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

Author:

La Greca Alejandro DamiánORCID,Pérez Nelba,Castañeda SheilaORCID,Milone Paula Melania,Scarafía María AgustinaORCID,Möbbs Alan Miqueas,Waisman Ariel,Moro Lucía Natalia,Sevlever Gustavo Emilio,Luzzani Carlos Daniel,Miriuka Santiago Gabriel

Abstract

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.

Funder

National Scientific and Technical Research Council

Scientific and Technical Research Fund

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference38 articles.

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