{"doi":"10.5281/zenodo.6938610","title":"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 similar to that of state-of-the-art methods for offline analysis. Moreover, CITE-On generalizes across calcium indicators, brain regions, and acquisition parameters in anesthetized and awake head-fixed mice. CITE-On represents a powerful tool to speed up image analysis and facilitate closed-loop approaches, for example in combined all-optical imaging and manipulation experiments.","journal":"Zenodo (CERN European Organization for Nuclear Research)","year":2022,"id":310322,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9485,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":397681,"name":"Marco Brondi","orcid":"0000-0002-3464-0095","position":1,"is_corresponding":false},{"id":856872,"name":"Pedro Lagomarsino de Leon Roig","orcid":null,"position":2,"is_corresponding":false},{"id":814557,"name":"Sebastiano Curreli","orcid":"0000-0003-4490-6835","position":3,"is_corresponding":false},{"id":847635,"name":"Mariangela Panniello","orcid":"0000-0002-1837-6116","position":4,"is_corresponding":false},{"id":328737,"name":"Dania Vecchia","orcid":"0000-0002-6091-538X","position":5,"is_corresponding":false},{"id":328740,"name":"Tommaso Fellin","orcid":"0000-0003-2718-7533","position":6,"is_corresponding":false},{"id":856049,"name":"Luca Sità","orcid":"0000-0003-3453-6201","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T00:33:19.712967Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}