48 results about "Cell tracking" patented technology

The invention relates to the technical field of cell detection and tracking, and discloses a cell multi-target tracking method, system and equipment, and the method comprises the steps: constructing a multi-cell video data set; and constructing an improved YOLOv5 target detection model, inputting the multi-cell video data set into the improved YOLOv5 target detection model for target detection to obtain a target detection result, and performing tracking processing on the target detection result in combination with a BoT-SORT algorithm to obtain a cell multi-target tracking result. According to the method, reliable input is provided for tracking by improving YOLOv5, optimizing cell feature extraction and improving low resolution and cell division scene detection precision, complete link optimization is formed through cooperation of a BoT-SORT algorithm, optimizing matching and trajectory management, and the cell tracking precision and efficiency are improved while real-time performance is guaranteed.

This invention provides a long-afterglow compound, system, preparation method, and application based on covalent bond coupling. The long-afterglow compound absorbs photons and transfers the absorbed photon energy within the molecule, undergoing a photochemical reaction that releases the energy as light, thus achieving afterglow luminescence. The structure of the long-afterglow compound is shown in Formula I, where X is selected from O or S; R is selected from a photosensitizer; and n is 1–15. The long-afterglow system includes a carrier medium and a long-afterglow compound, wherein the carrier medium is used to dissolve, disperse, or adsorb the long-afterglow compound. This invention can achieve near-infrared luminescence at 660 nm and 718 nm, and can be applied in fields such as bioimaging, immune detection, cell tracking, biosensing, and information encryption.

According to exemplary embodiments, a cell tracking controller can be provided. The cell tracking controller may comprise: a cell ID collection unit for collecting a cell ID, which is identification information of a battery cell; a data collection unit for collecting at least one from among inspection data of the battery cell, measurement data of the battery cell, and equipment data collected from equipment of a battery cell manufacturing process or an equipment controller for controlling the equipment; and a cell ID mapping unit for mapping, to the cell ID, at least one from among the inspection data, the measurement data, and the equipment data corresponding to the cell ID, wherein the cell ID collection, the data collection and the data mapping can be performed in real time.

A memory apparatus includes memory cells connected to word lines and configured to store a threshold voltage corresponding to data states. The memory cells are disposed in memory holes coupled to bit lines. A control means applies program pulses to selected ones of the word lines. The control means determines when the threshold voltage of each of the memory cells exceeds a lower verify level of one of the data states targeted and maintains a respective count of a number of the program pulses subsequently applied thereto before reaching a lockout state. Each of the program pulses is divided into phases. The control means sets a voltage of one of the bit lines coupled to each of the memory cells at a stepped up level as a function of the respective count and according to each of the phases in which the voltage is set to the stepped up level.

A cell tracking method, according to one embodiment of the present disclosure, may comprise the steps of: acquiring a cell ID corresponding to a semi-finished cell; acquiring a holder ID corresponding to a holder in which the semi-finished cell is disposed; and matching the cell ID with the holder ID.

The invention relates to the technical field of bioinformatics, and discloses a three-dimensional virtual myocardial cell reconstruction method, system, equipment and medium based on cell membrane boundary division, a multi-feature joint matching strategy is adopted, the cross-layer cell tracking accuracy is greatly improved, and the problem of trajectory breakage caused by large volume and multi-core characteristics of myocardial cells is solved; secondly, the data processing efficiency is remarkably improved through an automatic feature extraction model; moreover, three-dimensional integration of space transcriptome data and cell morphological characteristics is innovatively realized, an adult myocardial cell three-dimensional model containing gene expression information is constructed on a single cell level for the first time, and unprecedented spatial resolution is provided for researching a molecular mechanism of heart diseases. The method is suitable for myocardial cell research, the technical framework of the method can be expanded to three-dimensional reconstruction of other large-volume cells such as skeletal muscle cells, neurons and hepatocytes, and the method has wide scientific research and clinical application value.

The methods have application to the tissue culture of plant cells, ovules and microspores. Automated imaging, automated cell tracking and predictive modeling are used to develop methods that predict the likelihood that a plant cell will develop into a desired phenotype and / or which cellular reprogramming factors will assist in this development. The methods taught herein can also be used to evaluate the toxicity effects of compounds on plant cells, predict genotypic responses to tissue culture and cellular reprogramming factors, determine cell ploidy status, and predict other types of cell phenotype development.

A cell tracking method according to an embodiment of the present disclosure may comprise the steps of: detecting a semi-finished cell on a process line; generating a virtual ID of the semi-finished cell on the basis of the detection of the semi-finished cell; acquiring a cell ID of the semi-finished cell by detecting a code object formed on the semi-finished cell; and matching the virtual ID and the cell ID.

The present application relates to a suicide gene system and its use as part of immunotherapy. In some embodiments, the suicide gene system is expressed in a CAR T-cell, optionally along with armoring proteins. The present application also discloses uses of the suicide gene system, such as in cell tracking, immune regulation, rapid elimination of CAR T-cells, and as part of a therapeutic treatment.

The invention discloses a pathological section three-dimensional scanning system. The system comprises a cell pathological section double-plane full-automatic scanning subsystem, a double-plane reflection type digital holographic tomography module and a cell online real-time tracking analysis module. Wherein the cell pathological section double-plane full-automatic scanning subsystem is used for controlling synchronous imaging of the upper surface and the lower surface of a target section; the biplane reflection type digital holographic tomography module is used for performing multi-angle illumination on a target slice to obtain a multi-angle hologram, and further realizing unmarked three-dimensional imaging by adopting a three-dimensional reconstruction algorithm combining a physical model and a deep learning model to obtain a reconstructed high-resolution three-dimensional image; and the cell online real-time tracking analysis module realizes real-time analysis by using deep learning based on the intensity and transmission coefficient graph of the reconstructed high-resolution three-dimensional image, realizes colony area detection and cell type identification, and locates the spatial position of an abnormal cell. According to the invention, the overall efficiency and resolution of pathological section imaging are improved.

The invention discloses a cell tracking probe as well as a preparation method and application thereof. The retention time of the existing dye is relatively short (generally only several hours); the dye is not tolerant to fixation treatment, so that the dye leaks from cells, and the problem of efflux also exists; more seriously, the novel cell tracking and cell viability fluorescent dye has fluorescence, and aims to provide the novel cell tracking and cell viability fluorescent dye which is longer in retention time, does not need an additional cleaning step and is smaller in toxicity aiming at the technical problems existing in the existing main calcein orange red dye.

According to exemplary embodiments, a battery cell tester may be provided. The battery cell tester may be configured to: generate test data on the basis of a test signal of a battery cell; receive a cell ID of the battery cell; generate mapping data by mapping, to the cell ID, the test data corresponding to the cell ID; and transmit the mapping data to at least one upper server. According to exemplary embodiments, a cell tracking controller may be provided.

According to the iPS precursor cell intelligent capture and identification method and device, the electronic equipment and the storage medium provided by the invention, the cell segmentation model is trained according to the training set cell image, other data sets are predicted according to the cell segmentation model, the cells are tracked according to the prediction result, and the tracking video is generated according to the tracking result. The method comprises the steps of obtaining a tracking video, extracting cell classification features according to the tracking video, training an iPS precursor prediction classification model according to the cell classification features, and predicting and identifying iPS precursor cells according to the iPS precursor prediction classification model. Compared with other technologies only involving part of intermediate tasks, the method has the advantages that a more comprehensive and coherent solution can be provided, the high efficiency and accuracy of cell analysis are ensured, the requirement of manual intervention is reduced, and the stability and repeatability of the cell recognition and tracking process are improved.

According to an exemplary embodiment, a cell tracking data management method is provided. The method comprises the following steps that battery cell tracking data including unidentified roll core IDs and roll core IDs adjacent to the unidentified roll core IDs are loaded, the roll core IDs are used for distinguishing roll cores, and the roll cores are of a winding structure of a positive electrode, a negative electrode and a diaphragm; and recovering the unidentified roll core ID based on the roll core ID.

A cell tracking method according to one embodiment of the present disclosure may comprise the steps of: acquiring, on the basis of a first sub-process included in a secondary battery manufacturing process, an electrode ID corresponding to a unit electrode; acquiring, on the basis of a second sub-process included in the secondary battery manufacturing process, a cell ID corresponding to a semi-finished cell including the unit electrode; and matching the electrode ID and the cell ID.

The utility model relates to the technical field of light tracking and cleaning, in particular to a cleaning mechanism and a photovoltaic concentrating cell tracking device thereof, comprising: an accommodating assembly, which comprises a supporting member and a rotating member, the supporting member is arranged on a photovoltaic concentrating cell panel, and the rotating member is arranged on the supporting member; the cleaning assembly comprises a placing piece, a driving piece and an adjusting piece, the placing piece is arranged on the supporting piece, the driving piece is arranged on the placing piece, the adjusting piece is arranged on the placing piece, and the containing assembly and the cleaning assembly are matched with each other, so that the cleaning effect is improved. When the tracking system does not collect sunlight any more, dust or dewdrops attached to the photovoltaic light gathering plate can be removed, the influence on the transmittance of light is reduced, the influence on the photoelectric conversion efficiency of a cell panel is reduced, and efficient and stable operation under various environmental conditions is achieved under the supporting effect of the auxiliary assembly.

Compositions and methods are directed to a diverse library of barcoded constructs expressing biologies that are known to be challenging to express. A high throughput screening assay is also disclosed.

The application discloses a zebrafish cardiovascular function intelligent identification and evaluation method, which comprises the following steps: taking an image of a zebrafish under a microscope, inputting the preprocessed image into a trained zebrafish identification and classification model, filtering out zebrafish images that are not conducive to observation, obtaining a segmentation result of cells or tissues through a zebrafish cell and tissue segmentation model, obtaining information data of blood cell flow rate, heart rate and ejection fraction through a cell tracking algorithm and waveform analysis, and visualizing the cardiovascular function. The method can improve the efficiency of zebrafish experimental data analysis and processing, automatically screen appropriate image data from a large amount of images obtained through experiments, analyze and obtain information data of the cardiovascular function with research value, reduce manual operation, has a simple processing procedure, needs relatively few parameters to be adjusted, and provides strong technical support for zebrafish related research and development of complex cardiovascular disease drugs.

The invention discloses a sperm cell detection-based processing method and a storage medium, a microscope camera is used to shoot sperm to be detected at fixed time intervals, and an improved YOLO target detection model is used to carry out sperm cell detection, so that accurate detection of sperm cells is realized; according to the method, sperm cells are tracked by using a sperm cell tracking model, sperm cell information is recorded into a database, data support is provided for subsequent analysis, and a method for judging the motion trail and length of target sperm cells is established according to the sperm cell information database. According to the method, the number of the sperm frame images is set, the motion trail length corresponding to the number of the sperm frame images and the sperm cell activity degree judgment threshold value are set, the sperm activity degree can be objectively evaluated, a scientific basis is provided for sperm quality evaluation, the sperm quality can be efficiently and accurately evaluated, and important data support is provided for reproductive medicine research.

This invention relates to a method for the directional induction of iPSCs into notochord cells. By precisely simulating embryonic development signaling pathways and combining innovative cell tracking tools, it achieves precise navigation of the differentiation path from pluripotent state to notochord cells, thereby significantly improving the differentiation yield and purity of iNCs.

The subject matter disclosed herein is generally directed to methods and compositions for tagging cells of interest, tracking evolution of the tagged cells, and recovering the original tagged cells for further study. Specifically, cells are tagged with a DNA construct encoding a barcode sequence comprising a guide sequence. Barcoded cells can then be recovered using a reporter construct having CRISPR target sequences specific for the cell having a barcode of interest.

The disclosure concerns a polypeptide that comprises (a) a binding domain specific for histamine-succinyl-glycine (HSG) and (b) a membrane anchor that is capable of anchoring the binding domain in a plasma membrane. The disclosure also concerns a cell expressing the polypeptide of the disclosure of the surface. The disclosure further concerns a nucleic acid encoding the polypeptide of the disclosure, a vector comprising the nucleic acid, and a method for producing a cell of the disclosure. In addition, the disclosure concerns a method for treating a disease in an individual comprising administering the cell of the disclosure to the individual and a related medical use, a method of tracking the cell in vivo, and related medical uses.

The invention relates to the technical field of image processing, in particular to an image processing method for dynamically monitoring cell proliferation. The method comprises the steps that an original microscopic image is acquired and preprocessed, a structure three-channel tensor is constructed based on the preprocessed microscopic image, a disturbance mechanism driven by structure response is introduced, and a disturbance tensor of the preprocessed microscopic image is obtained; projecting the disturbance tensor of the preprocessed microscopic image to a combined space-frequency domain to obtain a multi-scale frequency response; superposing the multi-scale frequency responses to obtain a space-frequency joint image response; and performing brightness compression and edge smoothing on the space-frequency combined image response to obtain a reconstructed microscopic image, and performing cell tracking and behavior recognition to realize dynamic monitoring of cell proliferation. The problems that in the cell proliferation dynamic monitoring process, image processing is not accurate, cell tracking is prone to being interrupted in a complex scene, and behavior recognition capacity lacks time sequence dynamic modeling capacity are solved.

The present invention relates to a Cell‑SORT cell tracking method and device based on deep learning. In view of the difficulties in cell tracking, such as few target appearance features and low resolution, the optimal model YOLOv7‑X in the current mainstream target detection model YOLO series is selected as the cell detection model, and its feature fusion module is modified to propose a high-resolution YOLOv7‑X‑A cell detection model. In view of the challenges of obvious target deformation and complex and changeable background noise in cell tracking, based on the SORT data association architecture, an optimized Kalman filter (KF+) is adopted to better predict the position of the target, and a BYTE matching mechanism is introduced to match the target detection frame twice, and a trajectory interpolation post-processing method is introduced to fill the trajectory. Finally, the improved YOLOv7‑X‑A cell detection model is combined with the reconstructed SORT data association method to propose a Cell‑SORT cell tracking method based on deep learning to achieve cell tracking with strong robustness and higher accuracy.

A computer-implemented method is provided for label-free cell tracking. The method comprises: obtaining a first time-lapse sequence (50) of cells and a second time-lapse sequence (52) of the cells, wherein: the first time-lapse sequence (50) comprises fluorescence images of the cells, the second time-lapse sequence (52) comprises label-free images of the cells, the label-free images corresponding to the fluorescence images in the first time-lapse sequence (50), and each one of the fluorescence images in the first time-lapse sequence (50) is captured at a time point corresponding to a time point at which a corresponding one of the label-free images in the second time-lapse sequence (52) is captured; identifying, within each one of the fluorescence images in the first time-lapse sequence (50), positions of the cells; matching, using an object tracking algorithm, the identified positions of each one of the cells through time in the fluorescence images in the first time-lapse sequence (50); generating, based on the matching, annotations indicating movements of each one of the cells through time; and training a machine learning model (30) using the second time-lapse sequence (52) and the generated annotations, the machine learning model (30) being trained to track cells in an input time-lapse sequence including label-free images.

According to exemplary embodiments, a battery manufacturing system may be provided. The system may comprise: a cell tracking controller configured to collect a cell ID, which is identification information of a battery cell; a data collection device configured to collect high-frequency data generated according to the progress of a process for the battery cell; and a mapping device configured to map the high-frequency data corresponding to the cell ID to the cell ID.

The application belongs to the technical field of cell tracking, and in particular discloses a cell tracking method based on deep learning and an ant colony algorithm, wherein multiple cells are accurately detected in a deep learning manner, double determination of the ant colony algorithm and Kalman filtering avoids target loss caused by irregular movement of cells, and accurate determination is made on cells with complex behaviors. The ant colony algorithm cost formula adopted by the application comprehensively considers the centroid information and the contour information, so that not only the centroid coordinate position is considered when interframe matching is performed, but also the cell morphological information is considered, and more accurate tracking effect is achieved when the cell has complex behaviors; the target detection method based on yolov7 has a good detection effect on similar targets of different sizes by using a mosaic enhanced data enhancement method, and the performance is not reduced due to adjustment of the microscope magnification; the method combining yolov7 and U-Net enhances the visibility of the system.

A cell tracking method for performing cell tracking on the basis of a plurality of cell images captured in time series, including an extraction process of extracting a tracking region corresponding to the cell for each cell images; a tracking process of calculating a change information in a position of the extracted tracking region and tracking the cell on the basis of the change information; a determination process of determining whether or not the cell as a tracking target is in a cell division state on the basis of the cell image; and an analysis process of analyzing a movement state of the cell on the basis of the change information from which the change information in a period of the cell division state is excluded when the cell is determined to be in the cell division state in the determination process.