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MusiJ: an ImageJ plugin for video nanoscopy

dc.contributor.authorAcuña Maldonado, Sebastian Andres
dc.contributor.authorStröhl, Florian
dc.contributor.authorOpstad, Ida Sundvor
dc.contributor.authorAhluwalia, Balpreet S.
dc.contributor.authorAgarwal, Krishna
dc.date.accessioned2020-06-17T17:17:04Z
dc.date.available2020-06-17T17:17:04Z
dc.date.issued2020-04-14
dc.description.abstractWe present an open-source implementation of the fluctuation-based nanoscopy method MUSICAL for ImageJ. This implementation improves the algorithm’s computational efficiency and takes advantage of multi-threading to provide orders of magnitude faster reconstructions than the original MATLAB implementation. In addition, the plugin is capable of generating super-resolution videos from large stacks of time-lapse images via an interleaved reconstruction, thus enabling easy-to-use multi-color super-resolution imaging of dynamic systems.en_US
dc.identifier.citationAcuña Maldonado SAA, Ströhl F, Opstad IS, Ahluwalia BS, Agarwal K. MusiJ: an ImageJ plugin for video nanoscopy. Biomedical Optics Express. 2020;11(5):2548-2559en_US
dc.identifier.cristinIDFRIDAID 1806243
dc.identifier.doi10.1364/BOE.382735
dc.identifier.issn2156-7085
dc.identifier.urihttps://hdl.handle.net/10037/18593
dc.language.isoengen_US
dc.publisherOptical Society of Americaen_US
dc.relation.ispartofOpstad, I.S. (2021). Bringing optical nanoscopy to life - Super-resolution microscopy of living cells. (Doctoral thesis). <a href=https://hdl.handle.net/10037/20306>https://hdl.handle.net/10037/20306</a>
dc.relation.ispartofAcuna Maldonado, S.A. (2023). Multiple Signal Classification Algorithm: A computational microscopy tool for fluorescence microscopy. (Doctoral thesis). <a href=https://hdl.handle.net/10037/31879>https://hdl.handle.net/10037/31879</a>.
dc.relation.journalBiomedical Optics Express
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/836355/EU/Development of Deep-UV Quantitative Microscopy for the Study of Mitochondrial Dysfunction/MitoQuant/en_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/RCN/BIOTEK2021/285571/Norway/Optimalisering: High-throughput and high-resolution pathology using chip-based nanoscopy//en_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/336716/EU/High-speed chip-based nanoscopy to discover real-time sub-cellular dynamics/NANOSCOPY/en_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/804233/EU/Label-free 3D morphological nanoscopy for studying sub-cellular dynamics in live cancer cells with high spatio-temporal resolution/3D-nanoMorph/en_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2020 Optical Society of Americaen_US
dc.subjectVDP::Technology: 500::Medical technology: 620en_US
dc.subjectVDP::Teknologi: 500::Medisinsk teknologi: 620en_US
dc.titleMusiJ: an ImageJ plugin for video nanoscopyen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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