Virtual reality-empowered deep-learning analysis of brain cells.
Journal
Nature methods
ISSN: 1548-7105
Titre abrégé: Nat Methods
Pays: United States
ID NLM: 101215604
Informations de publication
Date de publication:
22 Apr 2024
22 Apr 2024
Historique:
received:
03
06
2022
accepted:
12
03
2024
medline:
23
4
2024
pubmed:
23
4
2024
entrez:
22
4
2024
Statut:
aheadofprint
Résumé
Automated detection of specific cells in three-dimensional datasets such as whole-brain light-sheet image stacks is challenging. Here, we present DELiVR, a virtual reality-trained deep-learning pipeline for detecting c-Fos
Identifiants
pubmed: 38649742
doi: 10.1038/s41592-024-02245-2
pii: 10.1038/s41592-024-02245-2
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : SFB 824
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : SFB 824
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : SFB 824
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 390857198
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : SFB 1052
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : TR 296
Organisme : Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research)
ID : 01KX2121
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : 949017
Organisme : Else Kröner-Fresenius-Stiftung (Else Kroner-Fresenius Foundation)
ID : 2020 EKSE.23
Informations de copyright
© 2024. The Author(s).
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