ASTRA: a deep learning algorithm for fast semantic segmentation of large-scale astrocytic networks.

ABSTRACT: Changes in the intracellular calcium concentration are a fundamental fingerprint of astrocytes, the main type of glial cell. Astrocyte calcium signals can be measured with two-photon microscopy, occur in anatomically restricted subcellular regions, and are coordinated across astrocytic networks. However, current analytical tools to identify the astrocytic subcellular regions where calcium signals occur are time-consuming and extensively rely on user-defined parameters. These limitations limit reproducibility and prevent scalability to large datasets and fields-of-view. Here, we present Astrocytic calcium Spatio-Temporal Rapid Analysis (ASTRA), a novel software combining deep learning with image feature engineering for fast and fully automated semantic segmentation of two-photon calcium ima

SUBMITTER: Bonato J 

PROVIDER: S-EPMC10187152 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature