A deep-learning approach for online cell identification and trace extraction in functional two-photon calcium imaging.

ABSTRACT: In vivo two-photon calcium imaging is a powerful approach in neuroscience. However, processing two-photon calcium imaging data is computationally intensive and time-consuming, making online frame-by-frame analysis challenging. This is especially true for large field-of-view (FOV) imaging. Here, we present CITE-On (Cell Identification and Trace Extraction Online), a convolutional neural network-based algorithm for fast automatic cell identification, segmentation, identity tracking, and trace extraction in two-photon calcium imaging data. CITE-On processes thousands of cells online, including during mesoscopic two-photon imaging, and extracts functional measurements from most neurons in the FOV. Applied to publicly available datasets, the offline version of CITE-On achieves performance simil

SUBMITTER: Sita L 

PROVIDER: S-EPMC8940911 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature