亚洲精品无码乱码成人91,丰满放荡岳乱妇91wW,亚洲精品国产成人综合久久久久久久久,成人精品鲁一鲁一区二区

Scan QR code and follow us: Gaofen (Beijing)
Close
location：Home-Support-Living Cell Imaging Analysis System-EOS Unlabeled cell segmentation ONE BY ONE
EOS Unlabeled cell segmentation ONE BY ONE
As the most fundamental life activity of cells, cell proliferation detection techniques are widely applied in research fields such as molecular biology, tumor biology, stem cell research, pharmacology, and pharmacokinetics. These techniques provide important data for exploring the rule of cell life activities, the pathogenesis of diseases, disease diagnosis, and treatment. The EOS Long-term Cell Imaging Workstation owns label-free cell proliferation classification application , which solves the pain points in the measurement process. The cell growth curve was formed based on image data. Coupled with a deeply trained AI neural network algorithm model, it can accurately classify various types of cells. It supports whole-well/area capture of 6- to 384-well plates, minimizing human hand to the greatest extent and enabling quantitative analysis of the entire process of cell proliferation.
Manual Introduction

A neat and smooth workflow


The independent EOS application app is easy to use. The capture view, cycle, and  objectives(4x, 10x, 20x, with 40x expansion supported) can all be set on the software without the  need for manual adjustment. After the settings are completed, the instrument automatically  collects images. The deeply trained AI neural network algorithm of EOS automatically identifies  the cell boundaries and generates a curve about the number of cells (/mm2) based on the flow of  time .   


The EOS Long-term Cell Imaging Workstation is friendly for high-throughput drug screening.  It can independently analyze the cell proliferation curves of individual wells in 96- to 384-well  plates. The data results are presented in the form of a dataset, enabling compound screening or  condition identification in a fast and simple way.

圖片2.png

High-precision label-free cell classification and counting


The vast majority of adherent cells have different morphologies. They may present relatively  complex shapes such as slender fusiform or synapse-like. At the same time, some semi-adherent  and semi-suspended cells are mixed with round suspended cells. Conducting precise label-free  classification of these cells is a relatively difficult task. The label-free cell proliferation  classification AI algorithm equipped in EOS has undergone in-depth training with a large amount  of data from multiple groups of models. It can meet the segmentation requirements of the vast  majority of cell types without the need for manual parameter adjustment.


     4(1).png


Whole-well capture and analysis


The EOS cell proliferation analysis is not limited to capture at specific locations selected  within the well plate. The instrument can be set to the area mode or the whole-well mode to  conduct unified analysis of cells in a specific area or the entire well, enabling every cell to realize its value.


image.png


Conclusion


The cell proliferation module of the EOS Long-term Cell Imaging Workstation non-invasively  and dynamically monitors changes in cell proliferation values based on image algorithms.  Through high-precision AI analysis and whole-well/area capture modes, it significantly reduces  human operation, improves data accuracy and stability, and eliminates reagent/environmental  interference. The neat workflow and high-precision analysis technology offer you a new  experience in cell proliferation analysis.