Artículo

Celldeath: A tool for detection of cell death in transmitted light microscopy images by deep learning-based visual recognition

la Greca, Alejandro Damián Icon; Pérez, Nelba ; Castañeda, Sheila Lucia Icon; Milone, Paula Melania Icon; Scarafia, Maria Agustina Icon; Möbbs, Alan Miqueas Icon; Waisman, Ariel Icon; Moro, Lucía Natalia Icon; Sevlever, Gustavo Emilio ; Luzzani, Carlos Daniel Icon; Miriuka, Santiago Gabriel Icon

Otros responsables

Fecha

2021-06-24

Editorial

Public Library of Science

Revista

Plos One

Título del libro

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Institución organizadora

ISSN

eISSN

1932-6203

ISBN

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Inglés

Tipo del evento

Clasificación temática

Resumen

Cell death experiments are routinely done in many labs around the world, these experiments are the backbone of many assays for drug development. Cell death detection is usually performed in many ways, and requires time and reagents. However, cell death is preceded by slight morphological changes in cell shape and texture. In this paper, we trained a neural network to classify cells undergoing cell death. We found that the network was able to highly predict cell death after one hour of exposure to camptothecin. Moreover, this prediction largely outperforms human ability. Finally, we provide a simple python tool that can broadly be used to detect cell death.

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Licencia Creative Commons

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