CaImAn an open source tool for scalable calcium imaging data analysis.
Elife
; 82019 01 17.
Article
em En
| MEDLINE
| ID: mdl-30652683
ABSTRACT
Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months. We present CaImAn, an open-source library for calcium imaging data analysis. CaImAn provides automatic and scalable methods to address problems common to pre-processing, including motion correction, neural activity identification, and registration across different sessions of data collection. It does this while requiring minimal user intervention, with good scalability on computers ranging from laptops to high-performance computing clusters. CaImAn is suitable for two-photon and one-photon imaging, and also enables real-time analysis on streaming data. To benchmark the performance of CaImAn we collected and combined a corpus of manual annotations from multiple labelers on nine mouse two-photon datasets. We demonstrate that CaImAn achieves near-human performance in detecting locations of active neurons.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
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Encéfalo
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Reconhecimento Automatizado de Padrão
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Cálcio
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Microscopia de Fluorescência
Tipo de estudo:
Prognostic_studies
Limite:
Animals
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Humans
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article