Imaging Screening Station
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Version 3.3 of the scanR High-Content Screening Station from Olympus Corp. provides fully automated image acquisition and data analysis while improving its deep-learning capabilities.
Using a self-learning microscopy approach, the scanR system’s artificial intelligence automatically analyzes data in an assay-based workflow. The deep-learning technology can detect cells, nuclei, and subcellular objects, extracting features from a list of more than 100 object parameters. Version 3.3 more accurately segments difficult-to-distinguish objects. It also features pretrained neural network models for nuclei and cells, which can be used in a broad range of standard applications including the ability to distinguish between confluent cells and dense nuclei, eliminating the time to train the neural network.
A well plate calibration assistant quickly and simply calibrates a new well plate for the system, and a new license level enables collaborators to open, review, and re-gate scanR analysis files for easier results sharing.
https://www.evidentscientific.com
/Buyers_Guide/Evident/c10687
Published: December 2021
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