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

DAMIÁN LA GRECA, ALEJANDRO; PÉREZ, NELBA; CASTAÑEDA, SHEILA; MILONE, PAULA MELANIA; SCARAFÍA, MARÍA AGUSTINA; MÖBBS, ALAN MIQUEAS; WAISMAN, ARIEL; MORO, LUCÍA NATALIA; SEVLEVER, GUSTAVO EMILIO; LUZZANI, CARLOS DANIEL; MIRIUKA, SANTIAGO GABRIEL

PLOS ONE

PUBLIC LIBRARY SCIENCE

Año: 2021 vol. 16

1932-6203

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.