Assessment of Neuronal Damage in Brain Slice Cultures Using Machine Learning Based on Spatial Features.

ABSTRACT: Neuronal damage presents a major health issue necessitating extensive research to identify mechanisms of neuronal cell death and potential therapeutic targets. Commonly used models are slice cultures out of different brain regions extracted from mice or rats, excitotoxically, ischemic, or traumatically lesioned and subsequently treated with potential neuroprotective agents. Thereby cell death is regularly assessed by measuring the propidium iodide (PI) uptake or counting of PI-positive nuclei. The applied methods have a limited applicability, either in terms of objectivity and time consumption or regarding its applicability. Consequently, new tools for analysis are needed. Here, we present a framework to mimic manual counting using machine learning algorithms as tools for semantic segmenta

SUBMITTER: Hohmann U 

PROVIDER: S-EPMC8531652 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature