Schematic representation of semi-automated algorithm for organoids analyzing.

<p>The pipeline begins with the acquisition of raw bright-field z-stack images from multiple fields of view (1). Then images are processed to generate a single, sharp EFSI for each well, cropped (2-3) and preprocessed for optimal segmentation by a trained U-Net convolutional neural network, wh...

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Bibliographic Details
Main Author:	Anna Demchenko (18449439) (author)
Other Authors:	Maxim Balyasin (18449445) (author), Elena Kondratyeva (18449463) (author), Tatiana Kyian (18449466) (author), Alyona Sorokina (12111066) (author), Marina Loguinova (3552146) (author), Svetlana Smirnikhina (6468677) (author)
Published:	2025
Subjects:	Biochemistry Cell Biology Genetics Biotechnology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified without fluorescent dyes organoid images remains induced swelling assays field images acquired cystic fibrosis patient studying respiratory diseases accurate segmentation tools algorithm processes bright div >< p respiratory organoids organoids segmentation automatic algorithm vitro </ union metric throughput analysis study presents stack fusion source dataset results demonstrate net architecture lung organoids image analysis healthy donor drug discovery derived organoids deep learning challenge due
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Schematic representation of semi-automated algorithm for organoids analyzing.

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