application relates to the technical field of sperm morphology analysis, and discloses a sperm morphology analysis method based on deep learning, which comprises the following operation steps: S1, preparing and dividing a data set, collecting sperm data of 85 male participants, for each participant, parameters of standard semen analysis, a video of living sperm, sperm fatty acid, a fatty acid composition of serum phospholipid, demographic data and WHO analysis data can be obtained, 60% of the data set is used for training, 20% is used as a verification set, and 20% is used as a test set; a 3-fold verification method is used; and the data set is expanded to prevent overfitting. The sperm morphology analysis method based on deep learning directly extracts time information and space information of sperm video by using a 3D convolutional neural network, realizes high-precision end-to-end sperm activity prediction, secondly, a deep separable convolution is used to replace ordinary convolution, the parameters of the convolutional network are reduced, and the calculation efficiency is improved.

The present invention relates to sperm image processing technology. Disclosed are a human sperm image color block impurity removal method, and an apparatus. The method comprises: acquiring a sperm image processed with a staining reagent; using a pre-trained instance segmentation model to perform segmentation processing on sperm heads, acrosome regions, and acrosome posterior regions in the sperm image, and performing post-processing, matching and assembling on segmentation results to obtain segmentation and identification information of all individual independent sperms in the image; and searching for color block impurities in segmentation and identification results, and deleting same, so as to obtain sperm segmentation results having no color block impurities. The method of the present invention has the advantages of simplicity and good operation effect, and is very suitable for practical use in industrial scenarios. In addition, by means of the method for filtering color block impurities, color block impurities of sperms segmented and recognized in a sperm image can be accurately and effectively deleted, and final sperm image segmentation and recognition results have no color block impurities, thereby improving the accuracy of computer-assisted sperm morphology analysis.

The invention provides an assisted reproduction IVF outcome prediction model based on an LSTM and LSTM-CNN fusion architecture and a construction method, and is applied to the field of data processing. The method comprises the following steps: acquiring assisted reproduction clinical layering core data (including IVF period original data and divided into conventional fertilization IVF and ICSI fertilization IVF according to a fertilization mode), key parameters (including sperm motility and the like in conventional IVF and additional sperm morphological images in ICSI) and target patient information; preprocessing the data, carrying out feature engineering, and generating multi-modal feature vectors adaptive to the two fertilization modes; then, an optimization prediction model is constructed, and an initial model and performance evaluation information are obtained; iteratively optimizing the model, introducing a new module to improve the multi-modal learning ability, and generating an SOTA level model through multi-index evaluation; and finally, processing target patient information by using the model, and outputting a personalized prediction reference scheme and clinical application value analysis information.

The invention discloses a method for detecting sperm morphological anomaly through an improved Pasteur staining method, and relates to the technical field of morphological analysis, and the method comprises the following steps: carrying out staining treatment on a sperm smear by using the improved Pasteur staining method to obtain a training data set and a test data set; based on a U-Net network, designing a convolutional neural network VCA-Net applied to sperm morphological anomaly detection; based on the training data set and the test data set, performing model training and testing on the designed convolutional neural network VCA-Net to obtain a final convolutional neural network VCA-Net; and evaluating the final convolutional neural network VCA-Net by using the evaluation index to complete the anomaly detection of the sperm morphology by the improved Pasteur staining method. The problems that in the prior art, SMA automatic detection is difficult to achieve, and manual detection consumes time and labor and is large in workload and high in subjectivity under existing microscopic imaging are solved.

The utility model relates to the field of sperm flaking equipment, in particular to a sperm morphology flaking machine, which comprises a pipetting driving device, a pipettor, a first moving device, an overturning mechanism, a liquid conveying mechanism and a hot air gun, the first moving device is matched to drive the pipettor to move so as to achieve the purpose of transferring a semen sample; the turnover mechanism is used for driving the filter cup to turn over, the filter cup is turned over after sperms are filtered out by the filter cup, the filtered sperms are scoured into the sample cup in cooperation with the infusion mechanism, the sperms are diluted, and flaking is facilitated; the first moving device drives the hot air gun to move, so that an air outlet of the hot air gun is aligned with a liquid inlet in the flaking device, and the hot air gun is started to accelerate flaking; through the mutual cooperation of the devices and the mechanisms, the problems of long sheet making time and relatively tedious process when a sample sheet is made at present are solved.

This invention provides the application of FAM205A in the preparation of a male infertility detection kit, detecting FAM205A gene abnormalities and / or abnormal FAM205A protein expression levels. By integrating proteomics analysis, functional validation, and a gene knockout mouse model, this invention demonstrates that FAM205A deficiency disrupts sperm morphology, spermatogenesis, motility, and fertilization capacity through a dual mechanism, making FAM205A a reliable diagnostic biomarker for idiopathic male infertility. FAM205A gene abnormalities can be detected through whole-genome sequencing, and abnormal FAM205A protein expression levels can be detected using antibodies that specifically bind to the FAM205A protein, leading to the development of a male infertility detection kit.

The present application relates to the field of biomedical detection reagent manufacturing and reproductive medicine technology, and particularly relates to a fluorescently labeled kit and method for evaluating sperm function and fertilization potential. The present application prepares a high-titer rabbit-derived monoclonal antibody combination capable of specifically recognizing and binding to key proteins such as DEFB126 highly related to the quality of embryo development in human sperm; the antibody is assembled with a fluorescently labeled secondary antibody, a nuclear dye, a concentrated washing solution, a mounting agent, a fixing agent, and a multi-well glass slide into a special detection kit. The kit can be used with a fluorescence microscope, an ordinary optical microscope, and image analysis software to achieve precise and quantitative analysis of the expression level and subcellular localization of key proteins such as DEFB126 and CATSPER2 in sperm, while being compatible with traditional sperm morphology and kinematic analysis, thereby providing an integrated molecular detection solution for sperm quality screening and embryo development potential prediction in assisted reproductive technology.

The present application relates to the technical field of in vitro detection, in particular to a rapid sperm morphology staining reagent and a staining method thereof; the rapid sperm morphology staining reagent of the present application can make semen spread rapidly and uniformly after 5 minutes by using bromelain and L-cysteine in combination. The staining reagent of the present application greatly shortens the pretreatment time of the sample and improves the detection efficiency.

The utility model relates to the technical field of sperm flaking, in particular to a sperm morphology observation flaking device which comprises a liquid inlet frame, a water absorption pad and a glass slide, mixed liquid composed of diluent and sperm can enter from a liquid inlet of the liquid inlet frame, sequentially passes through a second cavity and a water absorption hole and finally flows onto the glass slide, and the mixed liquid is separated from the liquid inlet frame. The mixed liquid slowly diffuses towards the periphery of the glass slide, meanwhile, the water absorption pad on the glass slide continuously absorbs liquid in the mixed liquid, sperms remain after the liquid is absorbed, and the sperms are dispersed and distributed on the glass slide at the moment, so that not only is rapid slide preparation realized, but also the sperms are hardly damaged in the slide preparation process; the problem that the sperms are damaged in the existing tabletting process is solved, and the real abnormal rate of the sperms can be reflected more accurately.

The present application relates to the field of biomedical detection reagent manufacturing and reproductive medicine technology, and particularly relates to a key protein kit for embryo development potential sperm and a use method thereof. The method is characterized in that a combination of antibodies capable of specifically recognizing a group of key proteins related to embryo development potential in human sperm is prepared, and the antibodies are assembled into a special detection kit together with a fluorescently labeled secondary antibody, a nuclear dye, a concentrated washing solution, a mounting agent and a pre-coated control multi-well slide. The kit can be used with a multi-modal imaging system (such as a fluorescence / confocal microscope, an ordinary optical microscope) and image analysis software to realize traditional analysis of sperm morphology and motility, and synchronous and accurate qualitative and quantitative analysis of the expression level and subcellular localization of the key proteins. The present application provides an integrated molecular detection solution, and provides a powerful tool for sperm quality screening and embryo development potential prediction in assisted reproductive technology.

The invention relates to a live pig sperm morphology intelligent identification method and system based on an improved YOLOv8 model, and the method comprises the following steps: collecting a boar sperm image sample, and marking the sperm image sample; preprocessing the labeled image data, uniformly formatting the image and a labeled file, converting the image and the labeled file into a labeled file in a YOLO format, and generating a training set and a verification set; an improved YOLOv8 target detection model is adopted, and on the basis of a YOLOv8m version, the annotation data are trained; in a sperm morphology detection task, a recall rate and mAP (at) 0.5 are used as evaluation indexes, a sperm target can be rapidly detected in an image through a YOLOv8 model obtained through training, and different sperm morphologies can be accurately identified; according to the intelligent identification method and system for the sperm morphology of the live pig based on the improved YOLOv8 model, large-scale sperm samples can be automatically processed through an efficient image identification and analysis technology, errors caused by manual operation are reduced, and the accuracy and consistency of detection are improved.

The invention relates to the technical field of biomedicine detection reagent manufacturing and reproductive medicine, in particular to a fluorescence labeling kit and method for evaluating sperm function and fertilization potential. According to the invention, a high-titer rabbit monoclonal antibody combination capable of specifically recognizing and combining key protein DEFB126 and the like which are highly related to embryonic development quality in human sperms is prepared; and assembling the antibody, a fluorescence labeled secondary antibody, a cell nucleus dye, a concentrated washing liquid, a mounting medium, a fixing agent and a porous glass slide into the special detection kit. The kit can be combined with a fluorescence microscope, a common optical microscope and image analysis software to realize accurate and quantitative analysis of expression levels and subcellular localization of DEFB126, CATSPER2 and other key proteins in sperms, and is compatible with traditional sperm morphology and kinematics analysis. An integrated molecular detection solution is provided for sperm quality screening and embryonic development potential prediction in an assisted reproduction technology.

The invention relates to the technical field of biology, and discloses a sperm morphological analysis method and system based on visual enhancement and knowledge reasoning, and the method comprises the steps: obtaining a sperm microscopic image, extracting a global feature map and generating a candidate region through a sperm region detection and feature extraction module, extracting independent features, and obtaining a sperm microscopic image; the visual relation enhancement module constructs a visual relation matrix to capture recessive relevance between candidate areas, and generates enhanced features through neighborhood feature weighted fusion; the knowledge guidance analysis module performs semantic reasoning on enhanced features in combination with visual features and a knowledge graph based on sperm morphology, performs reasoning on attribute categories, and optimizes reasoning results through a neighborhood propagation mechanism to obtain semantic attribute features; and the refined classification module of the fusion features performs global form classification and fine-grained attribute classification of each sperm part on the sperm instances according to the enhanced features and the semantic attribute features. According to the method, overlapped sperms in a complex background can be processed, and the capability of analyzing and explaining sperm morphology is improved.