A deep learning approach for automation in neurite tracing and cell size estimation from differential contrast images under healthy and hypoxic condition.

Chronic hypoxia is known to be a major cause of neurite length retraction followed be degeneration. Specifically, laser scanning confocal microscopy (LSCM) based-contrast imaging is used for monitoring neuronal morphology under hypoxic condition. Although imaging of neurons using LSCM via differential contrast imaging (DIC) is a powerful tool to identify the neuronal states under degenerative condition, fully automated quantification of neurite length and cell shape remains challenging.